Background: Racial differences in metabolomic profiles may reflect underlying differences in social determinants of health by self-reported race and may be related to racial disparities in coronary heart disease (CHD) among women in the United States. However, the magnitude of differences in metabolomic profiles between Black and White women in the United States has not been well-described. It also remains unknown whether such differences are related to differences in CHD risk. Methods: Plasma metabolomic profiles were analyzed using liquid chromatography-tandem mass spectrometry in the WHI-OS (Women's Health Initiative-Observational Study; 138 Black and 696 White women), WHI-HT trials (WHI-Hormone Therapy; 156 Black and 1138 White women), MESA (Multi-Ethnic Study of Atherosclerosis; 114 Black and 219 White women), JHS (Jackson Heart Study; 1465 Black women with 107 incident CHD cases), and NHS (Nurses' Health Study; 2506 White women with 136 incident CHD cases). First, linear regression models were used to estimate associations between self-reported race and 472 metabolites in WHI-OS (discovery); findings were replicated in WHI-HT and validated in MESA. Second, we used elastic net regression to construct a racial difference metabolomic pattern (RDMP) representing differences in the metabolomic patterns between Black and White women in the WHI-OS; the RDMP was validated in the WHI-HT and MESA. Third, using conditional logistic regressions in the WHI (717 CHD cases and 719 matched controls), we examined associations of metabolites with large differences in levels by race and the RDMP with risk of CHD, and the results were replicated in Black women from the JHS and White women from the NHS. Results: Of the 472 tested metabolites, levels of 259 (54.9%) metabolites, mostly lipid metabolites and amino acids, significantly differed between Black and White women in both WHI-OS and WHI-HT after adjusting for baseline characteristics, socioeconomic status, lifestyle factors, baseline health conditions, and medication use (false discovery rate <0.05); similar trends were observed in MESA. The RDMP, composed of 152 metabolites, was identified in the WHI-OS and showed significantly different distributions between Black and White women in the WHI-HT and MESA. Higher RDMP quartiles were associated with an increased risk of incident CHD (odds ratio=1.51 [0.97-2.37] for the highest quartile comparing to the lowest; Ptrend=0.02), independent of self-reported race and known CHD risk factors. In race-stratified analyses, the RDMP-CHD associations were more pronounced in White women. Similar patterns were observed in Black women from the JHS and White women from the NHS. Conclusions: Metabolomic profiles significantly and substantially differ between Black and White women and may be associated with CHD risk and racial disparities in US women.

Background: Prior studies relating proteomics markers to incident AF screened for limited numbers of proteins. Methods and Results: We performed proteomics assays among participants from the Framingham Heart Study Offspring attending their fifth examination. Plasma protein levels (n=1373) were measured by the SOMAscan proteomic profiling platform. We used robust inference for the Cox proportional hazards model to relate each protein level with incident AF. In addition, we examined the association between AF-related genetic loci and levels of proteins associated with AF. Our study included 1885 participants (mean age 55+/-10 years, 54% women) who had proteomic profiles measured. A total of 349 participants developed AF during follow-up (mean follow-up 18.3 years). We observed that 8 proteins were significantly associated with incident AF after adjusting for age, sex, technical covariates, and correction for multiple testing ( P < 0.05/1373=3.6x10(-5)). After additional adjustments for clinical factors associated with AF, ADAMTS13 and N-terminal pro-B-type natriuretic peptide remained significantly associated with the risk of incident AF (hazard ratio, 0.78; 95% CI, 0.70-0.88; and 1.44; 95% CI, 1.22-1.70, respectively; P < 3.6x10(-5) for both). None of the 8 proteins were encoded by genes at AF-related genetic loci previously identified by genome-wide association studies. Conclusions: We identified 8 proteins associated with risk of incident AF after adjustment for age and sex; 2 proteins were associated with AF after adjustment for AF risk factors. Future studies are needed to replicate our findings, identify whether the markers are mechanistically related to AF development, and whether they are clinically useful for identification of future AF risk.