GWAS of fingerprint patterns.

J. BOWSER; K. NEISWANGER; C. SANCHEZ; J.T. HECHT; I.M. ORIOLI; M.L. MARAZITA; J. CHERNUS; S. RAJAGOPALAN; J. CARLSON; A. CZEIZEL; J. SALAMANCA; S. WEINBERG; E. FEINGOLD; J. ROOSENBOOM; E.J. LESLIE; T. SOEJIMA; E.E. CASTILLA; F.A. POLETTA

Orlando

Congreso; American Society of Human Genetics 67 Annual Meeting; 2017

American Society of Human Genetics

Human fingerprint patterns are a highly heritable phenotype known to be associated with important diseases such as schizophrenia and heart disease. Understanding fingerprint genetics may help dissect the underlying biology of such diseases, as well as providing insight into more general developmental processes.Fingerprints can be conceived of as a high-dimensional phenotype with various measures on each finger. Beyond classification into common pattern types (arches, loops, and whorls), more refined phenotypes such as ridge counts have been developed. Using the correlation structure of pattern types across study subjects? ten fingers, we constructed several multi-finger phenotypes and performed genome-wide association scans on them.The subjects are a set of approximately 1400 individuals recruited from the Pittsburgh Orofacial Cleft Study?a larger study of the genetics of cleft lip and palate. After imputation, genotypes were available for seven million SNPs. Since subjects include cleft cases, their cleft-free relatives, and control families from several populations, a mixed model was used to account for population structure and relatedness in performing the GWAS.Results showed differing levels of genetic control for different fingers and patterns. Signals included replication of genes previously reported for other fingerprint phenotypes as well as several newly-nominated loci.This work was supported by NIH DE016148.