Biomedical subjects

Tianyi Huang

Publications and source records attributed to Tianyi Huang.

3 recordsLinked to original sources

PubMed2026

Obesity Polygenic Risk and Healthy Lifestyle Interactions on Weight Trajectories in Women and Men.

BACKGROUND: Genetics and environmental factors contribute to obesity risk, but the extent to which healthy behaviors can offset genetic susceptibility remains unclear. We examined the interaction between obesity polygenic risk and a composite healthy lifestyle score on body mass index (BMI) trajectories in women and men. METHODS: We analyzed 13 780 women from the Nurses' Health Study and 8242 men from the Health Professionals Follow-Up Study, all of European ancestry and free of major chronic disease at baseline. The lifestyle score comprised American Heart Association Essential 8 components (nonsmoking, physical activity, healthy eating, adequate sleep) plus moderate alcohol intake, modeled as a time-varying variable. A genome-wide polygenic score for BMI was derived from genome-wide association study. Adjusted linear mixed-effects models estimated associations and interactions on biennial BMI measures over up to 26 years. RESULTS: Each SD increase in the polygenic score was associated with 1.80 kg/m2 (95% CI, 1.72-1.87) and 1.12 kg/m2 (95% CI, 1.06-1.19) higher BMI in women and men, respectively. Significant interactions between the polygenic score and healthy lifestyle score (both P<0.05) showed a dose-response attenuation of the genetic effects with healthier lifestyles. Comparing the healthiest with the least healthy lifestyle groups, genetic effects on BMI were 35% lower in women and 28% lower in men. In sensitivity analyses, higher diet quality and physical activity consistently attenuated genetic associations in both cohorts, whereas current smoking showed similar effects in women only. CONCLUSIONS: Adherence to a healthier lifestyle attenuated the association between obesity polygenic risk and BMI in a dose-response manner.

Humans↗

PubMed2025

Sleep-disordered breathing subtypes and future diet quality in the Multi-Ethnic Study of Atherosclerosis.

OBJECTIVES: Sleep-disordered breathing (SDB) and diet quality impact cardiometabolic disease, but few studies have examined if SDB influences diet quality. This study estimated the association between SDB subtypes (with and without sleepiness) and future diet quality in the Multi-Ethnic Study of Atherosclerosis. METHODS: Probable SDB was characterized by self-reported physician-diagnosed sleep apnea (PDSA) or habitual snoring and subtyped by presence or absence of sleepiness. A food frequency questionnaire measured diet 1.6 years before, and 7.8 years after SDB assessment. Diet quality was measured with the Alternate Healthy Eating Index-2010 (AHEI). Mean differences in AHEI at follow-up by SDB subtypes were estimated with multivariable linear regression adjusting for baseline AHEI, demographic, and lifestyle factors. RESULTS: Among 3294 participants (mean age 62 years, 51% women), 29.5% had SDB. When grouped by sleepiness, 20.6% had SDB without, and 8.9% had SDB with, sleepiness. Adjusting for baseline diet and potential confounders, those with SDB had lower follow-up AHEI scores compared with unaffected individuals (mean AHEI difference [95% CI]: -1.02 [-1.69, -0.35]). Upon stratifying by sleepiness, both groups had lower AHEI scores at follow-up compared with unaffected individuals, and the difference was greater for those with sleepiness (mean score difference [95% CI]: -0.8 [-1.56, -0.04], without sleepiness; -1.52 [-2.59, -0.45], with sleepiness). The difference between those with and without sleepiness was not statistically significant. CONCLUSIONS: In a multi-ethnic cohort, SDB was associated with lower diet quality after 7.8 years and this association was larger among participants with SDB with sleepiness.

Humans↗

PubMed2025

Steroid hormone biosynthesis and dietary related metabolites associated with excessive daytime sleepiness.

BACKGROUND: Excessive daytime sleepiness (EDS) is a complex sleep problem that affects approximately 33% of the United States population. Although EDS usually occurs in conjunction with insufficient sleep and other sleep and circadian disorders, recent studies have shown unique genetic markers and metabolic pathways underlying EDS. Here, we aimed to further elucidate the biological profile of EDS using large-scale single- and pathway-level metabolomics analyses. METHODS: Metabolomics data were available for 877 metabolites in 6071 individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). EDS was assessed using the Epworth Sleepiness Scale (ESS) questionnaire. We performed linear regression for each metabolite on the continuous ESS score, adjusting for demographic, lifestyle, and physiological confounders, and in sex specific groups. Subsequently, gaussian graphical modelling was performed coupled with pathway and enrichment analyses to generate a holistic interactive network of the metabolomic profile of EDS associations. FINDINGS: We identified seven metabolites belonging to steroids, sphingomyelin, and long-chain fatty acids sub-pathways in the primary model associated with EDS, and an additional three metabolites in the male-specific analysis. INTERPRETATION: Our findings indicate that an EDS metabolomic profile is characterised by endogenous and dietary metabolites within the steroid hormone biosynthesis pathway, with some pathways that differ by sex. These pathways may be useful for understanding the causes or consequences of EDS and related sleep disorders. FUNDING: Details regarding funding supporting this work and all studies involved are provided in the acknowledgements section.

Humans↗