Exome-Wide Rare Variant Analysis From the DiscovEHR Study Identifies Novel Candidate Predisposition Genes for Endometrial Cancer

Front Oncol. 2019 Jul 5;9:574. doi: 10.3389/fonc.2019.00574. eCollection 2019.


Endometrial cancer is the fourth most commonly diagnosed cancer in women. Family history is a known risk factor for endometrial cancer. The incidence of endometrial cancer in a first-degree relative elevates the relative risk to range between 1.3 and 2.8. It is unclear to what extent or what other novel germline variants are at play in endometrial cancer. We aim to address this question by utilizing whole exome sequencing as a means to identify novel, rare variant associations between exonic regions and endometrial cancer. The MyCode community health initiative is an excellent resource for this study with germline whole exome data for 60,000 patients available in the first phase, and further 30,000 patients independently sequenced in the second phase as part of DiscovEHR study. We conducted exome-wide rare variant association using 472 cases and 4,110 controls in 60,000 patients (discovery cohort); and 261 cases and 1,531 controls from 30,000 patients (replication cohort). After binning rare germline variants into genes, case-control association tests performed using Optimal Unified Approach for Rare-Variant Association, SKAT-O. Seven genes, including RBM12, NDUFB6, ATP6V1A, RECK, SLC35E1, RFX3 (Bonferroni-corrected P < 0.05) and ATP8A1 (suggestive P < 10-5), and one long non-coding RNA, DLGAP4-AS1 (Bonferroni-corrected P < 0.05), were associated with endometrial cancer. Notably, RECK, and ATP8A1 were replicated from the replication cohort (suggestive threshold P < 0.05). Additionally, a pathway-based rare variant analysis, using pathogenic and likely pathogenic variants, identified two significant pathways, pyrimidine metabolism and protein processing in the endoplasmic reticulum (Bonferroni-corrected P < 0.05). In conclusion, our results using the single-source electronic health records (EHR) linked to genomic data highlights candidate genes and pathways associated with endometrial cancer and indicates rare variants involvement in endometrial cancer predisposition, which could help in personalized prognosis and also further our understanding of its genetic etiology.

Keywords: DiscovEHR cohort; EHR; EHR-linked Biobank; cancer predisposition gene; endometrial cancer; rare variant.