The Analysis Coordinating Group (ACG) is overseen by the EC-4C and includes ADSP PIs and other investigators from the ADSP. A primary function of the ACG is to exchange information on all activities of the ADSP and disperse that information to ADSP members.
This group includes all ADSP members. Please see the ADSP Membership Policy for information about becoming a member.
The AI/ML Executive Committee comprises the AI/ML Consortium MPIs and NIA program officers. They meet to discuss administrative topics for the Consortium.
The ADSP AI/ML Consortium is applying cognitive systems approaches to the analysis of AD genetic and related data. Analysis of the data generated and harmonized by the ADSP will help to identify new genes and genetic pathways that will reveal risk and protective factors for AD and guide the field toward novel therapeutic approaches to the disease. The AI/ML Working Group meets to share research updates.
The goal of the Analysis Working Group (AWG) is to provide a space for the discussion of behind-the-scenes details involved in the analysis of the complex ADSP data. This contrasts with the ACG which is focused on keeping all investigators abreast of the analyses proposed and in process.
The EC-4C is the governing body of the ADSP and is responsible for both ADSP administrative duties and enhancing collaborative efforts to meet the goals of the ADSP.
The ADSP Functional Genomics Consortium (FunGen-AD) aims to apply cutting-edge genomics technologies and high-throughput genetic screening to understand the functional impacts underlying the genetic basis of susceptibility and resilience of Alzheimer’s disease, and to identify genetics-guided targets for the prevention, diagnosis, and treatment of Alzheimer’s disease and related dementias (AD/ADRD). The work group meets to discuss FunGen-AD projects and other administrative items.
The FunGen Consortium MPIs meet to discuss administrative topics for the Consortium.
The FunGen Trainee Network aims to support trainee career development by fostering a collaborative community across computational and experimental research in functional genomics. The Network will provide a structured forum for trainees to present and discuss their research, gain exposure to diverse scientific approaches, and develop skills in scientific communication. Through regular meetings and ongoing interaction via a shared communication platform, the Network promotes peer mentoring, knowledge exchange, and professional growth, strengthening trainees’ career readiness and connections within the broader research community.
The FunGen xQTL Project provides comprehensive molecular quantitative trait loci (xQTL) analyses across multiple molecular phenotypes, along with integrative analysis for neurodegenerative disorders, particularly Alzheimer’s disease.
The ADSP Follow-Up Study Sequencing (FUS-Seq) working group meets to discuss activities of the FUS 2.0 Diversity Initiative: Recruitment and Retention of Diversity Cohorts, including challenges and progress in collecting samples for genotyping, sequencing, and harmonization.
GCAD is funded by the NIA to harmonize relevant whole genome/exome sequencing data for the identification of risk/causative/protective genetic variants and eventual therapeutic targets for AD. GCAD is responsible for generating project-level sequence datasets, implementing quality control (QC) on them, and making them publicly available for research. The GCAD-QC working group meeting is used to discuss genomic data production, QC, and release progress.
The Gene Verification Committee (GVC) reviews published human genetic evidence that specific loci or genes are associated with AD or contribute to AD risk. The GVC uses a four-tier system to evaluate the quality of evidence supporting associations to inform prioritization of loci and genes for investment in functional genomic methods leading to selection of therapeutic targets.
The ADSP Phenotype Harmonization Consortium (PHC) was established to harmonize the rich endophenotype data across cohort studies to enable modern genomic analyses of ADRD. The mission of the PHC is to work in coordination with other ADSP working groups and initiatives to streamline access to endophenotype data, provide high quality phenotype harmonization across domains, and provide comprehensive documentation of both data availability and harmonization procedures, with the goal of generating harmonized data that will become a “legacy” dataset perpetually curated and shared through NIAGADS. The PHC WG meets to discuss activities and share research updates.
The ADSP Program Planning Committee (PPC) works together to create the goals, agendas, formats, and speaker rosters for the ADSP Annual Program Meetings. The PPC also gives guidance needed to enable the Coordinating Center (CC) to carry out the logistics and planning for the meeting. The NIA program staff will ensure that the PPC proposals align with programmatic and Institute objectives.
The Protective Variants (PV) working group aims to identify variants, genes, and gene sets that modify the effect of known AD risk factors such as APOE-ε4, age, and sex. Protective genetic factors are a high priority as potential AD therapeutic targets. PV activities focus on APOE-ε4 extremes analyses and deviations from risk predicted by AD models generated from APOE, age, and sex. Analyses use multi-ethnic ADSP and AD genetics community sequencing and genotyping array datasets, as appropriate.
The ADSP Strategic Planning Committee (SPC) works together to strategically evaluate, define, and (as needed) reshape the ADSP’s organization and governance to address existing challenges and support the ADSP’s scientific and analytic goals. The SPC’s objective is to strengthen an ADSP-wide culture of collaboration, innovation, and transparency, as well as to improve efficiency, enhance communication, and simplify logistical hurdles.
The Structural Variants (SV) working group studies small indels (insertions and deletions; <50 bp); larger deletions, duplications, and insertions; and balanced forms, such as inversions and translocations. Members discuss progress from multiple laboratories using multiple approaches. The goal is to generate call sets by multiple methods with known specificity and sensitivity characteristics.