COLLECTION OF MULTIPLEX FAMILIES WITH UNEXPLAINED EARLY-ONSET ALZHEIMER’S DISEASE FOR GENOMIC RESEARCH

Abstract

The ongoing genomic studies of Alzheimer's disease (AD) primarily focus on non-Hispanic White participants affected by late-onset AD or the study of early onset AD cases from families showing Mendelian inheritance associated with mutations in APP, PSEN1 and PSEN2. However, mutations in these three genes explain only ∼10% of EOAD cases, and among mutation carriers age at onset (AAO) is often highly variable. There are no concerted large-scale efforts to collect and study the remaining 90% of EOAD cases “unexplained” by known mutations in APP, PSEN1, and PSEN2. Our current sample exists of 85 multiplex Caribbean Hispanic and 22 non-Hispanic White families without known EOAD mutations and at least 2 EOAD cases per family recruited through the EFIGA and CAP efforts. EOAD was defined as age of onset (age at first symptom or diagnosis) before the age of 65. Our overall goal is to build up a larger resource of ”unexplained” EOAD families for genomic analyses by extension of the existing and recruitment of additional multiplex EOAD families. In the 85 Caribbean Hispanic families, 979 individuals were sampled, out of these 62.3% are women, 505 individuals are free of dementia and 200 have EOAD (mean AAO: 56.8±7.5); 101 of these cases have an onset < 60 years. 60.5% of the affecteds and 43.3% of the unaffecteds are carriers of an APOEe4 allele. In the 22 non-Hispanic White families, over 120 EOAD cases and controls were sampled. Of these 57.5% are women, 68 are free of dementia, and 52 have EOAD (mean AAO: 53.2±6.2). Of those, 42 have onset under age 60. Additional late-onset AD cases are available for these families. The slight difference in mean age of onset in EOAD cases between the two cohorts is likely explained by differences in ascertainment (ie. age at first symptom or diagnosis). Building up a larger resource of ”unexplained” EOAD families for genomic analyses will fill a critical gap in AD research, can help identify novel variants not detectable by the ongoing efforts and allows to examine the role of variants discovered in LOAD datasets in samples with earlier onset.