A novel strategy for clustering major depression individuals using whole-genome sequencing variant data
Chenglong Yu, Bernhard T Baune, Julio Licinio, Ma-Li Wong
SCIENTIFIC REPORTS | NATURE PUBLISHING GROUP | Published : 2017
Major depressive disorder (MDD) is highly prevalent, resulting in an exceedingly high disease burden. The identification of generic risk factors could lead to advance prevention and therapeutics. Current approaches examine genotyping data to identify specific variations between cases and controls. Compared to genotyping, whole-genome sequencing (WGS) allows for the detection of private mutations. In this proof-of-concept study, we establish a conceptually novel computational approach that clusters subjects based on the entirety of their WGS. Those clusters predicted MDD diagnosis. This strategy yielded encouraging results, showing that depressed Mexican-American participants were grouped clo..View full abstract
Awarded by National Health and Medical Research Council (Australia)
Awarded by NIH
Awarded by NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
The authors have been supported by grants APP1051931 and APP1070935 (M.L.W.), and APP1060524 (B.T.B) from the National Health and Medical Research Council (Australia), NIH grant GM61394 (J.L. and M.L.W.), and institutional funds from the South Australian Health and Medical Research Institute.