Enhanced polygenic risk score incorporating gene-environment interaction suggests the association of major depressive disorder with cardiac and lung function.

BACKGROUND: Depression has been linked to an increased risk of cardiovascular and respiratory diseases; however, its impact on cardiac and lung function remains unclear, especially when accounting for potential gene-environment interactions. METHODS: We developed a novel polygenic and gene-environment interaction risk score (PGIRS) integrating the major genetic effect and gene-environment interaction effect of depression-associated loci. The single nucleotide polymorphisms (SNPs) demonstrating major genetic effect or environmental interaction effect were obtained from genome-wide SNP association and SNP-environment interaction analyses of depression. We then calculated the depression PGIRS for non-depressed individuals, using smoking and alcohol consumption as environmental factors. Using linear regression analysis, we assessed the associations of PGIRS and conventional polygenic risk score (PRS) with lung function (N = 42 886) and cardiac function (N = 1791) in the subjects with or without exposing to smoking and alcohol drinking. RESULTS: We detected significant associations of depression PGIRS with cardiac and lung function, contrary to conventional depression PRS. Among smokers, forced vital capacity exhibited a negative association with PGIRS (ß = -0.037, FDR = 1.00 × 10-8), contrasting with no significant association with PRS (ß = -0.002, FDR = 0.943). In drinkers, we observed a positive association between cardiac index with PGIRS (ß = 0.088, FDR = 0.010), whereas no such association was found with PRS (ß = 0.040, FDR = 0.265). Notably, in individuals who both smoked and drank, forced expiratory volume in 1-second demonstrated a negative association with PGIRS (ß = -0.042, FDR = 6.30 × 10-9), but not with PRS (ß = -0.003, FDR = 0.857). CONCLUSIONS: Our findings underscore the profound impact of depression on cardiac and lung function, highlighting the enhanced efficacy of considering gene-environment interactions in PRS-based studies.

Association between white matter hyperintensity and anxiety/depression.

Although previous studies have explored the associations of white matter hyperintensity with psychiatric disorders, the sample size is small and the conclusions are inconsistent. The present study aimed to further systematically explore the association in a larger sample. All data were extracted from the UK Biobank. First, general linear regression models and logistic regression models were used to assess the association between white matter hyperintensity volume and anxiety/depression. White matter hyperintensity has been classified into periventricular white matter hyperintensity and deep white matter hyperintensity. Anxiety was determined by General Anxiety Disorder-7 score (n = 17,221) and self-reported anxiety (n = 15,333), depression was determined by Patient Health Questionnaire-9 score (n = 17,175), and self-reported depression (n = 14,519). Moreover, we employed Cox proportional hazard models to explore the association between white matter hyperintensity volume and anxiety/depression. The covariates included in fully adjusted model are age, gender, body mass index, Townsend deprivation index, healthy physical activity, cigarette consumption, alcohol consumption, educational attainment, diabetes, hypertension, and coronary heart disease. The results of the fully adjusted model showed that white matter hyperintensity volume was significantly associated with General Anxiety Disorder-7 score (periventricular white matter hyperintensity: ß = 0.152, deep white matter hyperintensity: ß = 0.094) and Patient Health Questionnaire-9 score (periventricular white matter hyperintensity: ß = 0.168). Logistic regression analysis results indicated that periventricular white matter hyperintensity volume (odds ratio = 1.153) was significantly associated with self-reported anxiety. After applying the Cox proportional hazard models, we found that larger white matter hyperintensity volume was associated with increased risk of depression (periventricular white matter hyperintensity: hazard ratio = 1.589, deep white matter hyperintensity: hazard ratio = 1.200), but not anxiety. In summary, our findings support a positive association between white matter hyperintensity volume and depression.

An atlas of causal association between micronutrients and osteoarthritis.

OBJECTIVE: This study examines the causal relationships between serum micronutrients and site-specific osteoarthritis (OA) using Mendelian Randomization (MR). METHODS: This study performed a two-sample MR analysis to explore causal links between 21 micronutrients and 11 OA outcomes. These outcomes encompass overall OA, seven site-specific manifestations, and three joint replacement subtypes. Sensitivity analyses using MR methods, such as the weighted median, MR-Egger, and MR-PRESSO, assessed potential horizontal pleiotropy and heterogeneity. Genome-wide association summary statistical data were utilized for both exposure and outcome data, including up to 826,690 participants with 177,517 OA cases. All data was sourced from Genome-wide association studies datasets from 2009 to 2023. RESULTS: In the analysis of associations between 21 micronutrients and 11 OA outcomes, 15 showed Bonferroni-corrected significance (P < 0.000216), without significant heterogeneity or horizontal pleiotropy. Key findings include strong links between gamma-tocopherol and spine OA (OR = 1.70), and folate with hand OA in finger joints (OR = 1.15). For joint replacements, calcium showed a notable association with a reduced likelihood of total knee replacement (TKR) (OR = 0.52) and total joint replacement (TJR) (OR = 0.56). Serum iron was significantly associated with an increased risk of total hip replacement (THR) (OR = 1.23), while folate indicated a protective effect (OR = 0.95). Various sex-specific associations were also uncovered. CONCLUSION: These findings underscore the critical role of micronutrients in osteoarthritis, providing valuable insights for preventive care and potential enhancement of treatment outcomes.

Causal relationship between gut microbiota and rheumatoid arthritis: a two-sample Mendelian randomisation study.

OBJECTIVES: To assess whether there is a bidirectional causal relationship between the composition of gut microbiota and rheumatoid arthritis (RA), and to identify specific pathogenic bacterial taxa via the Mendelian randomisation (MR) analysis. METHODS: We acquired single nucleotide polymorphisms (SNPs) associated with the composition of gut microbiota (n=18,340) and with RA (n=331,313) from publicly available genome-wide association studies (GWAS). The genome-wide threshold was 1 × 10-5 in the forward MR analysis and was 5 × 10-8 in the reverse MR analysis. Inverse variance weighted (IVW) was the main method to analyse causality, and MR results were verified by several sensitivity analyses including weighted median, MR Egger, and MR Pleiotropy Residual Sum and Outlier (PRESSO). RESULTS: The IVW method suggested that eight taxa were positively correlated with RA, including: MollicutesRF9 (pIVW <0.01), Alphaproteobacteria (pIVW <0.01), Betaproteobacteria (p IVW =0.04), Bacteroidaceae (pIVW <0.01), Adlercreutzia (pIVW <0.01), Bacteroides (pIVW <0.01), Butyricimonas (p IVW =0.03) and Holdemanella (pIVW =0.03). Six bacterial taxa were negatively correlated with RA, including Desulfovibrionales (pIVW = 0.01), Methanobacteriales (pIVW <0.01), Methanobacteria (PIVW <0.01), Desulfovibrionaceae (pIVW <0.01), Methanobacteriaceae (pIVW <0.01) and Butyrivibrio (pIVW =0.02). Heterogeneity (p>0.05) and pleiotropy (p>0.05) analysis confirmed the robustness of the MR results. CONCLUSIONS: We identified some specific bacterial taxa that were causally associated with the risk of RA, providing new insights into prevention and diagnosis of RA.

Assessing the joint effects of mitochondrial genes and physical activity on the psychiatric phenotype of subjective well-being based on the UK Biobank data.

Subjective well-being (SWB) is an important measure for mental health status. Previous research has shown that physical activity can affect an individual's well-being, yet the underlying molecular mechanism remains to be clarified. In this study, we aim to evaluate the potential interactions between mitochondrial genes and physical activity (PA) as well as their combined effects on individual well-being. SWB phenotype data in UK Biobank were enrolled for this study including nine aspects such as work/job satisfaction, health satisfaction, family relationship satisfaction, friendships satisfaction, financial situation satisfaction, ever depressed for a whole week, general happiness, general happiness with own health and belief that own life is meaningful. We made analysis for each aspects separately. Firstly, mitochondria-wide association studies (MiWAS) was conducted to assess the association of mitochondrial Single Nucleotide Polymorphisms SNP with each aspect of SWB. Then an interaction analysis of mitochondrial DNA (mtDNA) mutation and PA was performed to evaluate their joint effect on SWB status. Meanwhile, these two analysis were made for female and male group separately as well as the total samples, all under the control of possible confounding factors including gender, age, Townsend Deprivation Index (TDI), education, alcohol consumption, smoking habits, and 10 principal components. MiWAS analysis identified 45 mtSNPs associated with 9 phenotypes of SWB. For example, m.15218A > G on MT-CYB in the health satisfaction phenotype of the total subjects. Gender-specific analyses found 30 mtSNPs in females and 58 in males, involving 13 mtGenes. In mtDNA-PA interaction analysis, we also identified 10 significant mtDNA-PA interaction sets for SWB. For instance, m.13020 T > C (MT-ND5) was associated with the SWB financial situation satisfaction phenotype in all subjects (P = 0.00577). In addition, MiWAS analysis identified 12 mtGene variants associated with SWB, as MT-ND1 and MT-ND2. However, in mtDNA-PA interactions we detected 7 mtDNA affecting psychiatric disorders occurring, as in the friendships satisfaction phenotype (m.3394 T > C on MT-ND1). Our study results suggest an implication of the interaction between mitochondrial function and physical activity in the risk of psychiatric disorder development.

Micronutrient-Associated Single Nucleotide Polymorphism and Mental Health: A Mendelian Randomization Study.

PURPOSE: Previous studies have demonstrated the link between micronutrients and mental health. However, it remains uncertain whether this connection is causal. We aim to investigate the potential causal effects of micronutrients on mental health based on linkage disequilibrium score (LDSC) regression and Mendelian randomization (MR) analysis. METHODS: Utilizing publicly available genome-wide association study (GWAS) summary datasets, we performed LDSC and MR analysis to identify candidate micronutrients with potential causal effects on mental health. Single nucleotide polymorphisms (SNPs) significantly linked with candidate micronutrients with a genome-wide significance level (p < 5 × 10-8) were selected as instrumental variables (IVs). To estimate the causal effect of candidate micronutrients on mental health, we employed inverse variance weighted (IVW) regression. Additionally, two sensitivity analyses, MR-Egger and weighted median, were performed to validate our results. RESULTS: We found evidence supporting significant causal associations between micronutrients and mental health. LDSC detected several candidate micronutrients, including serum iron (genetic correlation = -0.134, p = 0.032) and vitamin C (genetic correlation = -0.335, p < 0.001) for attention-deficit/hyperactivity disorder (ADHD), iron-binding capacity (genetic correlation = 0.210, p = 0.037) for Alzheimer's disease (AD), and vitamin B12 (genetic correlation = -0.178, p = 0.044) for major depressive disorder (MDD). Further MR analysis suggested a potential causal relationship between vitamin B12 and MDD (b = -0.139, p = 0.009). There was no significant heterogeneity or pleiotropy, indicating the validity of the findings. CONCLUSION: In this study, we identified underlying causal relationships between micronutrients and mental health. Notably, more research is necessary to clarify the underlying biological mechanisms by which micronutrients affect mental health.

Dietary diversity score and the acceleration of biological aging: a population-based study of 88,039 participants.

OBJECTIVES: Our study aimed to investigate the association of dietary diversity score (DDS), as reflected by five dietary categories, with biological age acceleration. DESIGN: A cross-sectional study. SETTING AND PARTICIPANTS: This study included 88,039 individuals from the UK Biobank. METHODS: Biological age (BA) was assessed using Klemerae-Doubal (KDM) and PhenoAge methods. The difference between BA and chronological age represents the age acceleration (AgeAccel), termed as "KDMAccel" and "PhenoAgeAccel". AgeAccel > 0 indicates faster aging. Generalized linear regression models were performed to assess the associations of DDS with AgeAccel. Similar analyses were performed for the five dietary categories. RESULTS: After adjusting for multiple variables, DDS was inversely associated with KDMAccel (ßHigh vs Low= -0.403, 95%CI: -0.492 to -0.314, P < 0.001) and PhenoAgeAccel (ßHigh vs Low= -0.545, 95%CI: -0.641 to -0.450, P < 0.001). Each 1-point increment in the DDS was associated with a 4.4% lower risk of KDMAccel and a 5.6% lower risk of PhenoAgeAccel. The restricted cubic spline plots demonstrated a non-linear dose-response association between DDS and the risk of AgeAccel. The consumption of grains (ßKDMAccel = -0.252, ßPhenoAgeAccel = -0.197), vegetables (ßKDMAccel = -0.044, ßPhenoAgeAccel = -0.077) and fruits (ßKDMAccel = -0.179, ßPhenoAgeAccel = -0.219) was inversely associated with the two AgeAccel, while meat and protein alternatives (ßKDMAccel = 0.091, ßPhenoAgeAccel = 0.054) had a positive association (All P < 0.001). Stratified analysis revealed stronger accelerated aging effects in males, smokers, and drinkers. A strengthening trend in the association between DDS and AgeAccel as TDI quartiles increased was noted. CONCLUSIONS: This study suggested that food consumption plays a role in aging process, and adherence to a higher diversity dietary is associated with the slowing down of the aging process.

Insight into the Causal Relationship between Gut Microbiota and Back Pain: A Two Sample Bidirectional Mendelian Randomization Study.

Observational studies have shown that alterations in gut microbiota composition are associated with low back pain. However, it remains unclear whether the association is causal. To reveal the causal association between gut microbiota and low back pain, a two-sample bidirectional Mendelian randomization (MR) analysis is performed. The inverse variance weighted regression (IVW) is performed as the principal MR analysis. MR-Egger and Weighted Median is further conducted as complementary analysis to validate the robustness of the results. Finally, a reverse MR analysis is performed to evaluate the possibility of reverse causation. The inverse variance weighted (IVW) method suggests that Peptostreptococcaceae (odds ratio [OR] 1.056, 95% confidence interval [CI] [1.015-1.098], P IVW = 0.010), and Lactobacillaceae (OR 1.070, 95% CI [1.026-1.115], P IVW = 0.003) are positively associated with back pain. The Ruminococcaceae (OR 0.923, 95% CI [0.849-0.997], P IVW = 0.033), Butyricicoccus (OR 0.920, 95% CI [0.868 - 0.972], P IVW = 0.002), and Lachnospiraceae (OR 0.948, 95% CI [0.903-0.994], P IVW = 0.022) are negatively associated with back pain. In this study, underlying causal relationships are identified among gut microbiota and low back pain. Notably, further research is needed on the biological mechanisms by which gut microbiota influences low back pain.

Evaluating the interaction between 3'aQTL and alcohol consumption/smoking on anxiety and depression: 3'aQTL-by-environment interaction study in UK Biobank cohort.

BACKGROUND: Smoking and alcohol consumption were associated with the development of depression and anxiety. 3'UTR APA quantitative trait loci (3'aQTLs) have been associated with multiple health states and conditions. Our aim is to evaluate the interactive effects of 3'aQTLs-alcohol consumption/tobacco smoking on the risk of anxiety and depression. METHODS: The 3'aQTL data of 13 brain regions were extracted from the large-scale 3'aQTL atlas. The phenotype data (frequency of cigarette smoking and alcohol drinking, anxiety score, self-reported anxiety, depression score and self-reported depression) of 90,399-103,011 adults aged 40-69 years living in the UK and contributing to the UK Biobank during 2006-2010, were obtained from the UK Biobank cohort. The frequency of cigarette smoking and alcohol drinking of each subject were defined by the amount of smoking and alcohol drinking of self-reported, respectively. The continuous alcohol consumption/smoking terms were further categorized in tertiles. 3'aQTL-by-environmental interaction analysis was then performed to evaluate the associations of gene-smoking/alcohol consumption interactions with anxiety and depression using generalized linear model (GLM) of PLINK 2.0 with an additive mode of inheritance. Furthermore, GLM was also used to explore the relationship between alcohol consumption/smoking with hazard of anxiety/depression stratified by allele for the significant genotyped SNPs that modified the alcohol consumption/smoking-anxiety/depression association. RESULTS: The interaction analysis identified several candidate 3'aQTLs-alcohol consumption interactions, such as rs7602638 located in PPP3R1 (ß = 0.08, P = 6.50 × 10-6) for anxiety score; rs10925518 located in RYR2 (OR = 0.95, P = 3.06 × 10-5) for self-reported depression. Interestingly, we also observed that the interactions between TMOD1 (ß = 0.18, P = 3.30 × 10-8 for anxiety score; ß = 0.17, P = 1.42 × 10-6 for depression score), ZNF407 (ß = 0.17, P = 2.11 × 10-6 for anxiety score; ß = 0.15, P = 4.26 × 10-5 for depression score) and alcohol consumption was not only associated with anxiety, but related to depression. Besides, we found that relationship between alcohol consumption and hazard of anxiety/depression was significantly different for different SNPs genotypes, such as rs34505550 in TMOD1 (AA: OR = 1.03, P = 1.79 × 10-6; AG: OR = 1.00, P = 0.94; GG: OR = 1.00, P = 0.21) for self-reported anxiety. LIMITATIONS: The identified 3'aQTLs-alcohol consumption/smoking interactions were associated with depression and anxiety, and its potential biological mechanisms need to be further revealed. CONCLUSIONS: Our study identified important interactions between candidate 3'aQTL and alcohol consumption/smoking on depression and anxiety, and found that the 3'aQTL may modify the associations between consumption/smoking with depression and anxiety. These findings may help to further explore the pathogenesis of depression and anxiety.