Larry D. Adams (United States of America)
Univerity of Miami John P. Hussman Institute for Human GeneticsAuthor Of 1 Presentation
IN DEPTH GENOMIC CHARACTERIZATION OF CHROMOSOME 5Q35 ALZHEIMER DISEASE RISK LOCUS IN AFRICAN ANCESTRY POPULATION.
Abstract
Aims
To identify novel genes contributing to AD in the African ancestry population, we performed multipoint linkage analyses and identified a peak LOD score on chr5q35 (HLOD=3.20) across 51 families (160 affected and 318 unaffected) as part of the Research in African American Alzheimer Disease Initiative (REAAADI) and Late-Onset AD Family Study (LOAD).
Methods
Short-read WGS data were generated for all families contributing to the signal and analyzed to prioritize variants in the consensus regions based on segregation with disease among affecteds and rarity (MAF<0.01). All variants were annotated for putative function including protein changes for coding and evidence for regulatory activity (ENCODE, RoadMap Epigenome) and chromatin interactions (publicly available HiC and promoter capture C) for noncoding variants. To identify larger structural variants in the remaining linked families, we performed long-read WGS using Oxford Nanopore’s Prometheon.
Results
Segregation analysis using WGS data identified a 3’UTR and synonymous variant in INSYN2B/FAM196B as well as a promoter variant in WWC1/KIBRA (MAF<0.01) segregating with disease in the family with the highest LOD score contributing to the linkage peak. Interestingly, four other AA families contributing to the chr5 linkage signal harbor different within-family shared variants located in INSYN2B’s promoter or in enhancer regions with evidence for interaction with INSYN2B’s promoter. Combining functional validation and structural variant calling in this region will help us better understand the contribution of this gene to AD development.
Conclusions
Our analyses provide evidence for candidate gene INSYN2B, encoding an inhibitory synaptic factor active in oligodendrocytes and neurons, to play a role in AD genetics in the AA population. This AA population-specific finding shows the importance of diversifying population-level genetic data to better understand the genetic determinants of AD on a global scale.