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Early life events and environmental factors are associated with type 2 diabetes (T2D) development. We assessed the combined effect of birth weight andambient air pollutants, and effect of their interaction on T2D risk. Totally, 6,474 T2D incidents were recorded over an 8.7-year follow-up period. The adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs) were 1.31 (1.26, 1.36) for each kilogram decrease in birth weight, and 1.08 (1.05, 1.11) for each standard deviation increase in air pollution score (APS). Birth weight<3000 g amplified the T2D risk associated with high APS. A combination of the lowest birth weight (<2500 g) and the highest quintile of APS led to over two-fold increase in T2D risk (aHR: 2.17; 95% CI: 1.79–2.64). There was a significant additive interaction between them. In conclusion, ambient air pollutants increase the risk for T2D, particularly in populations with low birth weight. [ABSTRACT FROM AUTHOR]

Background: Depression and anxiety are two mental disorders that are often comorbid. However, the associations of long-term air pollution exposure with depression and anxiety remain inconclusive. Objective: We conducted a cross-sectional and prospective study to examine the associations of ambient exposure to particulate matter (PM) with a diameter of [less than or equal to]2.5 [micro]m (P[M.sub.2.5]), [less than or equal to]10 [micro]m (P[M.sub.10]), and 2.5-10 [micro]m (P[M.sub.coarse]), nitrogen oxides (N[O.sub.x]), and nitrogen dioxide (N[O.sub.2]) with the risk of depression and anxiety in the UK Biobank. Methods: This study included 398,241 participants from the UK Biobank, 128,456 of whom participated the 7-y online mental health survey. A total of 345,876 individuals were free of depression and anxiety at baseline; of those, 16,185 developed incident mental disorders during a median of 8.7 y of follow-up. Depression and anxiety were assessed using hospital admission records and mental health questionnaires. Associations of air pollution with prevalent and incident mental disorders were examined using logistic regression and Cox regression models, respectively. Results: Elevated levels of the five air pollutants were associated with higher odds of mental disorders at baseline. Levels of four pollutants but not P[M.sub.coarse] were also associated with higher odds and risks of mental disorders during follow-up; specifically, hazard ratios [HR, 95% confidence interval (CI)] of an interquartile range increase in P[M.sub.2.5], P[M.sub.10], N[O.sub.x], and N[O.sub.2] for incident mental disorders were 1.03 (95% CI: 1.01, 1.05), 1.06 (95% CI: 1.04, 1.08), 1.03 (95% CI: 1.01, 1.05), and 1.06 (95% CI: 1.04, 1.09), respectively. An air pollution index reflecting combined effects of pollutants also demonstrated a positive association with the risk of mental disorders. HR (95% CI) of incident mental disorders were 1.11 (95% CI: 1.05, 1.18) in the highest quintile group in comparison with the lowest quintile of the air pollution index. We further observed that the associations between air pollution and mental disorders differed by a genetic risk score based on single nucleotide polymorphisms previously associated with genetic susceptibility to mental disorders in the UK Biobank cohort. Discussion: To our knowledge, this research is one of the largest cohort studies that demonstrates an association between mental health disorders and exposure to long-term air pollution, which could be further enhanced by genetic predisposition. https://doi.org/10.1289/EHP10391, Introduction Depression and anxiety are common mental health disorders that often co-occur and can broadly impact the longevity by promoting aging-related conditions. (1,2) With the rapidly increasing prevalence of depression [...]

Aims: We aimed to examine the longitudinal associations of birth weight with plasma metabolites in adulthood, and further quantify the proportions of the links between birth weight and incident adult type 2 diabetes (T2D) that were mediated by plasma metabolites. Materials and Methods: A total of 62,033 participants with complete nuclear magnetic resonance metabolomics and birth weight data from the UK Biobank were included in this study. Linear regression was used to assess the associations between birth weight and metabolites. Cox regression was used to estimate hazard ratios for T2D associated with metabolites. We further performed mediation analyses to estimate the extent to which metabolites might mediate the association between birth weight and T2D risk. Results: Low birth weight was associated with the adverse metabolic responses across multiple metabolic pathways, including lipoprotein subclasses, amino acids, fatty acids (FA), and inflammation. Metabolites associated with higher birth weight tended to be associated with a lower risk of T2D (Pearson correlation coefficient: −0.85). A total of 62 metabolites showed statistically significant mediation effects in the protective association of higher birth weight and T2D risk, including large‐sized very low‐density lipoprotein particles and triglyceride concentrations as well as saturated, and monounsaturated FA and glycoprotein acetyls. Conclusions: We identified a range of metabolites that reflect the adult metabolic response to birth weight, some of which might lie on the pathway between birth weight and adult T2D risk. [ABSTRACT FROM AUTHOR]

Background To establish a polysocial risk score (PsRS) incorporating various social factors for capturing the dementia risk and investigate the benefits of favorable social conditions across different genetic backgrounds. Methods This prospective cohort study comprised 345 439 participants initially free of dementia from the UK Biobank. A total of 10 social factors were summed to create a PsRS. A polygenic risk score (PRS) was constructed based on genome-wide significant variants. Results During a median follow-up of 12.5 years, we documented 4 595 incident all-cause dementia events including 2 067 Alzheimer's disease (AD) events and 1 028 vascular dementia (VD) events. Each additional PsRS was associated with a 19% increased risk of all-cause dementia (hazard ratio [HR], 1.19; 95% confidence interval [CI], 1.17 to 1.21), a 13% increased risk of AD (1.13; 1.10 to 1.16), and a 24% increased risk of VD (1.24; 1.19 to 1.29). 29% (24% to 33%) of dementia cases, 22% (14% to 29%) of AD cases, and 39% (28% to 48%) of VD cases were associated with a disadvantageous social environment. In addition, among participants at a high genetic risk, the low social risk was linked to a lower incidence rate of all-cause dementia, AD, and VD compared to those who had a high social risk, with reductions of 67.8%, 64.5%, and 84.2%, respectively. Conclusions The PsRS could be effectively used in discriminating individuals at high risk of dementia. Around a quarter of dementia events could have a connection with a disadvantageous social environment, especially for those genetically susceptible to dementia. [ABSTRACT FROM AUTHOR]

Background Telomere length has been linked to various health outcomes. To comprehensively investigate the causal effects of telomere length throughout the human disease spectrum, we conducted a phenome-wide Mendelian randomization study (MR-PheWAS) and a systematic review of MR studies. Methods We conducted a PheWAS to screen for associations between telomere length and 1 035 phenotypes in the UK Biobank (n = 408 354). The exposure of interest was the genetic risk score (GRS) of telomere length. Observed associations passing multiple testing corrections were assessed for causality by 2-sample MR analysis. A systematic review of MR studies on telomere length was performed to harmonize the published evidence and complement our findings. Results Of the 1 035 phenotypes tested, PheWAS identified 29 and 78 associations of telomere length GRS at a Bonferroni- and false discovery rate-corrected threshold; 24 and 66 distinct health outcomes were causal in the following principal MR analysis. The replication MR using data from the FinnGen study provided evidence of causal effects of genetically instrumented telomere length on 28 out of 66 outcomes, including decreased risks of 5 diseases in respiratory diseases, digestive diseases, and myocardial infarction, and increased risks of 23 diseases, mainly comprised neoplasms, diseases of the genitourinary system, and essential hypertension. A systematic review of 53 MR studies found evidence to support 16 out of the 66 outcomes. Conclusions This large-scale MR-PheWAS identified a wide range of health outcomes that were possibly affected by telomere length, and suggested that susceptibility to telomere length may vary across disease categories. [ABSTRACT FROM AUTHOR]

Objective: Type 2 diabetes (T2D) is caused by both genetic and cardiometabolic risk factors. However, the magnitude of the genetic predisposition of T2D in the Chinese population remains largely unknown. Methods: This study included 93,488 participants from the China Kadoorie Biobank, and multiple polygenic risk scores (PRS) were calculated. A common cardiometabolic risk score (CRS) using smoking, alcohol consumption, physical activity, diet, obesity, blood pressure, and blood lipids was constructed to investigate the effects of cardiometabolic risk factors on T2D. Furthermore, an equation based on ideal PRS, CRS, and their interaction was established to explore the combined effects on T2D. Results: An ideally fitting PRS model (variance explained, R2 = 7.6%) was reached based on multiple PRS calculation methods. An additive interaction between PRS and CRS (coefficient = 28%, 95% CI: 0.20–0.36, p < 0.001) was found. The R2 of the T2D predictive model could increase to 8.3% when CRS and the interaction terms of PRS × CRS were considered. In the etiological composition of T2D, the ratio of genetic risk effect, cardiometabolic risk effect, and interaction between genetic and cardiometabolic factors was 67:16:17. Conclusions: This study identified an ideally fitting PRS model for identifying and predicting the risk of T2D suitable for the Chinese population. The quantified proportional structure of genetic risk factors, cardiometabolic risk factors, and their interaction was detected, which elucidated the critical effect of genetic factors. [ABSTRACT FROM AUTHOR]

Objectives: Depression and anxiety are two major categories of mental disorders that are highly prevalent in the general population. This study aims to explore the genetic modification effects of physical frailty on the morbidity of mental disorders.Methods: Using data from UK Biobank, we calculate genetic risk scores for depression, anxiety and mental disorders based on 37/44 single-nucleotide polymorphisms (SNPs) of Major Depressive Disorder (MDD) and 9/10 SNPs of anxiety. Frailty status was defined by a modified version of the frailty phenotype based on five individual components. Cox proportional hazard models were used to estimate the hazard ratio (HR) and 95% confidence interval (CI) of depression and anxiety risk among groups with different frailty status.Results: Of 267,755 participants in UK Biobank, 4,905 (2%) were considered frail, 98,907 (37%) pre-frail and 163,943 (61%) not frail. Compared with the non-frail group, the pre-frail group (HR = 1.53; [95% CI:1.47–1.61]), and frail group (HR = 2.75; [95% CI:2.46–3.07]) were significantly associated with increased risk of depression. Per 1-number increment in frailty component counts were significantly associated with increased risk of mental disorders. In each genetic risk score (GRS) strata, people with pre-frailty and frailty suffered higher risks of mental disorders than the non-frail group.Conclusion: Our results indicate that physical frailty plays an important role in the incidence of mental disorders, even after adjustments for covariates, and patients with genetic individual differences are also affected. Therefore, it is crucial that while diagnosing mental disorders, professionals pay closer attention to those patients who present symptoms of frailty. [ABSTRACT FROM AUTHOR]