1
|
Lu R, Shah K, Toedebusch CD, Hess A, Richardson R, Mignot E, Schindler SE, Benzinger TLS, Flores S, Hassenstab J, Xiong C, Morris JC, Holtzman DM, Lucey BP. Associations of Cerebrospinal Fluid Orexin-A, Alzheimer Disease Biomarkers, and Cognitive Performance. Ann Clin Transl Neurol 2025. [PMID: 39957622 DOI: 10.1002/acn3.70009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2024] [Revised: 12/29/2024] [Accepted: 01/28/2025] [Indexed: 02/18/2025] Open
Abstract
OBJECTIVE Cerebrospinal fluid (CSF) orexin-A has been suggested to be a biomarker of Alzheimer disease (AD). In both cognitively unimpaired healthy older adults and individuals with symptomatic AD, CSF orexin-A is positively associated with CSF Aβ42, p-tau181, and total tau (t-tau) concentrations. However, a recent systematic review and meta-analysis did not support differences in orexin-A between AD and controls. In this study, we tested the association between CSF orexin-A concentrations, AD biomarkers, and cognitive performance in older adults with and without symptomatic AD. METHODS Two hundred and seventy community-dwelling older adults underwent standardized cognitive assessments, sleep monitoring with a single-channel electroencephalography test, one night of home sleep apnea testing, biofluid and imaging AD biomarker measurement within 1 year of sleep monitoring, and APOE genotyping. Plasma and CSF AD biomarkers were measured by immunoassay or mass spectrometry. CSF orexin-A was measured by radioimmunoassay. RESULTS CSF orexin-A levels did not differ by amyloid positivity, cognitive status, or AD stage. However, CSF AD biomarkers (Aβ40, Aβ42, and t-tau) were positively associated with CSF orexin-A levels even after correction for multiple comparisons. CSF orexin-A was not associated with any measure of cognitive performance. INTERPRETATION This study showed that CSF orexin-A is associated with multiple CSF AD biomarkers, but not with AD pathology or cognitive performance. We hypothesize that this is due to similar mechanisms of production/release of these proteins with sleep-wake activity. Future studies measuring other forms of orexin peptides, such as orexin-B, may provide evidence for orexin as a marker for AD.
Collapse
Affiliation(s)
- Ruijin Lu
- Division of Biostatistics, Washington University School of Medicine, St Louis, Missouri, USA
| | - Krish Shah
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri, USA
| | - Cristina D Toedebusch
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri, USA
| | - Ashley Hess
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri, USA
| | - Rachel Richardson
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri, USA
| | - Emmanuel Mignot
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, California, USA
| | - Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, Missouri, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, Missouri, USA
| | - Tammie L S Benzinger
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, Missouri, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, Missouri, USA
- Department of Radiology, Washington University School of Medicine, St Louis, Missouri, USA
| | - Shaney Flores
- Department of Radiology, Washington University School of Medicine, St Louis, Missouri, USA
| | - Jason Hassenstab
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri, USA
| | - Chengjie Xiong
- Division of Biostatistics, Washington University School of Medicine, St Louis, Missouri, USA
| | - John C Morris
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, Missouri, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, Missouri, USA
| | - David M Holtzman
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, Missouri, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, Missouri, USA
| | - Brendan P Lucey
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, Missouri, USA
| |
Collapse
|
2
|
Landau SM, Harrison TM, Baker SL, Boswell MS, Lee J, Taggett J, Ward TJ, Chadwick T, Murphy A, DeCarli C, Schwarz CG, Vemuri P, Jack CR, Koeppe RA, Jagust WJ. Positron emission tomography harmonization in the Alzheimer's Disease Neuroimaging Initiative: A scalable and rigorous approach to multisite amyloid and tau quantification. Alzheimers Dement 2025; 21:e14378. [PMID: 39559932 PMCID: PMC11772732 DOI: 10.1002/alz.14378] [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: 06/04/2024] [Revised: 10/07/2024] [Accepted: 10/10/2024] [Indexed: 11/20/2024]
Abstract
INTRODUCTION A key goal of the Alzheimer's Disease NeuroImaging Initiative (ADNI) positron emission tomography (PET) Core is to harmonize quantification of β-amyloid (Aβ) and tau PET image data across multiple scanners and tracers. METHODS We developed an analysis pipeline (Berkeley PET Imaging Pipeline, B-PIP) for ADNI Aβ and tau PET images and applied it to PET data from other multisite studies. Steps include image pre-processing, refacing, magnetic resonance imaging (MRI)/PET co-registration, visual quality control (QC), quantification of tracer uptake, and standardization of Aβ and tau standardized uptake value ratios (SUVrs) across tracers. RESULTS Measurements from 10,105 cross-sectional and longitudinal Aβ and tau PET scans acquired in several studies between 2010 and 2024 can be processed, harmonized, and directly merged across tracers and cohorts. DISCUSSION The B-PIP developed in ADNI is a scalable image harmonization approach used in several observational studies and clinical trials that facilitates rigorous Aβ and tau PET quantification and data sharing. HIGHLIGHTS Quantitative results from ADNI Aβ and tau PET data are generated using a rigorous, scalable image processing pipeline This pipeline has been applied to PET data from several other large, multisite studies and trials Quantitative outcomes are harmonizable across studies and are shared with the scientific community.
Collapse
Affiliation(s)
- Susan M. Landau
- Neuroscience DepartmentUniversity of CaliforniaBerkeleyCaliforniaUSA
| | | | - Suzanne L. Baker
- Molecular Biophysics and Integrated BioimagingLawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | - Martin S. Boswell
- Molecular Biophysics and Integrated BioimagingLawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | - JiaQie Lee
- Neuroscience DepartmentUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - Jacinda Taggett
- Neuroscience DepartmentUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - Tyler J. Ward
- Neuroscience DepartmentUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - Trevor Chadwick
- Neuroscience DepartmentUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - Alice Murphy
- Neuroscience DepartmentUniversity of CaliforniaBerkeleyCaliforniaUSA
| | | | | | | | | | - Robert A. Koeppe
- Department of RadiologyUniversity of MichiganAnn ArborMichiganUSA
| | - William J. Jagust
- Neuroscience DepartmentUniversity of CaliforniaBerkeleyCaliforniaUSA
- Molecular Biophysics and Integrated BioimagingLawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | | |
Collapse
|
3
|
Dolatshahi M, Commean PK, Rahmani F, Xu Y, Liu J, Hosseinzadeh Kassani S, Naghashzadeh M, Lloyd L, Nguyen C, McBee Kemper A, Hantler N, Ly M, Yu G, Flores S, Ippolito JE, Song SK, Sirlin CB, Dai W, Mittendorfer B, Morris JC, Benzinger TLS, Raji CA. Relationships between abdominal adipose tissue and neuroinflammation with diffusion basis spectrum imaging in midlife obesity. Obesity (Silver Spring) 2025; 33:41-53. [PMID: 39517107 DOI: 10.1002/oby.24188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Revised: 09/26/2024] [Accepted: 09/27/2024] [Indexed: 11/16/2024]
Abstract
OBJECTIVE This study investigated how obesity, BMI ≥ 30 kg/m2, abdominal adiposity, and systemic inflammation relate to neuroinflammation using diffusion basis spectrum imaging. METHODS We analyzed data from 98 cognitively normal midlife participants (mean age: 49.4 [SD 6.2] years; 34 males [34.7%]; 56 with obesity [57.1%]). Participants underwent brain and abdominal magnetic resonance imaging (MRI), blood tests, and amyloid positron emission tomography (PET) imaging. Abdominal visceral and subcutaneous adipose tissue (VAT and SAT, respectively) was segmented, and Centiloids were calculated. Diffusion basis spectrum imaging parameter maps were created using an in-house script, and tract-based spatial statistics assessed white matter differences in high versus low BMI values, VAT, SAT, insulin resistance, systemic inflammation, and Centiloids, with age and sex as covariates. RESULTS Obesity, high VAT, and high SAT were linked to lower axial diffusivity, reduced fiber fraction, and increased restricted fraction in white matter. Obesity was additionally associated with higher hindered fraction and lower fractional anisotropy. Also, individuals with high C-reactive protein showed lower axial diffusivity. Higher restricted fraction correlated with continuous BMI and SAT particularly in male individuals, whereas VAT effects were similar in male and female individuals. CONCLUSIONS The findings suggest that, at midlife, obesity and abdominal fat are associated with reduced brain axonal density and increased inflammation, with visceral fat playing a significant role in both sexes.
Collapse
Affiliation(s)
- Mahsa Dolatshahi
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Paul K Commean
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Farzaneh Rahmani
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Yifei Xu
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Jingxia Liu
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, Missouri, USA
| | | | - Mahshid Naghashzadeh
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - LaKisha Lloyd
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Caitlyn Nguyen
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Abby McBee Kemper
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Nancy Hantler
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Maria Ly
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Gary Yu
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Shaney Flores
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Joseph E Ippolito
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Sheng-Kwei Song
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California, Los Angeles, California, USA
| | - Weiying Dai
- Department of Computer Science, State University of New York at Binghamton, Binghamton, New York, USA
| | - Bettina Mittendorfer
- Departments of Medicine and Nutrition & Exercise Physiology, University of Missouri School of Medicine, Columbia, Missouri, USA
| | - John C Morris
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri, USA
| | - Tammie L S Benzinger
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Cyrus A Raji
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri, USA
| |
Collapse
|
4
|
Harrison TM, Ward T, Taggett J, Maillard P, Lockhart SN, Jung Y, Lovato LC, Koeppe R, Jagust WJ, Harvey D, Masdeu JC, Oh H, Gitelman DR, Aggarwal NT, Espeland MA, Cleveland ML, Whitmer R, Farias ST, Salloway S, Pavlik V, Yu M, Tangney C, Snyder H, Carrillo M, Baker LD, Vemuri P, DeCarli C, Landau SM. The POINTER Imaging baseline cohort: Associations between multimodal neuroimaging biomarkers, cardiovascular health, and cognition. Alzheimers Dement 2025; 21:e14399. [PMID: 39641363 PMCID: PMC11772730 DOI: 10.1002/alz.14399] [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: 06/11/2024] [Revised: 10/11/2024] [Accepted: 10/21/2024] [Indexed: 12/07/2024]
Abstract
INTRODUCTION The U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER) is evaluating lifestyle interventions in older adults at risk for cognitive decline and dementia. Here we characterize the baseline data set of the POINTER Imaging ancillary study. METHODS Participants underwent health and cognitive assessments and neuroimaging with multimodal positron emission tomography (PET) (beta-amyloid [Aβ] and tau) and magnetic resonance imaging (MRI). Framingham risk score (FRS) was used to quantify cardiovascular disease (CVD) risk. RESULTS A total of 1052 participants (31% from underrepresented ethnoracial groups) were enrolled. Compared to Aβ-, Aβ+ (29%) participants were older, had higher apolipoprotein E (APOE) ε4 carriage rate and white matter hyperintensity volume, and greater temporal tau. FRS was related to MRI measures, but not AD biomarkers. FRS and tau had independent effects on cognition. DISCUSSION In this heterogenous, at-risk cohort, CVD risk was related to more abnormal brain structure and poorer cognition, representing a putative non-AD (Alzheimer's disease) pathway to brain injury and cognitive decline. HIGHLIGHTS ·The U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER) cohort is enriched for cardiovascular disease (CVD) and poor lifestyle ·POINTER Imaging collected multimodal neuroimaging data in this unique, at-risk cohort ·Amyloid burden was related to age, apolipoprotein E (APOE) ε4 carriage, and measures of disease progression ·Associations between amyloid and tau, and tau and cognition, were relatively weak ·CVD risk and tau pathology were independently related to memory.
Collapse
Affiliation(s)
| | - Tyler Ward
- University of California BerkeleyBerkeleyCaliforniaUSA
| | | | | | | | | | - Laura C. Lovato
- Wake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | | | - William J. Jagust
- University of California BerkeleyBerkeleyCaliforniaUSA
- Lawrence Berkeley National LaboratoryBerkeley, CaliforniaUSA
| | | | - Joseph C. Masdeu
- Nantz National Alzheimer CenterHouston Methodist and Weill CornellHoustonTexasUSA
| | - Hwamee Oh
- Brown UniversityProvidenceRhode IslandUSA
| | | | | | - Mark A. Espeland
- Wake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | | | | | | | | | | | - Melissa Yu
- Baylor College of MedicineHoustonTexasUSA
| | | | | | | | - Laura D. Baker
- Wake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | | | | | | | | |
Collapse
|
5
|
Mormino EC, Biber SA, Rahman‐Filipiak A, Arfanakis K, Clark L, Dage JL, Detre JA, Dickerson BC, Donohue MC, Kecskemeti S, Hohman TJ, Jagust WJ, Keene DC, Kukull W, Levendovszky SR, Rosen H, Thompson PM, Villemagne VL, Wolk DA, Okonkwo OC, Rabinvovici GD, Rivera‐Mindt M, Foroud T, Johnson SC. The Consortium for Clarity in ADRD Research Through Imaging (CLARiTI). Alzheimers Dement 2025; 21:e14383. [PMID: 39588767 PMCID: PMC11772703 DOI: 10.1002/alz.14383] [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: 06/07/2024] [Revised: 10/10/2024] [Accepted: 10/11/2024] [Indexed: 11/27/2024]
Abstract
The presence of multiple pathologies is the largest predictor of dementia. A major gap in the field is the in vivo detection of mixed pathologies and their antecedents. The Alzheimer's Disease Research Centers (ADRCs) are uniquely positioned to address this gap. The ADRCs longitudinally follow ≈ 17,000 participants, ranging from cognitively unimpaired to dementia, arising from Alzheimer's disease (AD) and related dementias (ADRD; e.g., AD, Lewy body disorders, vascular). Motivated by the Alzheimer's Disease Neuroimaging Initiative's (ADNI) impact, the ADRC Consortium for Clarity in ADRD Research Through Imaging (CLARiTI) was formed. Leveraging existing ADRC infrastructure, CLARiTI will integrate standardized imaging and plasma collection to characterize mixed pathologies and use community-engaged research methods to ensure that ≥ 25% of the sample is from underrepresented populations (e.g., ethnoculturally minoritized, low education). The resulting ADRD profiles, within a more diverse sample, will provide key resources for ADRCs and an unprecedented, more generalizable publicly available imaging-plasma dataset. HIGHLIGHTS: In vivo detection of mixed pathologies is critical for Alzheimer's disease and related dementias research. The Alzheimer's Disease Research Centers (ADRCs) are uniquely positioned to address gaps related to mixed pathologies. The ADRC Consortium for Clarity in ADRD Research Through Imaging (CLARiTI) will enhance this national program by adding standardized imaging and plasma collection to existing ADRC infrastructure. This effort will provide key resources for ADRCs and an unprecedented publicly available imaging-plasma-neuropath dataset.
Collapse
Affiliation(s)
- Elizabeth C. Mormino
- Department of Neurology and Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
- Wu Tsai Neurosciences InstituteStanford University School of Medicine, Cogen FacilityStanfordCaliforniaUSA
| | - Sarah A. Biber
- National Alzheimer's Coordinating CenterUniversity of WashingtonSeattleWashingtonUSA
| | | | | | - Lindsay Clark
- Department of MedicineUniversity of Wisconsin School of Medicine and Public Health, Health Sciences Learning CenterMadisonWisconsinUSA
| | - Jeffrey L. Dage
- Department of NeurologyIndiana University School of MedicineIndianapolisIndianaUSA
- Stark Neurosciences Research InstituteIndiana University School of MedicineIndianapolisIndianaUSA
| | - John A. Detre
- Department of NeurologyPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Bradford C. Dickerson
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Michael C. Donohue
- Department of NeurologyKeck School of Medicine, University of Southern CaliforniaLos AngelesCaliforniaUSA
- Alzheimer's Therapeutic Research Institute (ATRI), University of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Steven Kecskemeti
- Department of MedicineUniversity of Wisconsin School of Medicine and Public Health, Health Sciences Learning CenterMadisonWisconsinUSA
| | - Timothy J. Hohman
- Department of NeurologyVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - William J. Jagust
- Department of EpidemiologySchool of Public HealthUniversity of CaliforniaBerkeleyCaliforniaUSA
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - Dirk C. Keene
- Department of Laboratory Medicine and PathologyUniversity of WashingtonSeattleWashingtonUSA
| | - Walter Kukull
- National Alzheimer's Coordinating CenterUniversity of WashingtonSeattleWashingtonUSA
- Department of EpidemiologyUniversity of WashingtonSeattleWashingtonUSA
| | | | - Howie Rosen
- Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Paul M. Thompson
- Department of Ophthalmology, Psychiatry and the Behavioral Sciences, RadiologyPsychiatry, and Engineering, Keck School of Medicine, University of Southern CaliforniaLos AngelesCaliforniaUSA
| | | | - David A. Wolk
- Department of NeurologyPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Ozioma C. Okonkwo
- Department of MedicineUniversity of Wisconsin School of Medicine and Public Health, Health Sciences Learning CenterMadisonWisconsinUSA
| | - Gil D. Rabinvovici
- Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Monica Rivera‐Mindt
- Department of PsychologyFordham UniversityBronxNew YorkUSA
- Department of NeurologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Tatiana Foroud
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Sterling C. Johnson
- Department of MedicineUniversity of Wisconsin School of Medicine and Public Health, Health Sciences Learning CenterMadisonWisconsinUSA
| |
Collapse
|
6
|
Terstege DJ, Galea LAM, Epp JR. Retrosplenial hypometabolism precedes the conversion from mild cognitive impairment to Alzheimer's disease. Alzheimers Dement 2024; 20:8979-8986. [PMID: 39470016 DOI: 10.1002/alz.14258] [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: 06/04/2024] [Revised: 08/06/2024] [Accepted: 08/21/2024] [Indexed: 10/30/2024]
Abstract
INTRODUCTION Not all individuals who experience mild cognitive impairment (MCI) transition through progressive stages of cognitive decline at the same rate, if at all. Previous observational studies have identified the retrosplenial cortex (RSC) as an early site of hypometabolism in MCI which seems to be predictive of later transition to Alzheimer's disease (AD). METHODS We examined N = 399 MCI subjects with baseline 18F-fluorodeoxyglucose positron emission tomography. Subjects were classified based on whether their diagnosis converted from MCI to AD. RESULTS Whole-brain metabolism was decreased in converters (MCI-AD). This effect was more prominent at the RSC, where MCI-AD subjects showed even greater hypometabolism. Observations of RSC hypometabolism and its utility in predicting transition from MCI-AD withstood statistical analyses in a large retrospective study. DISCUSSION These results point to the utility of incorporating RSC hypometabolism into predictive models of AD progression risk and call for further examination of mechanisms underlying this relationship. HIGHLIGHTS Not all individuals who develop MCI will progress to AD. Individuals with MCI who progress to AD show early whole-brain hypometabolism. Early hypometabolism is particularly prominent at the RSC.
Collapse
Affiliation(s)
- Dylan J Terstege
- Department of Cell Biology and Anatomy, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Liisa A M Galea
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Jonathan R Epp
- Department of Cell Biology and Anatomy, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| |
Collapse
|
7
|
Jagust WJ, Koeppe RA, Rabinovici GD, Villemagne VL, Harrison TM, Landau SM. The ADNI PET Core at 20. Alzheimers Dement 2024; 20:7340-7349. [PMID: 39108002 PMCID: PMC11485322 DOI: 10.1002/alz.14165] [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: 04/30/2024] [Revised: 07/09/2024] [Accepted: 07/11/2024] [Indexed: 10/18/2024]
Abstract
The Alzheimer's Disease Neuroimaging Initiative (ADNI) PET Core has evolved over time, beginning with positron emission tomography (PET) imaging of a subsample of participants with [18F]fluorodeoxyglucose (FDG)-PET, adding tracers for measurement of β-amyloid, followed by tau tracers. This review examines the evolution of the ADNI PET Core, the novel aspects of PET imaging in each stage of ADNI, and gives an accounting of PET images available in the ADNI database. The ADNI PET Core has been and continues to be a rich resource that provides quantitative PET data and preprocessed PET images to the scientific community, allowing interrogation of both basic and clinically relevant questions. By standardizing methods across different PET scanners and multiple PET tracers, the Core has demonstrated the feasibility of large-scale, multi-center PET studies. Data managed and disseminated by the PET Core has been critical to defining pathophysiological models of Alzheimer's disease (AD) and helped to drive methods used in modern therapeutic trials. HIGHLIGHTS: The ADNI PET Core began with FDG-PET and now includes three amyloid and three tau PET ligands. The PET Core has standardized acquisition and analysis of multitracer PET images. The ADNI PET Core helped to develop methods that have facilitated clinical trials in AD.
Collapse
Affiliation(s)
- William J. Jagust
- Department of NeuroscienceUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - Robert A. Koeppe
- Department of RadiologyUniversity of MichiganAnn ArborMichiganUSA
| | - Gil D. Rabinovici
- Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | | | | | - Susan M. Landau
- Department of NeuroscienceUniversity of CaliforniaBerkeleyCaliforniaUSA
| | | |
Collapse
|
8
|
Brier MR, Schindler SE, Salter A, Perantie D, Shelley N, Judge B, Keefe S, Kirmess KM, Verghese PB, Yarasheski KE, Venkatesh V, Raji C, Gordon BA, Bateman RJ, Morris JC, Naismith RT, Holtzman DM, Benzinger TL, Cross AH. Unexpected Low Rate of Amyloid-β Pathology in Multiple Sclerosis Patients. Ann Neurol 2024; 96:453-459. [PMID: 38963256 PMCID: PMC11324391 DOI: 10.1002/ana.27027] [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: 04/08/2024] [Revised: 05/29/2024] [Accepted: 06/13/2024] [Indexed: 07/05/2024]
Abstract
The life expectancy of people with multiple sclerosis (MS) has increased, yet we have noted that development of a typical Alzheimer disease dementia syndrome is uncommon. We hypothesized that Alzheimer disease pathology is uncommon in MS patients. In 100 MS patients, the rate of amyloid-β plasma biomarker positivity was approximately half the rate in 300 non-MS controls matched on age, sex, apolipoprotein E proteotype, and cognitive status. Interestingly, most MS patients who did have amyloid-β pathology had features atypical for MS at diagnosis. These results support that MS is associated with reduced Alzheimer disease risk, and suggest new avenues of research. ANN NEUROL 2024;96:453-459.
Collapse
Affiliation(s)
- Matthew R. Brier
- Department of Neurology, Washington University in St. Louis
- Mallinckrodt Institute of Radiology, Washington University in St. Louis
| | | | - Amber Salter
- Department of Neurology, University of Texas Southwestern Medical Center
| | - Dana Perantie
- Department of Neurology, Washington University in St. Louis
| | - Nicole Shelley
- Department of Neurology, Washington University in St. Louis
| | - Bradley Judge
- Department of Neurology, Washington University in St. Louis
| | - Sarah Keefe
- Mallinckrodt Institute of Radiology, Washington University in St. Louis
| | | | | | | | | | - Cyrus Raji
- Mallinckrodt Institute of Radiology, Washington University in St. Louis
| | - Brian A. Gordon
- Mallinckrodt Institute of Radiology, Washington University in St. Louis
| | | | - John C. Morris
- Department of Neurology, Washington University in St. Louis
| | | | | | | | - Anne H. Cross
- Department of Neurology, Washington University in St. Louis
| |
Collapse
|
9
|
Johns E, Vossler HA, Young CB, Carlson ML, Winer JR, Younes K, Park J, Rathmann‐Bloch J, Smith V, Harrison TM, Landau S, Henderson V, Wagner A, Sha SJ, Zeineh M, Zaharchuk G, Poston KL, Davidzon GA, Mormino EC. Florbetaben amyloid PET acquisition time: Influence on Centiloids and interpretation. Alzheimers Dement 2024; 20:5299-5310. [PMID: 38962867 PMCID: PMC11350032 DOI: 10.1002/alz.13893] [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: 02/22/2024] [Revised: 04/18/2024] [Accepted: 04/22/2024] [Indexed: 07/05/2024]
Abstract
INTRODUCTION Amyloid positron emission tomography (PET) acquisition timing impacts quantification. METHODS In florbetaben (FBB) PET scans of 245 adults with and without cognitive impairment, we investigated the impact of post-injection acquisition time on Centiloids (CLs) across five reference regions. CL equations for FBB were derived using standard methods, using FBB data collected between 90 and 110 min with paired Pittsburgh compound B data. Linear mixed models and t-tests evaluated the impact of acquisition time on CL increases. RESULTS CL values increased significantly over the scan using the whole cerebellum, cerebellar gray matter, and brainstem as reference regions, particularly in amyloid-positive individuals. In contrast, CLs based on white matter-containing reference regions decreased across the scan. DISCUSSION The quantification of CLs in FBB PET imaging is influenced by both the overall scan acquisition time and the choice of reference region. Standardized acquisition protocols or the application of acquisition time-specific CL equations should be implemented in clinical protocols. HIGHLIGHTS Acquisition timing affects florbetaben positron emission tomography (PET) scan quantification, especially in amyloid-positive participants. The impact of acquisition timing on quantification varies across common reference regions. Consistent acquisitions and/or appropriate post-injection adjustments are needed to ensure comparability of PET data.
Collapse
Affiliation(s)
- Emily Johns
- Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
| | - Hillary A. Vossler
- Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
| | - Christina B. Young
- Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
| | - Mackenzie L. Carlson
- Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
| | - Joseph R. Winer
- Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
| | - Kyan Younes
- Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
| | - Jennifer Park
- Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
| | | | - Viktorija Smith
- Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
| | - Theresa M. Harrison
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - Susan Landau
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - Victor Henderson
- Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
- Department of Epidemiology and Population HealthStanford UniversityStanfordCaliforniaUSA
| | - Anthony Wagner
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
- Stanford UniversityWu Tsai Neuroscience InstituteStanfordCaliforniaUSA
| | - Sharon J. Sha
- Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
- Stanford UniversityWu Tsai Neuroscience InstituteStanfordCaliforniaUSA
| | - Michael Zeineh
- Department of RadiologyStanford University School of MedicineStanfordCaliforniaUSA
| | - Greg Zaharchuk
- Department of RadiologyStanford University School of MedicineStanfordCaliforniaUSA
| | - Kathleen L. Poston
- Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
- Stanford UniversityWu Tsai Neuroscience InstituteStanfordCaliforniaUSA
| | - Guido A. Davidzon
- Department of RadiologyStanford University School of MedicineStanfordCaliforniaUSA
| | - Elizabeth C. Mormino
- Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
- Stanford UniversityWu Tsai Neuroscience InstituteStanfordCaliforniaUSA
| |
Collapse
|
10
|
Su Y, Protas H, Luo J, Chen K, Alosco ML, Adler CH, Balcer LJ, Bernick C, Au R, Banks SJ, Barr WB, Coleman MJ, Dodick DW, Katz DI, Marek KL, McClean MD, McKee AC, Mez J, Daneshvar DH, Palmisano JN, Peskind ER, Turner RW, Wethe JV, Rabinovici G, Johnson K, Tripodis Y, Cummings JL, Shenton ME, Stern RA, Reiman EM. Flortaucipir tau PET findings from former professional and college American football players in the DIAGNOSE CTE research project. Alzheimers Dement 2024; 20:1827-1838. [PMID: 38134231 PMCID: PMC10984430 DOI: 10.1002/alz.13602] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Revised: 10/27/2023] [Accepted: 11/20/2023] [Indexed: 12/24/2023]
Abstract
INTRODUCTION Tau is a key pathology in chronic traumatic encephalopathy (CTE). Here, we report our findings in tau positron emission tomography (PET) measurements from the DIAGNOSE CTE Research Project. METHOD We compare flortaucipir PET measures from 104 former professional players (PRO), 58 former college football players (COL), and 56 same-age men without exposure to repetitive head impacts (RHI) or traumatic brain injury (unexposed [UE]); characterize their associations with RHI exposure; and compare players who did or did not meet diagnostic criteria for traumatic encephalopathy syndrome (TES). RESULTS Significantly elevated flortaucipir uptake was observed in former football players (PRO+COL) in prespecified regions (p < 0.05). Association between regional flortaucipir uptake and estimated cumulative head impact exposure was only observed in the superior frontal region in former players over 60 years old. Flortaucipir PET was not able to differentiate TES groups. DISCUSSION Additional studies are needed to further understand tau pathology in CTE and other individuals with a history of RHI.
Collapse
Affiliation(s)
- Yi Su
- Banner Alzheimer's Institute and Arizona Alzheimer's ConsortiumPhoenixArizonaUSA
| | - Hillary Protas
- Banner Alzheimer's Institute and Arizona Alzheimer's ConsortiumPhoenixArizonaUSA
| | - Ji Luo
- Banner Alzheimer's Institute and Arizona Alzheimer's ConsortiumPhoenixArizonaUSA
| | - Kewei Chen
- Banner Alzheimer's Institute and Arizona Alzheimer's ConsortiumPhoenixArizonaUSA
| | - Michael L. Alosco
- Department of NeurologyBoston University Alzheimer's Disease Research CenterBoston University CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Charles H. Adler
- Department of NeurologyMayo Clinic College of Medicine, Mayo Clinic ArizonaScottsdaleArizonaUSA
| | - Laura J. Balcer
- Departments of NeurologyNYU Grossman School of MedicineNew YorkNew YorkUSA
- Department of Population Health and OphthalmologyNYU Grossman School of MedicineNew YorkNew YorkUSA
| | - Charles Bernick
- Cleveland Clinic Lou Ruvo Center for Brain HealthLas VegasNevadaUSA
- Department of NeurologyUniversity of WashingtonSeattleWashingtonUSA
| | - Rhoda Au
- Department of NeurologyBoston University Alzheimer's Disease Research CenterBoston University CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Framingham Heart StudyFraminghamMassachusettsUSA
- Slone Epidemiology Center; Departments of Anatomy & Neurobiology, Neurology, and MedicineDepartment of EpidemiologyBoston University Chobanian & Avedisian School of Medicine; Boston University School of Public HealthBostonMassachusettsUSA
| | - Sarah J. Banks
- Departments of Neuroscience and PsychiatryUniversity of CaliforniaSan DiegoCaliforniaUSA
| | - William B. Barr
- Departments of NeurologyNYU Grossman School of MedicineNew YorkNew YorkUSA
| | - Michael J. Coleman
- Departments of Psychiatry and RadiologyPsychiatry Neuroimaging LaboratoryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - David W. Dodick
- Department of NeurologyMayo Clinic College of Medicine, Mayo Clinic ArizonaScottsdaleArizonaUSA
| | - Douglas I. Katz
- Department of NeurologyBoston University Alzheimer's Disease Research CenterBoston University CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Encompass Health Braintree Rehabilitation HospitalBraintreeMassachusettsUSA
| | - Kenneth L. Marek
- Institute for Neurodegenerative Disorders, Invicro, LLCNew HavenConnecticutUSA
| | - Michael D. McClean
- Department of Environmental HealthBoston University School of Public HealthBostonMassachusettsUSA
| | - Ann C. McKee
- Department of NeurologyBoston University Alzheimer's Disease Research CenterBoston University CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- VA Boston Healthcare SystemBostonMassachusettsUSA
| | - Jesse Mez
- Department of NeurologyBoston University Alzheimer's Disease Research CenterBoston University CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Framingham Heart StudyFraminghamMassachusettsUSA
| | - Daniel H. Daneshvar
- Department of Physical Medicine & RehabilitationMassachusetts General Hospital, Spaulding Rehabilitation Hospital, Harvard Medical SchoolCharlestownMassachusettsUSA
| | - Joseph N. Palmisano
- Boston University Alzheimer's Disease Research Center, Boston University CTE Center, Biostatistics and Epidemiology Data Analytics Center (BEDAC), Boston University School of Public HealthBostonMassachusettsUSA
| | - Elaine R. Peskind
- Department of Psychiatry and Behavioral SciencesVA Northwest Mental Illness Research, Education, and Clinical Center, VA Puget Sound Health Care System; University of Washington School of MedicineSeattleWashingtonUSA
| | - Robert W. Turner
- Department of Clinical Research & LeadershipThe George Washington University School of Medicine & Health SciencesWashingtonDistrict of ColumbiaUSA
| | - Jennifer V. Wethe
- Department of Psychiatry and PsychologyMayo Clinic School of Medicine, Mayo Clinic ArizonaScottsdaleArizonaUSA
| | - Gil Rabinovici
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Keith Johnson
- Gordon Center for Medical Imaging, Mass General Research Institute, Harvard Medical SchoolBostonMassachusettsUSA
| | - Yorghos Tripodis
- Department of NeurologyBoston University Alzheimer's Disease Research CenterBoston University CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
| | - Jeffrey L. Cummings
- Department of Brain HealthChambers‐Grundy Center for Transformative NeuroscienceSchool of Integrated Health Sciences, University of Nevada Las VegasLas VegasNevadaUSA
| | - Martha E. Shenton
- Departments of Psychiatry and RadiologyPsychiatry Neuroimaging LaboratoryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Robert A. Stern
- Department of NeurologyBoston University Alzheimer's Disease Research CenterBoston University CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Eric M. Reiman
- Banner Alzheimer's Institute and Arizona Alzheimer's ConsortiumPhoenixArizonaUSA
- University of Arizona, Arizona State University, Translational Genomics Research InstitutePhoenixArizonaUSA
| | | |
Collapse
|
11
|
Petersen ME, Zhang F, Hall JR, Julovich D, Rissman RA, Meeker KL, Phillips N, Large S, Ances BM, O'Bryant SE. Characterization of Ptau181 Among a Diverse Community-Based Cohort: A HABS-HD Study. J Alzheimers Dis 2024; 100:S63-S73. [PMID: 39177606 DOI: 10.3233/jad-240633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/24/2024]
Abstract
Background Examination of Alzheimer's disease (AD) related biomarkers among diverse communities has remained limited. Objective The aim of this study was to expand on prior work to provide a characterization of ptau181 among a diverse community sample. Consideration was taken regarding the impact of comorbidities on ptau181 levels including medical. Methods 3,228 (n = 770 African American [AA], n = 1,231 Hispanic, and n = 1,227 non-Hispanic white [NHW]) Health and Aging Brain Study- Health Disparities (HABS-HD) participants were included in this study. ANCOVAs were conducted to examine differences in ptau181 levels across race and ethnic groups. Violin plots were also generated stratified by APOEɛ4 carrier status, Amyloid PET positivity status, medical comorbidity (hypertension, dyslipidemia, chronic kidney disease [CKD], and diabetes) and by cognitive diagnosis. Results Ptau181 levels were found to differ between Hispanics and NHW after covarying for age, sex, and APOEɛ4 status. Amyloid PET positivity was associated with higher ptau181 levels across all groups. APOEɛ4 positivity status was only significantly associated with ptau181 levels among AAs. Across all race and ethnic groups, those with a diagnosis of CKD had higher levels of ptau181. When stratified by cognitive diagnosis, cognitively unimpaired Hispanics had higher ptau181 if they also had a diagnosis of CKD or diabetes. p-values ≤0.01. Conclusions Differences in ptau181 levels were shown in a diverse community sample. Medical comorbidities had a differing effect on ptau181 levels particularly among Hispanics even without cognitive impairment. Findings support the need for future work to consider comorbid conditions when examining the utility of ptau181.
Collapse
Affiliation(s)
- Melissa E Petersen
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, TX, USA
- Deparment of Family Medicine, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Fan Zhang
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, TX, USA
- Deparment of Family Medicine, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - James R Hall
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, TX, USA
- Deparment of Family Medicine, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - David Julovich
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Robert A Rissman
- Keck School of Medicine of USC, Alzheimer's Therapeutic Research Institute, San Diego, CA, USA
| | - Karin L Meeker
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, TX, USA
- Deparment of Family Medicine, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Nicole Phillips
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Stephanie Large
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Beau M Ances
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Sid E O'Bryant
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, TX, USA
- Deparment of Family Medicine, University of North Texas Health Science Center, Fort Worth, TX, USA
| |
Collapse
|
12
|
Burnham SC, Iaccarino L, Pontecorvo MJ, Fleisher AS, Lu M, Collins EC, Devous MD. A review of the flortaucipir literature for positron emission tomography imaging of tau neurofibrillary tangles. Brain Commun 2023; 6:fcad305. [PMID: 38187878 PMCID: PMC10768888 DOI: 10.1093/braincomms/fcad305] [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: 05/04/2023] [Revised: 09/13/2023] [Accepted: 11/14/2023] [Indexed: 01/09/2024] Open
Abstract
Alzheimer's disease is defined by the presence of β-amyloid plaques and neurofibrillary tau tangles potentially preceding clinical symptoms by many years. Previously only detectable post-mortem, these pathological hallmarks are now identifiable using biomarkers, permitting an in vivo definitive diagnosis of Alzheimer's disease. 18F-flortaucipir (previously known as 18F-T807; 18F-AV-1451) was the first tau positron emission tomography tracer to be introduced and is the only Food and Drug Administration-approved tau positron emission tomography tracer (Tauvid™). It has been widely adopted and validated in a number of independent research and clinical settings. In this review, we present an overview of the published literature on flortaucipir for positron emission tomography imaging of neurofibrillary tau tangles. We considered all accessible peer-reviewed literature pertaining to flortaucipir through 30 April 2022. We found 474 relevant peer-reviewed publications, which were organized into the following categories based on their primary focus: typical Alzheimer's disease, mild cognitive impairment and pre-symptomatic populations; atypical Alzheimer's disease; non-Alzheimer's disease neurodegenerative conditions; head-to-head comparisons with other Tau positron emission tomography tracers; and technical considerations. The available flortaucipir literature provides substantial evidence for the use of this positron emission tomography tracer in assessing neurofibrillary tau tangles in Alzheimer's disease and limited support for its use in other neurodegenerative disorders. Visual interpretation and quantitation approaches, although heterogeneous, mostly converge and demonstrate the high diagnostic and prognostic value of flortaucipir in Alzheimer's disease.
Collapse
Affiliation(s)
| | | | | | | | - Ming Lu
- Avid, Eli Lilly and Company, Philadelphia, PA 19104, USA
| | | | | |
Collapse
|
13
|
Younes K, Smith V, Johns E, Carlson ML, Winer J, He Z, Henderson VW, Greicius MD, Young CB, Mormino EC. Temporal tau asymmetry spectrum influences divergent behavior and language patterns in Alzheimer`s disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.10.23296836. [PMID: 37986964 PMCID: PMC10659470 DOI: 10.1101/2023.11.10.23296836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Understanding psychiatric symptoms in Alzheimer`s disease (AD) is crucial for advancing precision medicine and therapeutic strategies. The relationship between AD behavioral symptoms and asymmetry in spatial tau PET patterns is unknown. Braak tau progression implicates the temporal lobes early. However, the clinical and pathological implications of temporal tau laterality remain unexplored. This cross-sectional study investigated the correlation between temporal tau PET asymmetry and behavior assessed using the neuropsychiatric inventory, and composite scores for memory, executive function, and language; using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. In the entire cohort, continuous right and left temporal tau contributions to behavior and cognition were evaluated controlling for age, sex, education, and tau burden on the contralateral side. Additionally, a temporal tau laterality index was calculated to define "asymmetry-extreme" groups (individuals with laterality indices greater than two standard deviations from the mean). 858 individuals (age=73.9±7.7 years, 434(50%) females) were included, comprising 438 cognitively unimpaired (CU) (53.4%) and 420 impaired (CI) participants (48.9%). In the full cohort analysis, right temporal tau was associated with worse behavior (B(SE)=7.19 (2.9), p-value=0.01) and left temporal tau was associated with worse language (B(SE)=1.4(0.2), p-value<0.0001). Categorization into asymmetry-extreme groups revealed 20 right- and 27 left-asymmetric participants. Within these extreme groups, four patterns of tau PET uptake were observed: anterior temporal, typical AD, typical AD with frontal involvement, and posterior. Asymmetrical tau burden is associated with distinct behavioral and cognitive profiles. Behavioral and socioemotional measures are needed to understand right-sided asymmetry in AD.
Collapse
Affiliation(s)
- Kyan Younes
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine
| | - Viktorija Smith
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine
| | - Emily Johns
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine
| | - Mackenzie L. Carlson
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine
| | - Joseph Winer
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine
| | - Zihuai He
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine
- Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, California
| | - Victor W. Henderson
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine
- Department of Epidemiology and Population Health, Stanford University
| | - Michael D. Greicius
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine
| | - Christina B. Young
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine
| | - Elizabeth C. Mormino
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine
- Wu Tsai Neuroscience Institute, Stanford, CA, USA
| | | |
Collapse
|
14
|
Lu J, Clement C, Hong J, Wang M, Li X, Cavinato L, Yen TC, Jiao F, Wu P, Wu J, Ge J, Sun Y, Brendel M, Lopes L, Rominger A, Wang J, Liu F, Zuo C, Guan Y, Zhao Q, Shi K. Improved interpretation of 18F-florzolotau PET in progressive supranuclear palsy using a normalization-free deep-learning classifier. iScience 2023; 26:107426. [PMID: 37564702 PMCID: PMC10410511 DOI: 10.1016/j.isci.2023.107426] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 05/28/2023] [Accepted: 07/17/2023] [Indexed: 08/12/2023] Open
Abstract
While 18F-florzolotau tau PET is an emerging biomarker for progressive supranuclear palsy (PSP), its interpretation has been hindered by a lack of consensus on visual reading and potential biases in conventional semi-quantitative analysis. As clinical manifestations and regions of elevated 18F-florzolotau binding are highly overlapping in PSP and the Parkinsonian type of multiple system atrophy (MSA-P), developing a reliable discriminative classifier for 18F-florzolotau PET is urgently needed. Herein, we developed a normalization-free deep-learning (NFDL) model for 18F-florzolotau PET, which achieved significantly higher accuracy for both PSP and MSA-P compared to semi-quantitative classifiers. Regions driving the NFDL classifier's decision were consistent with disease-specific topographies. NFDL-guided radiomic features correlated with clinical severity of PSP. This suggests that the NFDL model has the potential for early and accurate differentiation of atypical parkinsonism and that it can be applied in various scenarios due to not requiring subjective interpretation, MR-dependent, and reference-based preprocessing.
Collapse
Affiliation(s)
- Jiaying Lu
- Department of Nuclear Medicine & PET Center & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai 200235, China
- Department of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland
| | - Christoph Clement
- Department of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland
| | - Jimin Hong
- Department of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland
| | - Min Wang
- Institute of Biomedical Engineering, School of Life Science, Shanghai University, Shanghai 200444, China
- Department of Informatics, Technical University of Munich, 80333 Munich, Germany
| | - Xinyi Li
- Department of Neurology & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai 200400, China
| | - Lara Cavinato
- Department of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland
- MOX - Modeling and Scientific Computing, Department of Mathematics, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
| | - Tzu-Chen Yen
- APRINOIA Therapeutics Co., Ltd, Suzhou 215122, China
| | - Fangyang Jiao
- Department of Nuclear Medicine & PET Center & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai 200235, China
| | - Ping Wu
- Department of Nuclear Medicine & PET Center & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai 200235, China
| | - Jianjun Wu
- Department of Neurology & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai 200400, China
| | - Jingjie Ge
- Department of Nuclear Medicine & PET Center & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai 200235, China
| | - Yimin Sun
- Department of Neurology & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai 200400, China
| | - Matthias Brendel
- Department of Nuclear Medicine, University of Munich, 80539 Munich, Germany
| | - Leonor Lopes
- Department of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland
| | - Axel Rominger
- Department of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland
| | - Jian Wang
- Department of Neurology & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai 200400, China
| | - Fengtao Liu
- Department of Neurology & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai 200400, China
| | - Chuantao Zuo
- Department of Nuclear Medicine & PET Center & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai 200235, China
- Human Phenome Institute, Fudan University, Shanghai 200433, China
| | - Yihui Guan
- Department of Nuclear Medicine & PET Center & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai 200235, China
| | - Qianhua Zhao
- Department of Neurology & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai 200400, China
| | - Kuangyu Shi
- Department of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland
- Department of Informatics, Technical University of Munich, 80333 Munich, Germany
| | - for the Progressive Supranuclear Palsy Neuroimage Initiative (PSPNI)
- Department of Nuclear Medicine & PET Center & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai 200235, China
- Department of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland
- Institute of Biomedical Engineering, School of Life Science, Shanghai University, Shanghai 200444, China
- Department of Informatics, Technical University of Munich, 80333 Munich, Germany
- Department of Neurology & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai 200400, China
- MOX - Modeling and Scientific Computing, Department of Mathematics, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
- APRINOIA Therapeutics Co., Ltd, Suzhou 215122, China
- Department of Nuclear Medicine, University of Munich, 80539 Munich, Germany
- Human Phenome Institute, Fudan University, Shanghai 200433, China
| |
Collapse
|
15
|
Lu J, Ju Z, Wang M, Sun X, Jia C, Li L, Bao W, Zhang H, Jiao F, Lin H, Yen TC, Cui R, Lan X, Zhao Q, Guan Y, Zuo C. Feasibility of 18F-florzolotau quantification in patients with Alzheimer's disease based on an MRI-free tau PET template. Eur Radiol 2023:10.1007/s00330-023-09571-7. [PMID: 37099173 DOI: 10.1007/s00330-023-09571-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 01/25/2023] [Accepted: 02/09/2023] [Indexed: 04/27/2023]
Abstract
OBJECTIVES Quantification of tau accumulation using positron emission tomography (PET) is critical for the diagnosis of Alzheimer's disease (AD). This study aimed to evaluate the feasibility of 18F-florzolotau quantification in patients with AD using a magnetic resonance imaging (MRI)-free tau PET template, since individual high-resolution MRI is costly and not always available in practice. METHODS 18F-florzolotau PET and MRI scans were obtained in a discovery cohort including (1) patients within the AD continuum (n = 87), (2) cognitively impaired patients with non-AD (n = 32), and (3) cognitively unimpaired subjects (n = 26). The validation cohort comprised 24 patients with AD. Following MRI-dependent spatial normalization (standard approach) in randomly selected subjects (n = 40) to cover the entire spectrum of cognitive function, selected PET images were averaged to create the 18F-florzolotau-specific template. Standardized uptake value ratios (SUVRs) were calculated in five predefined regions of interest (ROIs). MRI-free and MRI-dependent methods were compared in terms of continuous and dichotomous agreement, diagnostic performances, and associations with specific cognitive domains. RESULTS MRI-free SUVRs had a high continuous and dichotomous agreement with MRI-dependent measures for all ROIs (intraclass correlation coefficient ≥ 0.980; agreement ≥ 94.5%). Similar findings were observed for AD-related effect sizes, diagnostic performances with respect to categorization across the cognitive spectrum, and associations with cognitive domains. The robustness of the MRI-free approach was confirmed in the validation cohort. CONCLUSIONS The use of an 18F-florzolotau-specific template is a valid alternative to MRI-dependent spatial normalization, improving the clinical generalizability of this second-generation tau tracer. KEY POINTS • Regional 18F-florzolotau SUVRs reflecting tau accumulation in the living brains are reliable biomarkers for the diagnosis, differential diagnosis, and assessment of disease severity in patients with AD. • The 18F-florzolotau-specific template is a valid alternative to MRI-dependent spatial normalization, improving the clinical generalizability of this second-generation tau tracer.
Collapse
Affiliation(s)
- Jiaying Lu
- Department of Nuclear Medicine & PET Center & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Zizhao Ju
- Department of Nuclear Medicine & PET Center & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Min Wang
- Institute of Biomedical Engineering, School of Life Science, Shanghai University, Shanghai, China
| | - Xun Sun
- Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Chenhao Jia
- Department of Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Ling Li
- Department of Nuclear Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Weiqi Bao
- Department of Nuclear Medicine & PET Center & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Huiwei Zhang
- Department of Nuclear Medicine & PET Center & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Fangyang Jiao
- Department of Nuclear Medicine & PET Center & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Huamei Lin
- Department of Nuclear Medicine & PET Center & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | | | - Ruixue Cui
- Department of Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
| | - Xiaoli Lan
- Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Qianhua Zhao
- Department of Neurology & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
| | - Yihui Guan
- Department of Nuclear Medicine & PET Center & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Chuantao Zuo
- Department of Nuclear Medicine & PET Center & National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
- Human Phenome Institute, Fudan University, Shanghai, China
| |
Collapse
|
16
|
Weiner MW, Harvey D, Landau SM, Veitch DP, Neylan TC, Grafman JH, Aisen PS, Petersen RC, Jack CR, Tosun D, Shaw LM, Trojanowski JQ, Saykin AJ, Hayes J, De Carli C. Traumatic brain injury and post-traumatic stress disorder are not associated with Alzheimer's disease pathology measured with biomarkers. Alzheimers Dement 2023; 19:884-895. [PMID: 35768339 PMCID: PMC10269599 DOI: 10.1002/alz.12712] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Revised: 05/08/2022] [Accepted: 05/13/2022] [Indexed: 11/06/2022]
Abstract
INTRODUCTION Epidemiological studies report an association between traumatic brain injury (TBI) and post-traumatic stress disorder (PTSD) and clinically diagnosed Alzheimer's disease (AD). We examined the association between TBI/PTSD and biomarker-defined AD. METHODS We identified 289 non-demented veterans with TBI and/or PTSD and controls who underwent clinical evaluation, cerebrospinal fluid (CSF) collection, magnetic resonance imaging (MRI), amyloid beta (Aβ) and tau positron emission tomography, and apolipoprotein E testing. Participants were followed for up to 5.2 years. RESULTS Exposure groups (TBI, PTSD, and TBI + PTSD) had higher prevalence of mild cognitive impairment (MCI: P < .0001) and worse Mini-Mental State Examination scores (PTSD: P = .008; TBI & PTSD: P = .009) than controls. There were no significant differences in other cognitive scores, MRI volumes, Aβ or tau accumulation, or in most longitudinal measures. DISCUSSION TBI and/or PTSD were not associated with elevated AD biomarkers. The poorer cognitive status of exposed veterans may be due to other comorbid pathologies.
Collapse
Affiliation(s)
- Michael W Weiner
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, California, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
- Department of Medicine, University of California, San Francisco, San Francisco, California, USA
- Department of Psychiatry, University of California, San Francisco, San Francisco, California, USA
- Department of Neurology, University of California, San Francisco, San Francisco, California, USA
| | - Danielle Harvey
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, Davis, California, USA
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California, USA
| | - Dallas P Veitch
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, California, USA
- Northern California Institute for Research and Education (NCIRE), Department of Veterans Affairs Medical Center, San Francisco, California, USA
| | - Thomas C Neylan
- Department of Psychiatry, University of California, San Francisco, San Francisco, California, USA
- Department of Neurology, University of California, San Francisco, San Francisco, California, USA
| | - Jordan H Grafman
- Shirley Ryan AbilityLab, Northwestern University School of Medicine, Chicago, Illinois, USA
| | - Paul S Aisen
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, La Jolla, California, USA
| | | | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Duygu Tosun
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, California, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Research, School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Research, School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences and Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Jacqueline Hayes
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, California, USA
- Northern California Institute for Research and Education (NCIRE), Department of Veterans Affairs Medical Center, San Francisco, California, USA
| | - Charles De Carli
- Department of Neurology and Center for Neuroscience, University of California Davis, Davis, California, USA
| |
Collapse
|
17
|
Wang X, Broce I, Deters KD, Fan CC, Banks SJ. Identification of Sex-Specific Genetic Variants Associated With Tau PET. Neurol Genet 2022; 8:e200043. [PMID: 36530928 PMCID: PMC9756308 DOI: 10.1212/nxg.0000000000200043] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 09/22/2022] [Indexed: 12/13/2022]
Abstract
Background and Objectives Important sex differences exist in tau pathology along the Alzheimer disease (AD) continuum, with women showing enhanced tau deposition compared with men, especially during the mild cognitive impairment (MCI) phase. This study aims to identify specific genetic variants associated with sex differences in regional tau aggregation, as measured with PET. Methods Four hundred ninety-three participants (women, n = 246; men, n = 247) who self-identified as White from the AD Neuroimaging Initiative study, with genotyping data and 18F-Flortaucipir tau PET data, were included irrespective of clinical diagnosis (cognitively normal [CN], MCI, and AD). We focused on the genetic variants within 10 genes previously shown to have sex-dependent effects on AD to reduce the burden of multiple comparisons: BIN1, MS4A6A, DNAJA2, FERMT2, APOC1, APOC1P1, FAM193B, C2orf47, TYW5, and CR1. Multivariate analysis of variance was applied to identify genetic variants associated with tau PET data in 3 regions of interests (composite regions of Braak I, Braak III/IV, and Braak V/VI stages) in women and men separately. We controlled for age, scanner manufacture, amyloid status, APOE ε4 carriership, diagnosis (CN vs MCI vs AD), and the first 10 genetic principal components to adjust for population stratification. Results We identified 3 genetic loci within 3 different genes associated with tau deposits specifically in women: rs79711283 within DNAJA2, rs113357081 within FERMT2, and rs74614106 within TYW5. In men, we also identified 3 loci within CR1 associated with tau deposits: rs115096248, rs113698814, and rs78150633. Discussion Our findings revealed sex-specific genetic variants associated with tau deposition independent of APOE ε4, amyloid status, and clinical diagnosis. These results provide potential molecular targets for understanding the mechanism of sex-specific tau aggregation and developing sex-specific gene-guided precision prevention or therapeutic interventions for AD.
Collapse
Affiliation(s)
- Xin Wang
- Department of Neurosciences (X.W., I.B., K.D.D., C.C.F., S.J.B.), University of California; and Center for Multimodal Imaging and Genetics (X.W., I.B., C.C.F., S.J.B.), University of California, San Diego, La Jolla
| | - Iris Broce
- Department of Neurosciences (X.W., I.B., K.D.D., C.C.F., S.J.B.), University of California; and Center for Multimodal Imaging and Genetics (X.W., I.B., C.C.F., S.J.B.), University of California, San Diego, La Jolla
| | - Kacie D Deters
- Department of Neurosciences (X.W., I.B., K.D.D., C.C.F., S.J.B.), University of California; and Center for Multimodal Imaging and Genetics (X.W., I.B., C.C.F., S.J.B.), University of California, San Diego, La Jolla
| | - Chun Chieh Fan
- Department of Neurosciences (X.W., I.B., K.D.D., C.C.F., S.J.B.), University of California; and Center for Multimodal Imaging and Genetics (X.W., I.B., C.C.F., S.J.B.), University of California, San Diego, La Jolla
| | - Sarah Jane Banks
- Department of Neurosciences (X.W., I.B., K.D.D., C.C.F., S.J.B.), University of California; and Center for Multimodal Imaging and Genetics (X.W., I.B., C.C.F., S.J.B.), University of California, San Diego, La Jolla
| |
Collapse
|