Ang Zhou’s research while affiliated with University of Cambridge and other places

(1) Background: Observational studies associate vitamin D deficiency with muscle disorders, while some clinical trial data support a minor association between the vitamin and skeletal muscle performance in healthy subjects. Vitamin D receptor knockout mice studies confirm the relationship between vitamin D and skeletal muscle; however, causal inference in humans is challenging due to the ethical implications of including vitamin D-deficient participants in randomized trials. This study uses genetic methods to safely explore causal underpinnings for the relationship between 25(OH)D concentrations and skeletal muscle-related traits, including grip strength and combined arm skeletal muscle mass, and extends this analysis to suspected pathophysiology in the form of probable sarcopenia and sarcopenic obesity. (2) Methods: We conducted Mendelian randomization (MR) analyses in up to 307,281 participants from the UK Biobank of whom 25,414 had probable sarcopenia and 16,520 had sarcopenic obesity. In total, 35 variants were used to instrument 25(OH)D and MR analyses conducted using multiple approaches. (3) Results: Genetic analyses provided support for a relationship between genetically predicted higher 25(OH)D and skeletal muscle traits, with linear MR analyses for grip strength showing 0.11 kg (95% CI 0.04, 0.19) greater contractile force per 10 unit higher 25(OH)D, while there was a modest association with skeletal muscle mass (0.01 kg (95% CI 0.003, 0.02) greater muscle mass). For probable sarcopenia risk, there was suggestive evidence for lower odds by higher 25(OH)D (OR 0.96 (95% CI 0.92, 1.00)); however, this did not reflect an association with sarcopenic obesity (OR 0.97 (95% CI 0.93, 1.02)), but was seen in probable sarcopenia cases who were not obese (OR 0.92 (95% CI 0.86, 0.98)). Results were similar across multiple MR approaches. (4) Conclusions: Our study supports a causal relationship between 25(OH)D and skeletal muscle health. While evidence for benefit did not extend to lower risk of sarcopenic obesity, effective vitamin D-deficiency prevention strategies may help reduce age-related muscle weakness.

Objective: Depression frequently co-exists with chronic pain. Contemporary models suggest that these conditions share pathobiological mechanisms, prompting a need to investigate their temporal association. This investigation aimed to explore two distinctly different chronic pain conditions, and their cross-sectional and prospective associations with depression. Methods: Self-reported information was available on chronic widespread pain (CWP), chronic low back pain (CLBP) (45y), and depression symptoms (45y and 50y) from up to 9377 participants in the 1958 British cohort. Depression symptom outcomes were derived by 'Clinical Interview Schedule-Revised' (45y) and 'Short Form-36' (50y). Relationships between both chronic pain conditions and depression symptoms were investigated by fitting four separate logistic regression models, each with varying levels of covariate adjustment, including depression at baseline. Results: CWP was associated with depression symptoms cross-sectionally (OR = 2.04, 95% CI 1.65; 2.52, p <0.001, n = 7629), and prospectively when fully-adjusted for baseline, sociodemographic, lifestyle, and health covariates (OR = 1.45, 95% CI 1.17; 1.80, p = <0.001, n = 6275). CLBP was associated with depression symptoms prospectively (full model: OR = 1.28, 95% CI 1.01; 1.61, p = 0.04, n = 6288). In fully-adjusted models the prospective association of CWP with depression symptoms was more heavily influenced by our covariates than CLBP with depression. Conclusion: Pain may be a stressor from which depression can arise. Development of depression is differentially associated upon the type of pain experienced. Screening for depression symptoms amongst individuals with both chronic pain conditions is indicated and should be repeated over time.

Twin studies suggest a considerable genetic contribution to the variability in 25-hydroxyvitamin D (25(OH)D) concentrations, reporting heritability estimates up to 80% in some studies. While genome-wide association studies (GWAS) suggest notably lower rates (13–16%), they have identified many independent variants that associate with serum 25(OH)D concentrations. These discoveries have provided some novel insight into the metabolic pathway, and in this review we outline findings from GWAS studies to date with a particular focus on 35 variants which have provided replicating evidence for an association with 25(OH)D across independent large-scale analyses. Some of the 25(OH)D associating variants are linked directly to the vitamin D metabolic pathway, while others may reflect differences in storage capacity, lipid metabolism, and pathways reflecting skin properties. By constructing a genetic score including these 25(OH)D associated variants we show that genetic differences in 25(OH)D concentrations persist across the seasons, and the odds of having low concentrations (<50 nmol/L) are about halved for individuals in the highest 20% of vitamin D genetic score compared to the lowest quintile, an impact which may have notable influences on retaining adequate levels. We also discuss recent studies on personalized approaches to vitamin D supplementation and show how Mendelian randomization studies can help inform public health strategies to reduce adverse health impacts of vitamin D deficiency.

Background: Low vitamin D status is often associated with systemic low-grade inflammation as reflected by elevated C-reactive protein (CRP) levels. We investigated the causality and direction of the association between vitamin D status and CRP using linear and non-linear Mendelian randomization (MR) analyses. Methods: MR analyses were conducted using data from 294 970 unrelated participants of White-British ancestry from the UK Biobank. Serum 25-hydroxyvitamin D [25(OH)D] and CRP concentrations were instrumented using 35 and 46 genome-wide significant variants, respectively. Results: In non-linear MR analysis, genetically predicted serum 25(OH)D had an L-shaped association with serum CRP, where CRP levels decreased sharply with increasing 25(OH)D concentration for participants within the deficiency range (<25 nmol/L) and levelled off at ∼50 nmol/L of 25(OH)D (Pnon-linear = 1.49E-4). Analyses using several pleiotropy-robust methods provided consistent results in stratified MR analyses, confirming the inverse association between 25(OH)D and CRP in the deficiency range (P = 1.10E-05) but not with higher concentrations. Neither linear or non-linear MR analysis supported a causal effect of serum CRP level on 25(OH)D concentration (Plinear = 0.32 and Pnon-linear = 0.76). Conclusion: The observed association between 25(OH)D and CRP is likely to be caused by vitamin D deficiency. Correction of low vitamin D status may reduce chronic inflammation.

Aims Low vitamin D status is associated with a higher risk for cardiovascular diseases (CVDs). Although most existing linear Mendelian randomization (MR) studies reported a null effect of vitamin D on CVD risk, a non-linear effect cannot be excluded. Our aim was to apply the non-linear MR design to investigate the association of serum 25-hydroxyvitamin D [25(OH)D] concentration with CVD risk. Methods and results The non-linear MR analysis was conducted in the UK Biobank with 44 519 CVD cases and 251 269 controls. Blood pressure (BP) and cardiac-imaging-derived phenotypes were included as secondary outcomes. Serum 25(OH)D concentration was instrumented using 35 confirmed genome-wide significant variants. We also estimated the potential reduction in CVD incidence attributable to correction of low vitamin D status. There was a L-shaped association between genetically predicted serum 25(OH)D and CVD risk (Pnon-linear = 0.007), where CVD risk initially decreased steeply with increasing concentrations and levelled off at around 50 nmol/L. A similar association was seen for systolic (Pnon-linear = 0.03) and diastolic (Pnon-linear = 0.07) BP. No evidence of association was seen for cardiac-imaging phenotypes (P = 0.05 for all). Correction of serum 25(OH)D level below 50 nmol/L was predicted to result in a 4.4% reduction in CVD incidence (95% confidence interval: 1.8– 7.3%). Conclusion Vitamin D deficiency can increase the risk of CVD. Burden of CVD could be reduced by population-wide correction of low vitamin D status.

We present a simple and efficient hypothesis-free machine learning pipeline for risk factor discovery that accounts for non-linearity and interaction in large biomedical databases with minimal variable pre-processing. In this study, mortality models were built using gradient boosting decision trees (GBDT) and important predictors were identified using a Shapley values-based feature attribution method, SHAP values. Cox models controlled for false discovery rate were used for confounder adjustment, interpretability, and further validation. The pipeline was tested using information from 502,506 UK Biobank participants, aged 37–73 years at recruitment and followed over seven years for mortality registrations. From the 11,639 predictors included in GBDT, 193 potential risk factors had SHAP values ≥ 0.05, passed the correlation test, and were selected for further modelling. Of the total variable importance summed up, 60% was directly health related, and baseline characteristics, sociodemographics, and lifestyle factors each contributed about 10%. Cox models adjusted for baseline characteristics, showed evidence for an association with mortality for 166 out of the 193 predictors. These included mostly well-known risk factors (e.g., age, sex, ethnicity, education, material deprivation, smoking, physical activity, self-rated health, BMI, and many disease outcomes). For 19 predictors we saw evidence for an association in the unadjusted but not adjusted analyses, suggesting bias by confounding. Our GBDT-SHAP pipeline was able to identify relevant predictors ‘hidden’ within thousands of variables, providing an efficient and pragmatic solution for the first stage of hypothesis free risk factor identification.

Context Multiple observational studies have reported an inverse relationship between 25-hydroxyvitamin D concentrations (25(OH)D) and type 2 diabetes (T2D). However, the results of short- and long-term interventional trials concerning the relationship between 25(OH)D and T2D risk have been inconsistent. Objectives and methods To evaluate the causal role of reduced blood 25(OH)D in T2D, here we have performed a bidirectional Mendelian randomization study using 59,890 individuals (5,862 T2D cases and 54,028 controls) from European and Asian Indian ancestries. We used six known SNPs, including three T2D SNPs and three vitamin D pathway SNPs, as a genetic instrument to evaluate the causality and direction of the association between T2D and circulating 25(OH)D concentration. Results Results of the combined meta-analysis of eight participating studies showed that a composite score of three T2D SNPs would significantly increase T2D risk by an odds ratio (OR) of 1.24, p = 1.82 × 10 –32 ; Z score 11.86, which, however, had no significant association with 25(OH)D status (Beta -0.02nmol/L ± SE 0.01nmol/L; p = 0.83; Z score -0.21). Likewise, the genetically instrumented composite score of 25(OH)D lowering alleles significantly decreased 25(OH)D concentrations (-2.1nmol/L ± SE 0.1nmol/L, p = 7.92 × 10 –78 ; Z score -18.68) but was not associated with increased risk for T2D (OR 1.00, p = 0.12; Z score 1.54). However, using 25(OH)D synthesis SNP (DHCR7; rs12785878) as an individual genetic instrument, a per allele reduction of 25(OH)D concentration (-4.2nmol/L ± SE 0.3nmol/L) was predicted to increase T2D risk by 5%, p = 0.004; Z score 2.84. This effect, however, was not seen in other 25(OH)D SNPs (GC rs2282679, CYP2R1 rs12794714) when used as an individual instrument. Conclusion Our new data on this bidirectional Mendelian randomization study suggests that genetically instrumented T2D risk does not cause changes in 25(OH)D levels. However, genetically regulated 25(OH)D deficiency due to vitamin D synthesis gene (DHCR7) may influence the risk of T2D.

Background: Machine learning (ML) can harness information from large databases with complex structures. We present a simple and fast hypothesis-free machine learning pipeline for risk factor discovery that accounts for non-linearity and interaction in large biomedical databases with minimal variable pre-processing. Methods: Mortality models were built using gradient boosting decision trees (GBDT) and important predictors were identified using SHAP values. Cox models controlled for false discovery rate were used for interpretability and further validation. The pipeline was tested using information from 502,506 UK Biobank participants, aged 37 to 73 years at recruitment and followed over seven years for mortality registrations. Results: From the 11,639 predictors included in GBDT, 193 potential risk factors had SHAP values 0.05 or greater and were selected for further modelling. Of the total variable importance summed up, 60% was directly health related, and baseline characteristics, sociodemographics, and lifestyle factors each contributed about 10%. Cox models adjusted for baseline characteristics, showed evidence for an association with mortality for 166 out of the 193 predictors. For 19 predictors we saw evidence for an association in the unadjusted but not adjusted analyses, suggesting confounding by basic characteristics. Identified "important" predictors included traditional risk factors such as age, sex, ethnicity, education, material deprivation, smoking, physical activity, self-rated health, BMI, hypertension, cardio-vascular diseases, cancer diagnoses and type 2 diabetes, as confirmed by previous studies. Conclusion: Our approach provides a fast and pragmatic solution for hypothesis free risk factor identification.