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Tucker A, Goldberg TE, Kim H. Biomarkers of sleep-wake disturbance as predictors of cognitive decline and accelerated disease progression. Expert Rev Mol Diagn 2024:1-9. [PMID: 39129222 DOI: 10.1080/14737159.2024.2389307] [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: 04/29/2024] [Accepted: 08/02/2024] [Indexed: 08/13/2024]
Abstract
INTRODUCTION In older adults, where sleep disturbances and cognitive impairment are common, mounting evidence suggests a potential connection between sleep and cognitive function, highlighting the significance of utilizing sleep as a biomarker for early detection of cognitive impairment to improve clinical outcomes in a noninvasive, cost-effective manner. AREAS COVERED This review describes the relationship between sleep and cognitive function in older adults, encompassing both subjective and objective measures of sleep quality, duration, architecture, and sleep-disordered breathing. The authors consider the directionality of the associations observed in prospective and cross-sectional studies, exploring whether sleep disturbances precede cognitive decline or vice versa. Furthermore, they discuss the potential bidirectional relationships between sleep and Alzheimer's disease (AD) risks in older adults while also examining the neurodegenerative pathways of this relationship. EXPERT OPINION Routine sleep monitoring in primary care settings has the potential to bolster early detection and treatment of sleep disturbance, and by extension, reduce the risk of dementia. Improving sleep assessment tools, such as wearables, provide scalable alternatives to traditional methods like polysomnography, potentially enabling widespread monitoring of sleep characteristics. Standardized measurement and inclusive participant recruitment are needed to enhance generalizability, while longitudinal studies are essential to understand the interaction between sleep and AD pathology.
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Affiliation(s)
- Aren Tucker
- Brain Aging and Mental Health Division, New York State Psychiatric Institute, New York, NY, USA
| | - Terry E Goldberg
- Brain Aging and Mental Health Division, New York State Psychiatric Institute, New York, NY, USA
- Department of Psychiatry, Columbia University Irving Medical Psychology, New York, NY, USA
- Department of Anesthisiology, Columbia University Irving Medical Psychology, New York, NY, USA
| | - Hyun Kim
- Brain Aging and Mental Health Division, New York State Psychiatric Institute, New York, NY, USA
- Department of Psychiatry, Columbia University Irving Medical Psychology, New York, NY, USA
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Lu Y, Pike JR, Chen J, Walker KA, Sullivan KJ, Thyagarajan B, Mielke MM, Lutsey PL, Knopman D, Gottesman RF, Sharrett AR, Coresh J, Mosley TH, Palta P. Changes in Alzheimer Disease Blood Biomarkers and Associations With Incident All-Cause Dementia. JAMA 2024:2821670. [PMID: 39068543 PMCID: PMC11284635 DOI: 10.1001/jama.2024.6619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 03/29/2024] [Indexed: 07/30/2024]
Abstract
Importance Plasma biomarkers show promise for identifying Alzheimer disease (AD) neuropathology and neurodegeneration, but additional examination among diverse populations and throughout the life course is needed. Objective To assess temporal plasma biomarker changes and their association with all-cause dementia, overall and among subgroups of community-dwelling adults. Design, Setting, and Participants In 1525 participants from the US-based Atherosclerosis Risk in Communities (ARIC) study, plasma biomarkers were measured using stored specimens collected in midlife (1993-1995, mean age 58.3 years) and late life (2011-2013, mean age 76.0 years; followed up to 2016-2019, mean age 80.7 years). Midlife risk factors (hypertension, diabetes, lipids, coronary heart disease, cigarette use, and physical activity) were assessed for their associations with change in plasma biomarkers over time. The associations of biomarkers with incident all-cause dementia were evaluated in a subpopulation (n = 1339) who were dementia-free in 2011-2013 and had biomarker measurements in 1993-1995 and 2011-2013. Exposure Plasma biomarkers of amyloid-β 42 to amyloid-β 40 (Aβ42:Aβ40) ratio, phosphorylated tau at threonine 181 (p-tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) were measured using the Quanterix Simoa platform. Main Outcomes and Measures Incident all-cause dementia was ascertained from January 1, 2012, through December 31, 2019, from neuropsychological assessments, semiannual participant or informant contact, and medical record surveillance. Results Among 1525 participants (mean age, 58.3 [SD, 5.1] years), 914 participants (59.9%) were women, and 394 participants (25.8%) were Black. A total of 252 participants (16.5%) developed dementia. Decreasing Aβ42:Aβ40 ratio and increasing p-tau181, NfL, and GFAP were observed from midlife to late life, with more rapid biomarker changes among participants carrying the apolipoprotein E epsilon 4 (APOEε4) allele. Midlife hypertension was associated with a 0.15-SD faster NfL increase and a 0.08-SD faster GFAP increase per decade; estimates for midlife diabetes were a 0.11-SD faster for NfL and 0.15-SD faster for GFAP. Only AD-specific biomarkers in midlife demonstrated long-term associations with late-life dementia (hazard ratio per SD lower Aβ42:Aβ40 ratio, 1.11; 95% CI, 1.02-1.21; per SD higher p-tau181, 1.15; 95% CI, 1.06-1.25). All plasma biomarkers in late life had statistically significant associations with late-life dementia, with NfL demonstrating the largest association (1.92; 95% CI, 1.72-2.14). Conclusions and Relevance Plasma biomarkers of AD neuropathology, neuronal injury, and astrogliosis increase with age and are associated with known dementia risk factors. AD-specific biomarkers' association with dementia starts in midlife whereas late-life measures of AD, neuronal injury, and astrogliosis biomarkers are all associated with dementia.
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Affiliation(s)
- Yifei Lu
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill
| | - James Russell Pike
- Department of Population Health, New York University Grossman School of Medicine, New York
- Division of Epidemiology, Department of Population Health, New York University Grossman School of Medicine, New York
| | - Jinyu Chen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - Keenan A. Walker
- Laboratory of Behavioral Neuroscience, National Institute on Aging Intramural Research Program, Baltimore, Maryland
| | - Kevin J. Sullivan
- Department of Medicine, MIND Center, University of Mississippi Medical Center, Jackson
| | - Bharat Thyagarajan
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis
| | - Michelle M. Mielke
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - Pamela L. Lutsey
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis
| | - David Knopman
- Department of Neurology, Mayo Clinic, Rochester, Minnesota
| | - Rebecca F. Gottesman
- National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, Maryland
| | - A. Richey Sharrett
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - Josef Coresh
- Division of Epidemiology, Department of Population Health, New York University Grossman School of Medicine, New York
- Optimal Aging Institute, New York University Grossman School of Medicine, New York
| | - Thomas H. Mosley
- Department of Medicine, MIND Center, University of Mississippi Medical Center, Jackson
| | - Priya Palta
- Department of Neurology, University of North Carolina at Chapel Hill
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Beshir SA, Hussain N, Menon VB, Al Haddad AHI, Al Zeer RAK, Elnour AA. Advancements and Challenges in Antiamyloid Therapy for Alzheimer's Disease: A Comprehensive Review. Int J Alzheimers Dis 2024; 2024:2052142. [PMID: 39081336 PMCID: PMC11288696 DOI: 10.1155/2024/2052142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 04/20/2024] [Accepted: 06/19/2024] [Indexed: 08/02/2024] Open
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder caused by the accumulation of amyloid-beta (Aβ) proteins and neurofibrillary tangles in the brain. There have been recent advancements in antiamyloid therapy for AD. This narrative review explores the recent advancements and challenges in antiamyloid therapy. In addition, a summary of evidence from antiamyloid therapy trials is presented with a focus on lecanemab. Lecanemab is the most recently approved monoclonal antibody that targets Aβ protofibrils for the treatment of patients with early AD and mild cognitive impairment (MCI). Lecanemab was the first drug shown to slow cognitive decline in patients with MCI or early onset AD dementia when administered as an infusion once every two weeks. In the Clarity AD trial, lecanemab was associated with infusion-site reactions (26.4%) and amyloid-related imaging abnormalities (12.6%). The clinical relevance and long-term side effects of lecanemab require further longitudinal observation. However, several challenges must be addressed before the drug can be routinely used in clinical practice. The drug's route of administration, need for imaging and genetic testing, affordability, accessibility, infrastructure, and potential for serious side effects are some of these challenges. Lecanemab's approval has fueled interest in the potential of other antiamyloid therapies, such as donanemab. Future research must focus on developing strategies to prevent AD; identify easy-to-use validated plasma-based assays; and discover newer user-friendly, and cost-effective drugs that target multiple pathways in AD pathology.
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Affiliation(s)
- Semira Abdi Beshir
- Department of Pharmacy PracticeDubai Pharmacy College for Girls, Dubai, UAE
| | - Nadia Hussain
- Department of Pharmaceutical SciencesCollege of PharmacyAl Ain University, Al Ain, UAE
- AAU Health and Biomedical Research CentreAl Ain University, Abu Dhabi, UAE
| | | | - Amal H. I. Al Haddad
- Chief Operations OfficeSheikh Shakhbout Medical City (SSMC)PureHealth, Abu Dhabi, UAE
| | | | - Asim Ahmed Elnour
- AAU Health and Biomedical Research CentreAl Ain University, Abu Dhabi, UAE
- College of PharmacyAl Ain UniversityAbu Dhabi Campus, Abu Dhabi, UAE
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Guo S, Yang J. Bayesian genome-wide TWAS with reference transcriptomic data of brain and blood tissues identified 141 risk genes for Alzheimer's disease dementia. Alzheimers Res Ther 2024; 16:120. [PMID: 38824563 PMCID: PMC11144322 DOI: 10.1186/s13195-024-01488-7] [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: 07/24/2023] [Accepted: 05/27/2024] [Indexed: 06/03/2024]
Abstract
BACKGROUND Transcriptome-wide association study (TWAS) is an influential tool for identifying genes associated with complex diseases whose genetic effects are likely mediated through transcriptome. TWAS utilizes reference genetic and transcriptomic data to estimate effect sizes of genetic variants on gene expression (i.e., effect sizes of a broad sense of expression quantitative trait loci, eQTL). These estimated effect sizes are employed as variant weights in gene-based association tests, facilitating the mapping of risk genes with genome-wide association study (GWAS) data. However, most existing TWAS of Alzheimer's disease (AD) dementia are limited to studying only cis-eQTL proximal to the test gene. To overcome this limitation, we applied the Bayesian Genome-wide TWAS (BGW-TWAS) method to leveraging both cis- and trans- eQTL of brain and blood tissues, in order to enhance mapping risk genes for AD dementia. METHODS We first applied BGW-TWAS to the Genotype-Tissue Expression (GTEx) V8 dataset to estimate cis- and trans- eQTL effect sizes of the prefrontal cortex, cortex, and whole blood tissues. Estimated eQTL effect sizes were integrated with the summary data of the most recent GWAS of AD dementia to obtain BGW-TWAS (i.e., gene-based association test) p-values of AD dementia per gene per tissue type. Then we used the aggregated Cauchy association test to combine TWAS p-values across three tissues to obtain omnibus TWAS p-values per gene. RESULTS We identified 85 significant genes in prefrontal cortex, 82 in cortex, and 76 in whole blood that were significantly associated with AD dementia. By combining BGW-TWAS p-values across these three tissues, we obtained 141 significant risk genes including 34 genes primarily due to trans-eQTL and 35 mapped risk genes in GWAS Catalog. With these 141 significant risk genes, we detected functional clusters comprised of both known mapped GWAS risk genes of AD in GWAS Catalog and our identified TWAS risk genes by protein-protein interaction network analysis, as well as several enriched phenotypes related to AD. CONCLUSION We applied BGW-TWAS and aggregated Cauchy test methods to integrate both cis- and trans- eQTL data of brain and blood tissues with GWAS summary data, identifying 141 TWAS risk genes of AD dementia. These identified risk genes provide novel insights into the underlying biological mechanisms of AD dementia and potential gene targets for therapeutics development.
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Affiliation(s)
- Shuyi Guo
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
- Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Jingjing Yang
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA.
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Niimi Y, Janelidze S, Sato K, Tomita N, Tsukamoto T, Kato T, Yoshiyama K, Kowa H, Iwata A, Ihara R, Suzuki K, Kasuga K, Ikeuchi T, Ishii K, Ito K, Nakamura A, Senda M, Day TA, Burnham SC, Iaccarino L, Pontecorvo MJ, Hansson O, Iwatsubo T. Combining plasma Aβ and p-tau217 improves detection of brain amyloid in non-demented elderly. Alzheimers Res Ther 2024; 16:115. [PMID: 38778353 PMCID: PMC11112892 DOI: 10.1186/s13195-024-01469-w] [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: 03/12/2024] [Accepted: 04/29/2024] [Indexed: 05/25/2024]
Abstract
BACKGROUND Maximizing the efficiency to screen amyloid-positive individuals in asymptomatic and non-demented aged population using blood-based biomarkers is essential for future success of clinical trials in the early stage of Alzheimer's disease (AD). In this study, we elucidate the utility of combination of plasma amyloid-β (Aβ)-related biomarkers and tau phosphorylated at threonine 217 (p-tau217) to predict abnormal Aβ-positron emission tomography (PET) in the preclinical and prodromal AD. METHODS We designed the cross-sectional study including two ethnically distinct cohorts, the Japanese trial-ready cohort for preclinica and prodromal AD (J-TRC) and the Swedish BioFINDER study. J-TRC included 474 non-demented individuals (CDR 0: 331, CDR 0.5: 143). Participants underwent plasma Aβ and p-tau217 assessments, and Aβ-PET imaging. Findings in J-TRC were replicated in the BioFINDER cohort including 177 participants (cognitively unimpaired: 114, mild cognitive impairment: 63). In both cohorts, plasma Aβ(1-42) (Aβ42) and Aβ(1-40) (Aβ40) were measured using immunoprecipitation-MALDI TOF mass spectrometry (Shimadzu), and p-tau217 was measured with an immunoassay on the Meso Scale Discovery platform (Eli Lilly). RESULTS Aβ-PET was abnormal in 81 participants from J-TRC and 71 participants from BioFINDER. Plasma Aβ42/Aβ40 ratio and p-tau217 individually showed moderate to high accuracies when detecting abnormal Aβ-PET scans, which were improved by combining plasma biomarkers and by including age, sex and APOE genotype in the models. In J-TRC, the highest AUCs were observed for the models combining p-tau217/Aβ42 ratio, APOE, age, sex in the whole cohort (AUC = 0.936), combining p-tau217, Aβ42/Aβ40 ratio, APOE, age, sex in the CDR 0 group (AUC = 0.948), and combining p-tau217/Aβ42 ratio, APOE, age, sex in the CDR 0.5 group (AUC = 0.955), respectively. Each subgroup results were replicated in BioFINDER, where the highest AUCs were seen for models combining p-tau217, Aβ42/40 ratio, APOE, age, sex in cognitively unimpaired (AUC = 0.938), and p-tau217/Aβ42 ratio, APOE, age, sex in mild cognitive impairment (AUC = 0.914). CONCLUSIONS Combination of plasma Aβ-related biomarkers and p-tau217 exhibits high performance when predicting Aβ-PET positivity. Adding basic clinical information (i.e., age, sex, APOE ε genotype) improved the prediction in preclinical AD, but not in prodromal AD. Combination of Aβ-related biomarkers and p-tau217 could be highly useful for pre-screening of participants in clinical trials of preclinical and prodromal AD.
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Affiliation(s)
- Yoshiki Niimi
- Unit for Early and Exploratory Clinical Development, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Kenichiro Sato
- Unit for Early and Exploratory Clinical Development, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan
- Department of Neuropathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Naoki Tomita
- Department of Aging Research and Geriatric Medicine, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- Department of Geriatric Medicine and Neuroimaging, Tohoku University Hospital, Sendai, Japan
| | - Tadashi Tsukamoto
- Department of Neurology, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Takashi Kato
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Aichi, Japan
| | - Kenji Yoshiyama
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Hisatomo Kowa
- Graduate School of Health Sciences, Kobe University, Hyogo, Japan
| | - Atsushi Iwata
- Department of Neurology, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan
| | - Ryoko Ihara
- Department of Neurology, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan
| | - Kazushi Suzuki
- Division of Neurology, Internal Medicine, National Defense Medical College, Saitama, Japan
| | - Kensaku Kasuga
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan
| | - Takeshi Ikeuchi
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan
| | - Kenji Ishii
- Integrated Research Initiative for Living Well With Dementia, Tokyo Metropolitan Institute for Geriatric and Gerontology, Tokyo, Japan
| | - Kengo Ito
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Aichi, Japan
| | - Akinori Nakamura
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Aichi, Japan
| | - Michio Senda
- Department of Molecular Imaging Research, Kobe City Medical Center General Hospital, Hyogo, Japan
| | | | | | | | | | - Oskar Hansson
- Unit for Early and Exploratory Clinical Development, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan.
- Memory Clinic, Skåne University Hospital, Lund, Sweden.
| | - Takeshi Iwatsubo
- Unit for Early and Exploratory Clinical Development, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan.
- Department of Neuropathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
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Chen A, Shea D, Daggett V. Performance of SOBA-AD blood test in discriminating Alzheimer's disease patients from cognitively unimpaired controls in two independent cohorts. Sci Rep 2024; 14:7946. [PMID: 38575622 PMCID: PMC10995183 DOI: 10.1038/s41598-024-57107-w] [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: 01/02/2024] [Accepted: 03/14/2024] [Indexed: 04/06/2024] Open
Abstract
Amyloid-beta (Aβ) toxic oligomers are critical early players in the molecular pathology of Alzheimer's disease (AD). We have developed a Soluble Oligomer Binding Assay (SOBA-AD) for detection of these Aβ oligomers that contain α-sheet secondary structure that discriminates plasma samples from patients on the AD continuum from non-AD controls. We tested 265 plasma samples from two independent cohorts to investigate the performance of SOBA-AD. Testing was performed at two different sites, with different personnel, reagents, and instrumentation. Across two cohorts, SOBA-AD discriminated AD patients from cognitively unimpaired (CU) subjects with 100% sensitivity, > 95% specificity, and > 98% area under the curve (AUC) (95% CI 0.95-1.00). A SOBA-AD positive readout, reflecting α-sheet toxic oligomer burden, was found in AD patients, and not in controls, providing separation of the two populations, aside from 5 SOBA-AD positive controls. Based on an earlier SOBA-AD study, the Aβ oligomers detected in these CU subjects may represent preclinical cases of AD. The results presented here support the value of SOBA-AD as a promising blood-based tool for the detection and confirmation of AD.
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Affiliation(s)
- Amy Chen
- AltPep Corporation, 1150 Eastlake Avenue N, Suite 800, Seattle, WA, 98109, USA
| | - Dylan Shea
- AltPep Corporation, 1150 Eastlake Avenue N, Suite 800, Seattle, WA, 98109, USA
- University of Washington, Box 355610, Seattle, WA, 98195-5610, USA
| | - Valerie Daggett
- AltPep Corporation, 1150 Eastlake Avenue N, Suite 800, Seattle, WA, 98109, USA.
- University of Washington, Box 355610, Seattle, WA, 98195-5610, USA.
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Tsoy E, La Joie R, VandeVrede L, Rojas JC, Yballa C, Chan B, Lago AL, Rodriguez A, Goode CA, Erlhoff SJ, Tee BL, Windon C, Lanata S, Kramer JH, Miller BL, Dilworth‐Anderson P, Boxer AL, Rabinovici GD, Possin KL. Scalable plasma and digital cognitive markers for diagnosis and prognosis of Alzheimer's disease and related dementias. Alzheimers Dement 2024; 20:2089-2101. [PMID: 38224278 PMCID: PMC10942726 DOI: 10.1002/alz.13686] [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: 09/01/2023] [Revised: 12/11/2023] [Accepted: 12/16/2023] [Indexed: 01/16/2024]
Abstract
INTRODUCTION With emergence of disease-modifying therapies, efficient diagnostic pathways are critically needed to identify treatment candidates, evaluate disease severity, and support prognosis. A combination of plasma biomarkers and brief digital cognitive assessments could provide a scalable alternative to current diagnostic work-up. METHODS We examined the accuracy of plasma biomarkers and a 10-minute supervised tablet-based cognitive assessment (Tablet-based Cognitive Assessment Tool Brain Health Assessment [TabCAT-BHA]) in predicting amyloid β positive (Aβ+) status on positron emission tomography (PET), concurrent disease severity, and functional decline in 309 older adults with subjective cognitive impairment (n = 49), mild cognitive impairment (n = 159), and dementia (n = 101). RESULTS Combination of plasma pTau181, Aβ42/40, neurofilament light (NfL), and TabCAT-BHA was optimal for predicting Aβ-PET positivity (AUC = 0.962). Whereas NfL and TabCAT-BHA optimally predicted concurrent disease severity, combining these with pTau181 and glial fibrillary acidic protein was most accurate in predicting functional decline. DISCUSSION Combinations of plasma and digital cognitive markers show promise for scalable diagnosis and prognosis of ADRD. HIGHLIGHTS The need for cost-efficient diagnostic and prognostic markers of AD is urgent. Plasma and digital cognitive markers provide complementary diagnostic contributions. Combination of these markers holds promise for scalable diagnosis and prognosis. Future validation in community cohorts is needed to inform clinical implementation.
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Affiliation(s)
- Elena Tsoy
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- Global Brain Health InstituteUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Renaud La Joie
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Lawren VandeVrede
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Julio C. Rojas
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Claire Yballa
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Brandon Chan
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Argentina Lario Lago
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Anne‐Marie Rodriguez
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Collette A. Goode
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Sabrina J. Erlhoff
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Boon Lead Tee
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- Global Brain Health InstituteUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Charles Windon
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Serggio Lanata
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- Global Brain Health InstituteUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Joel H. Kramer
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- Global Brain Health InstituteUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Bruce L. Miller
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- Global Brain Health InstituteUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Peggye Dilworth‐Anderson
- Department of Health Policy and ManagementGillings School of Global Public HealthUniversity of North Carolina Chapel HillChapel HillCaliforniaUSA
| | - Adam L. Boxer
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Gil D. Rabinovici
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Katherine L. Possin
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- Global Brain Health InstituteUniversity of California San FranciscoSan FranciscoCaliforniaUSA
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Cogswell PM, Lundt ES, Therneau TM, Wiste HJ, Graff‐Radford J, Algeciras‐Schimnich A, Lowe VJ, Mielke MM, Schwarz CG, Senjem ML, Gunter JL, Knopman DS, Vemuri P, Petersen RC, Jack Jr CR. Modeling the temporal evolution of plasma p-tau in relation to amyloid beta and tau PET. Alzheimers Dement 2024; 20:1225-1238. [PMID: 37963289 PMCID: PMC10916944 DOI: 10.1002/alz.13539] [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: 07/21/2023] [Revised: 10/02/2023] [Accepted: 10/11/2023] [Indexed: 11/16/2023]
Abstract
INTRODUCTION The timing of plasma biomarker changes is not well understood. The goal of this study was to evaluate the temporal co-evolution of plasma and positron emission tomography (PET) Alzheimer's disease (AD) biomarkers. METHODS We included 1408 Mayo Clinic Study of Aging and Alzheimer's Disease Research Center participants. An accelerated failure time (AFT) model was fit with amyloid beta (Aβ) PET, tau PET, plasma p-tau217, p-tau181, and glial fibrillary acidic protein (GFAP) as endpoints. RESULTS Individual timing of plasma p-tau progression was strongly associated with Aβ PET and GFAP progression. In the population, GFAP became abnormal first, then Aβ PET, plasma p-tau, and tau PET temporal meta-regions of interest when applying cut points based on young, cognitively unimpaired participants. DISCUSSION Plasma p-tau is a stronger indicator of a temporally linked response to elevated brain Aβ than of tau pathology. While Aβ deposition and a rise in GFAP are upstream events associated with tau phosphorylation, the temporal link between p-tau and Aβ PET was the strongest. HIGHLIGHTS Plasma p-tau progression was more strongly associated with Aβ than tau PET. Progression on plasma p-tau was associated with Aβ PET and GFAP progression. P-tau181 and p-tau217 become abnormal after Aβ PET and before tau PET. GFAP became abnormal first, before plasma p-tau and Aβ PET.
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Affiliation(s)
| | - Emily S. Lundt
- Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
| | - Terry M. Therneau
- Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
| | - Heather J. Wiste
- Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
| | | | | | - Val J. Lowe
- Department of RadiologyMayo ClinicRochesterMinnesotaUSA
| | - Michelle M. Mielke
- Department of Epidemiology and PreventionWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | | | - Matthew L. Senjem
- Department of RadiologyMayo ClinicRochesterMinnesotaUSA
- Department of Information TechnologyMayo ClinicRochesterMinnesotaUSA
| | | | | | | | - Ronald C. Petersen
- Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
- Department of NeurologyMayo ClinicRochesterMinnesotaUSA
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9
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Sandau US, Wiedrick JT, McFarland TJ, Galasko DR, Fanning Z, Quinn JF, Saugstad JA. Analysis of the longitudinal stability of human plasma miRNAs and implications for disease biomarkers. Sci Rep 2024; 14:2148. [PMID: 38272952 PMCID: PMC10810819 DOI: 10.1038/s41598-024-52681-5] [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: 08/17/2023] [Accepted: 01/18/2024] [Indexed: 01/27/2024] Open
Abstract
There is great interest in developing clinical biomarker assays that can aid in non-invasive diagnosis and/or monitoring of human diseases, such as cancer, cardiovascular disease, and neurological diseases. Yet little is known about the longitudinal stability of miRNAs in human plasma. Here we assessed the intraindividual longitudinal stability of miRNAs in plasma from healthy human adults, and the impact of common factors (e.g., hemolysis, age) that may confound miRNA data. We collected blood by venipuncture biweekly over a 3-month period from 22 research participants who had fasted overnight, isolated total RNA, then performed miRNA qPCR. Filtering and normalization of the qPCR data revealed amplification of 134 miRNAs, 74 of which had high test-retest reliability and low percentage level drift, meaning they were stable in an individual over the 3-month time period. We also determined that, of nuisance factors, hemolysis and tobacco use have the greatest impact on miRNA levels and variance. These findings support that many miRNAs show intraindividual longitudinal stability in plasma from healthy human adults, including some reported as candidate biomarkers for Alzheimer's disease.
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Affiliation(s)
- Ursula S Sandau
- Department of Anesthesiology and Perioperative Medicine, Oregon Health and Science University, Portland, OR, USA
| | - Jack T Wiedrick
- Biostatistics and Design Program, Oregon Health and Science University, Portland, OR, USA
| | - Trevor J McFarland
- Department of Anesthesiology and Perioperative Medicine, Oregon Health and Science University, Portland, OR, USA
| | - Douglas R Galasko
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | - Zoe Fanning
- Department of Neurology, Oregon Health and Science University, Portland, OR, USA
| | - Joseph F Quinn
- Department of Neurology, Oregon Health and Science University, Portland, OR, USA
| | - Julie A Saugstad
- Department of Anesthesiology and Perioperative Medicine, Oregon Health and Science University, Portland, OR, USA.
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10
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Gutierrez-Tordera L, Papandreou C, Novau-Ferré N, García-González P, Rojas M, Marquié M, Chapado LA, Papagiannopoulos C, Fernàndez-Castillo N, Valero S, Folch J, Ettcheto M, Camins A, Boada M, Ruiz A, Bulló M. Exploring small non-coding RNAs as blood-based biomarkers to predict Alzheimer's disease. Cell Biosci 2024; 14:8. [PMID: 38229129 PMCID: PMC10790437 DOI: 10.1186/s13578-023-01190-5] [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: 09/29/2023] [Accepted: 12/27/2023] [Indexed: 01/18/2024] Open
Abstract
BACKGROUND Alzheimer's disease (AD) diagnosis relies on clinical symptoms complemented with biological biomarkers, the Amyloid Tau Neurodegeneration (ATN) framework. Small non-coding RNA (sncRNA) in the blood have emerged as potential predictors of AD. We identified sncRNA signatures specific to ATN and AD, and evaluated both their contribution to improving AD conversion prediction beyond ATN alone. METHODS This nested case-control study was conducted within the ACE cohort and included MCI patients matched by sex. Patients free of type 2 diabetes underwent cerebrospinal fluid (CSF) and plasma collection and were followed-up for a median of 2.45-years. Plasma sncRNAs were profiled using small RNA-sequencing. Conditional logistic and Cox regression analyses with elastic net penalties were performed to identify sncRNA signatures for A+(T|N)+ and AD. Weighted scores were computed using cross-validation, and the association of these scores with AD risk was assessed using multivariable Cox regression models. Gene ontology (GO) and Kyoto encyclopaedia of genes and genomes (KEGG) enrichment analysis of the identified signatures were performed. RESULTS The study sample consisted of 192 patients, including 96 A+(T|N)+ and 96 A-T-N- patients. We constructed a classification model based on a 6-miRNAs signature for ATN. The model could classify MCI patients into A-T-N- and A+(T|N)+ groups with an area under the curve of 0.7335 (95% CI, 0.7327 to 0.7342). However, the addition of the model to conventional risk factors did not improve the prediction of AD beyond the conventional model plus ATN status (C-statistic: 0.805 [95% CI, 0.758 to 0.852] compared to 0.829 [95% CI, 0.786, 0.872]). The AD-related 15-sncRNAs signature exhibited better predictive performance than the conventional model plus ATN status (C-statistic: 0.849 [95% CI, 0.808 to 0.890]). When ATN was included in this model, the prediction further improved to 0.875 (95% CI, 0.840 to 0.910). The miRNA-target interaction network and functional analysis, including GO and KEGG pathway enrichment analysis, suggested that the miRNAs in both signatures are involved in neuronal pathways associated with AD. CONCLUSIONS The AD-related sncRNA signature holds promise in predicting AD conversion, providing insights into early AD development and potential targets for prevention.
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Affiliation(s)
- Laia Gutierrez-Tordera
- Nutrition and Metabolic Health Research Group, Department of Biochemistry and Biotechnology, Rovira i Virgili University (URV), 43201, Reus, Spain
- Institute of Health Pere Virgili (IISPV), 43204, Reus, Spain
- Center of Environmental, Food and Toxicological Technology-TecnATox, Rovira i Virgili University, 43201, Reus, Spain
| | - Christopher Papandreou
- Nutrition and Metabolic Health Research Group, Department of Biochemistry and Biotechnology, Rovira i Virgili University (URV), 43201, Reus, Spain.
- Institute of Health Pere Virgili (IISPV), 43204, Reus, Spain.
- Center of Environmental, Food and Toxicological Technology-TecnATox, Rovira i Virgili University, 43201, Reus, Spain.
| | - Nil Novau-Ferré
- Nutrition and Metabolic Health Research Group, Department of Biochemistry and Biotechnology, Rovira i Virgili University (URV), 43201, Reus, Spain
- Institute of Health Pere Virgili (IISPV), 43204, Reus, Spain
- Center of Environmental, Food and Toxicological Technology-TecnATox, Rovira i Virgili University, 43201, Reus, Spain
| | - Pablo García-González
- ACE Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), 08028, Barcelona, Spain
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Carlos III Health Institute, 28031, Madrid, Spain
| | - Melina Rojas
- Nutrition and Metabolic Health Research Group, Department of Biochemistry and Biotechnology, Rovira i Virgili University (URV), 43201, Reus, Spain
- Institute of Health Pere Virgili (IISPV), 43204, Reus, Spain
- Center of Environmental, Food and Toxicological Technology-TecnATox, Rovira i Virgili University, 43201, Reus, Spain
| | - Marta Marquié
- ACE Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), 08028, Barcelona, Spain
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Carlos III Health Institute, 28031, Madrid, Spain
| | - Luis A Chapado
- Laboratory of Epigenetics of Lipid Metabolism, Instituto Madrileño de Estudios Avanzados (IMDEA)-Alimentación, CEI UAM+CSIC, 28049, Madrid, Spain
| | - Christos Papagiannopoulos
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, 45500, Ioannina, Greece
| | - Noèlia Fernàndez-Castillo
- Department de Genetics, Microbiology and Statistics, Faculty of Biology, Universitat de Barcelona, 08007, Barcelona, Spain
| | - Sergi Valero
- ACE Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), 08028, Barcelona, Spain
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Carlos III Health Institute, 28031, Madrid, Spain
| | - Jaume Folch
- Nutrition and Metabolic Health Research Group, Department of Biochemistry and Biotechnology, Rovira i Virgili University (URV), 43201, Reus, Spain
- Institute of Health Pere Virgili (IISPV), 43204, Reus, Spain
- Center of Environmental, Food and Toxicological Technology-TecnATox, Rovira i Virgili University, 43201, Reus, Spain
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Carlos III Health Institute, 28031, Madrid, Spain
| | - Miren Ettcheto
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Carlos III Health Institute, 28031, Madrid, Spain
- Department of Pharmacology, Toxicology and Therapeutic Chemistry, Faculty of Pharmacy and Food Science, Universitat de Barcelona, 08028, Barcelona, Spain
- Institute of Neuroscience, Universitat de Barcelona, 08035, Barcelona, Spain
| | - Antoni Camins
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Carlos III Health Institute, 28031, Madrid, Spain
- Department of Pharmacology, Toxicology and Therapeutic Chemistry, Faculty of Pharmacy and Food Science, Universitat de Barcelona, 08028, Barcelona, Spain
- Institute of Neuroscience, Universitat de Barcelona, 08035, Barcelona, Spain
| | - Mercè Boada
- ACE Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), 08028, Barcelona, Spain
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Carlos III Health Institute, 28031, Madrid, Spain
| | - Agustín Ruiz
- ACE Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), 08028, Barcelona, Spain
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Carlos III Health Institute, 28031, Madrid, Spain
| | - Mònica Bulló
- Nutrition and Metabolic Health Research Group, Department of Biochemistry and Biotechnology, Rovira i Virgili University (URV), 43201, Reus, Spain.
- Institute of Health Pere Virgili (IISPV), 43204, Reus, Spain.
- Center of Environmental, Food and Toxicological Technology-TecnATox, Rovira i Virgili University, 43201, Reus, Spain.
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, 28029, Madrid, Spain.
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Korologou-Linden R, Kalsi J, Kafetsouli D, Olawale A, Iwata A, Wingfield D, Mummery D, Hayhoe B, Robinson O, Majeed A, Middleton LT. Novel Blood-Based Biomarkers and Disease Modifying Therapies for Alzheimer's Disease. Are We Ready for the New Era? J Prev Alzheimers Dis 2024; 11:897-902. [PMID: 39044500 PMCID: PMC11266440 DOI: 10.14283/jpad.2024.83] [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] [Received: 02/23/2024] [Accepted: 03/17/2024] [Indexed: 07/25/2024]
Abstract
Recent positive trials for novel disease modifying therapies of anti-amyloid monoclonal antibodies represent a paradigm shift in the prevention and management of Alzheimer's disease, a relentlessly progressive and debilitating disease of old age. The reported efficacy of these new agents when given early in the disease trajectory is dependent on an early and accurate disease diagnosis, which is currently based on cerebrospinal fluid tests or/and neuro-imaging studies such as positron emission tomography. These confirmatory tests provide in vivo evidence of the pathological signature of Alzheimer's disease, of increased cerebral amyloid and tau burden and neurodegeneration. The emergence of blood-based biomarkers represents another breakthrough, offering a less invasive and scalable diagnostic tool that could be applied in both primary and specialist care settings, potentially revolutionizing Alzheimer's disease clinical pathways. However, healthcare systems face challenges in the adoption of these new technologies and therapies due to diagnostic and treatment capacity constraints, as well as financial and infrastructure requirements.
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Affiliation(s)
- R Korologou-Linden
- Roxanna Korologou-Linden, Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, 11th Floor, Charing Cross Hospital Campus, W6 8RP, , Tel: +44 20 3311 0208
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12
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Grari O, Elmoujtahide D, Sebbar E, Choukri M. The Biochemistry Behind Cognitive Decline: Biomarkers of Alzheimer's Disease. EJIFCC 2023; 34:276-283. [PMID: 38303754 PMCID: PMC10828533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 02/03/2024]
Abstract
Alzheimer's disease (AD) is the most prevalent type of dementia. Pathologically, the disease is marked by neurofibrillary tangles (NFT), which are aberrant accumulations of the tau protein that develop inside neurons, and extracellular plaque deposits of the amyloid β peptide (Aβ). These pathological lesions are present in the brain before the beginning of clinical manifestations. However, despite advancements in the comprehension of AD pathophysiology, timely and accurate clinical diagnosis remains challenging. Therefore, developing biomarkers capable of detecting AD during the preclinical phase holds enormous promise for precise diagnosis since detecting the disease early is crucial because it enables interventions when treatments may be more effective. This article intends to provide a comprehensive review of AD biomarkers, discussing their significance, classification, and recent developments in the field.
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Affiliation(s)
- O. Grari
- : Faculty of Medicine and Pharmacy, Mohammed I University, Oujda, Morocco
- : Department of Biochemistry, Mohammed VI University Hospital, Oujda, Morocco
| | - D. Elmoujtahide
- : Faculty of Medicine and Pharmacy, Mohammed I University, Oujda, Morocco
- : Department of Biochemistry, Mohammed VI University Hospital, Oujda, Morocco
| | - E. Sebbar
- : Faculty of Medicine and Pharmacy, Mohammed I University, Oujda, Morocco
- : Department of Biochemistry, Mohammed VI University Hospital, Oujda, Morocco
| | - M. Choukri
- : Faculty of Medicine and Pharmacy, Mohammed I University, Oujda, Morocco
- : Department of Biochemistry, Mohammed VI University Hospital, Oujda, Morocco
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13
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Spargo D, Zur R, Lin P, Synnott P, Klein E, Hartry A. Estimating prevalence of early symptomatic Alzheimer's disease in the United States. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12497. [PMID: 38034853 PMCID: PMC10682565 DOI: 10.1002/dad2.12497] [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: 07/18/2023] [Revised: 10/12/2023] [Accepted: 10/19/2023] [Indexed: 12/02/2023]
Abstract
INTRODUCTION Understanding the prevalence of treatment-eligible Alzheimer's disease (AD) is crucial for policy planning. METHODS We used a comprehensive literature review and population cascade approach to estimate the number of amyloid-positive, clinically diagnosed patients with mild cognitive impairment (MCI) or mild dementia due to AD in the United States. RESULTS An estimated 666,646 individuals were identified as having MCI due to AD (range: 351,926-1,227,776) and 620,850 individuals as having mild dementia due to AD (range: 445,082-820,339). In a US population of 76 million individuals aged 60 or older in 2021, the estimates of MCI and mild dementia due to AD increased with age. CONCLUSIONS As earlier diagnosis of AD and new disease-modifying treatments become available, accurate population estimates are required to reduce uncertainty in the number of clinically diagnosed patients eligible for amyloid-targeting therapies.
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Affiliation(s)
| | | | - Pei‐Jung Lin
- Center for the Evaluation of Value and Risk in HealthInstitute for Clinical Research and Health Policy StudiesTufts Medical CenterBostonMassachusettsUSA
| | - Patricia Synnott
- Center for the Evaluation of Value and Risk in HealthInstitute for Clinical Research and Health Policy StudiesTufts Medical CenterBostonMassachusettsUSA
| | - Eric Klein
- Eli Lilly and CompanyIndianapolisIndianaUSA
| | - Ann Hartry
- Eli Lilly and CompanyIndianapolisIndianaUSA
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14
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Cho S, Chu MK. Serological Biomarkers of Chronic Migraine. Curr Pain Headache Rep 2023; 27:531-542. [PMID: 37561314 DOI: 10.1007/s11916-023-01154-x] [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] [Accepted: 07/07/2023] [Indexed: 08/11/2023]
Abstract
PURPOSE OF REVIEW Chronic migraine (CM) is a chronic form of migraine that differs from episodic migraine (EM) in terms of prevalence, comorbidities, response to treatment, and biomarkers. The aim of this review was to summarize the recent findings on serological biomarkers of CM. RECENT FINDINGS Neuronal, inflammatory, and vascular markers have been investigated to assess their diagnostic and prognostic ability and treatment effectiveness. Several markers showed significant alterations according to disease status and treatment response in CM. Calcitonin gene-related peptide (CGRP), glutamate, and adiponectin appear to be the most promising blood biomarkers for CM. Most studies have shown altered ictal and interictal levels of these markers in CM compared with those in EM and controls. Additionally, they showed a significant association with treatment outcomes. Total adiponectin and high-molecular-weight adiponectin levels were less studied as biomarkers of CM than CGRP and glutamate levels but showed promising results. The development of suitable biomarkers could revolutionize the diagnosis and treatment of CM and ultimately decrease the disability and societal costs of the disease.
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Affiliation(s)
- Soomi Cho
- Department of Neurology, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea
| | - Min Kyung Chu
- Department of Neurology, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
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15
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Suridjan I, van der Flier WM, Monsch AU, Burnie N, Baldor R, Sabbagh M, Vilaseca J, Cai D, Carboni M, Lah JJ. Blood-based biomarkers in Alzheimer's disease: Future directions for implementation. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12508. [PMID: 38058357 PMCID: PMC10696162 DOI: 10.1002/dad2.12508] [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: 06/23/2023] [Revised: 09/22/2023] [Accepted: 10/30/2023] [Indexed: 12/08/2023]
Abstract
INTRODUCTION Disease-modifying therapies (DMTs) for Alzheimer's disease (AD) will increase diagnostic demand. A non-invasive blood-based biomarker (BBBM) test for detection of amyloid-β pathology may reduce diagnostic barriers and facilitate DMT initiation. OBJECTIVE To explore heterogeneity in AD care pathways and potential role of BBBM tests. METHODS Survey of 213 healthcare professionals/payers in US/China/UK/Germany/Spain/France and two advisory boards (US/Europe). RESULTS Current diagnostic pathways are heterogeneous, meaning many AD patients are missed while low-risk patients undergo unnecessary procedures. Confirmatory amyloid testing (cerebrospinal fluid biomarkers/positron emission tomography) is utilized in few patients, resulting in diagnostic/treatment delays. A high negative-predictive-value test could streamline the diagnostic pathway by reducing unnecessary procedures in low-risk patients; supporting confirmatory testing where needed. Imminent approval of DMTs will increase need for fast and reliable AD diagnostic tests. DISCUSSION An easy-to-use, accurate, non-invasive BBBM test for amyloid pathology could guide diagnostic procedures or referral, streamlining early diagnosis and DMT initiation. Highlights This study explored AD care pathways and how BBBM may meet diagnostic demandsCurrent diagnostic pathways are heterogeneous, with country and setting variationsMany AD patients are missed, while low-risk patients undergo unnecessary proceduresAn easy-to-use, accurate, non-invasive BBBM test for amyloid pathology is neededThis test could streamline early diagnosis of amyloid pathology and DMT initiation.
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Affiliation(s)
| | - Wiesje M. van der Flier
- Alzheimer Center AmsterdamNeurology, Epidemiology and Data Science, Vrije Universiteit AmsterdamAmsterdam UMC location VUmcAmsterdamThe Netherlands
- Amsterdam NeuroscienceNeurodegenerationAmsterdamThe Netherlands
| | - Andreas U. Monsch
- Memory ClinicUniversity Department of Geriatric Medicine FELIX PLATTERBaselSwitzerland
| | | | - Robert Baldor
- Department of Family Medicine and Community HealthUMass Chan Medical School, North WorcesterMassachusettsUSA
| | - Marwan Sabbagh
- Barrow Neurological InstituteDignity Health/St Joseph's Hospital and Medical CenterPhoenixArizonaUSA
| | - Josep Vilaseca
- Department of MedicineUniversitat de Vic‐Central Catalonia UniversityVicSpain
- Primary Health Care ServiceAlthaia Foundation ‐ Clinical and University Network in Manresa, Dr. Joan SolerManresaSpain
| | - Dongming Cai
- Alzheimer's Disease Research CenterIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- N. Bud Grossman Center for Memory Research and CareUniversity of MinnesotaMinneapolisMinnesotaUSA
- Geriatric ResearchEducation and Clinical Center (GRECC)Minneapolis VA Health Care System, One Veterans DrMinneapolisMinnesotaUSA
| | | | - James J. Lah
- Goizueta Alzheimer's Disease Research CenterEmory University School of MedicineAtlantaGeorgiaUSA
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16
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Monane M, Johnson KG, Snider BJ, Turner RS, Drake JD, Maraganore DM, Bicksel JL, Jacobs DH, Ortega JL, Henderson J, Jiang Y, Huang S, Coppinger J, Fogelman I, West T, Braunstein JB. A blood biomarker test for brain amyloid impacts the clinical evaluation of cognitive impairment. Ann Clin Transl Neurol 2023; 10:1738-1748. [PMID: 37550958 PMCID: PMC10578891 DOI: 10.1002/acn3.51863] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 07/06/2023] [Accepted: 07/09/2023] [Indexed: 08/09/2023] Open
Abstract
OBJECTIVE The objective of this study was to examine clinicians' patient selection and result interpretation of a clinically validated mass spectrometry test measuring amyloid beta and ApoE blood biomarkers combined with patient age (PrecivityAD® blood test) in symptomatic patients evaluated for Alzheimer's disease (AD) or other causes of cognitive decline. METHODS The Quality Improvement and Clinical Utility PrecivityAD Clinician Survey (QUIP I, ClinicalTrials.gov Identifier: NCT05477056) was a prospective, single-arm cohort study among 366 patients evaluated by neurologists and other cognitive specialists. Participants underwent blood biomarker testing and received an amyloid probability score (APS), indicating the likelihood of a positive result on an amyloid positron emission tomography (PET) scan. The primary study outcomes were appropriateness of patient selection as well as result interpretation associated with PrecivityAD blood testing. RESULTS A 95% (347/366) concordance rate was noted between clinicians' patient selection and the test's intended use criteria. In the final analysis including these 347 patients (median age 75 years, 56% women), prespecified test result categories incorporated 133 (38%) low APS, 162 (47%) high APS, and 52 (15%) intermediate APS patients. Clinicians' pretest and posttest AD diagnosis probability changed from 58% to 23% in low APS patients and 71% to 89% in high APS patients (p < 0.0001). Anti-AD drug therapy decreased by 46% in low APS patients (p < 0.0001) and increased by 57% in high APS patients (p < 0.0001). INTERPRETATION These findings demonstrate the clinical utility of the PrecivityAD blood test in clinical care and may have added relevance as new AD therapies are introduced.
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Affiliation(s)
| | - Kim G. Johnson
- Department of Psychiatry & Behavioral SciencesDuke UniversityDurhamNorth CarolinaUSA
| | - B. Joy Snider
- Washington University School of MedicineSt. LouisMissouriUSA
| | | | - Jonathan D. Drake
- Warren Alpert Medical School at Brown UniversityProvidenceRhode IslandUSA
| | | | | | | | | | | | | | | | | | | | - Tim West
- C2N Diagnostics, LLCSt. LouisMissouriUSA
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Manolopoulos A, Delgado-Peraza F, Mustapic M, Pucha KA, Nogueras-Ortiz C, Daskalopoulos A, Knight DD, Leoutsakos JM, Oh ES, Lyketsos CG, Kapogiannis D. Comparative assessment of Alzheimer's disease-related biomarkers in plasma and neuron-derived extracellular vesicles: a nested case-control study. Front Mol Biosci 2023; 10:1254834. [PMID: 37828917 PMCID: PMC10565036 DOI: 10.3389/fmolb.2023.1254834] [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: 07/07/2023] [Accepted: 09/12/2023] [Indexed: 10/14/2023] Open
Abstract
Introduction: Alzheimer's disease (AD) is currently defined according to biomarkers reflecting the core underlying neuropathological processes: Aβ deposition, Tau, and neurodegeneration (ATN). The soluble phase of plasma and plasma neuron-derived extracellular vesicles (NDEVs) are increasingly being investigated as sources of biomarkers. The aim of this study was to examine the comparative biomarker potential of these two biofluids, as well as the association between respective biomarkers. Methods: We retrospectively identified three distinct diagnostic groups of 44 individuals who provided samples at baseline and at a mean of 3.1 years later; 14 were cognitively unimpaired at baseline and remained so (NRM-NRM), 13 had amnestic MCI that progressed to AD dementia (MCI-DEM) and 17 had AD dementia at both timepoints (DEM-DEM). Plasma NDEVs were isolated by immunoaffinity capture targeting the neuronal markers L1CAM, GAP43, and NLGN3. In both plasma and NDEVs, we assessed ATN biomarkers (Aβ42, Aβ40, total Tau, P181-Tau) alongside several other exploratory markers. Results: The Aβ42/Aβ40 ratio in plasma and NDEVs was lower in MCI-DEM than NRM-NRM at baseline and its levels in NDEVs decreased over time in all three groups. Similarly, plasma and NDEV-associated Aβ42 was lower in MCI-DEM compared to NRM-NRM at baseline and its levels in plasma decreased over time in DEM-DEM. For NDEV-associated proBDNF, compared to NRM-NRM, its levels were lower in MCI-DEM and DEM-DEM at baseline, and they decreased over time in the latter group. No group differences were found for other exploratory markers. NDEV-associated Aβ42/Aβ40 ratio and proBDNF achieved the highest areas under the curve (AUCs) for discriminating between diagnostic groups, while proBDNF was positively associated with Mini-Mental State Examination (MMSE) score. No associations were found between the two biofluids for any assessed marker. Discussion: The soluble phase of plasma and plasma NDEVs demonstrate distinct biomarker profiles both at a single time point and longitudinally. The lack of association between plasma and NDEV measures indicates that the two types of biofluids demonstrate distinct biomarker signatures that may be attributable to being derived through different biological processes. NDEV-associated proBDNF may be a useful biomarker for AD diagnosis and monitoring.
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Affiliation(s)
- Apostolos Manolopoulos
- Intramural Research Program, Laboratory of Clinical Investigation, National Institute on Aging, Baltimore, MD, United States
| | - Francheska Delgado-Peraza
- Intramural Research Program, Laboratory of Clinical Investigation, National Institute on Aging, Baltimore, MD, United States
| | - Maja Mustapic
- Intramural Research Program, Laboratory of Clinical Investigation, National Institute on Aging, Baltimore, MD, United States
| | - Krishna Ananthu Pucha
- Intramural Research Program, Laboratory of Clinical Investigation, National Institute on Aging, Baltimore, MD, United States
| | - Carlos Nogueras-Ortiz
- Intramural Research Program, Laboratory of Clinical Investigation, National Institute on Aging, Baltimore, MD, United States
| | - Alexander Daskalopoulos
- Intramural Research Program, Laboratory of Clinical Investigation, National Institute on Aging, Baltimore, MD, United States
| | - De’Larrian DeAnté Knight
- Intramural Research Program, Laboratory of Clinical Investigation, National Institute on Aging, Baltimore, MD, United States
| | - Jeannie-Marie Leoutsakos
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, United States
- Richman Family Precision Medicine Center of Excellence in Alzheimer’s Disease, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Esther S. Oh
- Richman Family Precision Medicine Center of Excellence in Alzheimer’s Disease, Johns Hopkins School of Medicine, Baltimore, MD, United States
- Division of Geriatric Medicine and Gerontology, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Constantine G. Lyketsos
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, United States
- Richman Family Precision Medicine Center of Excellence in Alzheimer’s Disease, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Dimitrios Kapogiannis
- Intramural Research Program, Laboratory of Clinical Investigation, National Institute on Aging, Baltimore, MD, United States
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Bucci M, Bluma M, Savitcheva I, Ashton NJ, Chiotis K, Matton A, Kivipelto M, Di Molfetta G, Blennow K, Zetterberg H, Nordberg A. Profiling of plasma biomarkers in the context of memory assessment in a tertiary memory clinic. Transl Psychiatry 2023; 13:268. [PMID: 37491358 PMCID: PMC10368630 DOI: 10.1038/s41398-023-02558-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 06/24/2023] [Accepted: 07/03/2023] [Indexed: 07/27/2023] Open
Abstract
Plasma biomarkers have shown promising performance in research cohorts in discriminating between different stages of Alzheimer's disease (AD). Studies in clinical populations are necessary to provide insights on the clinical utility of plasma biomarkers before their implementation in real-world settings. Here we investigated plasma biomarkers (glial fibrillary acidic protein (GFAP), tau phosphorylated at 181 and 231 (pTau181, pTau231), amyloid β (Aβ) 42/40 ratio, neurofilament light) in 126 patients (age = 65 ± 8) who were admitted to the Clinic for Cognitive Disorders, at Karolinska University Hospital. After extensive clinical assessment (including CSF analysis), patients were classified as: mild cognitive impairment (MCI) (n = 75), AD (n = 25), non-AD dementia (n = 16), no dementia (n = 9). To refine the diagnosis, patients were examined with [18F]flutemetamol PET (Aβ-PET). Aβ-PET images were visually rated for positivity/negativity and quantified in Centiloid. Accordingly, 68 Aβ+ and 54 Aβ- patients were identified. Plasma biomarkers were measured using single molecule arrays (SIMOA). Receiver-operated curve (ROC) analyses were performed to detect Aβ-PET+ using the different biomarkers. In the whole cohort, the Aβ-PET centiloid values correlated positively with plasma GFAP, pTau231, pTau181, and negatively with Aβ42/40 ratio. While in the whole MCI group, only GFAP was associated with Aβ PET centiloid. In ROC analyses, among the standalone biomarkers, GFAP showed the highest area under the curve discriminating Aβ+ and Aβ- compared to other plasma biomarkers. The combination of plasma biomarkers via regression was the most predictive of Aβ-PET, especially in the MCI group (prior to PET, n = 75) (sensitivity = 100%, specificity = 82%, negative predictive value = 100%). In our cohort of memory clinic patients (mainly MCI), the combination of plasma biomarkers was sensitive in ruling out Aβ-PET negative individuals, thus suggesting a potential role as rule-out tool in clinical practice.
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Affiliation(s)
- Marco Bucci
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, SE-14186, Stockholm, Sweden
| | - Marina Bluma
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden
| | - Irina Savitcheva
- Medical Radiation Physics and Nuclear Medicine, Karolinska University, SE-14186, Stockholm, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, SE-43180, Mölndal, Sweden
| | - Konstantinos Chiotis
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden
- Department of Neurology, Karolinska University Hospital, SE-14186, Stockholm, Sweden
| | - Anna Matton
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden
| | - Miia Kivipelto
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, SE-14186, Stockholm, Sweden
| | - Guglielmo Di Molfetta
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, SE-43180, Mölndal, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, SE-43180, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, SE-43180, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, SE-43180, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, SE-43180, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
- UK Dementia Research Institute at UCL, London, WC1N 3BG, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden.
- Theme Inflammation and Aging, Karolinska University Hospital, SE-14186, Stockholm, Sweden.
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Schindler SE, Atri A. The role of cerebrospinal fluid and other biomarker modalities in the Alzheimer's disease diagnostic revolution. NATURE AGING 2023; 3:460-462. [PMID: 37202514 PMCID: PMC10720501 DOI: 10.1038/s43587-023-00400-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
A major transformation in dementia diagnosis and care appears imminent and will depend on three major types of biomarkers: molecular imaging, blood-based biomarkers, and cerebrospinal fluid biomarkers. Each modality has unique strengths and limitations that suggest its optimal uses in research, clinical trials, and clinical diagnosis.
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Affiliation(s)
- Suzanne E Schindler
- Department of Neurology, Washington University in St Louis, St Louis, MO, USA.
- Charles F. and Joanne Knight Alzheimer Disease Research Center, St Louis, MO, USA.
| | - Alireza Atri
- Banner Sun Health Research Institute, Banner Health, Sun City, AZ, USA
- Center for Brain/Mind Medicine, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
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20
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Wei H, Masurkar AV, Razavian N. On gaps of clinical diagnosis of dementia subtypes: A study of Alzheimer's disease and Lewy body disease. Front Aging Neurosci 2023; 15:1149036. [PMID: 37025965 PMCID: PMC10070837 DOI: 10.3389/fnagi.2023.1149036] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 03/06/2023] [Indexed: 04/08/2023] Open
Abstract
Introduction Alzheimer's disease (AD) and Lewy body disease (LBD) are the two most common neurodegenerative dementias and can occur in combination (AD+LBD). Due to overlapping biomarkers and symptoms, clinical differentiation of these subtypes could be difficult. However, it is unclear how the magnitude of diagnostic uncertainty varies across dementia spectra and demographic variables. We aimed to compare clinical diagnosis and post-mortem autopsy-confirmed pathological results to assess the clinical subtype diagnosis quality across these factors. Methods We studied data of 1,920 participants recorded by the National Alzheimer's Coordinating Center from 2005 to 2019. Selection criteria included autopsy-based neuropathological assessments for AD and LBD, and the initial visit with Clinical Dementia Rating (CDR) stage of normal, mild cognitive impairment, or mild dementia. Longitudinally, we analyzed the first visit at each subsequent CDR stage. This analysis included positive predictive values, specificity, sensitivity and false negative rates of clinical diagnosis, as well as disparities by sex, race, age, and education. If autopsy-confirmed AD and/or LBD was missed in the clinic, the alternative clinical diagnosis was analyzed. Findings In our findings, clinical diagnosis of AD+LBD had poor sensitivities. Over 61% of participants with autopsy-confirmed AD+LBD were diagnosed clinically as AD. Clinical diagnosis of AD had a low sensitivity at the early dementia stage and low specificities at all stages. Among participants diagnosed as AD in the clinic, over 32% had concurrent LBD neuropathology at autopsy. Among participants diagnosed as LBD, 32% to 54% revealed concurrent autopsy-confirmed AD pathology. When three subtypes were missed by clinicians, "No cognitive impairment" and "primary progressive aphasia or behavioral variant frontotemporal dementia" were the leading primary etiologic clinical diagnoses. With increasing dementia stages, the clinical diagnosis accuracy of black participants became significantly worse than other races, and diagnosis quality significantly improved for males but not females. Discussion These findings demonstrate that clinical diagnosis of AD, LBD, and AD+LBD are inaccurate and suffer from significant disparities on race and sex. They provide important implications for clinical management, anticipatory guidance, trial enrollment and applicability of potential therapies for AD, and promote research into better biomarker-based assessment of LBD pathology.
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Affiliation(s)
- Hui Wei
- Manning College of Information and Computer Sciences, University of Massachusetts Amherst, Amherst, MA, United States
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, United States
| | - Arjun V. Masurkar
- Center for Cognitive Neurology, Department of Neurology, NYU Grossman School of Medicine, New York, NY, United States
- Neuroscience Institute, NYU Grossman School of Medicine, New York, NY, United States
| | - Narges Razavian
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, United States
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, United States
- Center for Data Science, New York University, New York, NY, United States
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