0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessIntroduction: Various forms of psychological distress, such as depression and anxiety, have been identified as risk factors for diabetes. However, there is limited evidence from population-based, epidemiologic studies investigating potential molecular mechanisms (e.g., metabolic dysregulation) linking psychological distress and diabetes development. Hypothesis: We assessed the hypothesis that a metabolite score reflecting psychological distress-related metabolic dysregulation is predictive of future diabetes risk in women. Methods: We conducted a nested case-control study of plasma metabolomics and diabetes risk in the Nurses’ Health Study, including 728 women (mean age: 55.2 years) with incident diabetes and 728 controls matched on age, race, fasting status, and time/date of blood collection. Blood samples were collected between 1989-1990 and incident diabetes was diagnosed between 1990-2012. Based on the metabolomic signature of chronic psychological distress we previously identified and validated in women (including coefficient estimates for individual metabolite associations), we calculated a weighted plasma metabolomic score of psychological distress comprised of 19 metabolites (e.g., serotonin, threonine, hippurate, biliverdin, glutamine, etc.). We used conditional logistic regression accounting for matching factors and other diabetes risk factors to estimate odds ratios (OR) and 95% CI for diabetes risk across quintiles of the distress-related metabolite score. Results: After adjusting for sociodemographic factors, family history of diabetes and health behaviors, the OR (95% CI) for diabetes risk across quintiles of the distress-related metabolite score was 1.00 (reference) for Q1, 1.11 (0.77, 1.61) for Q2, 1.64 (1.14, 2.35) for Q3, 2.07 (1.42, 3.01) for Q4, and 2.35 (1.60, 3.47) for Q5. Each 1-unit increase in the score was associated with 26% higher diabetes risk (95% CI: 1.15, 1.38; p-trend<0.0001). This association was moderately attenuated after additional adjustment for baseline body mass index (OR per 1-unit increase: 1.13; 95% CI: 1.02, 1.25; p-trend=0.02). Further, psychological distress assessed via self-report (defined as presence of depression or anxiety) was associated with modestly increased diabetes risk in the same sample (OR: 1.25; 95% CI: 1.01, 1.55). The metabolite score mediated 20.7% (95% CI: 5.1, 56.1) of the association between psychological distress and diabetes risk (p=0.0065). Conclusions: Our results suggest that the distress-related metabolite score was significantly associated with diabetes risk in women and partly mediated the association between self-reported psychological distress and diabetes risk. These findings provide supporting evidence that metabolic dysregulation may be an important mechanism underlying the observed association between psychological distress and diabetes risk.
Tianyi Huang, Yiwen Zhu, Katherine H. Shutta, Raji Balasubramanian, Oana A. Zeleznik, Kathryn M. Rexrode, Clary B. Clish, Qi Sun, Frank B Hu, Laura D. Kubzansky, Susan E. Hankinson (2023). Abstract MP58: A Plasma Metabolite Score Related to Psychological Distress and Future Diabetes Risk: A Nested Case-Control Study in US Women. , 147(Suppl_1), DOI: https://doi.org/10.1161/circ.147.suppl_1.mp58.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2023
Authors
11
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1161/circ.147.suppl_1.mp58
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access