PT  - JOURNAL ARTICLE
AU  - Hanmin Guo
AU  - Lin Hou
AU  - Yu Shi
AU  - Sheng Chih Jin
AU  - Xue Zeng
AU  - Boyang Li
AU  - Richard P. Lifton
AU  - Martina Brueckner
AU  - Hongyu Zhao
AU  - Qiongshi Lu
TI  - Quantifying concordant genetic effects of <em>de novo</em> mutations on multiple disorders
AID  - 10.1101/2021.06.13.448234
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.06.13.448234
4099  - http://biorxiv.org/content/early/2021/06/14/2021.06.13.448234.short
4100  - http://biorxiv.org/content/early/2021/06/14/2021.06.13.448234.full
AB  - Exome sequencing on tens of thousands of parent-proband trios has identified numerous deleterious de novo mutations (DNMs) and implicated risk genes for many disorders. Recent studies have suggested shared genes and pathways are enriched for DNMs across multiple disorders. However, existing analytic strategies only focus on genes that reach statistical significance for multiple disorders and require large trio samples in each study. As a result, these methods are not able to characterize the full landscape of genetic sharing due to polygenicity and incomplete penetrance. In this work, we introduce EncoreDNM, a novel statistical framework to quantify shared genetic effects between two disorders characterized by concordant enrichment of DNMs in the exome. EncoreDNM makes use of exome-wide, summary-level DNM data, including genes that do not reach statistical significance in single-disorder analysis, to evaluate the overall and annotation-partitioned genetic sharing between two disorders. Applying EncoreDNM to DNM data of nine disorders, we identified abundant pairwise enrichment correlations, especially in genes intolerant to pathogenic mutations and genes highly expressed in fetal tissues. These results suggest that EncoreDNM improves current analytic approaches and may have broad applications in DNM studies.Competing Interest StatementThe authors have declared no competing interest.