The functional impact of rare variation across the regulatory cascade

Author:

Li TaiboORCID,Ferraro Nicole,Strober Benjamin J.ORCID,Aguet FrancoisORCID,Kasela SilvaORCID,Arvanitis MariosORCID,Ni BohanORCID,van de Wiel LaurensORCID,Hershberg ElliotORCID,Ardlie Kristin,Arking Dan E.ORCID,Beer Rebecca L.,Brody Jennifer,Blackwell Thomas W,Clish ClaryORCID,Gabriel Stacey,Gerszten RobertORCID,Guo Xiuqing,Gupta Namrata,Johnson W. CraigORCID,Lappalainen TuuliORCID,Lin Henry J.ORCID,Liu Yongmei,Nickerson Deborah A.,Papanicolaou George,Pritchard Jonathan K.ORCID,Qasba Pankaj,Shojaie AliORCID,Smith Josh,Sotoodehnia Nona,Taylor Kent D.ORCID,Tracy Russell P.ORCID,Van Den Berg DavidORCID,Wheeler Matthew,Rich Stephen S.ORCID,Rotter Jerome I.ORCID,Battle Alexis,Montgomery Stephen B.ORCID

Abstract

AbstractEach human genome has tens of thousands of rare genetic variants; however, identifying impactful rare variants remains a major challenge. We demonstrate how use of personal multi-omics can enable identification of impactful rare variants by using the Multi-Ethnic Study of Atherosclerosis (MESA) which included several hundred individuals with whole genome sequencing, transcriptomes, methylomes, and proteomes collected across two time points, ten years apart. We evaluated each multi-omic phenotype’s ability to separately and jointly inform functional rare variation. By combining expression and protein data, we observed rare stop variants 62x and rare frameshift variants 216x as frequently as controls, compared to 13x to 27x for expression or protein effects alone. We developed a Bayesian hierarchical model to prioritize specific rare variants underlying multi-omic signals across the regulatory cascade. With this approach, we identified rare variants that exhibited large effect sizes on multiple complex traits including height, schizophrenia, and Alzheimer’s disease.

Publisher

Cold Spring Harbor Laboratory

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