Late onset Alzheimer?s disease (LOAD) with onset after age 60 years is the most frequent neurodegenerative disease affecting all ethnic and racial groups. Although the causes remain unclear, studies in case-control cohorts and families with multiple affected members support a genetic etiology for LOAD. To date, large genome- wide association (GWAS) and sequencing studies of LOAD have been carried out mostly in non-Hispanic White populations, and have so far identified over 21 loci associated with increased risk of LOAD. The same loci have also been identified in ethnically diverse populations (Caribbean-Hispanics and African-Americans), some of them with even large genetic effects such as ABCA7 in African Americans. Novel genes were also discovered by GWAS in non-White populations (e.g. FBXL7 in Caribbean Hispanics), ultimately proving their potential to reveal novel pathways or mechanisms underlying LOAD risk and prevention. Data from the 10/66 Dementia Research Group estimates the prevalence of dementia in Mexico to be ~7.3% for people 60 years of age and older, and is projected to increase up to 400% by 2050. Despite this high prevalence, Mexican population is underrepresented in genetic studies. To our knowledge, other than APOE gene effect on the disease, there are few genetic investigations of LOAD among individuals of Mexican ancestry in the United States or elsewhere. The underrepresentation of individuals of Mexican and other ancestries in genetic and translational research ultimately affects the possibility of leveraging their contribution on clinical genomic applications such as genetic testing, counseling and ultimately precision medicine approaches.
We aim to define risk and protective genetic loci on LOAD and related dementias in individuals with Mexican ancestry. To that end, the proposed study will establish the first large-scale investigation of the genetic bases for LOAD and related disorders among individuals of Mexican ancestry. We propose to build on an existing unique and outstanding cohort, the ?Mexican Health and Aging Study? (MHAS); this is a prospective national longitudinal study, which began in 2001, has aimed to evaluate the impact of age-related diseases among Mexican adults living in both urban and rural settings. Over a 20-years follow-up, MHAS has collected demographic and clinical data (including cognitive assessment) in 15,000 individuals of Mexican ancestry aged 50 and older. Specifically we propose to: 1) obtain saliva in all MHAS participants over age 60 years who will be interview in the fall of 2018 as part of the 5th MHAS follow-up wave, and perform a genome wide association study (GWAS) and admixture mapping for dementia using DNA extracted from ~10,000 participants. 2) validate clinical dementia classification with an extended cognitive Mex-Cog battery in a sub-sample of ~2500 MHAS participants 60 years of age or older to be consistent with NIA-Alzheimer Association recommendations; this will also be used to validate the clinical diagnoses used for the GWAS in the previous aim. 3) perform whole genome sequencing in the subsample of MHAS subjects with validated diagnosis.
. The proposed project aims to investigate risk and protective genetic loci for late-onset Alzheimer?s disease (LOAD) and related dementias among individuals of Mexican ancestry, a fast growing population in and outside U.S., characterized by high prevalence and incidence rate of LOAD, yet underrepresented in genetic studies. Leveraging a large deeply-phenotyped ongoing longitudinal study of aging in Mexico (MHAS), we propose to use saliva from ~10,000 individuals, age 60 or older, to first conduct a GWAS along admixture mapping. We will then perform extensive cognitive assessment in order to refine the clinical diagnosis, enrich the neuropsychological endophenotypes, and harmonized the clinical assessment for a subset of cases and controls that will then undergo whole genome sequencing, ultimately expanding the genetic diversity of cohorts with available genetic data for the scientific community investigating LOAD.
