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Biomedical subjects

A Heather Eliassen

Publications and source records attributed to A Heather Eliassen.

2 recordsLinked to original sources

Multi-population GWAS meta-analysis identifies bladder cancer susceptibility loci and highlights genetic regulation of smoking-related risk.

Bladder cancer is the ninth most common cancer worldwide, caused by genetic and environmental risk factors. Here, we report the findings of a multi-population meta-analysis of genome-wide association studies, including 32,470 individuals with and 1,753,462 without bladder cancer. We identify 70 independent risk loci, of which 43 are novel. Using a 70-marker polygenic risk score (HR = 1.63 per standard deviation), we increase the area under the curve from 0.71 (baseline risk model) to 0.75. Integrative analyses reveal the enrichment of the associated variants within accessible chromatin regions, and of the prioritized genes within pathways for xenobiotic metabolism and smoking behavior. Specifically, we show that the 15q25.1 variant rs71581744-ACCCC/A co-localizes with tissue-specific CHRNA3 expression, modulates mRNA stability, and associates with risk of muscle-invasive bladder cancer among current smokers. Together, these findings substantially expand the known genetic architecture of bladder cancer risk and highlight the germline regulation of smoking behavior as a mechanism driving bladder cancer susceptibility.

Humans

Cross-omics risk scores of inflammation markers are associated with all-cause mortality: The Canadian Longitudinal Study on Aging.

Inflammation is a critical component of chronic diseases, aging progression, and lifespan. Omics signatures may characterize inflammation status beyond blood biomarkers. We leveraged genetics (polygenic risk score [PRS]), metabolomics (metabolomic risk score [MRS]), and epigenetics (epigenetic risk score [ERS]) to build multi-omics-multi-marker risk scores for inflammation status represented by the level of circulating C-reactive protein (CRP), interleukin 6 (IL-6), and tumor necrosis factor alpha (TNF-α). We found that multi-omics risk scores generally outperformed single-omics risk scores in predicting all-cause mortality in the Canadian Longitudinal Study on Aging. Compared with circulating inflammation biomarkers, some multi-omics risk scores had a higher hazard ratio (HR) for all-cause mortality when including both score and circulating IL-6 in the same model (1-SD IL-6 MRS-ERS: HR = 2.20 [1.55-3.13] vs. 1-SD circulating IL-6 HR = 0.94 [0.67,1.32]. 1-SD IL-6 PRS-MRS: HR = 1.47 [1.35,1.59] vs. 1-SD circulating IL-6 HR = 1.33 [1.18, 1.51]. 1-SD PRS-MRS-ERS: HR = 1.95 [1.40, 2.70] vs. 1-SD circulating IL-6: HR = 0.99 [0.71, 1.39]). In the Nurses' Health Study (NHS), NHS II, and Health Professional Follow-up Study with available omics, 1 SD of IL-6 PRS and 1-SD IL-6 PRS-MRS had HR = 1.12 [1.00,1.26] and HR = 1.13 [1.01,1.26] among individuals >65 years old without mutual adjustment of the score and circulating IL-6. Our study demonstrates that some multi-omics scores for inflammation markers may characterize important inflammation burden for an individual beyond those represented by blood biomarkers and improve our prediction capability for the aging process and lifespan.

Humans