Abstract
Background Ovarian cancer has few known risk factors, hampering identification of high-risk women. Thus, we assessed the association of pre-diagnostic plasma metabolites (N=420) with risk.
Methods We included 252 cases (176 serous/poorly differentiated; 34 non-serous [endometrioid/clear cell]) diagnosed 3-23 years after blood collection and 252 matched controls from the Nurses’ Health Studies. Multivariable logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) comparing the 90th-10thpercentile in metabolite levels, using permutation tests to account for testing multiple correlated hypotheses. Weighted gene co-expression network analysis (WGCNA) modules (n=10) summarized by the first principal component and metabolite set enrichment analysis (MSEA; n=23) were also evaluated.
Results Pseudouridine had the strongest statistical association with ovarian cancer risk overall (OR=2.56, 95%CI=1.48-4.45; p=0.001/adjusted-p=0.15). C36:2 phosphatidylcholine (PC) plasmalogen had the strongest statistical association with lower risk (OR=0.11, 95%CI=0.03-0.35; p<0.001/adjusted-p=0.06) and pseudouridine with higher risk (OR=9.84, 95%CI=2.89-37.82; p<0.001/adjusted-p=0.07) of non-serous tumors. No metabolites were associated with risk after multiple testing correction. Seven WGCNA modules and 15 classes were associated with risk at FDR≤0.20. Triacylglycerols (TAGs) characterized 3 of 7 significant WGCNA modules, were an enriched class, and showed heterogeneity by tumor aggressiveness (case-only heterogeneity-p<10−4). TAG association with risk overall and serous tumors differed by acly carbon content and saturation.
Conclusion Pseudouridine may be a novel risk factor for ovarian cancer. TAGs may also be important, particularly for rapidly fatal tumors, with associations differing by structural features. Validation in independent prospective studies and complementary experimental work to understand biological mechanisms is needed.
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