Whole genome sequencing of the Mexican Health Aging Study (MHAS) cohort

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Abstract We aim to conduct traditional and innovative genetic analyses of whole-genome sequencing (WGS) data generated from a sub-sample of 3,500 participants from the Mexican Health Aging Study (MHAS). We have already been funded to collect saliva for DNA extraction and to perform genome-wide a association study in this Mexican sample (grant # R56-AG059756, PI: Tosto, Barral, Mayeux). Accumulating evidence supports a strong genetic component underpinning physiopathology of Late onset Alzheimer’s disease (LOAD). European population studies still dominate the pool of available genomic data resulting in a lack of generalizability of findings across diverse and minority populations. By 2020, the prevalence of dementia in Latin America will increase by 120%, compared to 49% in North America. It is therefore pivotal to increase representation of Hispanics and Latinos in genetic investigations. Mexicans are not currently represented in large genetic studies for LOAD. They show a unique genetic profile with one of the highest Native- American ancestral component percentages (~50%). This population may harbor unique LOAD risk/protective alleles, which are rare or absent in other populations. Furthermore, it may shed lights on the contribution of native ancestry on LOAD risk, which is still unknown. Our group has so far collected 9,162 saliva and blood samples from MHAS participants aged 60 and older and stored them at National Cell Repository for Alzheimer’s Disease (NCRAD). MHAS also provides a rich set of phenotypes (demographical, cognitive and medical assessment) with 20-years period of follow-up. The participants that will undergo whole genome sequencing (N~3,500 who meet clinical criteria for dementia and cognitively healthy; ratio 1:4) are characterized by an additional in-depth cognitive evaluation for which we have been already funded. The availability of extensive cognitive endophenotypes will facilitate a plethora of investigations beyond the classical case-control design (i.e. survival analyses and cognitive trajectories); it will ensure the accuracy of LOAD diagnosis, and will facilitate phenotype harmonization across different sequencing cohorts. We propose to: Aim 1) conduct traditional and innovative analysis of the whole genome sequence data generated in a sub-sample of 3,500 MHAS participants 60 years of age or older who meet diagnostic criteria for LOAD and healthy controls (ratio ~1:4); Aim 2) Conduct functional validation of genomic findings prioritized by WGS analyses; Aim 3) Share phenotypic and genomic data with the scientific community.