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Alzheimer’s Disease Sequencing Project Phenotype Harmonization Consortium (ADSP-PHC)

PI
Mez, Jesse
DAR ID
10522
Initial Approval Date
April 19, 2022
Current DAR Status
Active
PI Institution
Boston University School of Medicine
PI Institution Country
United States
PI Institution Type
Non-Profit

Requested Datasets (1)

NG00067Alzheimer's Disease Sequencing Project Umbrella Study

Research Use Statement
The ADSP-PHC was established to harmonize the rich endophenotype data across cohort studies to enable modern genomic analyses of ADRD with the ultimate goal to generate harmonized data that will become a “legacy” dataset perpetually curated and shared NIAGADS. The ADSP-PHC will facilitate phenotypic data harmonization for ADSP participants with genetic and genomic data. This effort represents a multi-disciplinary approach leveraging interdisciplinary expertise in large-scale genetic and genomic studies, clinical neuroscience, neuroimaging, psychometrics, and bioinformatics. This study will utilize a team structure consisting of two coordinating centers to oversee activities of all harmonization teams and to oversee coordination with other ADSP workgroups and initiatives, a Storage and Informatics Core that will oversee the coordination between LONI and NIAGADS for all data storage, compliance, and dissemination, a CHARGE Coordination Core to oversee the alignment of data and protocols with CHARGE workgroups, an Integration & Analytics Core that will enable data integration across phenotypes to facilitate downstream machine learning applications, and eight Domain-Specific Harmonization Teams tasked with harmonization in their area of expertise. The endophenotypes that will be harmonized by this project include Cognition, Fluid Biomarkers, Amyloid PET, Structural MRI, White Matter Hyperintensities, White Matter Integrity, Vascular Risk Factors, and Neuropathology.
Site PIs on this project include: Jesse Mez (Boston University), Adam Brickman (Columbia University), Andy Saykin (Indiana University), Elizabeth Mormino (Stanford University), Pauline Maillard (UC Davis), Duygu Tosun-Turgut (UC San Francisco), Christos Davatzikos (University of Pennsylvania), Arthur Toga (USC); Mohamad Habes (University of Texas Health Science Center at San Antonio), Michael Cuccaro (University of Miami), Paul Crane (University of Washington), Bennett Landman (Vanderbilt University), Timothy Hohman (Vanderbilt University Medical Center), and Carlos Cruchaga (Washington University in St. Louis).

Non-Technical Summary
The growing availability of endophenotypic data in cohort studies of Alzheimer’s disease and related dementias (ADRD) provides an exciting opportunity to further characterize the genetic architecture of this devastating disease. However, there is a pressing need to develop and apply advanced harmonization approaches to align ADRD endophenotypes across cohorts. The goal of this coordinated national initiative – the AD Sequencing Project Phenotype Harmonization Consortium, or “ADSP-PHC” – is to provide a centralized database of robust endophenotypes for large-scale genomic analyses that will accelerate the identification of novel targets for therapeutic intervention in ADRD. will accelerate the identification of novel targets for therapeutic intervention in ADRD.

Reported Publications (20)

Publications shown are those reported by investigators through NIAGADS DAR reporting and renewal processes and may not represent a complete list of publications associated with the project.

  1. Amyloid PET predicts longitudinal functional and cognitive trajectories in a heterogeneous cohort. Younes K, et al. Alzheimer's & dementia : the journal of the Alzheimer's Association. 2025. PMID: 40145384
  2. Approaches to Timescale Choice in Cognitive Aging Research and Potential Implications for Estimated Exposure Effects: Coordinated Analyses in 10 Cohorts of Older Adults. Hayes-Larson E, et al. Epidemiology (Cambridge, Mass.). 2025. PMID: 40164562
  3. Beyond NACC's Uniform Data Set for cognition: the impact of additional items on measurement precision. Choi SE, et al. Alzheimer's & dementia : the journal of the Alzheimer's Association. 2025. PMID: 40960068
  4. Bridging the gap: addressing NACC's evolving cognition batteries across UDS versions. Lee ML, et al. Alzheimer's & dementia : the journal of the Alzheimer's Association. 2025. PMID: 41266285
  5. Correction to "Beyond NACC's Uniform Data Set for cognition: The impact of additional items on measurement precision". Alzheimer's & dementia : the journal of the Alzheimer's Association. 2025. PMID: 41253740
  6. Facets of language performance in early-onset and late-onset Alzheimer's disease dementia. Gallée J, et al. Alzheimer's & dementia : the journal of the Alzheimer's Association. 2025. PMID: 40990522
  7. Modeling heterogeneity in cognitive trajectories in the Framingham Heart Study. Fang Y, et al. Frontiers in aging neuroscience. 2025. PMID: 40636900
  8. Multi-ancestry genome-wide meta-analysis of 56,241 individuals identifies known and novel cross-population and ancestry-specific associations as novel risk loci for Alzheimer's disease. Rajabli F, et al. Genome biology. 2025. PMID: 40676597
  9. Novel modelling approaches to elucidate the genetic architecture of resilience to Alzheimer's disease. Phillips JM, et al. Brain : a journal of neurology. 2025. PMID: 40111762
  10. The Association of Circulating Immune Cells With Cognitive Function, Brain Imaging, and Incident All-cause and Alzheimer's Dementia: The Framingham Offspring Study. Cao Y, et al. The journals of gerontology. Series A, Biological sciences and medical sciences. 2025. PMID: 40168089
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  1. The dynamics of cognitive decline toward Alzheimer's disease progression: Results from ADSP-PHC's harmonized cognitive composites. Kang K, et al. Alzheimer's & dementia : the journal of the Alzheimer's Association. 2025. PMID: 40538025
  2. White Matter Abnormalities and Cognition in Aging and Alzheimer Disease. Peter C, et al. JAMA neurology. 2025. PMID: 40513084
  3. Association of amyloid and cardiovascular risk with cognition: Findings from KBASE. Chaudhuri S, et al. Alzheimer's & dementia : the journal of the Alzheimer's Association. 2024. PMID: 39511852
  4. Cognitively defined Alzheimer's dementia subgroups have distinct atrophy patterns. Crane PK, et al. Alzheimer's & dementia : the journal of the Alzheimer's Association. 2024. PMID: 38093529
  5. Longitudinal change in memory performance as a strong endophenotype for Alzheimer's disease. Archer DB, et al. Alzheimer's & dementia : the journal of the Alzheimer's Association. 2024. PMID: 37985223
  6. Sex-specific genetic architecture of late-life memory performance. Eissman JM, et al. Alzheimer's & dementia : the journal of the Alzheimer's Association. 2024. PMID: 37984853
  7. A genome-wide search for pleiotropy in more than 100,000 harmonized longitudinal cognitive domain scores. Kang M, et al. Molecular neurodegeneration. 2023. PMID: 37349795
  8. Associations of Sex, Race, and Apolipoprotein E Alleles With Multiple Domains of Cognition Among Older Adults. Walters S, et al. JAMA neurology. 2023. PMID: 37459083
  9. Ceiling effects and differential measurement precision across calibrated cognitive scores in the Framingham Study. Scollard P, et al. Neuropsychology. 2023. PMID: 37276135
  10. Measurement precision across cognitive domains in the Alzheimer's Disease Neuroimaging Initiative (ADNI) data set. Crane PK, et al. Neuropsychology. 2023. PMID: 37276134