INTRODUCTION: Analysis of sequence data in high-risk pedigrees is a powerful approach to detect rare predisposition variants.
METHODS: Rare, shared candidate predisposition variants were identified from exome sequencing 19 Alzheimer's disease (AD)-affected cousin pairs selected from high-risk pedigrees. Variants were further prioritized by risk association in various external datasets. Candidate variants emerging from these analyses were tested for co-segregation to additional affected relatives of the original sequenced pedigree members.
RESULTS: AD-affected high-risk cousin pairs contained 564 shared rare variants. Eleven variants spanning 10 genes were prioritized in external datasets: rs201665195 (ABCA7), and rs28933981 (TTR) were previously implicated in AD pathology; rs141402160 (NOTCH3) and rs140914494 (NOTCH3) were previously reported; rs200290640 (PIDD1) and rs199752248 (PIDD1) were present in more than one cousin pair; rs61729902 (SNAP91), rs140129800 (COX6A2, AC026471), and rs191804178 (MUC16) were not present in a longevity cohort; and rs148294193 (PELI3) and rs147599881 (FCHO1) approached significance from analysis of AD-related phenotypes. Three variants were validated via evidence of co-segregation to additional relatives (PELI3, ABCA7, and SNAP91).
DISCUSSION: These analyses support ABCA7 and TTR as AD risk genes, expand on previously reported NOTCH3 variant identification, and prioritize seven additional candidate variants.
Digital Object Identifier (DOI)
National Cancer Institute. Grant Number: P30 CA42014
NHLBI. Grant Number: RC2 HL103010
BrightFocus Foundation and the National Institute on Aging in the list of funders
Data from Alzheimer’s Disease Genetics Consortium (ADGC) were appropriately downloaded from dbGaP (accession: phs000372.v1.p1). We acknowledge the contributions of the members of the ADGC listed in Appendix: Alzheimer’s Disease Genetics Consortium Collaborators.
Teerlink, Craig C.; Miller, Justin B.; Vance, Elizabeth L.; Staley, Lyndsay A.; Stevens, Jeffrey; Tavana, Justina P.; Cloward, Matthew E.; Page, Madeline L.; Dayton, Louisa; Alzheimer's Disease Genetics Consortium; Cannon-Albright, Lisa A.; and Kauwe, John S. K., "Analysis of High-Risk Pedigrees Identifies 12 Candidate Variants for Alzheimer's Disease" (2021). Institute for Biomedical Informatics Faculty Publications. 14.