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Stewart PV, Tapscott BE, Davis B, Boscarino JJ, Sanders K, Rodgers SE, Lichtenstein ML. Validation and extension of the quick dementia rating system (QDRS). APPLIED NEUROPSYCHOLOGY. ADULT 2024; 31:1375-1382. [PMID: 36240388 DOI: 10.1080/23279095.2022.2129056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Informant report dementia severity staging measures, such as the Quick Dementia Rating System (QDRS) offer clinicians useful diagnostic and staging information. These measures also potentially avoid many of the pitfalls inherent in mental status examinations (e.g., cultural bias, educational bias, floor and ceiling effects). We derive cut points for the QDRS and comprehensively examine their classification accuracy in a large, diagnostically heterogeneous, rural, memory disorder clinic sample. Our findings suggest the QDRS may be helpful when used in the context of a comprehensive diagnostic and staging evaluation. When used in isolation, the QDRS is insufficiently accurate for diagnosis and staging of dementia.
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Affiliation(s)
| | - Brian E Tapscott
- Department of Psychiatry and Behavioral Sciences, Cleveland Clinic Akron General, Akron, OH, USA
| | - Beate Davis
- Department of Psychiatry, Geisinger, Danville, PA, USA
| | - Joseph J Boscarino
- Department of Neurosurgery and Brain Repair, University of South Florida Morsani College of Medicine, Tampa, FL, USA
| | | | | | - Maya L Lichtenstein
- Department of Neurology, Memory and Cognition Program, Geisinger, Wilkes-Barre, PA, USA
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2
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Kang JW, Khatib LA, Heston MB, Dilmore AH, Labus JS, Deming Y, Schimmel L, Blach C, McDonald D, Gonzalez A, Bryant M, Sanders K, Schwartz A, Ulland TK, Johnson SC, Asthana S, Carlsson CM, Chin NA, Blennow K, Zetterberg H, Rey FE, Kaddurah-Daouk R, Knight R, Bendlin BB. Gut Microbiome Compositional and Functional Features Associate with Alzheimer's Disease Pathology. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.09.04.24313004. [PMID: 39281749 PMCID: PMC11398448 DOI: 10.1101/2024.09.04.24313004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/18/2024]
Abstract
BACKGROUND The gut microbiome is a potentially modifiable factor in Alzheimer's disease (AD); however, understanding of its composition and function regarding AD pathology is limited. METHODS Shallow-shotgun metagenomic data was used to analyze fecal microbiome from participants enrolled in the Wisconsin Microbiome in Alzheimer's Risk Study, leveraging clinical data and cerebrospinal fluid (CSF) biomarkers. Differential abundance and ordinary least squares regression analyses were performed to find differentially abundant gut microbiome features and their associations with CSF biomarkers of AD and related pathologies. RESULTS Gut microbiome composition and function differed between people with AD and cognitively unimpaired individuals. The compositional difference was replicated in an independent cohort. Differentially abundant gut microbiome features were associated with CSF biomarkers of AD and related pathologies. DISCUSSION These findings enhance our understanding of alterations in gut microbial composition and function in AD, and suggest that gut microbes and their pathways are linked to AD pathology.
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Affiliation(s)
- Jea Woo Kang
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA Address: 600 Highland Ave, J5/1 Mezzanine, Madison, WI, USA 53792
| | - Lora A Khatib
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA Address: 9461 Gilman Dr, La Jolla, CA, USA 92093
- Neurosciences Graduate Program, University of California San Diego, La Jolla, California, USA Address: 9500 Gilman Dr, La Jolla, CA, USA 92093
| | - Margo B Heston
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA Address: 600 Highland Ave, J5/1 Mezzanine, Madison, WI, USA 53792
| | - Amanda H Dilmore
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA Address: 9461 Gilman Dr, La Jolla, CA, USA 92093
| | - Jennifer S Labus
- Integrative Biostatistics and Bioinformatics Core (IBBC) at the Goodman-Luskin Microbiome Center Address: 42-210 CHS, Los Angeles, CA, USA 90095
- G. Oppenheimer Center for Neurobiology of Stress and Resilience Address: 10833 Le Conte Ave, Los Angeles, CA, USA 90095
- UCLA Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine at UCLA Address: 100 Medical Plaza, Los Angeles, CA, USA 90095
| | - Yuetiva Deming
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA Address: 600 Highland Ave, J5/1 Mezzanine, Madison, WI, USA 53792
| | - Leyla Schimmel
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA Address: 905 W Main St, Durham, NC, USA 27701
| | - Colette Blach
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA Address: 300 N Duke St, Durham, NC, USA 27701
| | - Daniel McDonald
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA Address: 9461 Gilman Dr, La Jolla, CA, USA 92093
| | - Antonio Gonzalez
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA Address: 9461 Gilman Dr, La Jolla, CA, USA 92093
| | - MacKenzie Bryant
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA Address: 9461 Gilman Dr, La Jolla, CA, USA 92093
| | - Karenina Sanders
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA Address: 9461 Gilman Dr, La Jolla, CA, USA 92093
| | - Ara Schwartz
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA Address: 9461 Gilman Dr, La Jolla, CA, USA 92093
| | - Tyler K Ulland
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA Address: 600 Highland Ave, J5/1 Mezzanine, Madison, WI, USA 53792
- Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, WI, USA Address: 1685 Highland Ave, Madison, WI, USA 53705
| | - Sterling C Johnson
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA Address: 600 Highland Ave, J5/1 Mezzanine, Madison, WI, USA 53792
| | - Sanjay Asthana
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA Address: 600 Highland Ave, J5/1 Mezzanine, Madison, WI, USA 53792
| | - Cynthia M Carlsson
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA Address: 600 Highland Ave, J5/1 Mezzanine, Madison, WI, USA 53792
| | - Nathaniel A Chin
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA Address: 600 Highland Ave, J5/1 Mezzanine, Madison, WI, USA 53792
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden Address: Blå stråket 15, vån 3 SU/Sahlgrenska 413 45 Göteborg, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden Address: Blå stråket 15, vån 3 SU/Sahlgrenska 413 45 Göteborg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden Address: Blå stråket 5, 413 45 Göteborg, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK Address: Queen Square, London WC1N 3BG, United Kingdom
- UK Dementia Research Institute at UCL, London, UK Address: 6th Floor, Maple House, Tottenham Ct Rd, London W1T 7NF, United Kingdom
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China Address: Units 1501-1502, 1512-1518, 15/F, Building 17W, Hong Kong Science Park, Shatin, N.T., Hong Kong
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA Address: 600 Highland Ave, J5/1 Mezzanine, Madison, WI, USA 53792
| | - Federico E Rey
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA Address: 1550 Linden Dr, Madison, WI, USA 53706
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA Address: 905 W Main St, Durham, NC, USA 27701
- Duke Institute of Brain Sciences, Duke University, Durham, NC, USA Address: 308 Research Dr, Durham, NC, USA 27710
- Department of Medicine, Duke University, Durham, NC, USA Address: 40 Duke Medicine Circle, 124 Davison Building, Durham, NC, USA 27710
| | - Rob Knight
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA Address: 9461 Gilman Dr, La Jolla, CA, USA 92093
- Center for Microbiome Innovation, Joan and Irwin Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA Address: Franklin Antonio Hall, Jacobs School of Engineering, 9500 Gilman Dr, La Jolla, CA, USA 92093
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA Address: 3235 Voigt Dr, La Jolla, CA, USA 92093
- Halıcıoğlu Data Science Institute, University of California, San Diego, La Jolla, CA, USA Address: 3234 Matthews Ln, La Jolla, CA, USA 92093
- Shu Chien-Gene Lay Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA Address: 3223 Voigt Dr, La Jolla, CA, USA 92093
| | - Barbara B Bendlin
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA Address: 600 Highland Ave, J5/1 Mezzanine, Madison, WI, USA 53792
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA Address: 610 Walnut Street, 9th Floor, Madison, WI, USA 53726
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Vikner T, Johnson KM, Cadman RV, Betthauser TJ, Wilson RE, Chin N, Eisenmenger LB, Johnson SC, Rivera-Rivera LA. CSF dynamics throughout the ventricular system using 4D flow MRI: associations to arterial pulsatility, ventricular volumes, and age. Fluids Barriers CNS 2024; 21:68. [PMID: 39215377 PMCID: PMC11363656 DOI: 10.1186/s12987-024-00570-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Accepted: 08/19/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND Cerebrospinal fluid (CSF) dynamics are increasingly studied in aging and neurological disorders. Models of CSF-mediated waste clearance suggest that altered CSF dynamics could play a role in the accumulation of toxic waste in the CNS, with implications for Alzheimer's disease and other proteinopathies. Therefore, approaches that enable quantitative and volumetric assessment of CSF flow velocities could be of value. In this study we demonstrate the feasibility of 4D flow MRI for simultaneous assessment of CSF dynamics throughout the ventricular system, and evaluate associations to arterial pulsatility, ventricular volumes, and age. METHODS In a cognitively unimpaired cohort (N = 43; age 41-83 years), cardiac-resolved 4D flow MRI CSF velocities were obtained in the lateral ventricles (LV), foramens of Monro, third and fourth ventricles (V3 and V4), the cerebral aqueduct (CA) and the spinal canal (SC), using a velocity encoding (venc) of 5 cm/s. Cerebral blood flow pulsatility was also assessed with 4D flow (venc = 80 cm/s), and CSF volumes were obtained from T1- and T2-weighted MRI. Multiple linear regression was used to assess effects of age, ventricular volumes, and arterial pulsatility on CSF velocities. RESULTS Cardiac-driven CSF dynamics were observed in all CSF spaces, with region-averaged velocity range and root-mean-square (RMS) velocity encompassing from very low in the LVs (RMS 0.25 ± 0.08; range 0.85 ± 0.28 mm/s) to relatively high in the CA (RMS 6.29 ± 2.87; range 18.6 ± 15.2 mm/s). In the regression models, CSF velocity was significantly related to age in 5/6 regions, to CSF space volume in 2/3 regions, and to arterial pulsatility in 3/6 regions. Group-averaged waveforms indicated distinct CSF flow propagation delays throughout CSF spaces, particularly between the SC and LVs. CONCLUSIONS Our findings show that 4D flow MRI enables assessment of CSF dynamics throughout the ventricular system, and captures independent effects of age, CSF space morphology, and arterial pulsatility on CSF motion.
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Affiliation(s)
- Tomas Vikner
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
- Department of Diagnostics and Intervention, Umeå University, Umeå, S-90187, Sweden
| | - Kevin M Johnson
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53726, USA
| | - Robert V Cadman
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
| | - Tobey J Betthauser
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
| | - Rachael E Wilson
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
| | - Nathaniel Chin
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
| | - Laura B Eisenmenger
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53726, USA
| | - Sterling C Johnson
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
| | - Leonardo A Rivera-Rivera
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA.
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA.
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA.
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Frau L, Jonaitis E, Langhough RE, Zuelsdorff M, Okonkwo O, Bruno D. The role of cognitive reserve and depression on executive function in older adults: A 10-year study from the Wisconsin Registry for Alzheimer's Prevention. Clin Neuropsychol 2024:1-23. [PMID: 39180168 DOI: 10.1080/13854046.2024.2388904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 07/31/2024] [Indexed: 08/26/2024]
Abstract
Objective: The current study examined the longitudinal relationship between cognitive reserve (CR), depression, and executive function (EF) in a cohort of older adults. Methods: 416 participants were selected from the Wisconsin Registry for Alzheimer's Prevention. They were native English speakers, aged ≥50+, and cognitively unimpaired at baseline, with no history of neurological or other psychiatric disorders aside from depression. Depression was assessed with the 20-item Center for Epidemiologic Studies Depression Scale (CES-D). A composite score, based on the premorbid IQ (WRAT-3 Reading subtest) and years of education was used to estimate CR. Another composite score from four cognitive tests was used to estimate EF. A moderation analysis was performed to evaluate the effects of CR and Depression on EF at follow-up after controlling for age, gender, and APOE risk score. Moreover, a multinomial logistic regression was used to predict conversion to Mild Cognitive Impairment (MCI) from the healthy baseline. Results: The negative relationship between depression and EF was stronger in individuals with higher CR levels, suggesting a possible floor effect at lower CR levels. In the multinomial regression, the interaction between CR and depression predicted conversion to MCI status, indicating that lower CR paired with more severe depression at baseline was associated with a higher risk of subsequent impairment. Conclusions: This study sheds light on the intricate relationship between depression and EF over time, suggesting that the association may be influenced by varying levels of CR. Further studies may replicate these findings in clinical populations.
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Affiliation(s)
- Loredana Frau
- School of Psychology, Liverpool, John Moores University, United Kingdom
| | - Erin Jonaitis
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Rebecca E Langhough
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Megan Zuelsdorff
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- School of Nursing (MZ), University of Wisconsin-Madison, Madison, Wisconsin
| | - Ozioma Okonkwo
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Davide Bruno
- School of Psychology, Liverpool, John Moores University, United Kingdom
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5
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Soldan A, Wang J, Pettigrew C, Davatzikos C, Erus G, Hohman TJ, Dumitrescu L, Bilgel M, Resnick SM, Rivera-Rivera LA, Langhough R, Johnson SC, Benzinger T, Morris JC, Laws SM, Fripp J, Masters CL, Albert MS. Alzheimer's disease genetic risk and changes in brain atrophy and white matter hyperintensities in cognitively unimpaired adults. Brain Commun 2024; 6:fcae276. [PMID: 39229494 PMCID: PMC11369827 DOI: 10.1093/braincomms/fcae276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 06/25/2024] [Accepted: 08/12/2024] [Indexed: 09/05/2024] Open
Abstract
Reduced brain volumes and more prominent white matter hyperintensities on MRI scans are commonly observed among older adults without cognitive impairment. However, it remains unclear whether rates of change in these measures among cognitively normal adults differ as a function of genetic risk for late-onset Alzheimer's disease, including APOE-ɛ4, APOE-ɛ2 and Alzheimer's disease polygenic risk scores (AD-PRS), and whether these relationships are influenced by other variables. This longitudinal study examined the trajectories of regional brain volumes and white matter hyperintensities in relationship to APOE genotypes (N = 1541) and AD-PRS (N = 1093) in a harmonized dataset of middle-aged and older individuals with normal cognition at baseline (mean baseline age = 66 years, SD = 9.6) and an average of 5.3 years of MRI follow-up (max = 24 years). Atrophy on volumetric MRI scans was quantified in three ways: (i) a composite score of regions vulnerable to Alzheimer's disease (SPARE-AD); (ii) hippocampal volume; and (iii) a composite score of regions indexing advanced non-Alzheimer's disease-related brain aging (SPARE-BA). Global white matter hyperintensity volumes were derived from fluid attenuated inversion recovery (FLAIR) MRI. Using linear mixed effects models, there was an APOE-ɛ4 gene-dose effect on atrophy in the SPARE-AD composite and hippocampus, with greatest atrophy among ɛ4/ɛ4 carriers, followed by ɛ4 heterozygouts, and lowest among ɛ3 homozygouts and ɛ2/ɛ2 and ɛ2/ɛ3 carriers, who did not differ from one another. The negative associations of APOE-ɛ4 with atrophy were reduced among those with higher education (P < 0.04) and younger baseline ages (P < 0.03). Higher AD-PRS were also associated with greater atrophy in SPARE-AD (P = 0.035) and the hippocampus (P = 0.014), independent of APOE-ɛ4 status. APOE-ɛ2 status (ɛ2/ɛ2 and ɛ2/ɛ3 combined) was not related to baseline levels or atrophy in SPARE-AD, SPARE-BA or the hippocampus, but was related to greater increases in white matter hyperintensities (P = 0.014). Additionally, there was an APOE-ɛ4 × AD-PRS interaction in relation to white matter hyperintensities (P = 0.038), with greater increases in white matter hyperintensities among APOE-ɛ4 carriers with higher AD-PRS. APOE and AD-PRS associations with MRI measures did not differ by sex. These results suggest that APOE-ɛ4 and AD-PRS independently and additively influence longitudinal declines in brain volumes sensitive to Alzheimer's disease and synergistically increase white matter hyperintensity accumulation among cognitively normal individuals. Conversely, APOE-ɛ2 primarily influences white matter hyperintensity accumulation, not brain atrophy. Results are consistent with the view that genetic factors for Alzheimer's disease influence atrophy in a regionally specific manner, likely reflecting preclinical neurodegeneration, and that Alzheimer's disease risk genes contribute to white matter hyperintensity formation.
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Affiliation(s)
- Anja Soldan
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Jiangxia Wang
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Corinne Pettigrew
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Christos Davatzikos
- Centre for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Guray Erus
- Centre for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Timothy J Hohman
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Logan Dumitrescu
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Murat Bilgel
- Laboratory of Behavioral Neuroscience, National Institute on Aging Intramural Research Program, Baltimore, MD 21224, USA
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging Intramural Research Program, Baltimore, MD 21224, USA
| | - Leonardo A Rivera-Rivera
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
| | - Rebecca Langhough
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
| | - Sterling C Johnson
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
| | - Tammie Benzinger
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - John C Morris
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Simon M Laws
- Centre for Precision Health, Edith Cowan University, Joondalup, WA 6027, Australia
| | - Jurgen Fripp
- Australian E-Health Research Centre, CSIRO Health & Biosecurity, Herston, QLD 4029, Australia
| | - Colin L Masters
- The Florey Institute, University of Melbourne, Parkville, VIC 3052, Australia
| | - Marilyn S Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
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Clark LR, Erickson CM, Chin NA, Basche KE, Ketchum FB, Rosario HL, Peterson AJ, Eveler ML, Johnson SC. Psychosocial implications of learning amyloid PET results in an observational cohort. Alzheimers Dement 2024. [PMID: 39129396 DOI: 10.1002/alz.14153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Revised: 06/28/2024] [Accepted: 07/02/2024] [Indexed: 08/13/2024]
Abstract
INTRODUCTION Information on the psychosocial impact of Alzheimer's disease (AD) biomarker testing in adults at risk of AD is needed to inform best practices for communicating biomarker results. METHODS Ninety-nine cognitively unimpaired older adults learned amyloid positron emission tomography (PET) results (mean age = 72.0 ± 4.8, 95% White, 28% elevated amyloid). Linear mixed-effects regression models were used to test the main effects and interaction of PET result × time on psychosocial outcomes up to 6 months after learning results. RESULTS A significant interaction of PET result × time was observed for concern about AD (β = 0.28, p = 0.02) and intrusive thoughts and avoidance (β = -0.82, p < 0.001). A main effect of PET result was observed for AD test-related distress (β = 12.09, p < 0.001). DISCUSSION Cognitively unimpaired adults learning elevated-amyloid PET results reported mildly intrusive thoughts/avoidance initially following disclosure, but these symptoms decreased over time. Concern about AD dementia and AD biomarker test-related distress remained higher in elevated-amyloid compared to non-elevated-amyloid participants. HIGHLIGHTS Longitudinal assessment of psychosocial reactions after amyloid PET disclosure was conducted. Transient highly intrusive thoughts or avoidance after learning elevated amyloid results. Persistent test result-related distress after receiving elevated-amyloid results. There is increased concern about AD dementia after receiving elevated-amyloid results. Happiness and relief are experienced after receiving non-elevated-amyloid results.
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Affiliation(s)
- Lindsay R Clark
- Department of Medicine, Division of Geriatrics & Gerontology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin, USA
| | - Claire M Erickson
- Department of Medical Ethics and Health Policy, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Nathaniel A Chin
- Department of Medicine, Division of Geriatrics & Gerontology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Kristin E Basche
- Department of Medicine, Division of Geriatrics & Gerontology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Fred B Ketchum
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Hannah L Rosario
- Department of Medicine, Division of Geriatrics & Gerontology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Amanda J Peterson
- Department of Medicine, Division of Geriatrics & Gerontology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Marcella L Eveler
- Department of Medicine, Division of Geriatrics & Gerontology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Sterling C Johnson
- Department of Medicine, Division of Geriatrics & Gerontology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
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7
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Rivera-Rivera LA, Roberts GS, Peret A, Langhough RE, Jonaitis EM, Du L, Field A, Eisenmenger L, Johnson SC, Johnson KM. Unraveling diurnal and technical variability in cerebral hemodynamics from neurovascular 4D-Flow MRI. J Cereb Blood Flow Metab 2024; 44:1362-1375. [PMID: 38340787 PMCID: PMC11342721 DOI: 10.1177/0271678x241232190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Revised: 12/20/2023] [Accepted: 12/30/2023] [Indexed: 02/12/2024]
Abstract
Neurovascular 4D-Flow MRI enables non-invasive evaluation of cerebral hemodynamics including measures of cerebral blood flow (CBF), vessel pulsatility index (PI), and cerebral pulse wave velocity (PWV). 4D-Flow measures have been linked to various neurovascular disorders including small vessel disease and Alzheimer's disease; however, physiological and technical sources of variability are not well established. Here, we characterized sources of diurnal physiological and technical variability in cerebral hemodynamics using 4D-Flow in a retrospective study of cognitively unimpaired older adults (N = 750) and a prospective study of younger adults (N = 10). Younger participants underwent repeated MRI sessions at 7am, 4 pm, and 10 pm. In the older cohort, having an MRI earlier on the day was significantly associated with higher CBF and lower PI. In prospective experiments, time of day significantly explained variability in CBF and PI; however, not in PWV. Test-retest experiments showed high CBF intra-session repeatability (repeatability coefficient (RPC) =7.2%), compared to lower diurnal repeatability (RPC = 40%). PI and PWV displayed similar intra-session and diurnal variability (PI intra-session RPC = 22%, RPC = 24% 7am vs 4 pm; PWV intra-session RPC = 17%, RPC = 21% 7am vs 4 pm). Overall, CBF measures showed low technical variability, supporting diurnal variability is from physiology. PI and PWV showed higher technical variability but less diurnal variability.
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Affiliation(s)
- Leonardo A Rivera-Rivera
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Grant S Roberts
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Anthony Peret
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Rebecca E Langhough
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Erin M Jonaitis
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Lianlian Du
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Aaron Field
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Laura Eisenmenger
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Sterling C Johnson
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Kevin M Johnson
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
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Denier-Fields DN, Gangnon RE, Rivera-Rivera LA, Betthauser TJ, Bendlin BB, Johnson SC, Engelman CD. Evaluating Life Simple Seven's influence on brain health outcomes: The intersection of lifestyle and dementia. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.29.24311179. [PMID: 39211877 PMCID: PMC11361218 DOI: 10.1101/2024.07.29.24311179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/04/2024]
Abstract
INTRODUCTION Lifestyle factors have been studied for dementia risk, but few have comprehensively assessed both Alzheimer's disease (AD) and cerebrovascular disease (CBVD) pathologies. Our research aims to determine the relationships between lifestyle and various dementia pathologies, challenging conventional research paradigms. METHODS Analyzing 1231 Wisconsin Registry for Alzheimer's Prevention (WRAP) study participants, we focused on Life Simple Seven (LS7) score calculations from questionnaire data and clinical vitals. We assessed brain health indicators including CBVD, AD, and cognition. RESULTS Higher LS7 scores were associated with better CBVD outcomes, including lower percent white matter hyperintensities and higher cerebral blood flow, and higher Preclinical Alzheimer's Composite 3 and Delayed Recall scores. No significant associations were observed between LS7 scores and AD markers of amyloid and tau accumulation. DISCUSSION This study provides evidence that the beneficial effects of LS7 on cognition are primarily mediated through cerebrovascular pathways rather than direct influences on AD pathology.
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Du L, Langhough RE, Wilson RE, Reyes RER, Hermann BP, Jonaitis EM, Betthauser TJ, Chin NA, Christian B, Chaby L, Jeromin A, Molfetta GD, Brum WS, Arslan B, Ashton N, Blennow K, Zetterberg H, Johnson SC. Longitudinal plasma phosphorylated-tau217 and other related biomarkers in a non-demented Alzheimer's risk-enhanced sample. Alzheimers Dement 2024. [PMID: 38970274 DOI: 10.1002/alz.14100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 05/16/2024] [Accepted: 06/04/2024] [Indexed: 07/08/2024]
Abstract
INTRODUCTION Understanding longitudinal change in key plasma biomarkers will aid in detecting presymptomatic Alzheimer's disease (AD). METHODS Serial plasma samples from 424 Wisconsin Registry for Alzheimer's Prevention participants were analyzed for phosphorylated-tau217 (p-tau217; ALZpath) and other AD biomarkers, to study longitudinal trajectories in relation to disease, health factors, and cognitive decline. Of the participants, 18.6% with known amyloid status were amyloid positive (A+); 97.2% were cognitively unimpaired (CU). RESULTS In the CU, amyloid-negative (A-) subset, plasma p-tau217 levels increased modestly with age but were unaffected by body mass index and kidney function. In the whole sample, average p-tau217 change rates were higher in those who were A+ (e.g., simple slopes(se) for A+ and A- at age 60 were 0.232(0.028) and 0.038(0.013))). High baseline p-tau217 levels predicted faster preclinical cognitive decline. DISCUSSION p-tau217 stands out among markers for its strong association with disease and cognitive decline, indicating its potential for early AD detection and monitoring progression. HIGHLIGHTS Phosphorylated-tau217 (p-tau217) trajectories were significantly different in people who were known to be amyloid positive. Subtle age-related trajectories were seen for all the plasma markers in amyloid-negative cognitively unimpaired. Kidney function and body mass index were not associated with plasma p-tau217 trajectories. Higher plasma p-tau217 was associated with faster preclinical cognitive decline.
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Affiliation(s)
- Lianlian Du
- Wisconsin Alzheimer's Disease Research Center, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Rebecca E Langhough
- Wisconsin Alzheimer's Disease Research Center, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Rachael E Wilson
- Wisconsin Alzheimer's Disease Research Center, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Ramiro Eduardo Rea Reyes
- Wisconsin Alzheimer's Disease Research Center, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Bruce P Hermann
- Wisconsin Alzheimer's Disease Research Center, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Neurology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Erin M Jonaitis
- Wisconsin Alzheimer's Disease Research Center, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Tobey J Betthauser
- Wisconsin Alzheimer's Disease Research Center, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Nathaniel A Chin
- Wisconsin Alzheimer's Disease Research Center, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Bradley Christian
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | | | | | - Guglielmo Di Molfetta
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Wagner S Brum
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
| | - Burak Arslan
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Nicholas Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- ICM Paris Brain Institute, ICM, Pitie-Salpetriere Hospital, Sorbonne University, Paris, France
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, Anhui, China
| | - Henrik Zetterberg
- Wisconsin Alzheimer's Disease Research Center, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
| | - Sterling C Johnson
- Wisconsin Alzheimer's Disease Research Center, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
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Panyard DJ, Reus LM, Ali M, Liu J, Deming YK, Lu Q, Kollmorgen G, Carboni M, Wild N, Visser PJ, Bertram L, Zetterberg H, Blennow K, Gobom J, Western D, Sung YJ, Carlsson CM, Johnson SC, Asthana S, Cruchaga C, Tijms BM, Engelman CD, Snyder MP. Post-GWAS multiomic functional investigation of the TNIP1 locus in Alzheimer's disease highlights a potential role for GPX3. Alzheimers Dement 2024; 20:5044-5053. [PMID: 38809917 PMCID: PMC11247664 DOI: 10.1002/alz.13848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 03/07/2024] [Accepted: 03/27/2024] [Indexed: 05/31/2024]
Abstract
INTRODUCTION Recent genome-wide association studies (GWAS) have reported a genetic association with Alzheimer's disease (AD) at the TNIP1/GPX3 locus, but the mechanism is unclear. METHODS We used cerebrospinal fluid (CSF) proteomics data to test (n = 137) and replicate (n = 446) the association of glutathione peroxidase 3 (GPX3) with CSF biomarkers (including amyloid and tau) and the GWAS-implicated variants (rs34294852 and rs871269). RESULTS CSF GPX3 levels decreased with amyloid and tau positivity (analysis of variance P = 1.5 × 10-5) and higher CSF phosphorylated tau (p-tau) levels (P = 9.28 × 10-7). The rs34294852 minor allele was associated with decreased GPX3 (P = 0.041). The replication cohort found associations of GPX3 with amyloid and tau positivity (P = 2.56 × 10-6) and CSF p-tau levels (P = 4.38 × 10-9). DISCUSSION These results suggest variants in the TNIP1 locus may affect the oxidative stress response in AD via altered GPX3 levels. HIGHLIGHTS Cerebrospinal fluid (CSF) glutathione peroxidase 3 (GPX3) levels decreased with amyloid and tau positivity and higher CSF phosphorylated tau. The minor allele of rs34294852 was associated with lower CSF GPX3. levels when also controlling for amyloid and tau category. GPX3 transcript levels in the prefrontal cortex were lower in Alzheimer's disease than controls. rs34294852 is an expression quantitative trait locus for GPX3 in blood, neutrophils, and microglia.
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Affiliation(s)
- Daniel J. Panyard
- Department of GeneticsStanford University School of MedicineStanford UniversityStanfordCaliforniaUSA
- Department of Population Health SciencesUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Lianne M. Reus
- Alzheimer Center Amsterdam, NeurologyVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Amsterdam Neuroscience, NeurodegenerationAmsterdamThe Netherlands
- Center for Neurobehavioral GeneticsUniversity of CaliforniaLos AngelesCaliforniaUSA
| | - Muhammad Ali
- Department of PsychiatryWashington University School of MedicineSt. LouisMissouriUSA
- NeuroGenomics and Informatics CenterWashington University School of MedicineSt. LouisMissouriUSA
- Hope Center for Neurological DisordersWashington University School of MedicineSt. LouisMissouriUSA
| | - Jihua Liu
- Department of Biostatistics and Medical InformaticsUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of StatisticsUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Yuetiva K. Deming
- Department of Population Health SciencesUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of MedicineUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Qiongshi Lu
- Department of Biostatistics and Medical InformaticsUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of StatisticsUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | | | | | | | - Pieter J. Visser
- Alzheimer Center Amsterdam, NeurologyVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Amsterdam Neuroscience, NeurodegenerationAmsterdamThe Netherlands
- Department of PsychiatryMaastricht UniversityMaastrichtThe Netherlands
- Department of Neurobiology, Care Sciences and Society, Division of NeurogeriatricsKarolinska InstitutetStockholmSweden
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome AnalyticsInstitutes of Neurogenetics and CardiogeneticsUniversity of LübeckLübeckGermany
- Department of PsychologyUniversity of OsloOsloNorway
| | - Henrik Zetterberg
- Institute of Neuroscience and PhysiologyThe Sahlgrenska Academy at the University of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Neurodegenerative DiseaseUCL Institute of NeurologyLondonUK
- UK Dementia Research Institute at UCLLondonUK
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
| | - Kaj Blennow
- Institute of Neuroscience and PhysiologyThe Sahlgrenska Academy at the University of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
| | - Johan Gobom
- Institute of Neuroscience and PhysiologyThe Sahlgrenska Academy at the University of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
| | - Dan Western
- Department of PsychiatryWashington University School of MedicineSt. LouisMissouriUSA
- NeuroGenomics and Informatics CenterWashington University School of MedicineSt. LouisMissouriUSA
- Hope Center for Neurological DisordersWashington University School of MedicineSt. LouisMissouriUSA
| | - Yun Ju Sung
- Department of PsychiatryWashington University School of MedicineSt. LouisMissouriUSA
- NeuroGenomics and Informatics CenterWashington University School of MedicineSt. LouisMissouriUSA
- Hope Center for Neurological DisordersWashington University School of MedicineSt. LouisMissouriUSA
| | - Cynthia M. Carlsson
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of MedicineUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Wisconsin Alzheimer's InstituteUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- William S. Middleton Memorial Veterans HospitalMadisonWisconsinUSA
| | - Sterling C. Johnson
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of MedicineUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Wisconsin Alzheimer's InstituteUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- William S. Middleton Memorial Veterans HospitalMadisonWisconsinUSA
| | - Sanjay Asthana
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of MedicineUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- William S. Middleton Memorial Veterans HospitalMadisonWisconsinUSA
| | - Carlos Cruchaga
- Department of PsychiatryWashington University School of MedicineSt. LouisMissouriUSA
- NeuroGenomics and Informatics CenterWashington University School of MedicineSt. LouisMissouriUSA
- Hope Center for Neurological DisordersWashington University School of MedicineSt. LouisMissouriUSA
| | - Betty M. Tijms
- Alzheimer Center Amsterdam, NeurologyVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Amsterdam Neuroscience, NeurodegenerationAmsterdamThe Netherlands
| | - Corinne D. Engelman
- Department of Population Health SciencesUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Michael P. Snyder
- Department of GeneticsStanford University School of MedicineStanford UniversityStanfordCaliforniaUSA
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Safai A, Jonaitis E, Langhough RE, Buckingha WR, Johnson SC, Powell WR, Kind AJH, Bendlin BB, Tiwari P. Association of neighborhood disadvantage with cognitive function and cortical disorganization in an unimpaired cohort. ARXIV 2024:arXiv:2406.13822v1. [PMID: 38947926 PMCID: PMC11213155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Objective Neighborhood disadvantage is associated with worse health and cognitive outcomes. Morphological similarity network (MSN) is a promising approach to elucidate cortical network patterns underlying complex cognitive functions. We hypothesized that MSNs could capture intricate changes in cortical patterns related to neighborhood disadvantage and cognitive function, potentially explaining some of the risk for later life cognitive impairment among individuals who live in disadvantaged contexts. Methods This cross-sectional study included cognitively unimpaired participants (n=524, age=62.96±8.377, gender (M:F)=181:343, ADI(L:H) =450,74) from the Wisconsin Alzheimer's Disease Research Center or Wisconsin Registry for Alzheimer's Prevention. Neighborhood disadvantage status was obtained using the Area Deprivation Index (ADI). Cognitive performance was assessed through six tests evaluating memory, executive functioning, and the modified preclinical Alzheimer's cognitive composite (mPACC). Morphological Similarity Networks (MSN) were constructed for each participant based on the similarity in distribution of cortical thickness of brain regions, followed by computation of local and global network features. We used linear regression to examine ADI associations with cognitive scores and MSN features. The mediating effect of MSN features on the relationship between ADI and cognitive performance was statistically assessed. Results Neighborhood disadvantage showed negative association with category fluency, implicit learning speed, story recall and mPACC scores, indicating worse cognitive function among those living in more disadvantaged neighborhoods. Local network features of frontal and temporal brain regions differed based on ADI status. Centrality of left lateral orbitofrontal region showed a partial mediating effect between association of neighborhood disadvantage and story recall performance. Conclusion Our findings suggest differences in local cortical organization by neighborhood disadvantage, which also partially mediated the relationship between ADI and cognitive performance, providing a possible network-based mechanism to, in-part, explain the risk for poor cognitive functioning associated with disadvantaged neighborhoods. Future work will examine the exposure to neighborhood disadvantage on structural organization of the brain.
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Affiliation(s)
- Apoorva Safai
- Departments of Radiology and Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USA
| | - Erin Jonaitis
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin - Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin - Madison, Madison, WI, USA
| | - Rebecca E Langhough
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin - Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin - Madison, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, Madison, WI, USA
| | - William R Buckingha
- Health Services and Care Research Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, Geriatrics Division, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Sterling C Johnson
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin - Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin - Madison, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, Madison, WI, USA
| | - W Ryan Powell
- Health Services and Care Research Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, Geriatrics Division, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Amy J H Kind
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin - Madison, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, Madison, WI, USA
- Health Services and Care Research Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Barbara B Bendlin
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin - Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin - Madison, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, Madison, WI, USA
| | - Pallavi Tiwari
- Departments of Radiology and Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USA
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Peterson A, Sathe A, Zaras D, Yang Y, Durant A, Deters KD, Shashikumar N, Pechman KR, Kim ME, Gao C, Khairi NM, Li Z, Yao T, Huo Y, Dumitrescu L, Gifford KA, Wilson JE, Cambronero F, Risacher SL, Beason-Held LL, An Y, Arfanakis K, Erus G, Davatzikos C, Tosun D, Toga AW, Thompson PM, Mormino EC, Zhang P, Schilling K, Albert M, Kukull W, Biber SA, Landman BA, Johnson SC, Schneider J, Barnes LL, Bennett DA, Jefferson AL, Resnick SM, Saykin AJ, Hohman TJ, Archer DB. Sex, racial, and APOE-ε4 allele differences in longitudinal white matter microstructure in multiple cohorts of aging and Alzheimer's disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.10.598357. [PMID: 38915636 PMCID: PMC11195046 DOI: 10.1101/2024.06.10.598357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
INTRODUCTION The effects of sex, race, and Apolipoprotein E (APOE) - Alzheimer's disease (AD) risk factors - on white matter integrity are not well characterized. METHODS Diffusion MRI data from nine well-established longitudinal cohorts of aging were free-water (FW)-corrected and harmonized. This dataset included 4,702 participants (age=73.06 ± 9.75) with 9,671 imaging sessions over time. FW and FW-corrected fractional anisotropy (FAFWcorr) were used to assess differences in white matter microstructure by sex, race, and APOE-ε4 carrier status. RESULTS Sex differences in FAFWcorr in association and projection tracts, racial differences in FAFWcorr in projection tracts, and APOE-ε4 differences in FW limbic and occipital transcallosal tracts were most pronounced. DISCUSSION There are prominent differences in white matter microstructure by sex, race, and APOE-ε4 carrier status. This work adds to our understanding of disparities in AD. Additional work to understand the etiology of these differences is warranted.
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Affiliation(s)
- Amalia Peterson
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
| | - Aditi Sathe
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN
| | - Dimitrios Zaras
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN
| | - Yisu Yang
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN
| | - Alaina Durant
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN
| | - Kacie D. Deters
- Department of Integrative Biology and Physiology, University of California, Los Angeles
| | - Niranjana Shashikumar
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN
| | - Kimberly R. Pechman
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN
| | - Michael E. Kim
- Department of Computer Science, Vanderbilt University, Nashville, TN
| | - Chenyu Gao
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN
| | - Nazirah Mohd Khairi
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN
| | - Zhiyuan Li
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN
| | - Tianyuan Yao
- Department of Computer Science, Vanderbilt University, Nashville, TN
| | - Yuankai Huo
- Department of Computer Science, Vanderbilt University, Nashville, TN
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN
| | - Logan Dumitrescu
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN
- Vanderbilt Brain Institute, Vanderbilt University Medical Center, Nashville, TN
| | - Katherine A. Gifford
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
| | - Jo Ellen Wilson
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN
- Center for Cognitive Medicine, Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN
- Veteran‘s Affairs, Geriatric Research, Education and Clinical Center, Tennessee Valley Healthcare System
| | - Francis Cambronero
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN
| | - Shannon L. Risacher
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN
| | - Lori L. Beason-Held
- Laboratory for Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD
| | - Yang An
- Laboratory for Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD
| | - Konstantinos Arfanakis
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL
- Department of Diagnostic Radiology, Rush University Medical Center, Chicago, IL
| | - Guray Erus
- Department of Radiology, University of Pennsylvania, Philadelphia, PA
| | | | - Duygu Tosun
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA
| | - Arthur W. Toga
- Laboratory of Neuroimaging, USC Stevens Institute of Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA
| | - Elizabeth C. Mormino
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA
| | - Panpan Zhang
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN
| | - Kurt Schilling
- Department of Radiology & Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN2
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN
| | | | | | | | - Marilyn Albert
- Department of Neurology, Johns Hopkins School of Medicine Baltimore, MD
| | - Walter Kukull
- National Alzheimer’s Coordinating Center, University of Washington, Seattle, WA
| | - Sarah A. Biber
- National Alzheimer’s Coordinating Center, University of Washington, Seattle, WA
| | - Bennett A. Landman
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
- Department of Computer Science, Vanderbilt University, Nashville, TN
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN
- Vanderbilt Brain Institute, Vanderbilt University Medical Center, Nashville, TN
- Department of Radiology & Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN2
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN
| | - Sterling C. Johnson
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI
| | - Julie Schneider
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL
| | - Lisa L. Barnes
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL
| | - Angela L. Jefferson
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
- Department of Computer Science, Vanderbilt University, Nashville, TN
| | - Susan M. Resnick
- Laboratory for Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD
| | - Andrew J. Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN
| | - Timothy J. Hohman
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN
- Vanderbilt Brain Institute, Vanderbilt University Medical Center, Nashville, TN
| | - Derek B. Archer
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN
- Vanderbilt Brain Institute, Vanderbilt University Medical Center, Nashville, TN
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Cody KA, Langhough RE, Zammit MD, Clark L, Chin N, Christian BT, Betthauser TJ, Johnson SC. Characterizing brain tau and cognitive decline along the amyloid timeline in Alzheimer's disease. Brain 2024; 147:2144-2157. [PMID: 38667631 PMCID: PMC11146417 DOI: 10.1093/brain/awae116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 02/23/2024] [Accepted: 03/24/2024] [Indexed: 06/04/2024] Open
Abstract
Recent longitudinal PET imaging studies have established methods to estimate the age at which amyloid becomes abnormal at the level of the individual. Here we recontextualized amyloid levels into the temporal domain to better understand the downstream Alzheimer's disease processes of tau neurofibrillary tangle (NFT) accumulation and cognitive decline. This cohort study included a total of 601 individuals from the Wisconsin Registry for Alzheimer's Prevention and Wisconsin Alzheimer's Disease Research Center that underwent amyloid and tau PET, longitudinal neuropsychological assessments and met clinical criteria for three clinical diagnosis groups: cognitively unimpaired (n = 537); mild cognitive impairment (n = 48); or dementia (n = 16). Cortical 11C-Pittsburgh compound B (PiB) distribution volume ratio (DVR) and sampled iterative local approximation were used to estimate amyloid positive (A+; global PiB DVR > 1.16 equivalent to 17.1 centiloids) onset age and years of A+ duration at tau PET (i.e. amyloid chronicity). Tau PET burden was quantified using 18F-MK-6240 standardized uptake value ratios (70-90 min, inferior cerebellar grey matter reference region). Whole-brain and region-specific approaches were used to examine tau PET binding along the amyloid timeline and across the Alzheimer's disease clinical continuum. Voxel-wise 18F-MK-6240 analyses revealed that with each decade of A+, the spatial extent of measurable tau spread (i.e. progressed) from regions associated with early to late NFT tau stages. Regional analyses indicated that tau burden in the entorhinal cortex was detectable, on average, within 10 years of A+ onset. Additionally, the entorhinal cortex was the region most sensitive to early amyloid pathology and clinical impairment in this predominantly preclinical sample. Among initially cognitively unimpaired (n = 472) individuals with longitudinal cognitive follow-up, mixed effects models showed significant linear and non-linear interactions of A+ duration and entorhinal tau on cognitive decline, suggesting a synergistic effect whereby greater A+ duration, together with a higher entorhinal tau burden, increases the likelihood of cognitive decline beyond their separable effects. Overall, the amyloid time framework enabled a spatiotemporal characterization of tau deposition patterns across the Alzheimer's disease continuum. This approach, which examined cross-sectional tau PET data along the amyloid timeline to make longitudinal disease course inferences, demonstrated that A+ duration explains a considerable amount of variability in the magnitude and topography of tau spread, which largely recapitulated NFT staging observed in human neuropathological studies. By anchoring disease progression to the onset of amyloid, this study provides a temporal disease context, which may help inform disease prognosis and timing windows for anti-amyloid therapies.
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Affiliation(s)
- Karly A Cody
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
| | - Rebecca E Langhough
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
| | - Matthew D Zammit
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, WI 53792, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Lindsay Clark
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
| | - Nathaniel Chin
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
| | - Bradley T Christian
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, WI 53792, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Tobey J Betthauser
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Sterling C Johnson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
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Xu Y, Sun Z, Jonaitis E, Deming Y, Lu Q, Johnson SC, Engelman CD. Mid-to-Late Life Healthy Lifestyle Modifies Genetic Risk for Longitudinal Cognitive Aging among Asymptomatic Individuals. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.26.24307953. [PMID: 38853902 PMCID: PMC11160812 DOI: 10.1101/2024.05.26.24307953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
IMPORTANCE Genetic and lifestyle factors contribute to an individual's risk of developing Alzheimer's disease. However, it is unknown whether and how adherence to healthy lifestyles can mitigate the genetic risk of Alzheimer's. OBJECTIVE The aim of this study is to investigate whether adherence to healthy lifestyles can modify the impact of genetic predisposition to Alzheimer's disease on later-life cognitive decline. DESIGN SETTING AND PARTICIPANTS This prospective cohort study included 891 adults of European ancestry, aged 40 to 65, who were without dementia and had complete healthy-lifestyle and cognition data during the follow-up. Participants joined the Wisconsin Registry for Alzheimer's Prevention (WRAP) beginning in 2001. We conducted replication analyses using a subsample with similar baseline age range from the Health and Retirement Study (HRS). EXPOSURES We assessed participants' exposures using a continuous non-APOE polygenic risk score for Alzheimer's, a binary indicator for APOE-ε4 carrier status, and a weighted healthy-lifestyle score, including factors such as no current smoking, regular physical activity, healthy diet, light to moderate alcohol consumption, and frequent cognitive activities. MAIN OUTCOMES AND MEASURES We z-standardized cognitive scores for global (Preclinical Alzheimer's Cognitive Composite score 3 - PACC3) and domain-specific assessments (delayed recall and immediate learning). RESULTS We followed 891 individuals for up to 10 years (mean [SD] baseline age, 58 [6] years, 31% male, 38% APOE-ε4 carriers). After false discovery rate (FDR) correction, we found statistically significant PRS × lifestyle × age interactions on preclinical cognitive decline but the evidence is stronger among APOE-ε4 carriers. Among APOE-ε4 carriers, PRS-related differences in overall and memory-related domains between people scoring 0-1 and 4-5 regarding healthy lifestyles became evident around age 67 after FDR correction. These findings were robust across several sensitivity analyses and were replicated in the population-based HRS. CONCLUSION A favorable lifestyle can mitigate the genetic risk associated with current known non-APOE genetic variants for longitudinal cognitive decline, and these protective effects are particularly pronounced among APOE-ε4 carriers.
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Affiliation(s)
- Yuexuan Xu
- G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University
| | - Zhongxuan Sun
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison
| | - Erin Jonaitis
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison
| | - Yuetiva Deming
- G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison
| | - Qiongshi Lu
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison
| | - Sterling C. Johnson
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison
| | - Corinne D. Engelman
- G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University
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Yan D, Hu B, Darst BF, Mukherjee S, Kunkle BW, Deming Y, Dumitrescu L, Wang Y, Naj A, Kuzma A, Zhao Y, Kang H, Johnson SC, Carlos C, Hohman TJ, Crane PK, Engelman CD, Lu Q. Biobank-wide association scan identifies risk factors for late-onset Alzheimer's disease and endophenotypes. eLife 2024; 12:RP91360. [PMID: 38787369 PMCID: PMC11126309 DOI: 10.7554/elife.91360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/25/2024] Open
Abstract
Rich data from large biobanks, coupled with increasingly accessible association statistics from genome-wide association studies (GWAS), provide great opportunities to dissect the complex relationships among human traits and diseases. We introduce BADGERS, a powerful method to perform polygenic score-based biobank-wide association scans. Compared to traditional approaches, BADGERS uses GWAS summary statistics as input and does not require multiple traits to be measured in the same cohort. We applied BADGERS to two independent datasets for late-onset Alzheimer's disease (AD; n=61,212). Among 1738 traits in the UK biobank, we identified 48 significant associations for AD. Family history, high cholesterol, and numerous traits related to intelligence and education showed strong and independent associations with AD. Furthermore, we identified 41 significant associations for a variety of AD endophenotypes. While family history and high cholesterol were strongly associated with AD subgroups and pathologies, only intelligence and education-related traits predicted pre-clinical cognitive phenotypes. These results provide novel insights into the distinct biological processes underlying various risk factors for AD.
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Affiliation(s)
- Donghui Yan
- University of Wisconsin-MadisonMadisonUnited States
| | - Bowen Hu
- Department of Statistics, University of Wisconsin-MadisonMadisonUnited States
| | - Burcu F Darst
- Department of Population Health Sciences, University of Wisconsin-MadisonMadisonUnited States
| | - Shubhabrata Mukherjee
- Division of General Internal Medicine, Department of Medicine, University of WashingtonSeattleUnited States
| | - Brian W Kunkle
- University of Miami Miller School of MedicineMiamiUnited States
| | - Yuetiva Deming
- Department of Population Health Sciences, University of Wisconsin-MadisonMadisonUnited States
| | - Logan Dumitrescu
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Vanderbilt University School of MedicineNashvilleUnited States
| | - Yunling Wang
- University of Wisconsin-MadisonMadisonUnited States
| | - Adam Naj
- School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Amanda Kuzma
- School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Yi Zhao
- School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Hyunseung Kang
- Department of Statistics, University of Wisconsin-MadisonMadisonUnited States
| | - Sterling C Johnson
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public HealthMadisonUnited States
- Geriatric Research Education and Clinical Center, Wm. S. Middleton Memorial VA HospitalMadisonUnited States
- Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public HealthMadisonUnited States
| | - Cruchaga Carlos
- Department of Psychiatry, Washington University in St. LouisSt. LouisUnited States
| | - Timothy J Hohman
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Vanderbilt University School of MedicineNashvilleUnited States
| | - Paul K Crane
- Division of General Internal Medicine, Department of Medicine, University of WashingtonSeattleUnited States
| | - Corinne D Engelman
- Department of Population Health Sciences, University of Wisconsin-MadisonMadisonUnited States
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public HealthMadisonUnited States
- Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public HealthMadisonUnited States
| | | | - Qiongshi Lu
- Department of Statistics, University of Wisconsin-MadisonMadisonUnited States
- Department of Biostatistics and Medical Informatics, University of Wisconsin-MadisonMadisonUnited States
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Lui KK, Dave A, Sprecher KE, Chappel-Farley MG, Riedner BA, Heston MB, Taylor CE, Carlsson CM, Okonkwo OC, Asthana S, Johnson SC, Bendlin BB, Mander BA, Benca RM. Older adults at greater risk for Alzheimer's disease show stronger associations between sleep apnea severity in REM sleep and verbal memory. Alzheimers Res Ther 2024; 16:102. [PMID: 38725033 PMCID: PMC11080222 DOI: 10.1186/s13195-024-01446-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 04/01/2024] [Indexed: 05/12/2024]
Abstract
BACKGROUND Obstructive sleep apnea (OSA) increases risk for cognitive decline and Alzheimer's disease (AD). While the underlying mechanisms remain unclear, hypoxemia during OSA has been implicated in cognitive impairment. OSA during rapid eye movement (REM) sleep is usually more severe than in non-rapid eye movement (NREM) sleep, but the relative effect of oxyhemoglobin desaturation during REM versus NREM sleep on memory is not completely characterized. Here, we examined the impact of OSA, as well as the moderating effects of AD risk factors, on verbal memory in a sample of middle-aged and older adults with heightened AD risk. METHODS Eighty-one adults (mean age:61.7 ± 6.0 years, 62% females, 32% apolipoprotein E ε4 allele (APOE4) carriers, and 70% with parental history of AD) underwent clinical polysomnography including assessment of OSA. OSA features were derived in total, NREM, and REM sleep. REM-NREM ratios of OSA features were also calculated. Verbal memory was assessed with the Rey Auditory Verbal Learning Test (RAVLT). Multiple regression models evaluated the relationships between OSA features and RAVLT scores while adjusting for sex, age, time between assessments, education years, body mass index (BMI), and APOE4 status or parental history of AD. The significant main effects of OSA features on RAVLT performance and the moderating effects of AD risk factors (i.e., sex, age, APOE4 status, and parental history of AD) were examined. RESULTS Apnea-hypopnea index (AHI), respiratory disturbance index (RDI), and oxyhemoglobin desaturation index (ODI) during REM sleep were negatively associated with RAVLT total learning and long-delay recall. Further, greater REM-NREM ratios of AHI, RDI, and ODI (i.e., more events in REM than NREM) were related to worse total learning and recall. We found specifically that the negative association between REM ODI and total learning was driven by adults 60 + years old. In addition, the negative relationships between REM-NREM ODI ratio and total learning, and REM-NREM RDI ratio and long-delay recall were driven by APOE4 carriers. CONCLUSION Greater OSA severity, particularly during REM sleep, negatively affects verbal memory, especially for people with greater AD risk. These findings underscore the potential importance of proactive screening and treatment of REM OSA even if overall AHI appears low.
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Affiliation(s)
- Kitty K Lui
- San Diego State University/University of California San Diego, Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
| | - Abhishek Dave
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
- Department of Cognitive Sciences, University of California, Irvine, CA, USA
| | - Kate E Sprecher
- Department of Population Health Sciences, University of Wisconsin-Madison, Madison, WI, USA
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Miranda G Chappel-Farley
- Department of Neurobiology and Behavior, University of California, Irvine, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, CA, USA
| | - Brady A Riedner
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | - Margo B Heston
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Chase E Taylor
- Department of Neuroscience, University of Kentucky, Lexington, KY, USA
| | - Cynthia M Carlsson
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
- Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Ozioma C Okonkwo
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
- Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Sanjay Asthana
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
- Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Sterling C Johnson
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
- Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Barbara B Bendlin
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
- Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Bryce A Mander
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA.
- Department of Cognitive Sciences, University of California, Irvine, CA, USA.
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, CA, USA.
| | - Ruth M Benca
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA.
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, USA.
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, CA, USA.
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA.
- Department of Psychiatry and Behavioral Medicine, Wake Forest University, Winston-Salem, NC, USA.
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Jonaitis EM, Hermann BP, Mueller KD, Clark LR, Du L, Betthauser TJ, Cody K, Gleason CE, Christian BT, Asthana S, Chappell RJ, Chin NA, Johnson SC, Langhough RE. Longitudinal normative standards for cognitive tests and composites using harmonized data from two Wisconsin AD-risk-enriched cohorts. Alzheimers Dement 2024; 20:3305-3321. [PMID: 38539269 PMCID: PMC11095443 DOI: 10.1002/alz.13774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 02/02/2024] [Accepted: 02/06/2024] [Indexed: 04/06/2024]
Abstract
INTRODUCTION Published norms are typically cross-sectional and often are not sensitive to preclinical cognitive changes due to dementia. We developed and validated demographically adjusted cross-sectional and longitudinal normative standards using harmonized outcomes from two Alzheimer's disease (AD) risk-enriched cohorts. METHODS Data from the Wisconsin Registry for Alzheimer's Prevention and the Wisconsin Alzheimer's Disease Research Center were combined. Quantile regression was used to develop unconditional (cross-sectional) and conditional (longitudinal) normative standards for 18 outcomes using data from cognitively unimpaired participants (N = 1390; mean follow-up = 9.25 years). Validity analyses (N = 2456) examined relationships between percentile scores (centiles), consensus-based cognitive statuses, and AD biomarker levels. RESULTS Unconditional and conditional centiles were lower in those with consensus-based impairment or biomarker positivity. Similarly, quantitative biomarker levels were higher in those whose centiles suggested decline. DISCUSSION This study presents normative standards for cognitive measures sensitive to pre-clinical changes. Future directions will investigate potential clinical applications of longitudinal normative standards. HIGHLIGHTS Quantile regression was used to construct longitudinal norms for cognitive tests. Poorer percentile scores were related to concurrent diagnosis and Alzheimer's disease biomarkers. A ShinyApp was built to display test scores and norms and flag low performance.
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Affiliation(s)
- Erin M. Jonaitis
- Wisconsin Alzheimer's InstituteSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Bruce P. Hermann
- Department of NeurologySchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Kimberly D. Mueller
- Department of Communication Sciences and DisordersUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Division of GeriatricsUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Lindsay R. Clark
- Division of GeriatricsUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans Hospital, MadisonMadisonWisconsinUSA
| | - Lianlian Du
- Wisconsin Alzheimer's InstituteSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Tobey J. Betthauser
- Wisconsin Alzheimer's Disease Research CenterSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Department of MedicineSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Karly Cody
- Wisconsin Alzheimer's Disease Research CenterSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Carey E. Gleason
- Wisconsin Alzheimer's Disease Research CenterSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Division of GeriatricsUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans Hospital, MadisonMadisonWisconsinUSA
- Department of MedicineSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Bradley T. Christian
- Wisconsin Alzheimer's Disease Research CenterSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Waisman CenterUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Department of Medical PhysicsSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Sanjay Asthana
- Wisconsin Alzheimer's Disease Research CenterSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Department of MedicineSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Richard J. Chappell
- Department of StatisticsSchool of ComputerData and Information SciencesUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Department of Biostatistics and Medical InformaticsSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Nathaniel A. Chin
- Wisconsin Alzheimer's Disease Research CenterSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Division of GeriatricsUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Sterling C. Johnson
- Wisconsin Alzheimer's InstituteSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans Hospital, MadisonMadisonWisconsinUSA
- Department of MedicineSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Rebecca E. Langhough
- Wisconsin Alzheimer's InstituteSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Department of MedicineSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
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Erickson CM, Ketchum FB, Basche KE, Chin NA, Eveler ML, Clark LR. Communicating Alzheimer's biomarker results to cognitively unimpaired research participants: Satisfaction, utility, and impact on research attitudes. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2024; 10:e12483. [PMID: 38882702 PMCID: PMC11177175 DOI: 10.1002/trc2.12483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Revised: 04/19/2024] [Accepted: 05/01/2024] [Indexed: 06/18/2024]
Abstract
Introduction Recruitment and retention pose a significant challenge to Alzheimer's disease (AD) research. Returning AD biomarker results to participants has been proposed as a means to improve recruitment and retention. We present findings related to participant satisfaction, utility, and impact on research attitudes from the amyloid positron emission tomography (PET) disclosure sub-study within the Wisconsin Registry for Alzheimer's Prevention (WRAP). Methods Ninety-nine cognitively unimpaired WRAP participants learned their amyloid PET results (mean age ± SD = 72.0 ± 4.8). Measures of reasons for wanting to learn results, study comprehension, result utility, visit satisfaction, research attitudes, and future study enrollment willingness were collected. Between-group, chi-squared analysis was conducted to determine differences by result type (elevated vs. not elevated amyloid PET result) in study comprehension, result utility, and visit satisfaction. Linear mixed-effects modeling was used to evaluate changes in research attitudes and enrollment willingness as a function of time, amyloid result type (elevated/not elevated), and their interaction. Results The reasons most frequently endorsed for wanting to learn amyloid PET result was a "desire to contribute to research on Alzheimer's disease dementia" and "to inform preventative measures [one] might take (e.g., change diet, exercise, or other lifestyle changes)." Overall, participants reported understanding the results and found learning them useful. Satisfaction with the study visits was overwhelmingly high, with over 80% agreeing with visit usefulness and their satisfaction. Few differences were found between participants who learned an elevated and not elevated result. Over the course of the study, participants who learned an elevated amyloid PET result reported higher willingness to enroll in drug trials (beta: 0.12, p = 0.01) and lifestyle interventions (beta: 0.10, p = 0.02) compared to participants who learned a not elevated result. Discussion Formal incorporation of disclosure practices may encourage participant recruitment and retention within AD research. Highlights Participants wanted to learn their amyloid results to contribute to research.Satisfaction with disclosure and post-disclosure visits was high overall.Returning AD biomarkers can increase willingness to participate in research.
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Affiliation(s)
- Claire M Erickson
- Department of Medical Ethics and Health Policy University of Pennsylvania Perelman School of Medicine Philadelphia Pennsylvania USA
| | - Fred B Ketchum
- Department of Neurology University of Wisconsin School of Medicine and Public Health Madison USA
| | - Kristin E Basche
- Department of Medicine Division of Geriatrics & Gerontology University of Wisconsin School of Medicine and Public Health Madison Wisconsin USA
| | - Nathaniel A Chin
- Department of Medicine Division of Geriatrics & Gerontology University of Wisconsin School of Medicine and Public Health Madison Wisconsin USA
| | - Marcella L Eveler
- Department of Medicine Division of Geriatrics & Gerontology University of Wisconsin School of Medicine and Public Health Madison Wisconsin USA
| | - Lindsay R Clark
- Department of Medicine Division of Geriatrics & Gerontology University of Wisconsin School of Medicine and Public Health Madison Wisconsin USA
- Geriatric Research Education and Clinical Center William S. Middleton Memorial Veterans Hospital Madison Wisconsin USA
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19
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Hamsanathan S, Anthonymuthu T, Prosser D, Lokshin A, Greenspan SL, Resnick NM, Perera S, Okawa S, Narasimhan G, Gurkar AU. A molecular index for biological age identified from the metabolome and senescence-associated secretome in humans. Aging Cell 2024; 23:e14104. [PMID: 38454639 PMCID: PMC11019119 DOI: 10.1111/acel.14104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Revised: 01/26/2024] [Accepted: 01/31/2024] [Indexed: 03/09/2024] Open
Abstract
Unlike chronological age, biological age is a strong indicator of health of an individual. However, the molecular fingerprint associated with biological age is ill-defined. To define a high-resolution signature of biological age, we analyzed metabolome, circulating senescence-associated secretome (SASP)/inflammation markers and the interaction between them, from a cohort of healthy and rapid agers. The balance between two fatty acid oxidation mechanisms, β-oxidation and ω-oxidation, associated with the extent of functional aging. Furthermore, a panel of 25 metabolites, Healthy Aging Metabolic (HAM) index, predicted healthy agers regardless of gender and race. HAM index was also validated in an independent cohort. Causal inference with machine learning implied three metabolites, β-cryptoxanthin, prolylhydroxyproline, and eicosenoylcarnitine as putative drivers of biological aging. Multiple SASP markers were also elevated in rapid agers. Together, our findings reveal that a network of metabolic pathways underlie biological aging, and the HAM index could serve as a predictor of phenotypic aging in humans.
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Affiliation(s)
- Shruthi Hamsanathan
- Aging Institute of UPMC and the University of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Tamil Anthonymuthu
- Department of Critical Care MedicineUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Denise Prosser
- Department of MedicineUniversity of Pittsburgh Medical Center and University of Pittsburgh Cancer InstitutePittsburghPennsylvaniaUSA
| | - Anna Lokshin
- Department of MedicineUniversity of Pittsburgh Medical Center and University of Pittsburgh Cancer InstitutePittsburghPennsylvaniaUSA
| | - Susan L. Greenspan
- Division of Geriatric Medicine, Department of MedicineUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Neil M. Resnick
- Aging Institute of UPMC and the University of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
- Division of Geriatric Medicine, Department of MedicineUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Subashan Perera
- Division of Geriatric Medicine, Department of MedicineUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
- Department of BiostatisticsUniversity of Pittsburgh Graduate School of Public HealthPittsburghPennsylvaniaUSA
| | - Satoshi Okawa
- Pittsburgh Heart, Lung, and Blood Vascular Medicine InstituteUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
- Department of Computational and Systems BiologyUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
- McGowan Institute for Regenerative MedicineUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Giri Narasimhan
- Bioinformatics Research Group (BioRG), School of Computing and Information Sciences, Biomolecular Sciences InstituteFlorida International UniversityMiamiFloridaUSA
| | - Aditi U. Gurkar
- Aging Institute of UPMC and the University of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
- Division of Geriatric Medicine, Department of MedicineUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
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20
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Martinelli F, Heinken A, Henning AK, Ulmer MA, Hensen T, González A, Arnold M, Asthana S, Budde K, Engelman CD, Estaki M, Grabe HJ, Heston MB, Johnson S, Kastenmüller G, Martino C, McDonald D, Rey FE, Kilimann I, Peters O, Wang X, Spruth EJ, Schneider A, Fliessbach K, Wiltfang J, Hansen N, Glanz W, Buerger K, Janowitz D, Laske C, Munk MH, Spottke A, Roy N, Nauck M, Teipel S, Knight R, Kaddurah-Daouk RF, Bendlin BB, Hertel J, Thiele I. Whole-body metabolic modelling reveals microbiome and genomic interactions on reduced urine formate levels in Alzheimer's disease. Sci Rep 2024; 14:6095. [PMID: 38480804 PMCID: PMC10937638 DOI: 10.1038/s41598-024-55960-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 02/29/2024] [Indexed: 03/17/2024] Open
Abstract
In this study, we aimed to understand the potential role of the gut microbiome in the development of Alzheimer's disease (AD). We took a multi-faceted approach to investigate this relationship. Urine metabolomics were examined in individuals with AD and controls, revealing decreased formate and fumarate concentrations in AD. Additionally, we utilised whole-genome sequencing (WGS) data obtained from a separate group of individuals with AD and controls. This information allowed us to create and investigate host-microbiome personalised whole-body metabolic models. Notably, AD individuals displayed diminished formate microbial secretion in these models. Additionally, we identified specific reactions responsible for the production of formate in the host, and interestingly, these reactions were linked to genes that have correlations with AD. This study suggests formate as a possible early AD marker and highlights genetic and microbiome contributions to its production. The reduced formate secretion and its genetic associations point to a complex connection between gut microbiota and AD. This holistic understanding might pave the way for novel diagnostic and therapeutic avenues in AD management.
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Affiliation(s)
- Filippo Martinelli
- School of Medicine, University of Galway, Galway, Ireland
- The Ryan Institute, University of Galway, Galway, Ireland
| | - Almut Heinken
- School of Medicine, University of Galway, Galway, Ireland
- The Ryan Institute, University of Galway, Galway, Ireland
- Inserm UMRS 1256 NGERE, University of Lorraine, Nancy, France
| | - Ann-Kristin Henning
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Maria A Ulmer
- Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Tim Hensen
- School of Medicine, University of Galway, Galway, Ireland
- The Ryan Institute, University of Galway, Galway, Ireland
| | - Antonio González
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Matthias Arnold
- Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Department of Psychiatry and Behavioural Sciences, Duke University, Durham, NC, USA
| | - Sanjay Asthana
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, USA
| | - Kathrin Budde
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Corinne D Engelman
- Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Mehrbod Estaki
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Hans-Jörgen Grabe
- German Center of Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Germany
| | - Margo B Heston
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, USA
| | - Sterling Johnson
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, USA
| | - Gabi Kastenmüller
- Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Cameron Martino
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Daniel McDonald
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Federico E Rey
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA
| | - Ingo Kilimann
- German Center of Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, University Medicine Rostock, Rostock, Germany
| | - Olive Peters
- German Center of Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Xiao Wang
- Department of Psychiatry, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Eike Jakob Spruth
- German Center of Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité, Berlin, Germany
| | - Anja Schneider
- German Center of Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, University of Bonn, Bonn, Germany
| | - Klaus Fliessbach
- German Center of Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, University of Bonn, Bonn, Germany
| | - Jens Wiltfang
- German Center of Neurodegenerative Diseases (DZNE), Goettingen, Germany
- Department of Psychiatry and Psychotherapy, University of Goettingen, Goettingen, Germany
- Neurosciences and Signaling Group, Department of Medical Sciences, Institute of Biomedicine (iBiMED), University of Aveiro, Aveiro, Portugal
| | - Niels Hansen
- Department of Psychiatry and Psychotherapy, University of Goettingen, Goettingen, Germany
| | - Wenzel Glanz
- German Center of Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Katharina Buerger
- German Center of Neurodegenerative Diseases (DZNE), Munich, Germany
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Daniel Janowitz
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Christoph Laske
- German Center of Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Section for Dementia Research, Hertie Institute for Clinical Brain Research, Tübingen, Germany
- Section for Dementia Research, Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Matthias H Munk
- German Center of Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Section for Dementia Research, Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Annika Spottke
- German Center of Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, University of Bonn, Bonn, Germany
| | - Nina Roy
- German Center of Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine, Greifswald, Germany
| | - Stefan Teipel
- German Center of Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, University Medicine Rostock, Rostock, Germany
| | - Rob Knight
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
- Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA
- Shu Chien-Gene Lay Department of Engineering, University of California San Diego, La Jolla, CA, USA
- Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA, USA
| | | | - Barbara B Bendlin
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, USA
| | - Johannes Hertel
- School of Medicine, University of Galway, Galway, Ireland.
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine, Greifswald, Germany.
| | - Ines Thiele
- School of Medicine, University of Galway, Galway, Ireland.
- The Ryan Institute, University of Galway, Galway, Ireland.
- School of Microbiology, University of Galway, Galway, Ireland.
- APC Microbiome Ireland, Cork, Ireland.
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21
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Jonaitis EM, Jeffers B, VandenLangenberg M, Ma Y, Van Hulle C, Langhough R, Du L, Chin NA, Przybelski RJ, Hogan KJ, Christian BT, Betthauser TJ, Okonkwo OC, Bendlin BB, Asthana S, Carlsson CM, Johnson SC. CSF Biomarkers in Longitudinal Alzheimer Disease Cohorts: Pre-Analytic Challenges. Clin Chem 2024; 70:538-550. [PMID: 38431278 PMCID: PMC10908554 DOI: 10.1093/clinchem/hvad221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 11/27/2023] [Indexed: 03/05/2024]
Abstract
BACKGROUND The sensitivity of amyloid to pre-analytic factors complicates cerebrospinal fluid (CSF) diagnostics for Alzheimer disease. We report reliability and validity evidence for automated immunoassays from frozen and fresh CSF samples in an ongoing, single-site research program. METHODS CSF samples were obtained from 2 Wisconsin cohorts (1256 measurements; 727 participants). Levels of amyloid beta 1-42 (Aβ42), phosphorylated tau 181 (pTau181), and total tau (tTau) were obtained using an Elecsys cobas e 601 platform. Repeatability and fixed effects of storage tube type, extraction method, and freezing were assessed via mixed models. Concordance with amyloid positron emission tomography (PET) was investigated with 238 participants having a temporally proximal PET scan. RESULTS Repeatability was high with intraclass correlation (ICC) ≥0.9, but tube type strongly affected measurements. Discriminative accuracy for PET amyloid positivity was strong across tube types (area under the curve [AUC]: Aβ42, 0.87; pTau181Aβ42 , 0.96), although optimal thresholds differed. CONCLUSIONS Under real-world conditions, the Elecsys platform had high repeatability. However, strong effects of pre-analytic factors suggest caution in drawing longitudinal inferences.
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Affiliation(s)
- Erin M Jonaitis
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
| | - Beckie Jeffers
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
| | - Monica VandenLangenberg
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
| | - Yue Ma
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
| | - Carol Van Hulle
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
| | - Rebecca Langhough
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
| | - Lianlian Du
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
| | - Nathaniel A Chin
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
| | - Robert J Przybelski
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
| | - Kirk J Hogan
- Department of Anesthesiology, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
| | - Bradley T Christian
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
- Department of Psychiatry, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
| | - Tobey J Betthauser
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
| | - Ozioma C Okonkwo
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
| | - Barbara B Bendlin
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
| | - Sanjay Asthana
- Geriatric Research Education and Clinical Center of the Wm. S. Middleton Memorial Veterans Hospital, Madison, WI, United States
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
| | - Cynthia M Carlsson
- Geriatric Research Education and Clinical Center of the Wm. S. Middleton Memorial Veterans Hospital, Madison, WI, United States
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
| | - Sterling C Johnson
- Geriatric Research Education and Clinical Center of the Wm. S. Middleton Memorial Veterans Hospital, Madison, WI, United States
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin—Madison, Madison, WI, United States
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22
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Ashton NJ, Brum WS, Di Molfetta G, Benedet AL, Arslan B, Jonaitis E, Langhough RE, Cody K, Wilson R, Carlsson CM, Vanmechelen E, Montoliu-Gaya L, Lantero-Rodriguez J, Rahmouni N, Tissot C, Stevenson J, Servaes S, Therriault J, Pascoal T, Lleó A, Alcolea D, Fortea J, Rosa-Neto P, Johnson S, Jeromin A, Blennow K, Zetterberg H. Diagnostic Accuracy of a Plasma Phosphorylated Tau 217 Immunoassay for Alzheimer Disease Pathology. JAMA Neurol 2024; 81:255-263. [PMID: 38252443 PMCID: PMC10804282 DOI: 10.1001/jamaneurol.2023.5319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 11/10/2023] [Indexed: 01/23/2024]
Abstract
Importance Phosphorylated tau (p-tau) is a specific blood biomarker for Alzheimer disease (AD) pathology, with p-tau217 considered to have the most utility. However, availability of p-tau217 tests for research and clinical use has been limited. Expanding access to this highly accurate AD biomarker is crucial for wider evaluation and implementation of AD blood tests. Objective To determine the utility of a novel and commercially available immunoassay for plasma p-tau217 to detect AD pathology and evaluate reference ranges for abnormal amyloid β (Aβ) and longitudinal change across 3 selected cohorts. Design, Setting, and Participants This cohort study examined data from 3 single-center observational cohorts: cross-sectional and longitudinal data from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort (visits October 2017-August 2021) and Wisconsin Registry for Alzheimer's Prevention (WRAP) cohort (visits February 2007-November 2020) and cross-sectional data from the Sant Pau Initiative on Neurodegeneration (SPIN) cohort (baseline visits March 2009-November 2021). Participants included individuals with and without cognitive impairment grouped by amyloid and tau (AT) status using PET or CSF biomarkers. Data were analyzed from February to June 2023. Exposures Magnetic resonance imaging, Aβ positron emission tomography (PET), tau PET, cerebrospinal fluid (CSF) biomarkers (Aβ42/40 and p-tau immunoassays), and plasma p-tau217 (ALZpath pTau217 assay). Main Outcomes and Measures Accuracy of plasma p-tau217 in detecting abnormal amyloid and tau pathology, longitudinal p-tau217 change according to baseline pathology status. Results The study included 786 participants (mean [SD] age, 66.3 [9.7] years; 504 females [64.1%] and 282 males [35.9%]). High accuracy was observed in identifying elevated Aβ (area under the curve [AUC], 0.92-0.96; 95% CI, 0.89-0.99) and tau pathology (AUC, 0.93-0.97; 95% CI, 0.84-0.99) across all cohorts. These accuracies were comparable with CSF biomarkers in determining abnormal PET signal. The detection of abnormal Aβ pathology using a 3-range reference yielded reproducible results and reduced confirmatory testing by approximately 80%. Longitudinally, plasma p-tau217 values showed an annual increase only in Aβ-positive individuals, with the highest increase observed in those with tau positivity. Conclusions and Relevance This study found that a commercially available plasma p-tau217 immunoassay accurately identified biological AD, comparable with results using CSF biomarkers, with reproducible cut-offs across cohorts. It detected longitudinal changes, including at the preclinical stage.
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Affiliation(s)
- Nicholas J. Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience Maurice Wohl Institute Clinical Neuroscience Institute, London, United Kingdom
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, United Kingdom
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Wagner S. Brum
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Guglielmo Di Molfetta
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Andrea L. Benedet
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Burak Arslan
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Erin Jonaitis
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
| | - Rebecca E. Langhough
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
| | - Karly Cody
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
| | - Rachael Wilson
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
| | - Cynthia M. Carlsson
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Geriatric Research Education and Clinical Center of the Wm. S. Middleton Memorial Veterans Hospital, Madison, Wisconsin
| | | | - Laia Montoliu-Gaya
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Juan Lantero-Rodriguez
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Nesrine Rahmouni
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre Intégré Universitaire de Santé et de Services Sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Cecile Tissot
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre Intégré Universitaire de Santé et de Services Sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Jenna Stevenson
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre Intégré Universitaire de Santé et de Services Sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Stijn Servaes
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre Intégré Universitaire de Santé et de Services Sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre Intégré Universitaire de Santé et de Services Sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Tharick Pascoal
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Alberto Lleó
- Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau, Hospital de Sant Pau, Universitat Autònoma de Barcelona, Hospital de la Santa Creu i Sant Pau, Barcelona, Catalunya
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Daniel Alcolea
- Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau, Hospital de Sant Pau, Universitat Autònoma de Barcelona, Hospital de la Santa Creu i Sant Pau, Barcelona, Catalunya
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Juan Fortea
- Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau, Hospital de Sant Pau, Universitat Autònoma de Barcelona, Hospital de la Santa Creu i Sant Pau, Barcelona, Catalunya
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre Intégré Universitaire de Santé et de Services Sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Sterling Johnson
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
| | | | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom
- UK Dementia Research Institute at UCL, London, United Kingdom
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
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Breen C, Papale LA, Clark LR, Bergmann PE, Madrid A, Asthana S, Johnson SC, Keleş S, Alisch RS, Hogan KJ. Whole genome methylation sequencing in blood identifies extensive differential DNA methylation in late-onset dementia due to Alzheimer's disease. Alzheimers Dement 2024; 20:1050-1062. [PMID: 37856321 PMCID: PMC10916976 DOI: 10.1002/alz.13514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 08/17/2023] [Accepted: 09/25/2023] [Indexed: 10/21/2023]
Abstract
INTRODUCTION DNA microarray-based studies report differentially methylated positions (DMPs) in blood between late-onset dementia due to Alzheimer's disease (AD) and cognitively unimpaired individuals, but interrogate < 4% of the genome. METHODS We used whole genome methylation sequencing (WGMS) to quantify DNA methylation levels at 25,409,826 CpG loci in 281 blood samples from 108 AD and 173 cognitively unimpaired individuals. RESULTS WGMS identified 28,038 DMPs throughout the human methylome, including 2707 differentially methylated genes (e.g., SORCS3, GABA, and PICALM) encoding proteins in biological pathways relevant to AD such as synaptic membrane, cation channel complex, and glutamatergic synapse. One hundred seventy-three differentially methylated blood-specific enhancers interact with the promoters of 95 genes that are differentially expressed in blood from persons with and without AD. DISCUSSION WGMS identifies differentially methylated CpGs in known and newly detected genes and enhancers in blood from persons with and without AD. HIGHLIGHTS Whole genome DNA methylation levels were quantified in blood from persons with and without Alzheimer's disease (AD). Twenty-eight thousand thirty-eight differentially methylated positions (DMPs) were identified. Two thousand seven hundred seven genes comprise DMPs. Forty-eight of 75 independent genetic risk loci for AD have DMPs. One thousand five hundred sixty-eight blood-specific enhancers comprise DMPs, 173 of which interact with the promoters of 95 genes that are differentially expressed in blood from persons with and without AD.
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Affiliation(s)
- Coleman Breen
- Department of StatisticsUniversity of Wisconsin, Medical Sciences CenterMadisonWisconsinUSA
| | - Ligia A. Papale
- Department of Neurological SurgeryUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Lindsay R. Clark
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans HospitalMadisonWisconsinUSA
| | - Phillip E. Bergmann
- Department of Neurological SurgeryUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Andy Madrid
- Department of Neurological SurgeryUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Sanjay Asthana
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans HospitalMadisonWisconsinUSA
- Wisconsin Alzheimer's InstituteUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Sterling C. Johnson
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans HospitalMadisonWisconsinUSA
- Wisconsin Alzheimer's InstituteUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Sündüz Keleş
- Department of StatisticsUniversity of Wisconsin, Medical Sciences CenterMadisonWisconsinUSA
- Department of Biostatistics and Medical InformaticsUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Reid S. Alisch
- Department of Neurological SurgeryUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Kirk J. Hogan
- Wisconsin Alzheimer's InstituteUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Department of AnesthesiologyUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
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Jauregi Zinkunegi A, Bruno D, Betthauser TJ, Koscik RL, Asthana S, Chin NA, Hermann BP, Johnson SC, Mueller KD. A comparison of story-recall metrics to predict hippocampal volume in older adults with and without cognitive impairment. Clin Neuropsychol 2024; 38:453-470. [PMID: 37349970 PMCID: PMC10739621 DOI: 10.1080/13854046.2023.2223389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 06/05/2023] [Indexed: 06/24/2023]
Abstract
Objective: Process-based scores of episodic memory tests, such as the recency ratio (Rr), have been found to compare favourably to, or to be better than, most conventional or "traditional" scores employed to estimate memory ability in older individuals (Bock et al., 2021; Bruno et al., 2019). We explored the relationship between process-based scores and hippocampal volume in older adults, while comparing process-based to traditional story recall-derived scores, to examine potential differences in their predictive abilities. Methods: We analysed data from 355 participants extracted from the WRAP and WADRC databases, who were classified as cognitively unimpaired, or exhibited mild cognitive impairment (MCI) or dementia. Story Recall was measured with the Logical Memory Test (LMT) from the Weschler Memory Scale Revised, collected within twelve months of the magnetic resonance imaging scan. Linear regression analyses were conducted with left or right hippocampal volume (HV) as outcomes separately, and with Rr, Total ratio, Immediate LMT, or Delayed LMT scores as predictors, along with covariates. Results: Higher Rr and Tr scores significantly predicted lower left and right HV, while Tr showed the best model fit of all, as indicated by AIC. Traditional scores, Immediate LMT and Delayed LMT, were significantly associated with left and right HV, but were outperformed by both process-based scores for left HV, and by Tr for right HV. Conclusions: Current findings show the direct relationship between hippocampal volume and all the LMT scores examined here, and that process-based scores outperform traditional scores as markers of hippocampal volume.
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Affiliation(s)
| | - Davide Bruno
- School of Psychology, Liverpool John Moores University, UK
| | - Tobey J. Betthauser
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin – Madison, Madison, WI, USA
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin – Madison, Madison, WI, USA
| | - Rebecca Langhough Koscik
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin – Madison, Madison, WI, USA
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin – Madison, Madison, WI, USA
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin – Madison, Madison, WI, USA
| | - Sanjay Asthana
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin – Madison, Madison, WI, USA
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin – Madison, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Veterans Hospital, Madison, WI, USA
| | - Nathaniel A. Chin
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin – Madison, Madison, WI, USA
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin – Madison, Madison, WI, USA
| | - Bruce P. Hermann
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin – Madison, Madison, WI, USA
- Department of Neurology, University of Wisconsin – Madison, Madison, WI, USA
| | - Sterling C. Johnson
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin – Madison, Madison, WI, USA
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin – Madison, Madison, WI, USA
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin – Madison, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Veterans Hospital, Madison, WI, USA
| | - Kimberly D. Mueller
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin – Madison, Madison, WI, USA
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin – Madison, Madison, WI, USA
- Department of Communication Sciences and Disorders, University of Wisconsin-Madison, Madison, WI, USA
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Xu Y, Sun Z, Jonaitis E, Deming Y, Lu Q, Johnson SC, Engelman CD. Apolipoprotein E moderates the association between non-APOE polygenic risk score for Alzheimer's disease and aging on preclinical cognitive function. Alzheimers Dement 2024; 20:1063-1075. [PMID: 37858606 PMCID: PMC10916952 DOI: 10.1002/alz.13515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 09/01/2023] [Accepted: 09/25/2023] [Indexed: 10/21/2023]
Abstract
INTRODUCTION Variation in preclinical cognitive decline suggests additional genetic factors related to Alzheimer's disease (eg, a non-APOE polygenic risk score [PRS]) may interact with the APOE ε4 allele to influence cognitive decline. METHODS We tested the PRS × APOE ε4 × age interaction on preclinical cognition using longitudinal data from the Wisconsin Registry for Alzheimer's Prevention. All analyses were fitted using a linear mixed-effects model and adjusted for within individual/family correlation among 1190 individuals. RESULTS We found statistically significant PRS × APOE ε4 × age interactions on immediate learning (P = 0.038), delayed recall (P < 0.001), and Preclinical Alzheimer's Cognitive Composite 3 score (P = 0.026). PRS-related differences in overall and memory-related cognitive domains between people with and without APOE ε4 emerge around age 70, with a much stronger adverse PRS effect among APOE ε4 carriers. The findings were replicated in a population-based cohort. DISCUSSIONS APOE ε4 can modify the association between PRS and cognition decline. HIGHLIGHTS APOE ε4 can modify the association between polygenic risk scores (PRSs) and longitudinal cognition decline, with the modifying effects more pronounced when the PRS is constructed using a conservative P threshold (eg, P < 5e-8 ). The adverse genetic effect caused by the combined effect of the currently known genetic variants is more detrimental among APOE ε4 carriers around age 70. Individuals who are APOE ε4 carriers with high PRSs are the most vulnerable to the harmful effects caused by genetic burden.
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Affiliation(s)
- Yuexuan Xu
- Department of Population Health ScienceSchool of Medicine and Public HealthUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Zhongxuan Sun
- Department of Biostatistics and Medical InformaticsSchool of Medicine and Public HealthUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Erin Jonaitis
- Wisconsin Alzheimer's InstituteUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Yuetiva Deming
- Department of Population Health ScienceSchool of Medicine and Public HealthUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of MedicineSchool of Medicine and Public HealthUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Qiongshi Lu
- Department of Biostatistics and Medical InformaticsSchool of Medicine and Public HealthUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Sterling C. Johnson
- Wisconsin Alzheimer's InstituteUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of MedicineSchool of Medicine and Public HealthUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Corinne D. Engelman
- Department of Population Health ScienceSchool of Medicine and Public HealthUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
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26
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Erickson CM, Chin NA, Ketchum FB, Eveler ML, Conway CE, Coughlin DM, Clark LR. The Room Where It Happens: Clinician Reflections on Returning Preclinical Alzheimer's Biomarker Results to Research Participants. J Prev Alzheimers Dis 2024; 11:1-6. [PMID: 38230711 PMCID: PMC10794852 DOI: 10.14283/jpad.2023.88] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2024]
Abstract
Disclosing Alzheimer's disease (AD) biomarkers to research participants is a growing practice. Here, we aim to synthesize the experiences of clinicians leading preclinical AD biomarker disclosure. Semi-structured interviews were conducted individually with each of the four clinicians conducting biomarker disclosure as a part of a longitudinal, observational AD cohort study. Study clinicians emphasized the importance of participant education, having adequate time available for the disclosure visit, and forms to facilitate disclosure. To train and support future clinicians conducting AD biomarker disclosure, our study clinicians highlighted providing information about AD and biomarkers, shadowing a disclosure visit, having team debriefing sessions, and collating a frequently asked questions document. To date, this is the first characterization of clinician reflections on disclosing AD biomarker result to cognitively unimpaired research participants. As more clinicians in research or clinical settings seek to disclose AD biomarker results, best practices for training clinicians to lead disclosure are necessary.
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Affiliation(s)
- C M Erickson
- Lindsay Clark, PhD, Clinical Science Center, 600 Highland Ave. J5/1 Mezzanine, Madison, WI 53792, USA,
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27
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Hale MR, Langhough R, Du L, Hermann BP, Van Hulle CA, Carboni M, Kollmorgen G, Basche KE, Bruno D, Sanson-Miles L, Jonaitis EM, Chin NA, Okonkwo OC, Bendlin BB, Carlsson CM, Zetterberg H, Blennow K, Betthauser TJ, Johnson SC, Mueller KD. Associations between recall of proper names in story recall and CSF amyloid and tau in adults without cognitive impairment. Neurobiol Aging 2024; 133:87-98. [PMID: 37925995 PMCID: PMC10842469 DOI: 10.1016/j.neurobiolaging.2023.09.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 09/26/2023] [Accepted: 09/28/2023] [Indexed: 11/07/2023]
Abstract
Neuropsychological measures sensitive to decline in the preclinical phase of Alzheimer's disease are needed. We previously demonstrated that higher amyloid-beta (Aβ) assessed by positron emission tomography in adults without cognitive impairment was associated with recall of fewer proper names in Logical Memory story recall. The current study investigated the association between proper names and cerebrospinal fluid biomarkers (Aβ42/40, phosphorylated tau181 [pTau181], neurofilament light) in 223 participants from the Wisconsin Registry for Alzheimer's Prevention. We assessed associations between biomarkers and delayed Logical Memory total score and proper names using binary logistic regressions. Sensitivity analyses used multinomial logistic regression and stratified biomarker groups. Lower Logical Memory total score and proper names scores from the most recent visit were associated with biomarker positivity. Relatedly, there was a 27% decreased risk of being classified Aβ42/40+/pTau181+ for each additional proper name recalled. A linear mixed effects model found that longitudinal change in proper names recall was predicted by biomarker status. These results demonstrate a novel relationship between proper names and Alzheimer's disease-cerebrospinal fluid pathology.
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Affiliation(s)
- Madeline R Hale
- Department of Communication Sciences and Disorders, University of Wisconsin-Madison, Madison, WI, USA
| | - Rebecca Langhough
- Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
| | - Lianlian Du
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Bruce P Hermann
- Department of Neurology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Carol A Van Hulle
- Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin School of Medicine & Public Health, Madison, WI, USA
| | | | | | - Kristin E Basche
- Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
| | - Davide Bruno
- School of Psychology, Liverpool John Moores University, Liverpool, UK
| | - Leah Sanson-Miles
- Department of Communication Sciences and Disorders, University of Wisconsin-Madison, Madison, WI, USA
| | - Erin M Jonaitis
- Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
| | - Nathaniel A Chin
- Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin School of Medicine & Public Health, Madison, WI, USA; VA Geriatric Research, Education and Clinical Center (GRECC), William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Ozioma C Okonkwo
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Barbara B Bendlin
- Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin School of Medicine & Public Health, Madison, WI, USA; VA Geriatric Research, Education and Clinical Center (GRECC), William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Cynthia M Carlsson
- Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin School of Medicine & Public Health, Madison, WI, USA
| | - Henrik Zetterberg
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK; UK Dementia Research Institute at UCL, London, UK; Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Tobey J Betthauser
- Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin School of Medicine & Public Health, Madison, WI, USA
| | - Sterling C Johnson
- Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin School of Medicine & Public Health, Madison, WI, USA; VA Geriatric Research, Education and Clinical Center (GRECC), William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Kimberly D Mueller
- Department of Communication Sciences and Disorders, University of Wisconsin-Madison, Madison, WI, USA; Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA.
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Ashford MT, Jin C, Neuhaus J, Diaz A, Aaronson A, Tank R, Eichenbaum J, Camacho MR, Fockler J, Ulbricht A, Flenniken D, Truran D, Mackin RS, Weiner MW, Mindt MR, Nosheny RL. Participant completion of longitudinal assessments in an online cognitive aging registry: The role of medical conditions. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2024; 10:e12438. [PMID: 38188606 PMCID: PMC10767283 DOI: 10.1002/trc2.12438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 11/08/2023] [Accepted: 11/16/2023] [Indexed: 01/09/2024]
Abstract
INTRODUCTION This study aimed to understand whether older adults' longitudinal completion of assessments in an online Alzheimer's disease and related dementias (ADRD)-related registry is influenced by self-reported medical conditions. METHODS Brain Health Registry (BHR) is an online cognitive aging and ADRD-related research registry that includes longitudinal health and cognitive assessments. Using logistic regressions, we examined associations between longitudinal registry completion outcomes and self-reported (1) number of medical conditions and (2) eight defined medical condition groups (cardiovascular, metabolic, immune system, ADRD, current psychiatric, substance use/abuse, acquired, other specified conditions) in adults aged 55+ (N = 23,888). Longitudinal registry completion outcomes were assessed by the completion of the BHR initial questionnaire (first questionnaire participants see at each visit) at least twice and completion of a cognitive assessment (Cogstate Brief Battery) at least twice. Models included ethnocultural identity, education, age, and subjective memory concern as covariates. RESULTS We found that the likelihood of longitudinally completing the initial questionnaire was negatively associated with reporting a diagnosis of ADRD and current psychiatric conditions but was positively associated with reporting substance use/abuse and acquired medical conditions. The likelihood of longitudinally completing the cognitive assessment task was negatively associated with number of reported medical conditions, as well as with reporting cardiovascular conditions, ADRD, and current psychiatric conditions. Previously identified associations between ethnocultural identity and longitudinal assessment completion in BHR remained after accounting for the presence of medical conditions. DISCUSSION This post hoc analysis provides novel, initial evidence that older adults' completion of longitudinal assessments in an online registry is associated with the number and types of participant-reported medical conditions. Our findings can inform future efforts to make online studies with longitudinal health and cognitive assessments more usable for older adults with medical conditions. The results need to be interpreted with caution due to selection biases, and the under-inclusion of minoritized communities.
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Affiliation(s)
- Miriam T. Ashford
- VA Advanced Imaging Research CenterSan Francisco Veteran's Administration Medical CenterSan FranciscoCaliforniaUSA
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
| | - Chengshi Jin
- University of California San Francisco Department of Epidemiology and Biostatistics San FranciscoSan FranciscoCaliforniaUSA
| | - John Neuhaus
- University of California San Francisco Department of Epidemiology and Biostatistics San FranciscoSan FranciscoCaliforniaUSA
| | - Adam Diaz
- VA Advanced Imaging Research CenterSan Francisco Veteran's Administration Medical CenterSan FranciscoCaliforniaUSA
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
| | - Anna Aaronson
- VA Advanced Imaging Research CenterSan Francisco Veteran's Administration Medical CenterSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Rachana Tank
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Dementia Research CentreUCL Institute of NeurologyUniversity College LondonLondonUK
| | - Joseph Eichenbaum
- VA Advanced Imaging Research CenterSan Francisco Veteran's Administration Medical CenterSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Monica R. Camacho
- VA Advanced Imaging Research CenterSan Francisco Veteran's Administration Medical CenterSan FranciscoCaliforniaUSA
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
| | - Juliet Fockler
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Aaron Ulbricht
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Derek Flenniken
- VA Advanced Imaging Research CenterSan Francisco Veteran's Administration Medical CenterSan FranciscoCaliforniaUSA
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
| | - Diana Truran
- VA Advanced Imaging Research CenterSan Francisco Veteran's Administration Medical CenterSan FranciscoCaliforniaUSA
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
| | - Robert Scott Mackin
- VA Advanced Imaging Research CenterSan Francisco Veteran's Administration Medical CenterSan FranciscoCaliforniaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Michael W. Weiner
- VA Advanced Imaging Research CenterSan Francisco Veteran's Administration Medical CenterSan FranciscoCaliforniaUSA
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of MedicineUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Monica Rivera Mindt
- Psychology, Latin American Latino Studies Institute& African and African American StudiesFordham UniversityJoint Appointment in NeurologyIcahn School of Medicine at Mount Sinai ‐ New YorkNew YorkNew YorkUSA
| | - Rachel L. Nosheny
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
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Yang Z, Wen J, Erus G, Govindarajan ST, Melhem R, Mamourian E, Cui Y, Srinivasan D, Abdulkadir A, Parmpi P, Wittfeld K, Grabe HJ, Bülow R, Frenzel S, Tosun D, Bilgel M, An Y, Yi D, Marcus DS, LaMontagne P, Benzinger TL, Heckbert SR, Austin TR, Waldstein SR, Evans MK, Zonderman AB, Launer LJ, Sotiras A, Espeland MA, Masters CL, Maruff P, Fripp J, Toga A, O’Bryant S, Chakravarty MM, Villeneuve S, Johnson SC, Morris JC, Albert MS, Yaffe K, Völzke H, Ferrucci L, Bryan NR, Shinohara RT, Fan Y, Habes M, Lalousis PA, Koutsouleris N, Wolk DA, Resnick SM, Shou H, Nasrallah IM, Davatzikos C. Five dominant dimensions of brain aging are identified via deep learning: associations with clinical, lifestyle, and genetic measures. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.29.23300642. [PMID: 38234857 PMCID: PMC10793523 DOI: 10.1101/2023.12.29.23300642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Brain aging is a complex process influenced by various lifestyle, environmental, and genetic factors, as well as by age-related and often co-existing pathologies. MRI and, more recently, AI methods have been instrumental in understanding the neuroanatomical changes that occur during aging in large and diverse populations. However, the multiplicity and mutual overlap of both pathologic processes and affected brain regions make it difficult to precisely characterize the underlying neurodegenerative profile of an individual from an MRI scan. Herein, we leverage a state-of-the art deep representation learning method, Surreal-GAN, and present both methodological advances and extensive experimental results that allow us to elucidate the heterogeneity of brain aging in a large and diverse cohort of 49,482 individuals from 11 studies. Five dominant patterns of neurodegeneration were identified and quantified for each individual by their respective (herein referred to as) R-indices. Significant associations between R-indices and distinct biomedical, lifestyle, and genetic factors provide insights into the etiology of observed variances. Furthermore, baseline R-indices showed predictive value for disease progression and mortality. These five R-indices contribute to MRI-based precision diagnostics, prognostication, and may inform stratification into clinical trials.
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Affiliation(s)
- Zhijian Yang
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Graduate Group in Applied Mathematics and Computational Science, University of Pennsylvania, Philadelphia, PA, USA
| | - Junhao Wen
- Laboratory of AI and Biomedical Science (LABS), Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, California, USA
| | - Guray Erus
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sindhuja T. Govindarajan
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Randa Melhem
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Elizabeth Mamourian
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yuhan Cui
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dhivya Srinivasan
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ahmed Abdulkadir
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Paraskevi Parmpi
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Germany
| | - Hans J. Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Germany
| | - Robin Bülow
- Institute of Diagnostic Radiology and Neuroradiology, University of Greifswald, Germany
| | - Stefan Frenzel
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Germany
| | - Duygu Tosun
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Murat Bilgel
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Yang An
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Dahyun Yi
- Institute of Human Behavioral Medicine, Medical Research Center Seoul National University, Seoul, Republic of Korea
| | - Daniel S. Marcus
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Pamela LaMontagne
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Tammie L.S. Benzinger
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Susan R. Heckbert
- Cardiovascular Health Research Unit and Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Thomas R. Austin
- Cardiovascular Health Research Unit and Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Shari R. Waldstein
- Department of Psychology, University of Maryland, Baltimore County, Catonsville, MD, USA
| | - Michele K. Evans
- Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, NIA/NIH/IRP, Baltimore, MD, USA
| | - Alan B. Zonderman
- Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, NIA/NIH/IRP, Baltimore, MD, USA
| | - Lenore J. Launer
- Neuroepidemiology Section, Intramural Research Program, National Institute on Aging, Bethesda, Maryland, USA
| | - Aristeidis Sotiras
- Department of Radiology and Institute of Informatics, Washington University in St. Luis, St. Luis, MO63110, USA
| | - Mark A. Espeland
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Colin L. Masters
- Florey Institute, The University of Melbourne, Parkville, VIC, 3052, Australia
| | - Paul Maruff
- Florey Institute, The University of Melbourne, Parkville, VIC, 3052, Australia
| | - Jurgen Fripp
- CSIRO Health and Biosecurity, Australian e-Health Research Centre CSIRO, Brisbane, Queensland, Australia
| | - Arthur Toga
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, California, USA
| | - Sid O’Bryant
- Institute for Translational Research University of North Texas Health Science Center Fort Worth Texas USA
| | - Mallar M. Chakravarty
- Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada
| | - Sylvia Villeneuve
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Sterling C. Johnson
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - John C. Morris
- Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
| | - Marilyn S. Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kristine Yaffe
- Departments of Neurology, Psychiatry and Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Luigi Ferrucci
- Translational Gerontology Branch, Longitudinal Studies Section, National Institute on Aging, National Institutes of Health, MedStar Harbor Hospital, 3001 S. Hanover Street, Baltimore, MD, USA
| | - Nick R. Bryan
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Russell T. Shinohara
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, & Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Yong Fan
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Mohamad Habes
- Biggs Alzheimer’s Institute, University of Texas San Antonio Health Science Center, USA
| | - Paris Alexandros Lalousis
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Nikolaos Koutsouleris
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- Section for Precision Psychiatry, Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University Munich, Munich, Germany
| | - David A. Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Susan M. Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Haochang Shou
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, & Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Ilya M. Nasrallah
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Christos Davatzikos
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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30
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Moon HS, Mahzarnia A, Stout J, Anderson RJ, Badea CT, Badea A. Feature attention graph neural network for estimating brain age and identifying important neural connections in mouse models of genetic risk for Alzheimer's disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.13.571574. [PMID: 38168445 PMCID: PMC10760088 DOI: 10.1101/2023.12.13.571574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Alzheimer's disease (AD) remains one of the most extensively researched neurodegenerative disorders due to its widespread prevalence and complex risk factors. Age is a crucial risk factor for AD, which can be estimated by the disparity between physiological age and estimated brain age. To model AD risk more effectively, integrating biological, genetic, and cognitive markers is essential. Here, we utilized mouse models expressing the major APOE human alleles and human nitric oxide synthase 2 to replicate genetic risk for AD and a humanized innate immune response. We estimated brain age employing a multivariate dataset that includes brain connectomes, APOE genotype, subject traits such as age and sex, and behavioral data. Our methodology used Feature Attention Graph Neural Networks (FAGNN) for integrating different data types. Behavioral data were processed with a 2D Convolutional Neural Network (CNN), subject traits with a 1D CNN, brain connectomes through a Graph Neural Network using quadrant attention module. The model yielded a mean absolute error for age prediction of 31.85 days, with a root mean squared error of 41.84 days, outperforming other, reduced models. In addition, FAGNN identified key brain connections involved in the aging process. The highest weights were assigned to the connections between cingulum and corpus callosum, striatum, hippocampus, thalamus, hypothalamus, cerebellum, and piriform cortex. Our study demonstrates the feasibility of predicting brain age in models of aging and genetic risk for AD. To verify the validity of our findings, we compared Fractional Anisotropy (FA) along the tracts of regions with the highest connectivity, the Return-to-Origin Probability (RTOP), Return-to-Plane Probability (RTPP), and Return-to-Axis Probability (RTAP), which showed significant differences between young, middle-aged, and old age groups. Younger mice exhibited higher FA, RTOP, RTAP, and RTPP compared to older groups in the selected connections, suggesting that degradation of white matter tracts plays a critical role in aging and for FAGNN's selections. Our analysis suggests a potential neuroprotective role of APOE2, relative to APOE3 and APOE4, where APOE2 appears to mitigate age-related changes. Our findings highlighted a complex interplay of genetics and brain aging in the context of AD risk modeling.
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Affiliation(s)
- Hae Sol Moon
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Quantitative Imaging and Analysis Laboratory, Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Ali Mahzarnia
- Quantitative Imaging and Analysis Laboratory, Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Jacques Stout
- Quantitative Imaging and Analysis Laboratory, Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Robert J Anderson
- Quantitative Imaging and Analysis Laboratory, Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Cristian T. Badea
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Quantitative Imaging and Analysis Laboratory, Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Alexandra Badea
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Quantitative Imaging and Analysis Laboratory, Department of Radiology, Duke University School of Medicine, Durham, NC, USA
- Brain Imaging and Analysis Center, Duke University School of Medicine, Durham, NC, USA
- Department of Neurology, Duke University School of Medicine, Durham, NC, USA
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31
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Du L, Hermann BP, Jonaitis EM, Cody KA, Rivera-Rivera L, Rowley H, Field A, Eisenmenger L, Christian BT, Betthauser TJ, Larget B, Chappell R, Janelidze S, Hansson O, Johnson SC, Langhough R. Harnessing cognitive trajectory clusterings to examine subclinical decline risk factors. Brain Commun 2023; 5:fcad333. [PMID: 38107504 PMCID: PMC10724051 DOI: 10.1093/braincomms/fcad333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 10/23/2023] [Accepted: 11/30/2023] [Indexed: 12/19/2023] Open
Abstract
Cognitive decline in Alzheimer's disease and other dementias typically begins long before clinical impairment. Identifying people experiencing subclinical decline may facilitate earlier intervention. This study developed cognitive trajectory clusters using longitudinally based random slope and change point parameter estimates from a Preclinical Alzheimer's disease Cognitive Composite and examined how baseline and most recently available clinical/health-related characteristics, cognitive statuses and biomarkers for Alzheimer's disease and vascular disease varied across these cognitive clusters. Data were drawn from the Wisconsin Registry for Alzheimer's Prevention, a longitudinal cohort study of adults from late midlife, enriched for a parental history of Alzheimer's disease and without dementia at baseline. Participants who were cognitively unimpaired at the baseline visit with ≥3 cognitive visits were included in trajectory modelling (n = 1068). The following biomarker data were available for subsets: positron emission tomography amyloid (amyloid: n = 367; [11C]Pittsburgh compound B (PiB): global PiB distribution volume ratio); positron emission tomography tau (tau: n = 321; [18F]MK-6240: primary regions of interest meta-temporal composite); MRI neurodegeneration (neurodegeneration: n = 581; hippocampal volume and global brain atrophy); T2 fluid-attenuated inversion recovery MRI white matter ischaemic lesion volumes (vascular: white matter hyperintensities; n = 419); and plasma pTau217 (n = 165). Posterior median estimate person-level change points, slopes' pre- and post-change point and estimated outcome (intercepts) at change point for cognitive composite were extracted from Bayesian Bent-Line Regression modelling and used to characterize cognitive trajectory groups (K-means clustering). A common method was used to identify amyloid/tau/neurodegeneration/vascular biomarker thresholds. We compared demographics, last visit cognitive status, health-related factors and amyloid/tau/neurodegeneration/vascular biomarkers across the cognitive groups using ANOVA, Kruskal-Wallis, χ2, and Fisher's exact tests. Mean (standard deviation) baseline and last cognitive assessment ages were 58.4 (6.4) and 66.6 (6.6) years, respectively. Cluster analysis identified three cognitive trajectory groups representing steep, n = 77 (7.2%); intermediate, n = 446 (41.8%); and minimal, n = 545 (51.0%) cognitive decline. The steep decline group was older, had more females, APOE e4 carriers and mild cognitive impairment/dementia at last visit; it also showed worse self-reported general health-related and vascular risk factors and higher amyloid, tau, neurodegeneration and white matter hyperintensity positive proportions at last visit. Subtle cognitive decline was consistently evident in the steep decline group and was associated with generally worse health. In addition, cognitive trajectory groups differed on aetiology-informative biomarkers and risk factors, suggesting an intimate link between preclinical cognitive patterns and amyloid/tau/neurodegeneration/vascular biomarker differences in late middle-aged adults. The result explains some of the heterogeneity in cognitive performance within cognitively unimpaired late middle-aged adults.
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Affiliation(s)
- Lianlian Du
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Bruce P Hermann
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Neurology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53705, USA
| | - Erin M Jonaitis
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Karly Alex Cody
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Leonardo Rivera-Rivera
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53705, USA
| | - Howard Rowley
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Aaron Field
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Laura Eisenmenger
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Bradley T Christian
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53705, USA
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Tobey J Betthauser
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Bret Larget
- Department of Statistics, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Rick Chappell
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA
| | | | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, Lund 205 02, Sweden
| | - Sterling C Johnson
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Rebecca Langhough
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
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32
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Lui K, Dave A, Sprecher K, Chappel-Farley M, Riedner B, Heston M, Taylor C, Carlsson C, Okonkwo O, Asthana S, Johnson S, Bendlin B, Mander B, Benca R. Older adults at greater risk for Alzheimer's disease show stronger associations between sleep apnea severity and verbal memory. RESEARCH SQUARE 2023:rs.3.rs-3683218. [PMID: 38076899 PMCID: PMC10705699 DOI: 10.21203/rs.3.rs-3683218/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/22/2023]
Abstract
Background Obstructive sleep apnea (OSA) increases risk for cognitive decline and Alzheimer's disease (AD). While the underlying mechanisms remain unclear, hypoxemia during OSA has been implicated in cognitive impairment. OSA during rapid eye movement (REM) sleep is usually more severe than in non-rapid eye movement (NREM) sleep, but the relative effect of oxyhemoglobin desaturation during REM versus NREM sleep on memory is not completely characterized. Here, we examined the impact of OSA, as well as the moderating effects of AD risk factors, on verbal memory in a sample of middle-aged and older adults with heightened AD risk. Methods Eighty-one adults (mean age:61.7±6.0 years, 62% females, 32% apolipoprotein E ε4 allele (APOE4) carriers, and 70% with parental history of AD) underwent clinical polysomnography including assessment of OSA. OSA features were derived in total, NREM, and REM sleep. REM-NREM ratios of OSA features were also calculated. Verbal memory was assessed with the Rey Auditory Verbal Learning Test (RAVLT). Multiple regression models evaluated the relationships between OSA features and RAVLT scores while adjusting for sex, age, time between assessments, education years, body mass index (BMI), and APOE4 status or parental history of AD. The significant main effects of OSA features on RAVLT performance and the moderating effects of AD risk factors (i.e., sex, age, APOE4 status, and parental history of AD) were examined. Results Apnea-hypopnea index (AHI), respiratory disturbance index (RDI), and oxyhemoglobin desaturation index (ODI) during REM sleep were negatively associated with RAVLT total learning and long-delay recall. Further, greater REM-NREM ratios of AHI, RDI, and ODI (i.e., more events in REM than NREM) were related to worse total learning and recall. We found specifically that the negative association between REM ODI and total learning was driven by adults 60+ years old. In addition, the negative relationships between REM-NREM ODI ratio and total learning and REM-NREM RDI ratio and long-delay recall were driven by APOE4 carriers. Conclusion Greater OSA severity, particularly during REM sleep, negatively affects verbal memory, especially for people with greater AD risk. These findings underscore the potential importance of proactive screening and treatment of REM OSA even if overall AHI appears low.
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Affiliation(s)
- Kitty Lui
- San Diego State University/University of California San Diego, Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - Abhishek Dave
- Department of Cognitive Sciences, University of California, Irvine
| | - Kate Sprecher
- Department of Population Health Sciences, University of Wisconsin-Madison
| | | | - Brady Riedner
- Department of Psychiatry, University of Wisconsin-Madison
| | - Margo Heston
- Department of Medicine, University of Wisconsin-Madison
| | - Chase Taylor
- Department of Neuroscience, University of Kentucky
| | - Cynthia Carlsson
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison
| | - Ozioma Okonkwo
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison
| | - Sanjay Asthana
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison
| | - Sterling Johnson
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison
| | | | - Bryce Mander
- Department of Psychiatry and Human Behavior, University of California, Irvine
| | - Ruth Benca
- Department of Psychiatry and Behavioral Medicine, Wake Forest University
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33
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Panyard DJ, McKetney J, Deming YK, Morrow AR, Ennis GE, Jonaitis EM, Van Hulle CA, Yang C, Sung YJ, Ali M, Kollmorgen G, Suridjan I, Bayfield A, Bendlin BB, Zetterberg H, Blennow K, Cruchaga C, Carlsson CM, Johnson SC, Asthana S, Coon JJ, Engelman CD. Large-scale proteome and metabolome analysis of CSF implicates altered glucose and carbon metabolism and succinylcarnitine in Alzheimer's disease. Alzheimers Dement 2023; 19:5447-5470. [PMID: 37218097 PMCID: PMC10663389 DOI: 10.1002/alz.13130] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 02/23/2023] [Accepted: 04/04/2023] [Indexed: 05/24/2023]
Abstract
INTRODUCTION A hallmark of Alzheimer's disease (AD) is the aggregation of proteins (amyloid beta [A] and hyperphosphorylated tau [T]) in the brain, making cerebrospinal fluid (CSF) proteins of particular interest. METHODS We conducted a CSF proteome-wide analysis among participants of varying AT pathology (n = 137 participants; 915 proteins) with nine CSF biomarkers of neurodegeneration and neuroinflammation. RESULTS We identified 61 proteins significantly associated with the AT category (P < 5.46 × 10-5 ) and 636 significant protein-biomarker associations (P < 6.07 × 10-6 ). Proteins from glucose and carbon metabolism pathways were enriched among amyloid- and tau-associated proteins, including malate dehydrogenase and aldolase A, whose associations with tau were replicated in an independent cohort (n = 717). CSF metabolomics identified and replicated an association of succinylcarnitine with phosphorylated tau and other biomarkers. DISCUSSION These results implicate glucose and carbon metabolic dysregulation and increased CSF succinylcarnitine levels with amyloid and tau pathology in AD. HIGHLIGHTS Cerebrospinal fluid (CSF) proteome enriched for extracellular, neuronal, immune, and protein processing. Glucose/carbon metabolic pathways enriched among amyloid/tau-associated proteins. Key glucose/carbon metabolism protein associations independently replicated. CSF proteome outperformed other omics data in predicting amyloid/tau positivity. CSF metabolomics identified and replicated a succinylcarnitine-phosphorylated tau association.
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Affiliation(s)
- Daniel J. Panyard
- Department of Population Health Sciences, University of Wisconsin-Madison; 610 Walnut Street, 707 WARF Building, Madison, WI 53726, United States of America
| | - Justin McKetney
- National Center for Quantitative Biology of Complex Systems, University of Wisconsin-Madison; Madison, WI 53706, United States of America
- Department of Biomolecular Chemistry, University of Wisconsin-Madison; Madison, WI 53506, United States of America
| | - Yuetiva K. Deming
- Department of Population Health Sciences, University of Wisconsin-Madison; 610 Walnut Street, 707 WARF Building, Madison, WI 53726, United States of America
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison; 600 Highland Avenue, J5/1 Mezzanine, Madison, WI 53792, United States of America
- Department of Medicine, University of Wisconsin-Madison; 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI 53705, United States of America
| | - Autumn R. Morrow
- Department of Population Health Sciences, University of Wisconsin-Madison; 610 Walnut Street, 707 WARF Building, Madison, WI 53726, United States of America
| | - Gilda E. Ennis
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison; 600 Highland Avenue, J5/1 Mezzanine, Madison, WI 53792, United States of America
| | - Erin M. Jonaitis
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison; 600 Highland Avenue, J5/1 Mezzanine, Madison, WI 53792, United States of America
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison; 610 Walnut Street, 9 Floor, Madison, WI 53726, United States of America
| | - Carol A. Van Hulle
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison; 600 Highland Avenue, J5/1 Mezzanine, Madison, WI 53792, United States of America
- Department of Medicine, University of Wisconsin-Madison; 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI 53705, United States of America
| | - Chengran Yang
- Department of Psychiatry, Washington University School of Medicine; St Louis, MO 63110, United States of America
- NeuroGenomics and Informatics Center, Washington University School of Medicine; St Louis, MO 63110, United States of America
- Hope Center for Neurological Disorders, Washington University School of Medicine; St Louis, MO 63110, United States of America
| | - Yun Ju Sung
- Department of Psychiatry, Washington University School of Medicine; St Louis, MO 63110, United States of America
- NeuroGenomics and Informatics Center, Washington University School of Medicine; St Louis, MO 63110, United States of America
- Hope Center for Neurological Disorders, Washington University School of Medicine; St Louis, MO 63110, United States of America
| | - Muhammad Ali
- Department of Psychiatry, Washington University School of Medicine; St Louis, MO 63110, United States of America
- NeuroGenomics and Informatics Center, Washington University School of Medicine; St Louis, MO 63110, United States of America
- Hope Center for Neurological Disorders, Washington University School of Medicine; St Louis, MO 63110, United States of America
| | | | | | | | - Barbara B. Bendlin
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison; 600 Highland Avenue, J5/1 Mezzanine, Madison, WI 53792, United States of America
- Department of Medicine, University of Wisconsin-Madison; 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI 53705, United States of America
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison; 610 Walnut Street, 9 Floor, Madison, WI 53726, United States of America
- William S. Middleton Memorial Veterans Hospital; 2500 Overlook Terrace, Madison, WI 53705, United States of America
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital; Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology; London, UK
- UK Dementia Research Institute at UCL; London, UK
- Hong Kong Center for Neurodegenerative Diseases; Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital; Mölndal, Sweden
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine; St Louis, MO 63110, United States of America
- NeuroGenomics and Informatics Center, Washington University School of Medicine; St Louis, MO 63110, United States of America
- Hope Center for Neurological Disorders, Washington University School of Medicine; St Louis, MO 63110, United States of America
| | - Cynthia M. Carlsson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison; 600 Highland Avenue, J5/1 Mezzanine, Madison, WI 53792, United States of America
- Department of Medicine, University of Wisconsin-Madison; 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI 53705, United States of America
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison; 610 Walnut Street, 9 Floor, Madison, WI 53726, United States of America
- William S. Middleton Memorial Veterans Hospital; 2500 Overlook Terrace, Madison, WI 53705, United States of America
| | - Sterling C. Johnson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison; 600 Highland Avenue, J5/1 Mezzanine, Madison, WI 53792, United States of America
- Department of Medicine, University of Wisconsin-Madison; 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI 53705, United States of America
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison; 610 Walnut Street, 9 Floor, Madison, WI 53726, United States of America
- William S. Middleton Memorial Veterans Hospital; 2500 Overlook Terrace, Madison, WI 53705, United States of America
| | - Sanjay Asthana
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison; 600 Highland Avenue, J5/1 Mezzanine, Madison, WI 53792, United States of America
- Department of Medicine, University of Wisconsin-Madison; 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI 53705, United States of America
- William S. Middleton Memorial Veterans Hospital; 2500 Overlook Terrace, Madison, WI 53705, United States of America
| | - Joshua J. Coon
- National Center for Quantitative Biology of Complex Systems, University of Wisconsin-Madison; Madison, WI 53706, United States of America
- Department of Biomolecular Chemistry, University of Wisconsin-Madison; Madison, WI 53506, United States of America
- Morgridge Institute for Research; Madison, WI 53706, United States of America
- Department of Chemistry, University of Wisconsin-Madison; Madison, WI 53506, United States of America
| | - Corinne D. Engelman
- Department of Population Health Sciences, University of Wisconsin-Madison; 610 Walnut Street, 707 WARF Building, Madison, WI 53726, United States of America
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Ramos AA, Galiano-Castillo N, Machado L. Cognitive Functioning of Unaffected First-degree Relatives of Individuals With Late-onset Alzheimer's Disease: A Systematic Literature Review and Meta-analysis. Neuropsychol Rev 2023; 33:659-674. [PMID: 36057684 PMCID: PMC10770217 DOI: 10.1007/s11065-022-09555-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Accepted: 06/10/2022] [Indexed: 10/14/2022]
Abstract
First-degree relatives of individuals with late-onset Alzheimer's disease (LOAD) are at increased risk for developing dementia, yet the associations between family history of LOAD and cognitive dysfunction remain unclear. In this quantitative review, we provide the first meta-analysis on the cognitive profile of unaffected first-degree blood relatives of LOAD-affected individuals compared to controls without a family history of LOAD. A systematic literature search was conducted in PsycINFO, PubMed /MEDLINE, and Scopus. We fitted a three-level structural equation modeling meta-analysis to control for non-independent effect sizes. Heterogeneity and risk of publication bias were also investigated. Thirty-four studies enabled us to estimate 218 effect sizes across several cognitive domains. Overall, first-degree relatives (n = 4,086, mean age = 57.40, SD = 4.71) showed significantly inferior cognitive performance (Hedges' g = -0.16; 95% CI, -0.25 to -0.08; p < .001) compared to controls (n = 2,388, mean age = 58.43, SD = 5.69). Specifically, controls outperformed first-degree relatives in language, visuospatial and verbal long-term memory, executive functions, verbal short-term memory, and verbal IQ. Among the first-degree relatives, APOE ɛ4 carriership was associated with more significant dysfunction in cognition (g = -0.24; 95% CI, -0.38 to -0.11; p < .001) compared to non-carriers (g = -0.14; 95% CI, -0.28 to -0.01; p = .04). Cognitive test type was significantly associated with between-group differences, accounting for 65% (R23 = .6499) of the effect size heterogeneity in the fitted regression model. No evidence of publication bias was found. The current findings provide support for mild but robust cognitive dysfunction in first-degree relatives of LOAD-affected individuals that appears to be moderated by cognitive domain, cognitive test type, and APOE ɛ4.
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Affiliation(s)
- Ari Alex Ramos
- Department of Psychology and Brain Health Research Centre, University of Otago, Dunedin, New Zealand.
- Brain Research New Zealand, Auckland, New Zealand.
- Department of Psychology, Pontifical Catholic University of Paraná, Rua Imaculada Conceição, 1155, Curitiba, CEP 80.215-901, Brazil.
| | - Noelia Galiano-Castillo
- Department of Physical Therapy, Health Sciences Faculty, "Cuidate" from Biomedical Group (BIO277), Instituto de Investigación Biosanitaria (ibs.GRANADA), and Sport and Health Research Center (IMUDs), Granada, Spain, University of Granada, Granada, Spain
| | - Liana Machado
- Department of Psychology and Brain Health Research Centre, University of Otago, Dunedin, New Zealand
- Brain Research New Zealand, Auckland, New Zealand
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Guo HF, Wu Y, Li J, Pan FF. Analysis of the relationship between blood pressure variability and subtle cognitive decline in older adults. World J Psychiatry 2023; 13:872-883. [DOI: 10.5498/wjp.v13.i11.872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 09/18/2023] [Accepted: 10/23/2023] [Indexed: 11/17/2023] Open
Abstract
BACKGROUND Blood pressure variability (BPV) has been shown to be related to mild cognitive impairment and Alzheimer's disease in a number of studies. However, the relationship between BPV and subtle cognitive decline (SCD) has received minimal attention in this field of research to date and has rarely been reported.
AIM To examine whether SCD is independently associated with changes in BPV in older adults.
METHODS Participants were selected based on having participated in cognitive function evaluation and ambulatory blood pressure measurement at the Shanghai Sixth People's Hospital Affiliated with Shanghai Jiao Tong University School of Medicine between June 2020 and August 2022. The participants included 182 individuals with SCD as the experimental group and 237 with normal cognitive function as the control group. The basic data, laboratory examinations, scale tests, and ambulatory blood pressure test results of the two groups were analyzed retrospectively, and the relationship between SCD and BPV was subsequently evaluated.
RESULTS Significant differences were observed between the two groups of participants (P < 0.05) in terms of age, education level, prevalence rate of diabetes, fasting blood glucose level, 24-h systolic blood pressure standard deviation and coefficient of variation, 24-h diastolic blood pressure standard deviation and coefficient of variation. The scale monitoring results showed significant differences in the scores for memory, attention, and visual space between the experimental and control groups. Logistic regression analysis indicated that age, education level, blood sugar level, and BPV were factors influencing cognitive decline. Linear regression analysis showed that there was an independent correlation between blood pressure variation and SCD, even after adjusting for related factors. Each of the above differences was still significant.
CONCLUSION This study suggests that increased BPV is associated with SCD.
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Affiliation(s)
- Hui-Feng Guo
- Department of Gerontology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Yi Wu
- Prenatal Diagnosis Center, International Peace Maternity & Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Jie Li
- Department of Gerontology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Feng-Feng Pan
- Department of Gerontology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
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Choi JJ, Koscik RL, Jonaitis EM, Panyard DJ, Morrow AR, Johnson SC, Engelman CD, Schmitz LL. Assessing the Biological Mechanisms Linking Smoking Behavior and Cognitive Function: A Mediation Analysis of Untargeted Metabolomics. Metabolites 2023; 13:1154. [PMID: 37999250 PMCID: PMC10673384 DOI: 10.3390/metabo13111154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Revised: 11/10/2023] [Accepted: 11/11/2023] [Indexed: 11/25/2023] Open
Abstract
(1) Smoking is the most significant preventable health hazard in the modern world. It increases the risk of vascular problems, which are also risk factors for dementia. In addition, toxins in cigarettes increase oxidative stress and inflammation, which have both been linked to the development of Alzheimer's disease and related dementias (ADRD). This study identified potential mechanisms of the smoking-cognitive function relationship using metabolomics data from the longitudinal Wisconsin Registry for Alzheimer's Prevention (WRAP). (2) 1266 WRAP participants were included to assess the association between smoking status and four cognitive composite scores. Next, untargeted metabolomic data were used to assess the relationships between smoking and metabolites. Metabolites significantly associated with smoking were then tested for association with cognitive composite scores. Total effect models and mediation models were used to explore the role of metabolites in smoking-cognitive function pathways. (3) Plasma N-acetylneuraminate was associated with smoking status Preclinical Alzheimer Cognitive Composite 3 (PACC3) and Immediate Learning (IMM). N-acetylneuraminate mediated 12% of the smoking-PACC3 relationship and 13% of the smoking-IMM relationship. (4) These findings provide links between previous studies that can enhance our understanding of potential biological pathways between smoking and cognitive function.
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Affiliation(s)
- Jerome J. Choi
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA; (J.J.C.); (A.R.M.)
| | - Rebecca L. Koscik
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA; (R.L.K.); (E.M.J.)
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Erin M. Jonaitis
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA; (R.L.K.); (E.M.J.)
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Daniel J. Panyard
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA 94305, USA;
| | - Autumn R. Morrow
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA; (J.J.C.); (A.R.M.)
| | - Sterling C. Johnson
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA; (R.L.K.); (E.M.J.)
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison, Madison, WI 53792, USA
- William S. Middleton Memorial Veterans Hospital, Middleton, WI 53705, USA
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Corinne D. Engelman
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA; (J.J.C.); (A.R.M.)
| | - Lauren L. Schmitz
- La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, WI 53706, USA;
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Weiner MW, Aaronson A, Eichenbaum J, Kwang W, Ashford MT, Gummadi S, Santhakumar J, Camacho MR, Flenniken D, Fockler J, Truran-Sacrey D, Ulbricht A, Mackin RS, Nosheny RL. Brain health registry updates: An online longitudinal neuroscience platform. Alzheimers Dement 2023; 19:4935-4951. [PMID: 36965096 PMCID: PMC10518371 DOI: 10.1002/alz.13077] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 02/28/2023] [Accepted: 03/08/2023] [Indexed: 03/27/2023]
Abstract
INTRODUCTION Remote, internet-based methods for recruitment, screening, and longitudinally assessing older adults have the potential to facilitate Alzheimer's disease (AD) clinical trials and observational studies. METHODS The Brain Health Registry (BHR) is an online registry that includes longitudinal assessments including self- and study partner-report questionnaires and neuropsychological tests. New initiatives aim to increase inclusion and engagement of commonly underincluded communities using digital, community-engaged research strategies. New features include multilingual support and biofluid collection capabilities. RESULTS BHR includes > 100,000 participants. BHR has made over 259,000 referrals resulting in 25,997 participants enrolled in 30 aging and AD studies. In addition, 28,278 participants are coenrolled in BHR and other studies with data linkage among studies. Data have been shared with 28 investigators. Recent efforts have facilitated the enrollment and engagement of underincluded ethnocultural communities. DISCUSSION The major advantages of the BHR approach are scalability and accessibility. Challenges include compliance, retention, cohort diversity, and generalizability. HIGHLIGHTS Brain Health Registry (BHR) is an online, longitudinal platform of > 100,000 members. BHR made > 259,000 referrals, which enrolled 25,997 participants in 32 studies. New efforts increased enrollment and engagement of underincluded communities in BHR. The major advantages of the BHR approach are scalability and accessibility. BHR provides a unique adjunct for clinical neuroscience research.
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Affiliation(s)
- Michael W. Weiner
- Northern California Institute for Research and Education (NCIRE), Department of Veterans Affairs Medical Center, San Francisco, California, USA
- VA Advanced Research Center, San Francisco, California, USA
- University of California, San Francisco Department of Radiology and Biomedical Imaging, San Francisco, California, USA
- University of California, San Francisco Department of Psychiatry and Behavioral Sciences, San Francisco, California, USA
- University of California, San Francisco Department of Medicine, San Francisco, California, USA
- University of California, San Francisco Department of Neurology, San Francisco, California, USA
| | - Anna Aaronson
- VA Advanced Research Center, San Francisco, California, USA
- University of California, San Francisco Department of Radiology and Biomedical Imaging, San Francisco, California, USA
| | - Joseph Eichenbaum
- VA Advanced Research Center, San Francisco, California, USA
- University of California, San Francisco Department of Radiology and Biomedical Imaging, San Francisco, California, USA
| | - Winnie Kwang
- VA Advanced Research Center, San Francisco, California, USA
- University of California, San Francisco Department of Radiology and Biomedical Imaging, San Francisco, California, USA
| | - Miriam T. Ashford
- Northern California Institute for Research and Education (NCIRE), Department of Veterans Affairs Medical Center, San Francisco, California, USA
- VA Advanced Research Center, San Francisco, California, USA
- University of California, San Francisco Department of Radiology and Biomedical Imaging, San Francisco, California, USA
| | - Shilpa Gummadi
- VA Advanced Research Center, San Francisco, California, USA
- University of California, San Francisco Department of Radiology and Biomedical Imaging, San Francisco, California, USA
| | - Jessica Santhakumar
- VA Advanced Research Center, San Francisco, California, USA
- University of California, San Francisco Department of Radiology and Biomedical Imaging, San Francisco, California, USA
| | - Monica R. Camacho
- Northern California Institute for Research and Education (NCIRE), Department of Veterans Affairs Medical Center, San Francisco, California, USA
- VA Advanced Research Center, San Francisco, California, USA
- University of California, San Francisco Department of Radiology and Biomedical Imaging, San Francisco, California, USA
| | - Derek Flenniken
- Northern California Institute for Research and Education (NCIRE), Department of Veterans Affairs Medical Center, San Francisco, California, USA
- VA Advanced Research Center, San Francisco, California, USA
- University of California, San Francisco Department of Radiology and Biomedical Imaging, San Francisco, California, USA
| | - Juliet Fockler
- VA Advanced Research Center, San Francisco, California, USA
- University of California, San Francisco Department of Radiology and Biomedical Imaging, San Francisco, California, USA
| | - Diana Truran-Sacrey
- Northern California Institute for Research and Education (NCIRE), Department of Veterans Affairs Medical Center, San Francisco, California, USA
- VA Advanced Research Center, San Francisco, California, USA
- University of California, San Francisco Department of Radiology and Biomedical Imaging, San Francisco, California, USA
| | - Aaron Ulbricht
- VA Advanced Research Center, San Francisco, California, USA
- University of California, San Francisco Department of Radiology and Biomedical Imaging, San Francisco, California, USA
| | - R. Scott Mackin
- VA Advanced Research Center, San Francisco, California, USA
- University of California, San Francisco Department of Psychiatry and Behavioral Sciences, San Francisco, California, USA
| | - Rachel L. Nosheny
- VA Advanced Research Center, San Francisco, California, USA
- University of California, San Francisco Department of Psychiatry and Behavioral Sciences, San Francisco, California, USA
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Gallagher RL, Koscik RL, Moody JF, Vogt NM, Adluru N, Kecskemeti SR, Van Hulle CA, Chin NA, Asthana S, Kollmorgen G, Suridjan I, Carlsson CM, Johnson SC, Dean DC, Zetterberg H, Blennow K, Alexander AL, Bendlin BB. Neuroimaging of tissue microstructure as a marker of neurodegeneration in the AT(N) framework: defining abnormal neurodegeneration and improving prediction of clinical status. Alzheimers Res Ther 2023; 15:180. [PMID: 37848950 PMCID: PMC10583332 DOI: 10.1186/s13195-023-01281-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 07/27/2023] [Indexed: 10/19/2023]
Abstract
BACKGROUND Alzheimer's disease involves accumulating amyloid (A) and tau (T) pathology, and progressive neurodegeneration (N), leading to the development of the AD clinical syndrome. While several markers of N have been proposed, efforts to define normal vs. abnormal neurodegeneration based on neuroimaging have been limited. Sensitive markers that may account for or predict cognitive dysfunction for individuals in early disease stages are critical. METHODS Participants (n = 296) defined on A and T status and spanning the AD-clinical continuum underwent multi-shell diffusion-weighted magnetic resonance imaging to generate Neurite Orientation Dispersion and Density Imaging (NODDI) metrics, which were tested as markers of N. To better define N, we developed age- and sex-adjusted robust z-score values to quantify normal and AD-associated (abnormal) neurodegeneration in both cortical gray matter and subcortical white matter regions of interest. We used general logistic regression with receiver operating characteristic (ROC) and area under the curve (AUC) analysis to test whether NODDI metrics improved diagnostic accuracy compared to models that only relied on cerebrospinal fluid (CSF) A and T status (alone and in combination). RESULTS Using internal robust norms, we found that NODDI metrics correlate with worsening cognitive status and that NODDI captures early, AD neurodegenerative pathology in the gray matter of cognitively unimpaired, but A/T biomarker-positive, individuals. NODDI metrics utilized together with A and T status improved diagnostic prediction accuracy of AD clinical status, compared with models using CSF A and T status alone. CONCLUSION Using a robust norms approach, we show that abnormal AD-related neurodegeneration can be detected among cognitively unimpaired individuals. Metrics derived from diffusion-weighted imaging are potential sensitive markers of N and could be considered for trial enrichment and as outcomes in clinical trials. However, given the small sample sizes, the exploratory nature of the work must be acknowledged.
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Affiliation(s)
- Rigina L Gallagher
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Medical Scientist Training Program, University of Wisconsin-Madison, Madison, WI, USA
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
| | - Rebecca Langhough Koscik
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
| | - Jason F Moody
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
| | - Nicholas M Vogt
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Medical Scientist Training Program, University of Wisconsin-Madison, Madison, WI, USA
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
| | - Nagesh Adluru
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Waisman Research Center, Madison, WI, USA
| | | | - Carol A Van Hulle
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
| | - Nathaniel A Chin
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
| | - Sanjay Asthana
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Veterans Administration, Madison, WI, USA
| | | | | | - Cynthia M Carlsson
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
- Veterans Administration, Madison, WI, USA
| | - Sterling C Johnson
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
- Veterans Administration, Madison, WI, USA
| | - Douglas C Dean
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Waisman Research Center, Madison, WI, USA
| | - Henrik Zetterberg
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Andrew L Alexander
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Waisman Research Center, Madison, WI, USA
| | - Barbara B Bendlin
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA.
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA.
- Wisconsin Alzheimer's Institute, Madison, WI, USA.
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Bruno D, Zinkunegi AJ, Pomara N, Zetterberg H, Blennow K, Koscik RL, Carlsson C, Bendlin B, Okonkwo O, Hermann BP, Johnson SC, Mueller KD. Cross-sectional associations of CSF tau levels with Rey's AVLT: A recency ratio study. Neuropsychology 2023; 37:628-635. [PMID: 35604714 PMCID: PMC9681933 DOI: 10.1037/neu0000821] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
OBJECTIVE The preeminent in vivo cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) are amyloid β 1-42 (Aβ42), phosphorylated Tau (p-tau), and total Tau (t-tau). The goal of this study was to examine how well traditional (total and delayed recall) and process-based (recency ratio [Rr]) measures derived from Rey's Auditory Verbal Learning test (AVLT) were associated with these biomarkers. METHOD Data from 235 participants (Mage = 65.5, SD = 6.9), who ranged from cognitively unimpaired to mild cognitive impairment, and for whom CSF values were available, were extracted from the Wisconsin Registry for Alzheimer's Prevention. Bayesian regression analyses were carried out using CSF scores as outcomes, AVLT scores as predictors, and controlling for demographic data and diagnosis. RESULTS We found moderate evidence that Rr was associated with both CSF p-tau (Bayesian factor [BFM] = 5.55) and t-tau (BFM = 7.28), above and beyond the control variables, while it did not correlate with CSF Aβ42 levels. In contrast, total and delayed recall scores were not linked with any of the AD biomarkers, in separate analyses. When comparing all memory predictors in a single regression, Rr remained the strongest predictor of CSF t-tau levels (BFM = 3.57). CONCLUSIONS Our findings suggest that Rr may be a better cognitive measure than commonly used AVLT scores to assess CSF levels of p-tau and t-tau in nondemented individuals. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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Affiliation(s)
- Davide Bruno
- School of Psychology, Liverpool John Moores University
| | | | - Nunzio Pomara
- Geriatric Psychiatry Division, Nathan Kline Institute, Orangeburg, New York, United States
- School of Medicine, New York University
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology
- UK Dementia Research Institute at UCL, London, United Kingdom
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Rebecca Langhough Koscik
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison
| | - Cynthia Carlsson
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison
- Department of Medicine, University of Wisconsin–Madison
- Geriatric Research Education and Clinical Center, William S. Middleton Veterans Hospital, Madison, Wisconsin, United States
| | - Barbara Bendlin
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison
- Department of Medicine, University of Wisconsin–Madison
| | - Ozioma Okonkwo
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison
- Department of Medicine, University of Wisconsin–Madison
| | - Bruce P. Hermann
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison
- Department of Neurology, University of Wisconsin–Madison
| | - Sterling C. Johnson
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison
- Department of Medicine, University of Wisconsin–Madison
- Geriatric Research Education and Clinical Center, William S. Middleton Veterans Hospital, Madison, Wisconsin, United States
| | - Kimberly D. Mueller
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison
- Department of Communication Sciences and Disorders, University of Wisconsin–Madison
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Dong R, Lu Q, Kang H, Suridjan I, Kollmorgen G, Wild N, Deming Y, Van Hulle CA, Anderson RM, Zetterberg H, Blennow K, Carlsson CM, Asthana S, Johnson SC, Engelman CD. CSF metabolites associated with biomarkers of Alzheimer's disease pathology. Front Aging Neurosci 2023; 15:1214932. [PMID: 37719875 PMCID: PMC10499619 DOI: 10.3389/fnagi.2023.1214932] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Accepted: 07/17/2023] [Indexed: 09/19/2023] Open
Abstract
Introduction Metabolomics technology facilitates studying associations between small molecules and disease processes. Correlating metabolites in cerebrospinal fluid (CSF) with Alzheimer's disease (AD) CSF biomarkers may elucidate additional changes that are associated with early AD pathology and enhance our knowledge of the disease. Methods The relative abundance of untargeted metabolites was assessed in 161 individuals from the Wisconsin Registry for Alzheimer's Prevention. A metabolome-wide association study (MWAS) was conducted between 269 CSF metabolites and protein biomarkers reflecting brain amyloidosis, tau pathology, neuronal and synaptic degeneration, and astrocyte or microglial activation and neuroinflammation. Linear mixed-effects regression analyses were performed with random intercepts for sample relatedness and repeated measurements and fixed effects for age, sex, and years of education. The metabolome-wide significance was determined by a false discovery rate threshold of 0.05. The significant metabolites were replicated in 154 independent individuals from then Wisconsin Alzheimer's Disease Research Center. Mendelian randomization was performed using genome-wide significant single nucleotide polymorphisms from a CSF metabolites genome-wide association study. Results Metabolome-wide association study results showed several significantly associated metabolites for all the biomarkers except Aβ42/40 and IL-6. Genetic variants associated with metabolites and Mendelian randomization analysis provided evidence for a causal association of metabolites for soluble triggering receptor expressed on myeloid cells 2 (sTREM2), amyloid β (Aβ40), α-synuclein, total tau, phosphorylated tau, and neurogranin, for example, palmitoyl sphingomyelin (d18:1/16:0) for sTREM2, and erythritol for Aβ40 and α-synuclein. Discussion This study provides evidence that CSF metabolites are associated with AD-related pathology, and many of these associations may be causal.
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Affiliation(s)
- Ruocheng Dong
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - Qiongshi Lu
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - Hyunseung Kang
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | | | | | | | - Yuetiva Deming
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - Carol A. Van Hulle
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - Rozalyn M. Anderson
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
- Geriatrics Research Education and Clinical Center, Middleton VA Hospital, Madison, WI, United States
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- UK Dementia Research Institute at UCL, London, United Kingdom
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, Hong Kong SAR, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Cynthia M. Carlsson
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
- Geriatrics Research Education and Clinical Center, Middleton VA Hospital, Madison, WI, United States
| | - Sanjay Asthana
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
- Geriatrics Research Education and Clinical Center, Middleton VA Hospital, Madison, WI, United States
| | - Sterling C. Johnson
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
- Geriatrics Research Education and Clinical Center, Middleton VA Hospital, Madison, WI, United States
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - Corinne D. Engelman
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
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Deming Y, Vasiljevic E, Morrow A, Miao J, Van Hulle C, Jonaitis E, Ma Y, Whitenack V, Kollmorgen G, Wild N, Suridjan I, Shaw LM, Asthana S, Carlsson CM, Johnson SC, Zetterberg H, Blennow K, Bendlin BB, Lu Q, Engelman CD. Neuropathology-based APOE genetic risk score better quantifies Alzheimer's risk. Alzheimers Dement 2023; 19:3406-3416. [PMID: 36795776 PMCID: PMC10427737 DOI: 10.1002/alz.12990] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 01/06/2023] [Accepted: 01/09/2023] [Indexed: 02/17/2023]
Abstract
INTRODUCTION Apolipoprotein E (APOE) ε4-carrier status or ε4 allele count are included in analyses to account for the APOE genetic effect on Alzheimer's disease (AD); however, this does not account for protective effects of APOE ε2 or heterogeneous effect of ε2, ε3, and ε4 haplotypes. METHODS We leveraged results from an autopsy-confirmed AD study to generate a weighted risk score for APOE (APOE-npscore). We regressed cerebrospinal fluid (CSF) amyloid and tau biomarkers on APOE variables from the Wisconsin Registry for Alzheimer's Prevention (WRAP), Wisconsin Alzheimer's Disease Research Center (WADRC), and Alzheimer's Disease Neuroimaging Initiative (ADNI). RESULTS The APOE-npscore explained more variance and provided a better model fit for all three CSF measures than APOE ε4-carrier status and ε4 allele count. These findings were replicated in ADNI and observed in subsets of cognitively unimpaired (CU) participants. DISCUSSION The APOE-npscore reflects the genetic effect on neuropathology and provides an improved method to account for APOE in AD-related analyses.
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Affiliation(s)
- Yuetiva Deming
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Eva Vasiljevic
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Autumn Morrow
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Jiacheng Miao
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Carol Van Hulle
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Erin Jonaitis
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Wisconsin Alzheimer's Institute, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Yue Ma
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Vanessa Whitenack
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | | | | | | | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sanjay Asthana
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
- William S. Middleton Memorial Veterans Hospital, Geriatric Research Education and Clinical Center, Madison, Wisconsin, USA
| | - Cynthia M Carlsson
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
- William S. Middleton Memorial Veterans Hospital, Geriatric Research Education and Clinical Center, Madison, Wisconsin, USA
| | - Sterling C Johnson
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
- William S. Middleton Memorial Veterans Hospital, Geriatric Research Education and Clinical Center, Madison, Wisconsin, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- UK Dementia Research Institute at UCL, London, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Barbara B Bendlin
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Qiongshi Lu
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Corinne D Engelman
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, Wisconsin, USA
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Erickson P, Simrén J, Brum WS, Ennis GE, Kollmorgen G, Suridjan I, Langhough R, Jonaitis EM, Van Hulle CA, Betthauser TJ, Carlsson CM, Asthana S, Ashton NJ, Johnson SC, Shaw LM, Blennow K, Andreasson U, Bendlin BB, Zetterberg H. Prevalence and Clinical Implications of a β-Amyloid-Negative, Tau-Positive Cerebrospinal Fluid Biomarker Profile in Alzheimer Disease. JAMA Neurol 2023; 80:2807607. [PMID: 37523162 PMCID: PMC10391361 DOI: 10.1001/jamaneurol.2023.2338] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 05/05/2023] [Indexed: 08/01/2023]
Abstract
Importance Knowledge is lacking on the prevalence and prognosis of individuals with a β-amyloid-negative, tau-positive (A-T+) cerebrospinal fluid (CSF) biomarker profile. Objective To estimate the prevalence of a CSF A-T+ biomarker profile and investigate its clinical implications. Design, Setting, and Participants This was a retrospective cohort study of the cross-sectional multicenter University of Gothenburg (UGOT) cohort (November 2019-January 2021), the longitudinal multicenter Alzheimer Disease Neuroimaging Initiative (ADNI) cohort (individuals with mild cognitive impairment [MCI] and no cognitive impairment; September 2005-May 2022), and 2 Wisconsin cohorts, Wisconsin Alzheimer Disease Research Center and Wisconsin Registry for Alzheimer Prevention (WISC; individuals without cognitive impairment; February 2007-November 2020). This was a multicenter study, with data collected from referral centers in clinical routine (UGOT) and research settings (ADNI and WISC). Eligible individuals had 1 lumbar puncture (all cohorts), 2 or more cognitive assessments (ADNI and WISC), and imaging (ADNI only) performed on 2 separate occasions. Data were analyzed on August 2022 to April 2023. Exposures Baseline CSF Aβ42/40 and phosphorylated tau (p-tau)181; cognitive tests (ADNI: modified preclinical Alzheimer cognitive composite [mPACC]; WISC: modified 3-test PACC [PACC-3]). Exposures in the ADNI cohort included [18F]-florbetapir amyloid positron emission tomography (PET), magnetic resonance imaging (MRI), [18F]-fluorodeoxyglucose PET (FDG-PET), and cross-sectional tau-PET (ADNI: [18F]-flortaucipir, WISC: [18F]-MK6240). Main Outcomes and Measures Primary outcomes were the prevalence of CSF AT biomarker profiles and continuous longitudinal global cognitive outcome and imaging biomarker trajectories in A-T+ vs A-T- groups. Secondary outcomes included cross-sectional tau-PET. Results A total of 7679 individuals (mean [SD] age, 71.0 [8.4] years; 4101 male [53%]) were included in the UGOT cohort, 970 individuals (mean [SD] age, 73 [7.0] years; 526 male [54%]) were included in the ADNI cohort, and 519 individuals (mean [SD] age, 60 [7.3] years; 346 female [67%]) were included in the WISC cohort. The prevalence of an A-T+ profile in the UGOT cohort was 4.1% (95% CI, 3.7%-4.6%), being less common than the other patterns. Longitudinally, no significant differences in rates of worsening were observed between A-T+ and A-T- profiles for cognition or imaging biomarkers. Cross-sectionally, A-T+ had similar tau-PET uptake to individuals with an A-T- biomarker profile. Conclusion and Relevance Results suggest that the CSF A-T+ biomarker profile was found in approximately 5% of lumbar punctures and was not associated with a higher rate of cognitive decline or biomarker signs of disease progression compared with biomarker-negative individuals.
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Affiliation(s)
- Pontus Erickson
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Joel Simrén
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Wagner S. Brum
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Gilda E. Ennis
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
| | | | | | - Rebecca Langhough
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
| | - Erin M. Jonaitis
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
| | - Carol A. Van Hulle
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
| | - Tobey J. Betthauser
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
| | - Cynthia M. Carlsson
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
- Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison
- Geriatric Research Education and Clinical Center of the Wm. S. Middleton Memorial Veterans Hospital, Madison, Wisconsin
| | - Sanjay Asthana
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
- Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison
- Geriatric Research Education and Clinical Center of the Wm. S. Middleton Memorial Veterans Hospital, Madison, Wisconsin
| | - Nicholas J. Ashton
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, King’s College London, London, England
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, England
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Sterling C. Johnson
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
| | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Ulf Andreasson
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Barbara B. Bendlin
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Institute of Neurology, Department of Neurodegenerative Disease, University College London, London, England
- UK Dementia Research Institute, University College London, London, England
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
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43
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Ashton NJ, Brum WS, Di Molfetta G, Benedet AL, Arslan B, Jonatis E, Langhough RE, Cody K, Wilson R, Carlsson CM, Vanmechelen E, Montoliu-Gaya L, Lantero-Rodriguez J, Rahmouni N, Tissot C, Stevenson J, Servaes S, Therriault J, Pascoal T, Lleó A, Alcolea D, Fortea J, Rosa-Neto P, Johnson S, Jeromin A, Blennow K, Zetterberg H. Diagnostic accuracy of the plasma ALZpath pTau217 immunoassay to identify Alzheimer's disease pathology. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.11.23292493. [PMID: 37502842 PMCID: PMC10370224 DOI: 10.1101/2023.07.11.23292493] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Importance Phosphorylated tau (pTau) is a specific blood biomarker for Alzheimer's disease (AD) pathology, with pTau217 considered to have the most utility. However, availability of pTau217 tests for research and clinical use has been limited. Expanding access to this highly accurate AD biomarker is crucial for wider evaluation and implementation of AD blood tests. Objective To determine the utility of a novel and commercially available Single molecule array (Simoa) for plasma pTau217 (ALZpath) to detect AD pathology. To evaluate references ranges for abnormal Aβ across three selected cohorts. Design Setting Participants Three single-centre observational cohorts were involved in the study: Translational Biomarkers in Aging and Dementia (TRIAD), Wisconsin Registry for Alzheimer's Prevention (WRAP), and Sant Pau Initiative on Neurodegeneration (SPIN). MRI, Aβ-PET, and tau-PET data were available for TRIAD and WRAP, while CSF biomarkers were additionally measured in a subset of TRIAD and SPIN. Plasma measurements of pTau181, pTau217 (ALZpath), pTau231, Aβ42/40, GFAP, and NfL, were available for all cohorts. Longitudinal blood biomarker data spanning 3 years for TRIAD and 8 years for WRAP were included. Exposures MRI, Aβ-PET, tau-PET, CSF biomarkers (Aβ42/40 and pTau immunoassays) and plasma pTau217 (ALZpath Simoa). Main Outcomes and Measures The accuracy of plasma pTau217 for detecting abnormal amyloid and tau pathology. Longitudinal pTau217 change according to baseline pathology status. Results The study included 786 participants (mean [SD] age, 66.3 [9.7] years; 504 females [64.1%]) were included in the study. High accuracy was observed in identifying elevated Aβ (AUC, 0.92-0.96; 95%CI 0.89-0.99) and tau pathology (AUC, 0.93-0.97; 95%CI 0.84-0.99) across all cohorts. These accuracies were significantly higher than other plasma biomarker combinations and comparable to CSF biomarkers. The detection of abnormal Aβ pathology using binary or three-range references yielded reproducible results. Longitudinally, plasma pTau217 showed an annual increase only in Aβ-positive individuals, with the highest increase observed in those with tau-positivity. Conclusions and Relevance The ALZpath plasma pTau217 Simoa assay accurately identifies biological AD, comparable to CSF biomarkers, with reproducible cut-offs across cohorts. It detects longitudinal changes, including at the preclinical stage, and is the first widely available, accessible, and scalable blood test for pTau217 detection.
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Affiliation(s)
- Nicholas J. Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience Maurice Wohl Institute Clinical Neuroscience Institute London UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation London UK
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Wagner S. Brum
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Guglielmo Di Molfetta
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Andrea L. Benedet
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Burak Arslan
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Erin Jonatis
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Rebecca E. Langhough
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Karly Cody
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Rachael Wilson
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Cynthia M. Carlsson
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
- Geriatric Research Education and Clinical Center of the Wm. S. Middleton Memorial Veterans Hospital, Madison, WI 53705, USA
| | | | - Laia Montoliu-Gaya
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Juan Lantero-Rodriguez
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Nesrine Rahmouni
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Cecile Tissot
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Jenna Stevenson
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Stijn Servaes
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Tharick Pascoal
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Alberto Lleó
- Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Hospital de la Santa Creu i Sant Pau, Barcelona, Catalunya
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Daniel Alcolea
- Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Hospital de la Santa Creu i Sant Pau, Barcelona, Catalunya
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Juan Fortea
- Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Hospital de la Santa Creu i Sant Pau, Barcelona, Catalunya
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Sterling Johnson
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
| | | | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
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44
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Salvadó G, Larsson V, Cody KA, Cullen NC, Jonaitis EM, Stomrud E, Kollmorgen G, Wild N, Palmqvist S, Janelidze S, Mattsson-Carlgren N, Zetterberg H, Blennow K, Johnson SC, Ossenkoppele R, Hansson O. Optimal combinations of CSF biomarkers for predicting cognitive decline and clinical conversion in cognitively unimpaired participants and mild cognitive impairment patients: A multi-cohort study. Alzheimers Dement 2023; 19:2943-2955. [PMID: 36648169 PMCID: PMC10350470 DOI: 10.1002/alz.12907] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Revised: 10/30/2022] [Accepted: 11/15/2022] [Indexed: 01/18/2023]
Abstract
INTRODUCTION Our objective was determining the optimal combinations of cerebrospinal fluid (CSF) biomarkers for predicting disease progression in Alzheimer's disease (AD) and other neurodegenerative diseases. METHODS We included 1,983 participants from three different cohorts with longitudinal cognitive and clinical data, and baseline CSF levels of Aβ42, Aβ40, phosphorylated tau at threonine-181 (p-tau), neurofilament light (NfL), neurogranin, α-synuclein, soluble triggering receptor expressed on myeloid cells 2 (sTREM2), glial fibrillary acidic protein (GFAP), YKL-40, S100b, and interleukin 6 (IL-6) (Elecsys NeuroToolKit). RESULTS Change of modified Preclinical Alzheimer's Cognitive Composite (mPACC) in cognitively unimpaired (CU) was best predicted by p-tau/Aβ42 alone (R2 ≥ 0.31) or together with NfL (R2 = 0.25), while p-tau/Aβ42 (R2 ≥ 0.19) was sufficient to accurately predict change of the Mini-Mental State Examination (MMSE) in mild cognitive impairment (MCI) patients. P-tau/Aβ42 (AUC ≥ 0.87) and p-tau/Aβ42 together with NfL (AUC ≥ 0.75) were the best predictors of conversion to AD and all-cause dementia, respectively. DISCUSSION P-tau/Aβ42 is sufficient for predicting progression in AD, with very high accuracy. Adding NfL improves the prediction of all-cause dementia conversion and cognitive decline.
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Affiliation(s)
- Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Victoria Larsson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Karly A Cody
- Wisconsin Alzheimer’s Disease Research Center University of Wisconsin School of Medicine and Public Health Madison Wisconsin, Madison, Wisconsin, USA
| | - Nicholas C Cullen
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Erin M Jonaitis
- Wisconsin Alzheimer’s Disease Research Center University of Wisconsin School of Medicine and Public Health Madison Wisconsin, Madison, Wisconsin, USA
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | | | | | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, United Kingdom
- UK Dementia Research Institute at UCL, London, United Kingdom
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Sterling C Johnson
- Wisconsin Alzheimer’s Disease Research Center University of Wisconsin School of Medicine and Public Health Madison Wisconsin, Madison, Wisconsin, USA
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Geriatric Research, Education and Clinical Center at the William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin, USA
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
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Vasiljevic E, Koscik RL, Jonaitis E, Betthauser T, Johnson SC, Engelman CD. Cognitive trajectories diverge by genetic risk in a preclinical longitudinal cohort. Alzheimers Dement 2023; 19:3108-3118. [PMID: 36723444 PMCID: PMC10390653 DOI: 10.1002/alz.12920] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 12/06/2022] [Accepted: 12/12/2022] [Indexed: 02/02/2023]
Abstract
INTRODUCTION We sought to characterize the timing of changes in cognitive trajectories related to genetic risk using the apolipoprotein E (APOE) score, a continuous measure of Alzheimer's disease (AD) risk. We also aimed to determine whether that timing was different when genetic risk was measured using an AD polygenic risk score (PRS) that contains APOE. METHODS We analyzed trajectories (N ≈1135) for four neuropsychological composite scores using mixed effects regression for longitudinal change across APOE scores and PRS of participants in the Wisconsin Registry for Alzheimer's Prevention, a longitudinal study of adults aged 40 to 70 at baseline, with a median participant follow-up time of 7.8 years. RESULTS We found a significant non-linear age-by-APOE score interaction in predicting cognitive decline. Cognitive trajectories diverged by APOE score at approximately 65 years of age. A 0.5 standard deviation difference in cognition between extreme percentiles of the PRS was predicted to occur 1 to 2 years before that of the APOE score. DISCUSSION Cognitive decline differs across time and APOE score. Estimates did not substantially shift with the AD PRS. HIGHLIGHTS The apolipoprotein E (APOE) score, a continuous measure, accounts for non-linear genetic risk of Alzheimer's disease. Non-linear age interacts with the APOE score to affect cognition. Cognitive decline starts to differ by APOE score levels at approximately age 65. Cognitive decline timing by polygenic risk (including APOE) is similar to APOE alone.
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Affiliation(s)
- Eva Vasiljevic
- Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, 610 Walnut Dr., Madison, WI 53726, USA
- Center for Demography of Health and Aging, University of Wisconsin-Madison, 1180 Observatory Drive Madison, WI 53706, USA
| | - Rebecca Langhough Koscik
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, 610 Walnut Street, 9th Floor, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, 600 Highland Avenue, MC 2420, Madison, Wisconsin 53792, USA
| | - Erin Jonaitis
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, 610 Walnut Street, 9th Floor, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, 600 Highland Avenue, MC 2420, Madison, Wisconsin 53792, USA
| | - Tobey Betthauser
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, 600 Highland Avenue, MC 2420, Madison, Wisconsin 53792, USA
- Department of Medicine, University of Wisconsin-Madison, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI 53705, USA
| | - Sterling C. Johnson
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, 610 Walnut Street, 9th Floor, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, 600 Highland Avenue, MC 2420, Madison, Wisconsin 53792, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, 2500 Overlook Terrace, Madison, WI 53705, USA
| | - Corinne D. Engelman
- Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, 610 Walnut Dr., Madison, WI 53726, USA
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, 610 Walnut Street, 9th Floor, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, 600 Highland Avenue, MC 2420, Madison, Wisconsin 53792, USA
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Ketchum FB, Chin NA, Erickson C, Lambrou NH, Basche K, Gleason CE, Clark L. The importance of the dyad: Participant perspectives on sharing biomarker results in Alzheimer's disease research. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2023; 9:e12416. [PMID: 37583545 PMCID: PMC10423755 DOI: 10.1002/trc2.12416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 06/23/2023] [Accepted: 06/25/2023] [Indexed: 08/17/2023]
Abstract
BACKGROUND In the asymptomatic "preclinical" phase of Alzheimer's disease (AD), abnormal biomarkers indicate risk for developing cognitive impairment. Biomarker information is increasingly being disclosed to participants in research settings, and biomarker testing and results disclosure will be implemented in clinical settings in the future. Biomarker disclosure has potential psychosocial benefits and harms, impacting affected individuals and their support person(s). Limited data are available about with whom research participants share their results, information that will be necessary to develop disclosure protocols and post-disclosure resources. Additionally, existing research has been conducted in largely White cohorts, limiting applicability to future clinical populations. METHODS We enrolled a diverse cohort of 329 adults (184 non-Hispanic White and 145 Black/African American individuals) who previously participated in AD research. After reviewing a vignette describing a hypothetical biomarker research study, participants indicated their anticipated willingness to share biomarker results with loved ones, and what reactions they anticipated from others. Using mixed-methods analysis, we identified responses related to willingness to share results. RESULTS A majority (78.7%) were willing to share their results with support persons. Many (59.6%) felt it would not be difficult to share, and most (90.6%) believed their loved ones would be supportive. The most common reasons for sharing were to prepare for possible future AD (41.0% of respondents), while the most common reason for not sharing was to avoid worrying loved ones (4.8% of respondents). A total of 7.3% of respondents related reasons regarding being unsure about sharing. DISCUSSION Participants' interest in sharing results supports integrating support persons into AD biomarker research, and may help maximize potential benefits for participants. Communicating with this "dyad" of research participant and support person(s) may improve involvement in research, and help prepare for implementation of clinical biomarker testing by clarifying communication preferences and the influence of support persons on psychosocial outcomes.
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Affiliation(s)
- Fred B. Ketchum
- Department of NeurologySchool of Medicine and Public HealthUniversity of WisconsinMadisonWisconsinUSA
| | - Nathaniel A. Chin
- Division of GeriatricsDepartment of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterMadisonWisconsinUSA
| | - Claire Erickson
- Department of Medical Ethics and Health PolicyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Nickolas H. Lambrou
- Division of GeriatricsDepartment of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Kristin Basche
- Division of GeriatricsDepartment of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Carey E. Gleason
- Division of GeriatricsDepartment of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterMadisonWisconsinUSA
- Geriatric ResearchEducation and Clinical CenterWilliam S. Middleton Memorial Veterans HospitalMadisonWisconsinUSA
| | - Lindsay Clark
- Division of GeriatricsDepartment of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterMadisonWisconsinUSA
- Geriatric ResearchEducation and Clinical CenterWilliam S. Middleton Memorial Veterans HospitalMadisonWisconsinUSA
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Erickson CM, Chin NA, Rosario HL, Peterson A, Johnson SC, Clark LR. Feasibility of virtual Alzheimer's biomarker disclosure: Findings from an observational cohort. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2023; 9:e12413. [PMID: 37521522 PMCID: PMC10382796 DOI: 10.1002/trc2.12413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Revised: 06/09/2023] [Accepted: 07/01/2023] [Indexed: 08/01/2023]
Abstract
Introduction Increased availability of Alzheimer's disease (AD) biomarker tests provides older adults with opportunities to seek out and learn results. We evaluated the feasibility of virtually returning AD biomarker results. Methods Trained study clinicians disclosed amyloid positron emission tomography (PET) results and provided dementia risk-reduction counseling via televideo to cognitively unimpaired participants already enrolled in AD research (n = 99; mean age ± SD: 72.0 ± 4.8; 67% women; 95% White; 28% amyloid elevated). Results Our study demonstrated acceptable levels of retention (93%), compliance (98%), adherence (98%), clinician competence (97%), education comprehension (quiz scores 14/15), and virtual visit functionality (rating 9.4/10). Depression, anxiety, and suicidality remained low and did not differ by amyloid result. Discussion Virtual return of amyloid PET results to cognitively unimpaired research participants is feasible and does not result in increased psychological symptoms. Technological barriers for some participants highlight the need for flexibility. These findings support the use of televideo in AD biomarker disclosure, although our study sample and design have important limitations for generalizability.
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Affiliation(s)
- Claire M. Erickson
- Department of Medical Ethics and Health PolicyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Nathaniel A. Chin
- Department of MedicineDivision of Geriatrics & GerontologyUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Hannah L. Rosario
- Department of MedicineDivision of Geriatrics & GerontologyUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Amanda Peterson
- Department of MedicineDivision of Geriatrics & GerontologyUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Sterling C. Johnson
- Department of MedicineDivision of Geriatrics & GerontologyUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's InstituteUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans HospitalMadisonWisconsinUSA
| | - Lindsay R. Clark
- Department of MedicineDivision of Geriatrics & GerontologyUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans HospitalMadisonWisconsinUSA
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Coughlan GT, Betthauser TJ, Boyle R, Koscik RL, Klinger HM, Chibnik LB, Jonaitis EM, Yau WYW, Wenzel A, Christian BT, Gleason CE, Saelzler UG, Properzi MJ, Schultz AP, Hanseeuw BJ, Manson JE, Rentz DM, Johnson KA, Sperling R, Johnson SC, Buckley RF. Association of Age at Menopause and Hormone Therapy Use With Tau and β-Amyloid Positron Emission Tomography. JAMA Neurol 2023; 80:462-473. [PMID: 37010830 PMCID: PMC10071399 DOI: 10.1001/jamaneurol.2023.0455] [Citation(s) in RCA: 34] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 12/16/2022] [Indexed: 04/04/2023]
Abstract
Importance Postmenopausal females represent around 70% of all individuals with Alzheimer disease. Previous literature shows elevated levels of tau in cognitively unimpaired postmenopausal females compared with age-matched males, particularly in the setting of high β-amyloid (Aβ). The biological mechanisms associated with higher tau deposition in female individuals remain elusive. Objective To examine the extent to which sex, age at menopause, and hormone therapy (HT) use are associated with regional tau at a given level of Aβ, both measured with positron emission tomography (PET). Design, Setting, and Participants This cross-sectional study included participants enrolled in the Wisconsin Registry for Alzheimer Prevention. Cognitively unimpaired males and females with at least 1 18F-MK-6240 and 11C-Pittsburgh compound B PET scan were analyzed. Data were collected between November 2006 and May 2021. Exposures Premature menopause (menopause at younger than 40 years), early menopause (menopause at age 40-45 years), and regular menopause (menopause at older than 45 years) and HT user (current/past use) and HT nonuser (no current/past use). Exposures were self-reported. Main Outcomes and Measures Seven tau PET regions that show sex differences across temporal, parietal, and occipital lobes. Primary analyses examined the interaction of sex, age at menopause or HT, and Aβ PET on regional tau PET in a series of linear regressions. Secondary analyses investigated the influence of HT timing in association with age at menopause on regional tau PET. Results Of 292 cognitively unimpaired individuals, there were 193 females (66.1%) and 99 males (33.9%). The mean (range) age at tau scan was 67 (49-80) years, 52 (19%) had abnormal Aβ, and 106 (36.3%) were APOEε4 carriers. There were 98 female HT users (52.2%) (past/current). Female sex (standardized β = -0.41; 95% CI, -0.97 to -0.32; P < .001), earlier age at menopause (standardized β = -0.38; 95% CI, -0.14 to -0.09; P < .001), and HT use (standardized β = 0.31; 95% CI, 0.40-1.20; P = .008) were associated with higher regional tau PET in individuals with elevated Aβ compared with male sex, later age at menopause, and HT nonuse. Affected regions included medial and lateral regions of the temporal and occipital lobes. Late initiation of HT (>5 years following age at menopause) was associated with higher tau PET compared with early initiation (β = 0.49; 95% CI, 0.27-0.43; P = .001). Conclusions and Relevance In this study, females exhibited higher tau compared with age-matched males, particularly in the setting of elevated Aβ. In females, earlier age at menopause and late initiation of HT were associated with increased tau vulnerability especially when neocortical Aβ elevated. These observational findings suggest that subgroups of female individuals may be at higher risk of pathological burden.
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Affiliation(s)
- Gillian T. Coughlan
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Tobey J. Betthauser
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin, School of Medicine and Public Health, Madison
- Department of Medicine, University of Wisconsin–Madison, Madison
| | - Rory Boyle
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Rebecca L. Koscik
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin, School of Medicine and Public Health, Madison
- Department of Medicine, University of Wisconsin–Madison, Madison
| | - Hannah M. Klinger
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Lori B. Chibnik
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, and the Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Erin M. Jonaitis
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin, School of Medicine and Public Health, Madison
- Department of Medicine, University of Wisconsin–Madison, Madison
| | - Wai-Ying Wendy Yau
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Allen Wenzel
- Department of Medicine, University of Wisconsin–Madison, Madison
| | - Bradley T. Christian
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin, School of Medicine and Public Health, Madison
| | - Carey E. Gleason
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin, School of Medicine and Public Health, Madison
| | - Ursula G. Saelzler
- Department of Psychiatry, University of California, San Diego, San Diego
| | - Michael J. Properzi
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Aaron P. Schultz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
- Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Bernard J. Hanseeuw
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
- Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Boston, Massachusetts
- Department of Neurology, Cliniques Universitaires Saint-Luc, Woluwe-Saint-Lambert, Belgium
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston
- Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium
| | - JoAnn E. Manson
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, and the Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Dorene M. Rentz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
- Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Keith A. Johnson
- Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Boston, Massachusetts
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Reisa Sperling
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
- Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Sterling C. Johnson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin, School of Medicine and Public Health, Madison
- Department of Medicine, University of Wisconsin–Madison, Madison
| | - Rachel F. Buckley
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
- Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Boston, Massachusetts
- Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Victoria, Australia
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Dong R, Denier-Fields DN, Van Hulle CA, Kollmorgen G, Suridjan I, Wild N, Lu Q, Anderson RM, Zetterberg H, Blennow K, Carlsson CM, Johnson SC, Engelman CD. Identification of plasma metabolites associated with modifiable risk factors and endophenotypes reflecting Alzheimer's disease pathology. Eur J Epidemiol 2023; 38:559-571. [PMID: 36964431 PMCID: PMC11070200 DOI: 10.1007/s10654-023-00988-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 03/05/2023] [Indexed: 03/26/2023]
Abstract
Modifiable factors can influence the risk for Alzheimer's disease (AD) and serve as targets for intervention; however, the biological mechanisms linking these factors to AD are unknown. This study aims to identify plasma metabolites associated with modifiable factors for AD, including MIND diet, physical activity, smoking, and caffeine intake, and test their association with AD endophenotypes to identify their potential roles in pathophysiological mechanisms. The association between each of the 757 plasma metabolites and four modifiable factors was tested in the wisconsin registry for Alzheimer's prevention cohort of initially cognitively unimpaired, asymptomatic middle-aged adults. After Bonferroni correction, the significant plasma metabolites were tested for association with each of the AD endophenotypes, including twelve cerebrospinal fluid (CSF) biomarkers, reflecting key pathophysiologies for AD, and four cognitive composite scores. Finally, causal mediation analyses were conducted to evaluate possible mediation effects. Analyses were performed using linear mixed-effects regression. A total of 27, 3, 23, and 24 metabolites were associated with MIND diet, physical activity, smoking, and caffeine intake, respectively. Potential mediation effects include beta-cryptoxanthin in the association between MIND diet and preclinical Alzheimer cognitive composite score, hippurate between MIND diet and immediate learning, glutamate between physical activity and CSF neurofilament light, and beta-cryptoxanthin between smoking and immediate learning. Our study identified several plasma metabolites that are associated with modifiable factors. These metabolites can be employed as biomarkers for tracking these factors, and they provide a potential biological pathway of how modifiable factors influence the human body and AD risk.
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Affiliation(s)
- Ruocheng Dong
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53726, USA
| | - Diandra N Denier-Fields
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53726, USA
- Department of Nutrition Science, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Carol A Van Hulle
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
| | | | | | - Norbert Wild
- Roche Diagnostics GmbH, 82377, Penzberg, Germany
| | - Qiongshi Lu
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
| | - Rozalyn M Anderson
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
- Geriatric Research Education and Clinical Center, William. S. Middleton Memorial Veterans Hospital, Madison, WI, 53705, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, S-43180, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, S-43180, Mölndal, Sweden
- UK Dementia Research Institute at UCL, London, WC1E 6BT, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, WC1H 0AL, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, S-43180, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, S-43180, Mölndal, Sweden
| | - Cynthia M Carlsson
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
- Geriatric Research Education and Clinical Center, William. S. Middleton Memorial Veterans Hospital, Madison, WI, 53705, USA
| | - Sterling C Johnson
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
- Geriatric Research Education and Clinical Center, William. S. Middleton Memorial Veterans Hospital, Madison, WI, 53705, USA
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53719, USA
| | - Corinne D Engelman
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53726, USA.
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA.
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53719, USA.
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50
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Mattsson-Carlgren N, Salvadó G, Ashton NJ, Tideman P, Stomrud E, Zetterberg H, Ossenkoppele R, Betthauser TJ, Cody KA, Jonaitis EM, Langhough R, Palmqvist S, Blennow K, Janelidze S, Johnson SC, Hansson O. Prediction of Longitudinal Cognitive Decline in Preclinical Alzheimer Disease Using Plasma Biomarkers. JAMA Neurol 2023; 80:360-369. [PMID: 36745413 PMCID: PMC10087054 DOI: 10.1001/jamaneurol.2022.5272] [Citation(s) in RCA: 83] [Impact Index Per Article: 83.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 11/12/2022] [Indexed: 02/07/2023]
Abstract
Importance Alzheimer disease (AD) pathology starts with a prolonged phase of β-amyloid (Aβ) accumulation without symptoms. The duration of this phase differs greatly among individuals. While this disease phase has high relevance for clinical trial designs, it is currently unclear how to best predict the onset of clinical progression. Objective To evaluate combinations of different plasma biomarkers for predicting cognitive decline in Aβ-positive cognitively unimpaired (CU) individuals. Design, Setting, and Participants This prospective population-based prognostic study evaluated data from 2 prospective longitudinal cohort studies (the Swedish BioFINDER-1 and the Wisconsin Registry for Alzheimer Prevention [WRAP]), with data collected from February 8, 2010, to October 21, 2020, for the BioFINDER-1 cohort and from August 11, 2011, to June 27, 2021, for the WRAP cohort. Participants were CU individuals recruited from memory clinics who had brain Aβ pathology defined by cerebrospinal fluid (CSF) Aβ42/40 in the BioFINDER-1 study and by Pittsburgh Compound B (PiB) positron emission tomography (PET) in the WRAP study. A total of 564 eligible Aβ-positive and Aβ-negative CU participants with available relevant data from the BioFINDER-1 and WRAP cohorts were included in the study; of those, 171 Aβ-positive participants were included in the main analyses. Exposures Baseline P-tau181, P-tau217, P-tau231, glial fibrillary filament protein, and neurofilament light measured in plasma; CSF biomarkers in the BioFINDER-1 cohort, and PiB PET uptake in the WRAP cohort. Main Outcomes and Measures The primary outcome was longitudinal measures of cognition (using the Mini-Mental State Examination [MMSE] and the modified Preclinical Alzheimer Cognitive Composite [mPACC]) over a median of 6 years (range, 2-10 years). The secondary outcome was conversion to AD dementia. Baseline biomarkers were used in linear regression models to predict rates of longitudinal cognitive change (calculated separately). Models were adjusted for age, sex, years of education, apolipoprotein E ε4 allele status, and baseline cognition. Multivariable models were compared based on model R2 coefficients and corrected Akaike information criterion. Results Among 171 Aβ-positive CU participants included in the main analyses, 119 (mean [SD] age, 73.0 [5.4] years; 60.5% female) were from the BioFINDER-1 study, and 52 (mean [SD] age, 64.4 [4.6] years; 65.4% female) were from the WRAP study. In the BioFINDER-1 cohort, plasma P-tau217 was the best marker to predict cognitive decline in the mPACC (model R2 = 0.41) and the MMSE (model R2 = 0.34) and was superior to the covariates-only models (mPACC: R2 = 0.23; MMSE: R2 = 0.04; P < .001 for both comparisons). Results were validated in the WRAP cohort; for example, plasma P-tau217 was associated with mPACC slopes (R2 = 0.13 vs 0.01 in the covariates-only model; P = .01) and MMSE slopes (R2 = 0.29 vs 0.24 in the covariates-only model; P = .046). Sparse models were identified with plasma P-tau217 as a predictor of cognitive decline. Power calculations for enrichment in hypothetical clinical trials revealed large relative reductions in sample sizes when using plasma P-tau217 to enrich for CU individuals likely to experience cognitive decline over time. Conclusions and Relevance In this study, plasma P-tau217 predicted cognitive decline in patients with preclinical AD. These findings suggest that plasma P-tau217 may be used as a complement to CSF or PET for participant selection in clinical trials of novel disease-modifying treatments.
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Affiliation(s)
- Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Gemma Salvadó
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Nicholas J. Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, London, United Kingdom
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, United Kingdom
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Pontus Tideman
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Lund University, Lund, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Lund University, Lund, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, University College London Institute of Neurology, Queen Square, London, United Kingdom
- UK Dementia Research Institute at University College London, London, United Kingdom
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, Hong Kong SAR, China
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Department of Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration Program, Amsterdam University Medical Centers, the Netherlands
| | - Tobey J. Betthauser
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
| | - Karly Alex Cody
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
| | - Erin M. Jonaitis
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
| | - Rebecca Langhough
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Lund University, Lund, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Sterling C. Johnson
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
| | - Oskar Hansson
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Lund University, Lund, Sweden
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