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Massive genetic compendiums such as the UK Biobank have become an invaluable resource for identifying genetic variants that are associated with complex diseases. Due to the difficulties of massive data collection, a common practice of these compendiums is to collect interval‐censored data. One challenge in analyzing such data is the lack of methodology available for genetic association studies with interval‐censored data. Genetic effects are difficult to detect because of their rare and weak nature, and often the time‐to‐event outcomes are transformed to binary phenotypes for access to more powerful signal detection approaches. However transforming the data to binary outcomes can result in loss of valuable information. To alleviate such challenges, this work develops methodology to associate genetic variant sets with multiple interval‐censored outcomes. Testing sets of variants such as genes or pathways is a common approach in genetic association settings to lower the multiple testing burden, aggregate small effects, and improve interpretations of results. Instead of performing inference with only a single outcome, utilizing multiple outcomes can increase statistical power by aggregating information across multiple correlated phenotypes. Simulations show that the proposed strategy can offer significant power gains over a single outcome approach. We apply the proposed test to the investigation that motivated this study, a search for the genes that perturb risks of bone fractures and falls in the UK Biobank. [ABSTRACT FROM AUTHOR]

Background: Chronic kidney disease (CKD) is a complex disorder that has become a high prevalence global health problem, with diabetes being its predominant pathophysiologic driver. Autosomal genetic variation only explains some of the predisposition to kidney disease. Variations in the mitochondrial genome (mtDNA) and nuclear-encoded mitochondrial genes (NEMG) are implicated in susceptibility to kidney disease and CKD progression, but they have not been thoroughly explored. Our aim was to investigate the association of variation in both mtDNA and NEMG with CKD (and related traits), with a particular focus on diabetes. Methods: We used the UK Biobank (UKB) and UK-ROI, an independent collection of individuals with type 1 diabetes mellitus (T1DM) patients. Results: Fourteen mitochondrial variants were associated with estimated glomerular filtration rate (eGFR) in UKB. Mitochondrial variants and haplogroups U, H and J were associated with eGFR and serum variables. Mitochondrial haplogroup H was associated with all the serum variables regardless of the presence of diabetes. Mitochondrial haplogroup X was associated with end-stage kidney disease (ESKD) in UKB. We confirmed the influence of several known NEMG on kidney disease and function and found novel associations for SLC39A13, CFL1, ACP2 or ATP5G1 with serum variables and kidney damage, and for SLC4A1, NUP210 and MYH14 with ESKD. The G allele of TBC1D32-rs113987180 was associated with higher risk of ESKD in patients with diabetes (OR:9.879; CI95%:4.440–21.980; P = 2.0E-08). In UK-ROI, AGXT2-rs71615838 and SURF1-rs183853102 were associated with diabetic nephropathies, and TFB1M-rs869120 with eGFR. Conclusions: We identified novel variants both in mtDNA and NEMG which may explain some of the missing heritability for CKD and kidney phenotypes. We confirmed the role of MT-ND5 and mitochondrial haplogroup H on renal disease (serum variables), and identified the MT-ND5-rs41535848G variant, along with mitochondrial haplogroup X, associated with higher risk of ESKD. Despite most of the associations were independent of diabetes, we also showed potential roles for NEMG in T1DM. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Whether genetic susceptibility to disease and dietary cholesterol (DC) absorption contribute to inconsistent associations of DC consumption with diabetes and cardiovascular disease (CVD) remains unclear. RESEARCH DESIGN AND METHODS: DC consumption was assessed by repeated 24-h dietary recalls in the UK Biobank. A polygenetic risk score (PRS) for DC absorption was constructed using genetic variants in the Niemann-Pick C1-Like 1 and ATP Binding Cassettes G5 and G8 genes. PRSs for diabetes, coronary artery disease, and stroke were also created. The associations of DC consumption with incident diabetes (n = 96,826) and CVD (n = 94,536) in the overall sample and by PRS subgroups were evaluated using adjusted Cox models. RESULTS: Each additional 300 mg/day of DC consumption was associated with incident diabetes (hazard ratio [HR], 1.17 [95% CI, 1.07–1.27]) and CVD (HR, 1.09 [95% CI, 1.03–1.17]), but further adjusting for BMI nullified these associations (HR for diabetes, 0.99 [95% CI, 0.90–1.09]; HR for CVD, 1.04 [95% CI, 0.98–1.12]). Genetic susceptibility to the diseases did not modify these associations (P for interaction ≥0.06). The DC-CVD association appeared to be stronger in people with greater genetic susceptibility to cholesterol absorption assessed by the non-high-density lipoprotein cholesterol-related PRS (P for interaction = 0.04), but the stratum-level association estimates were not statistically significant. CONCLUSIONS: DC consumption was not associated with incident diabetes and CVD, after adjusting for BMI, in the overall sample and in subgroups stratified by genetic predisposition to cholesterol absorption and the diseases. Nevertheless, whether genetic predisposition to cholesterol absorption modifies the DC-CVD association requires further investigation. [ABSTRACT FROM AUTHOR]

The incidence of early-onset colorectal cancer (EOCRC; diagnosed <50 years of age) is rising globally; however, the causes underlying this trend are largely unknown. CRC has strong genetic and environmental determinants, yet common genetic variants and causal modifiable risk factors underlying EOCRC are unknown. We conducted the first EOCRC-specific genome-wide association study (GWAS) and Mendelian randomization (MR) analyses to explore germline genetic and causal modifiable risk factors associated with EOCRC. We conducted a GWAS meta-analysis of 6176 EOCRC cases and 65 829 controls from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO), the Colorectal Transdisciplinary Study (CORECT), the Colon Cancer Family Registry (CCFR), and the UK Biobank. We then used the EOCRC GWAS to investigate 28 modifiable risk factors using two-sample MR. We found two novel risk loci for EOCRC at 1p34.1 and 4p15.33, which were not previously associated with CRC risk. We identified a deleterious coding variant (rs36053993, G396D) at polyposis-associated DNA repair gene MUTYH (odds ratio 1.80, 95% confidence interval 1.47-2.22) but show that most of the common genetic susceptibility was from noncoding signals enriched in epigenetic markers present in gastrointestinal tract cells. We identified new EOCRC-susceptibility genes, and in addition to pathways such as transforming growth factor (TGF) β, suppressor of Mothers Against Decapentaplegic (SMAD), bone morphogenetic protein (BMP) and phosphatidylinositol kinase (PI3K) signaling, our study highlights a role for insulin signaling and immune/infection-related pathways in EOCRC. In our MR analyses, we found novel evidence of probable causal associations for higher levels of body size and metabolic factors—such as body fat percentage, waist circumference, waist-to-hip ratio, basal metabolic rate, and fasting insulin—higher alcohol drinking, and lower education attainment with increased EOCRC risk. Our novel findings indicate inherited susceptibility to EOCRC and suggest modifiable lifestyle and metabolic targets that could also be used to risk-stratify individuals for personalized screening strategies or other interventions. • We conducted GWAS and MR analyses to identify the causes of EOCRC. • We identified two novel risk loci specific to EOCRC and confirmed the involvement of several known CRC risk variants in EOCRC. • We also identified new EOCRC risk genes and highlighted the prominent role of pathways such as insulin signaling in EOCRC. • We identified probable causal associations for body size, fasting insulin, alcohol intake, and educational level with EOCRC. [ABSTRACT FROM AUTHOR]

In recent years, the utility of polygenic risk scores (PRS) in forecasting disease susceptibility from genome-wide association studies (GWAS) results has been widely recognised. Yet, these models face limitations due to overfitting and the potential overestimation of effect sizes in correlated variants. To surmount these obstacles, we devised the Stacked Neural Network Polygenic Risk Score (SNPRS). This novel approach synthesises outputs from multiple neural network models, each calibrated using genetic variants chosen based on diverse p-value thresholds. By doing so, SNPRS captures a broader array of genetic variants, enabling a more nuanced interpretation of the combined effects of these variants. We assessed the efficacy of SNPRS using the UK Biobank data, focusing on the genetic risks associated with breast and prostate cancers, as well as quantitative traits like height and BMI. We also extended our analysis to the Korea Genome and Epidemiology Study (KoGES) dataset. Impressively, our results indicate that SNPRS surpasses traditional PRS models and an isolated deep neural network in terms of accuracy, highlighting its promise in refining the efficacy and relevance of PRS in genetic studies. [ABSTRACT FROM AUTHOR]

Background: Inflammatory bowel disease (IBD) and Parkinson's disease (PD) are chronic disorders that have been suggested to share common pathophysiological processes. LRRK2 has been implicated as playing a role in both diseases. Exploring the genetic basis of the IBD-PD comorbidity through studying high-impact rare genetic variants can facilitate the identification of the novel shared genetic factors underlying this comorbidity. Methods: We analyzed whole exomes from the BioMe BioBank and UK Biobank, and whole genomes from a cohort of 67 European patients diagnosed with both IBD and PD to examine the effects of LRRK2 missense variants on IBD, PD and their co-occurrence (IBD-PD). We performed optimized sequence kernel association test (SKAT-O) and network-based heterogeneity clustering (NHC) analyses using high-impact rare variants in the IBD-PD cohort to identify novel candidate genes, which we further prioritized by biological relatedness approaches. We conducted phenome-wide association studies (PheWAS) employing BioMe BioBank and UK Biobank whole exomes to estimate the genetic relevance of the 14 prioritized genes to IBD-PD. Results: The analysis of LRRK2 missense variants revealed significant associations of the G2019S and N2081D variants with IBD-PD in addition to several other variants as potential contributors to increased or decreased IBD-PD risk. SKAT-O identified two significant genes, LRRK2 and IL10RA, and NHC identified 6 significant gene clusters that are biologically relevant to IBD-PD. We observed prominent overlaps between the enriched pathways in the known IBD, PD, and candidate IBD-PD gene sets. Additionally, we detected significantly enriched pathways unique to the IBD-PD, including MAPK signaling, LPS/IL-1 mediated inhibition of RXR function, and NAD signaling. Fourteen final candidate IBD-PD genes were prioritized by biological relatedness methods. The biological importance scores estimated by protein–protein interaction networks and pathway and ontology enrichment analyses indicated the involvement of genes related to immunity, inflammation, and autophagy in IBD-PD. Additionally, PheWAS provided support for the associations of candidate genes with IBD and PD. Conclusions: Our study confirms and uncovers new LRRK2 associations in IBD-PD. The identification of novel inflammation and autophagy-related genes supports and expands previous findings related to IBD-PD pathogenesis, and underscores the significance of therapeutic interventions for reducing systemic inflammation. [ABSTRACT FROM AUTHOR]

Existing imaging genetics studies have been mostly limited in scope by using imaging-derived phenotypes defined by human experts. Here, leveraging new breakthroughs in self-supervised deep representation learning, we propose a new approach, image-based genome-wide association study (iGWAS), for identifying genetic factors associated with phenotypes discovered from medical images using contrastive learning. Using retinal fundus photos, our model extracts a 128-dimensional vector representing features of the retina as phenotypes. After training the model on 40,000 images from the EyePACS dataset, we generated phenotypes from 130,329 images of 65,629 British White participants in the UK Biobank. We conducted GWAS on these phenotypes and identified 14 loci with genome-wide significance (p<5×10−8 and intersection of hits from left and right eyes). We also did GWAS on the retina color, the average color of the center region of the retinal fundus photos. The GWAS of retina colors identified 34 loci, 7 are overlapping with GWAS of raw image phenotype. Our results establish the feasibility of this new framework of genomic study based on self-supervised phenotyping of medical images. Author summary: Imaging genetics is a research field focused on understanding how genetic variations influence observable traits or diseases that can be visualized through medical imaging. Previous studies in imaging genetics have mostly relied on traits identified by human experts. In this study, we used a self-supervised contrastive learning algorithm that automatically identifies features in fundus images that are unique to each individual yet consistent between their left and right eyes. These features are represented as a set of 128 numbers that can quantitatively describe the characteristics of each individual's fundus images without human labeling bias. We then conducted genome wide association studies (GWAS) to explore the associations between these features and genetic variations using paired fundus images and genetic data from the UK Biobank. Our findings indicate that these features are linked to genetic signals associated with eye measurements, eye diseases, pigmentation, and vessel development. Additionally, we found that GWAS of this set of features identified new genetic signals not detected in GWAS only using retina color. These results establish the feasibility of this self-supervised phenotyping approach for imaging genetics studies. [ABSTRACT FROM AUTHOR]

Background: In this study we used Mendelian randomization (MR) to investigate the potential causal association of lipoprotein (a) [Lp(a)] levels with pulse wave velocity (PWV). Methods: Genetic variants associated with Lp(a) were retrieved from the UK Biobank GWAS (N = 290,497). A non‐ overlapping GWAS based on a European cohort (N = 7,000) was used to obtain genetic associations with PWV (outcome) and utilized two different measures for the same trait, brachial–ankle (baPWV) and carotid–femoral (cfPWV) PWV. We applied a two‐sample MR using the inverse variance weighting method (IVW) and a series of sensitivity analyses for 170 SNPs that were selected as instrumental variables (IVs). Results: Our analyses do not support a causal association between Lp(a) and PWV for neither measurement [βiwv(baPWV) = −.0005, p =.8 and βiwv(cfPWV) = −.006, p =.16]. The above findings were consistent across sensitivity analyses including weighted median, mode‐based estimation, MR‐Egger regression and MR‐PRESSO. Conclusion: We did not find evidence indicating that Lp(a) is causally associated with PWV, the gold standard marker of arterial stiffness. [ABSTRACT FROM AUTHOR]

Hypertension is a leading risk factor for cardiovascular disease and is modulated by genetic variants. This study aimed to assess the effect of obesity genetic liability and physical activity on hypertension among European and African ancestry individuals within the UK Biobank (UKB). Participants were 230 115 individuals of European ancestry and 3239 individuals of African ancestry from UKB. Genetic liability for obesity were estimated using previously published data including genetic variants and effect sizes for body mass index (BMI), waist‐hip ratio (WHR) and waist circumference (WC) using Plink software. The outcome was defined as stage 2 hypertension (systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥90 mmHg, or the use of anti‐hypertensive medications). The association between obesity genetic liability and the outcome was assessed across categories of self‐reported physical activity using logistic regression. Among European ancestry participants, there was up to a 1.2 greater odds of hypertension in individuals with high genetic liability and low physical activity compared to individuals with low genetic liability and high physical activity (p < 0.001). In individuals engaging in low levels of physical activity compared with moderate/high physical activity, the effect of BMI genetic liability on hypertension was greater (pinteraction = 0.04). There was no evidence of an association between obesity genetic liability and hypertension in individuals of African ancestry in the whole sample or within separate physical activity groups (p > 0.05). This study suggests that higher physical activity levels are associated with lower odds of stage 2 hypertension among European ancestry individuals who carry high genetic liability for obesity. This cannot be inferred for individuals of African ancestry, possibly due to the low African ancestry sample size within the UKB. [ABSTRACT FROM AUTHOR]

Tomicus piniperda is a common pest of pine trees responsible for significant economic damage. Although the impact of T. piniperda on forestry is likely to increase in the future due to climate change, little is known about its dispersal within the United Kingdom (UK) or between continental Europe and the UK.This study addressed these knowledge gaps using mitochondrial and microsatellite DNA markers.Mitochondrial DNA revealed high levels of genetic diversity as previously reported for this species across Europe. Nuclear DNA diversity revealed two geographically incoherent groups (Scotland, Wales, Belgium and the Netherlands vs. England and Switzerland). These genetic patterns likely reflect a combination of historical gene flow, anthropogenic introduction and restricted contemporary gene flow between the UK and Europe.Significant structure was found among UK samples suggesting T. piniperda might not disperse extensively between pine stands. This differs from widespread gene flow across continental Europe and may be due to the low percentage of land covered by forests in the UK in addition to the high fragmentation of its forest cover.Genetic variation was higher among the Scottish samples compared to those from more southern clines, suggesting the potential proximity of Scotland to a Pleistocene glacial refuge for T. piniperda. [ABSTRACT FROM AUTHOR]

Variability in quantitative traits has clinical, ecological, and evolutionary significance. Most genetic variants identified for complex quantitative traits have only a detectable effect on the mean of trait. We have developed the mean-variance test (MVtest) to simultaneously model the mean and log-variance of a quantitative trait as functions of genotypes and covariates by using estimating equations. The advantages of MVtest include the facts that it can detect effect modification, that multiple testing can follow conventional thresholds, that it is robust to non-normal outcomes, and that association statistics can be meta-analyzed. In simulations, we show control of type I error of MVtest over several alternatives. We identified 51 and 37 previously unreported associations for effects on blood-pressure variance and mean, respectively, in the UK Biobank. Transcriptome-wide association studies revealed 633 significant unique gene associations with blood-pressure mean variance. MVtest is broadly applicable to studies of complex quantitative traits and provides an important opportunity to detect novel loci. We developed MVtest to simultaneously model the mean and log variance of quantitative traits as functions of genotypes and covariates by using estimating equations. MVtest can detect effect modification, and association statistics can be meta-analyzed. MVtest is applicable to studies of complex quantitative traits and provides an opportunity to detect novel vQTLs. [ABSTRACT FROM AUTHOR]

Background: The liking for sweet taste is a powerful driver for consuming added sugars, and therefore, understanding how sweet liking is formed is a critical step in devising strategies to lower added sugars consumption. However, current research on the influence of genetic and environmental factors on sweet liking is mostly based on research conducted with individuals of European ancestry. Whether these results can be generalized to people of other ancestry groups warrants investigation. Methods: We will determine the differences in allele frequencies in sweet-related genetic variants and their effects on sweet liking in 426 adults of either African or East Asian ancestry, who have the highest and lowest average added sugars intake, respectively, among ancestry groups in the U.S. We will collect information on participants' sweet-liking phenotype, added sugars intake (sweetness exposure), anthropometric measures, place-of-birth, and for immigrants, duration of time living in the U.S. and age when immigrated. Ancestry-specific polygenic scores of sweet liking will be computed based on the effect sizes of the sweet-related genetic variants on the sweet-liking phenotype for each ancestry group. The predictive validity of the polygenic scores will be tested using individuals of African and East Asian ancestry from the UK Biobank. We will also compare sweet liking between U.S.-born individuals and immigrants within each ancestry group to test whether differences in environmental sweetness exposure during childhood affect sweet liking in adulthood. Discussion: Expanding genetic research on taste to individuals from ancestry groups traditionally underrepresented in such research is consistent with equity goals in sensory and nutrition science. Findings from this study will help in the development of a more personalized nutrition approach for diverse populations. Trial registration: This protocol has been preregistered with the Center for Open Science (https://doi.org/10.17605/OSF.IO/WPR9E). [ABSTRACT FROM AUTHOR]

Background: Genetic variants that severely alter protein products (e.g. nonsense, frameshift) are often associated with disease. For some genes, these predicted loss-of-function variants (pLoFs) are observed throughout the gene, whilst in others, they occur only at specific locations. We hypothesised that, for genes linked with monogenic diseases that display incomplete penetrance, pLoF variants present in apparently unaffected individuals may be limited to regions where pLoFs are tolerated. To test this, we investigated whether pLoF location could explain instances of incomplete penetrance of variants expected to be pathogenic for Mendelian conditions. Methods: We used exome sequence data in 454,773 individuals in the UK Biobank (UKB) to investigate the locations of pLoFs in a population cohort. We counted numbers of unique pLoF, missense, and synonymous variants in UKB in each quintile of the coding sequence (CDS) of all protein-coding genes and clustered the variants using Gaussian mixture models. We limited the analyses to genes with ≥ 5 variants of each type (16,473 genes). We compared the locations of pLoFs in UKB with all theoretically possible pLoFs in a transcript, and pathogenic pLoFs from ClinVar, and performed simulations to estimate the false-positive rate of non-uniformly distributed variants. Results: For most genes, all variant classes fell into clusters representing broadly uniform variant distributions, but genes in which haploinsufficiency causes developmental disorders were less likely to have uniform pLoF distribution than other genes (P < 2.2 × 10−6). We identified a number of genes, including ARID1B and GATA6, where pLoF variants in the first quarter of the CDS were rescued by the presence of an alternative translation start site and should not be reported as pathogenic. For other genes, such as ODC1, pLoFs were located approximately uniformly across the gene, but pathogenic pLoFs were clustered only at the end, consistent with a gain-of-function disease mechanism. Conclusions: Our results suggest the potential benefits of localised constraint metrics and that the location of pLoF variants should be considered when interpreting variants. [ABSTRACT FROM AUTHOR]

Genetic effects can be sex-specific, particularly for traits such as testosterone, a sex hormone. While sex-stratified analysis provides easily interpretable sex-specific effect size estimates, the presence of sex-differences in SNP effect implies a SNP×sex interaction. This suggests the usage of the often overlooked joint test, testing for an SNP's main and SNP×sex interaction effects simultaneously. Notably, even without individual-level data, the joint test statistic can be derived from sex-stratified summary statistics through an omnibus meta-analysis. Utilizing the available sex-stratified summary statistics of the UK Biobank, we performed such omnibus meta-analyses for 290 quantitative traits. Results revealed that this approach is robust to genetic effect heterogeneity and can outperform the traditional sex-stratified or sex-combined main effect-only tests. Therefore, we advocate using the omnibus meta-analysis that captures both the main and interaction effects. Subsequent sex-stratified analysis should be conducted for sex-specific effect size estimation and interpretation. Author summary: When genetic variant effects on complex traits differ between females and males, sex-stratified analysis is often applied, offering easy-to-interpret, sex-specific effect estimates. However, from the viewpoint of maximizing the power and robustness of association testing, sex-stratified analysis may not be the best analytical strategy. As sex-specific genetic effects imply an SNP×sex interaction effect, jointly testing SNP main effects and SNP×sex interactions could be more powerful than sex-stratified analysis or the standard main-effect testing. Furthermore, this joint test is applicable even when individual-level data are not available, by leveraging sex-specific summary statistics through an omnibus meta-analysis. In this study, we performed such an omnibus meta-analysis using the UK Biobank data. Across 290 phenotypes, our results showed that this method is generally comparable to traditional analyses and excels by identifying new loci for traits such as testosterone, which standard tests do not detect. Our findings suggest that leveraging genetic heterogeneity enhances the detection of genetic associations, with significant implications for the future analysis of diverse data. [ABSTRACT FROM AUTHOR]

The "missing" heritability of complex traits may be partly explained by genetic variants interacting with other genes or environments that are difficult to specify, observe, and detect. We propose a new kernel-based method called Latent Interaction Testing (LIT) to screen for genetic interactions that leverages pleiotropy from multiple related traits without requiring the interacting variable to be specified or observed. Using simulated data, we demonstrate that LIT increases power to detect latent genetic interactions compared to univariate methods. We then apply LIT to obesity-related traits in the UK Biobank and detect variants with interactive effects near known obesity-related genes (URL: https://CRAN.R-project.org/package=lit). [ABSTRACT FROM AUTHOR]

It remains unknown whether adiposity subtypes are differentially associated with colorectal cancer (CRC). To move beyond single-trait anthropometric indicators, we derived four multi-trait body shape phenotypes reflecting adiposity subtypes from principal components analysis on body mass index, height, weight, waist-to-hip ratio, and waist and hip circumference. A generally obese (PC1) and a tall, centrally obese (PC3) body shape were both positively associated with CRC risk in observational analyses in 329,828 UK Biobank participants (3728 cases). In genome-wide association studies in 460,198 UK Biobank participants, we identified 3414 genetic variants across four body shapes and Mendelian randomization analyses confirmed positive associations of PC1 and PC3 with CRC risk (52,775 cases/45,940 controls from GECCO/CORECT/CCFR). Brain tissue-specific genetic instruments, mapped to PC1 through enrichment analysis, were responsible for the relationship between PC1 and CRC, while the relationship between PC3 and CRC was predominantly driven by adipose tissue-specific genetic instruments. This study suggests distinct putative causal pathways between adiposity subtypes and CRC. [ABSTRACT FROM AUTHOR]

The solute carrier organic anion transporter family member 1B1 (SLCO1B1) encodes the organic anion-transporting polypeptide 1B1 (OATP1B1 protein) that transports statins to liver cells. Common genetic variants in SLCO1B1, such as *5, cause altered systemic exposure to statins and therefore affect statin outcomes, with potential pharmacogenetic applications; yet, evidence is inconclusive. We studied common and rare SLCO1B1 variants in up to 64,000 patients from UK Biobank prescribed simvastatin or atorvastatin, combining whole-exome sequencing data with up to 25-year routine clinical records. We studied 51 predicted gain/loss-of-function variants affecting OATP1B1. Both SLCO1B1*5 alone and the SLCO1B1*15 haplotype increased LDL during treatment (beta*5 = 0.08 mmol/L, p = 6 × 10−8; beta*15 = 0.03 mmol/L, p = 3 × 10−4), as did the likelihood of discontinuing statin prescriptions (hazard ratio*5 = 1.12, p = 0.04; HR*15 = 1.05, p = 0.04). SLCO1B1*15 and SLCO1B1*20 increased the risk of General Practice (GP)-diagnosed muscle symptoms (HR*15 = 1.22, p = 0.003; HR*20 = 1.25, p = 0.01). We estimated that genotype-guided prescribing could potentially prevent 18% and 10% of GP-diagnosed muscle symptoms experienced by statin patients, with *15 and *20, respectively. The remaining common variants were not individually significant. Rare variants in SLCO1B1 increased LDL in statin users by up to 1.05 mmol/L, but replication is needed. We conclude that genotype-guided treatment could reduce GP-diagnosed muscle symptoms in statin patients; incorporating further SLCO1B1 variants into clinical prediction scores could improve LDL control and decrease adverse events, including discontinuation. [ABSTRACT FROM AUTHOR]

Machine learning (ML) methods are increasingly becoming crucial in genome-wide association studies for identifying key genetic variants or SNPs that statistical methods might overlook. Statistical methods predominantly identify SNPs with notable effect sizes by conducting association tests on individual genetic variants, one at a time, to determine their relationship with the target phenotype. These genetic variants are then used to create polygenic risk scores (PRSs), estimating an individual's genetic risk for complex diseases like cancer or cardiovascular disorders. Unlike traditional methods, ML algorithms can identify groups of low-risk genetic variants that improve prediction accuracy when combined in a mathematical model. However, the application of ML strategies requires addressing the feature selection challenge to prevent overfitting. Moreover, ensuring the ML model depends on a concise set of genomic variants enhances its clinical applicability, where testing is feasible for only a limited number of SNPs. In this study, we introduce a robust pipeline that applies ML algorithms in combination with feature selection (ML-FS algorithms), aimed at identifying the most significant genomic variants associated with the coronary artery disease (CAD) phenotype. The proposed computational approach was tested on individuals from the UK Biobank, differentiating between CAD and non-CAD individuals within this extensive cohort, and benchmarked against standard PRS-based methodologies like LDpred2 and Lassosum. Our strategy incorporates cross-validation to ensure a more robust evaluation of genomic variant-based prediction models. This method is commonly applied in machine learning strategies but has often been neglected in previous studies assessing the predictive performance of polygenic risk scores. Our results demonstrate that the ML-FS algorithm can identify panels with as few as 50 genetic markers that can achieve approximately 80% accuracy when used in combination with known risk factors. The modest increase in accuracy over PRS performances is noteworthy, especially considering that PRS models incorporate a substantially larger number of genetic variants. This extensive variant selection can pose practical challenges in clinical settings. Additionally, the proposed approach revealed novel CAD-genetic variant associations. [ABSTRACT FROM AUTHOR]

Background: Despite substantial research revealing that patients with rheumatoid arthritis (RA) have excessive morbidity and mortality of cardiovascular disease (CVD), the mechanism underlying this association has not been fully known. This study aims to systematically investigate the phenotypic and genetic correlation between RA and CVD. Methods: Based on UK Biobank, we conducted two cohort studies to evaluate the phenotypic relationships between RA and CVD, including atrial fibrillation (AF), coronary artery disease (CAD), heart failure (HF), and stroke. Next, we used linkage disequilibrium score regression, Local Analysis of [co]Variant Association, and bivariate causal mixture model (MiXeR) methods to examine the genetic correlation and polygenic overlap between RA and CVD, using genome-wide association summary statistics. Furthermore, we explored specific shared genetic loci by conjunctional false discovery rate analysis and association analysis based on subsets. Results: Compared with the general population, RA patients showed a higher incidence of CVD (hazard ratio [HR] = 1.21, 95% confidence interval [CI]: 1.15–1.28). We observed positive genetic correlations of RA with AF and stroke, and a mixture of negative and positive local genetic correlations underlying the global genetic correlation for CAD and HF, with 13 ~ 33% of shared genetic variants for these trait pairs. We further identified 23 pleiotropic loci associated with RA and at least one CVD, including one novel locus (rs7098414, TSPAN14, 10q23.1). Genes mapped to these shared loci were enriched in immune and inflammatory-related pathways, and modifiable risk factors, such as high diastolic blood pressure. Conclusions: This study revealed the shared genetic architecture of RA and CVD, which may facilitate drug target identification and improved clinical management. [ABSTRACT FROM AUTHOR]

Sarcopenic obesity (SO) is an age-related disease characterized by the coexistence of excessive adiposity and low muscle mass or function. Although obesity and sarcopenia are heritable conditions, the genetic determinants of SO have not been fully understood. We conducted a large-scale exome-wide association analysis of SO in a sequenced sample of 2 887 cases and 113 284 controls and an imputed sample of 4 003 cases and 161 990 controls in the UK Biobank cohort. Single-variant association analysis identified one locus 1q41 (lead SNP rs1417066 , LYPLAL1-AS1 , odds ratio [OR] = 1.15, 95% confidence interval [CI] = [1.11–1.19], p  = 1.75 × 10−14) that was significantly associated with SO at the exome-wide significance level (p  < 1 × 10-8). Colocalization analysis in the Genotype-Tissue Expression expression quantitative trait locus database showed that LYPLAL1-AS1 was colocalized with SO in multiple musculoskeletal-related tissues. Gene-based burden test of rare loss-of-function variants identified 5 genes at the gene-wise significance level (p  < 4.3 × 10−6): PDE3B (OR = 2.48, p  = 1.10 × 10−6), MYOZ3 (OR = 25.49, p  = 1.41 × 10−7), SLC15A3 (OR = 4.75, p  = 6.82 × 10−7), RNF130 (OR = 25.83, p  = 4.07 × 10−6), and TNK2 (OR = 4.25, p  = 8.75 × 10−8). Overall, our study uncovered the genetic effects of both common and rare variants on SO susceptibility, expanded existing knowledge of the genetic architecture of SO, and improved understanding of the genetic mechanisms underlying SO. [ABSTRACT FROM AUTHOR]

Background: Previous studies have shown that lifestyle/environmental factors could accelerate the development of age-related hearing loss (ARHL). However, there has not yet been a study investigating the joint association among genetics, lifestyle/environmental factors, and adherence to healthy lifestyle for risk of ARHL. We aimed to assess the association between ARHL genetic variants, lifestyle/environmental factors, and adherence to healthy lifestyle as pertains to risk of ARHL. Methods: This case–control study included 376,464 European individuals aged 40 to 69 years, enrolled between 2006 and 2010 in the UK Biobank (UKBB). As a replication set, we also included a total of 26,523 individuals considered of European ancestry and 9834 individuals considered of African-American ancestry through the Penn Medicine Biobank (PMBB). The polygenic risk score (PRS) for ARHL was derived from a sensorineural hearing loss genome-wide association study from the FinnGen Consortium and categorized as low, intermediate, high, and very high. We selected lifestyle/environmental factors that have been previously studied in association with hearing loss. A composite healthy lifestyle score was determined using seven selected lifestyle behaviors and one environmental factor. Results: Of the 376,464 participants, 87,066 (23.1%) cases belonged to the ARHL group, and 289,398 (76.9%) individuals comprised the control group in the UKBB. A very high PRS for ARHL had a 49% higher risk of ARHL than those with low PRS (adjusted OR, 1.49; 95% CI, 1.36–1.62; P <.001), which was replicated in the PMBB cohort. A very poor lifestyle was also associated with risk of ARHL (adjusted OR, 3.03; 95% CI, 2.75–3.35; P <.001). These risk factors showed joint effects with the risk of ARHL. Conversely, adherence to healthy lifestyle in relation to hearing mostly attenuated the risk of ARHL even in individuals with very high PRS (adjusted OR, 0.21; 95% CI, 0.09–0.52; P <.001). Conclusions: Our findings of this study demonstrated a significant joint association between genetic and lifestyle factors regarding ARHL. In addition, our analysis suggested that lifestyle adherence in individuals with high genetic risk could reduce the risk of ARHL. [ABSTRACT FROM AUTHOR]

Background Coexisting long-term conditions (LTCs) in psoriasis and their potential causal associations with the disease are not well -established. Objectives To determine distinct clusters of LTCs in people with psoriasis and the potential bidirectional causal association between these LTCs and psoriasis. Methods Using latent class analysis, cross-sectional data from people with psoriasis from the UK Biobank were analysed to identify distinct psoriasis-related comorbidity profiles. Linkage disequilibrium score regression (LDSR) was applied to compute the genetic correlation between psoriasis and LTCs. Two-sample bidirectional Mendelian randomization (MR) analysis assessed the potential causal direction using independent genetic variants that reached genome-wide significance (P < 5 × 10–8). Results Five comorbidity clusters were identified in a population of 10 873 people with psoriasis. LDSR revealed that psoriasis was positively genetically correlated with heart failure [genetic correlation (rg) = 0.23, P = 8.8 × 10−8], depression (rg = 0.12, P = 2.7 × 10−5), coronary artery disease (CAD; rg = 0.15, P = 2 × 10−4) and type 2 diabetes (rg = 0.19, P = 3 × 10−3). Genetic liability to CAD was associated with an increased risk of psoriasis [inverse variance weighted (IVW) odds ratio (ORIVW) 1.159, 95% confidence interval (CI) 1.055–1.274; P = 2 × 10−3]. The MR pleiotropy residual sum and outlier (MR-PRESSO; ORMR-PRESSO 1.13, 95% CI 1.042–1.228; P = 6 × 10−3) and the MR-robust adjusted profile score (RAPS) (ORMR-RAPS 1.149, 95% CI 1.062–1.242; P = 5 × 10−4) approaches corroborate the IVW findings. The weighted median (WM) generated similar and consistent effect estimates but was not statistically significant (ORWM 1.076, 95% CI 0.949–1.221; P = 0.25). Evidence for a suggestive increased risk was detected for CAD (ORIVW 1.031, 95% CI 1.003–1.059; P = 0.03) and heart failure (ORIVW 1.019, 95% CI 1.005–1.033; P = 9 × 10−3) in those with a genetic liability to psoriasis; however, MR sensitivity analyses did not reach statistical significance. Conclusions Five distinct clusters of psoriasis comorbidities were observed with these findings to offer opportunities for an integrated approach to comorbidity prevention and treatment. Coexisting LTCs share with psoriasis common genetic and nongenetic risk factors, and aggressive lifestyle modification in these people is anticipated to have an impact beyond psoriasis risk. Genetically predicted CAD is possibly associated with an increased risk of psoriasis, altering our prior knowledge. [ABSTRACT FROM AUTHOR]

Clozapine is the only licensed medication for treatment-resistant schizophrenia (TRS). Few predictors for variation in response to clozapine have been identified, but clozapine metabolism is known to influence therapeutic response and adverse side effects. Here, we expand on genome-wide studies of clozapine metabolism, previously focused on common genetic variation, by analysing whole-exome sequencing data from 2062 individuals with schizophrenia taking clozapine in the UK. We investigated whether rare genomic variation in genes and gene sets involved in the clozapine metabolism pathway influences plasma concentrations of clozapine metabolites, assessed through the longitudinal analysis of 6585 pharmacokinetic assays. We observed a statistically significant association between the burden of rare damaging coding variants (MAF ≤ 1 %) in gene sets broadly related to drug pharmacokinetics and lower clozapine (β = −0.054, SE = 0.019, P -value = 0.005) concentrations in plasma. We estimate that the effects in clozapine plasma concentrations of a single damaging allele in this gene set are akin to reducing the clozapine dose by about 35 mg/day. The gene-based analysis identified rare variants in CYP1A2 , which encodes the enzyme responsible for converting clozapine to norclozapine, as having the strongest effects of any gene on clozapine metabolism (β = 0.324, SE = 0.124, P = 0.009). Our findings support the hypothesis that rare genetic variants in known drug-metabolising enzymes and transporters can markedly influence clozapine plasma concentrations; these results suggest that pharmacogenomic efforts trying to predict clozapine metabolism and personalise drug therapy could benefit from the inclusion of rare damaging variants in pharmacogenes beyond those already identified and catalogued as PGx star alleles. [ABSTRACT FROM AUTHOR]

PURPOSE: Pancreatic cancer (PC) is a deadly disease most often diagnosed in late stages. Identification of high-risk subjects could both contribute to preventative measures and help diagnose the disease at earlier timepoints. However, known risk factors, assessed independently, are currently insufficient for accurately stratifying patients. We use large-scale data from the UK Biobank (UKB) to identify genetic variant-smoking interaction effects and show their importance in risk assessment. METHODS: We draw data from 15,086,830 genetic variants and 315,512 individuals in the UKB. There are 765 cases of PC. Crucially, robust resampling corrections are used to overcome well-known challenges in hypothesis testing for interactions. Replication analysis is conducted in two independent cohorts totaling 793 cases and 570 controls. Integration of functional annotation data and construction of polygenic risk scores (PRS) demonstrate the additional insight provided by interaction effects. RESULTS: We identify the genome-wide significant variant rs77196339 on chromosome 2 (per minor allele odds ratio in never-smokers, 2.31 [95% CI, 1.69 to 3.15]; per minor allele odds ratio in ever-smokers, 0.53 [95% CI, 0.30 to 0.91]; P = 3.54 × 10−8) as well as eight other loci with suggestive evidence of interaction effects (P < 5 × 10−6). The rs77196339 region association is validated (P <.05) in the replication sample. PRS incorporating interaction effects show improved discriminatory ability over PRS of main effects alone. CONCLUSION: This study of genome-wide germline variants identified smoking to modify the effect of rs77196339 on PC risk. Interactions between known risk factors can provide critical information for identifying high-risk subjects, given the relative inadequacy of models considering only main effects, as demonstrated in PRS. Further studies are necessary to advance toward comprehensive risk prediction approaches for PC. We study interactions between germline variants and smoking that can perturb pancreatic cancer risk. [ABSTRACT FROM AUTHOR]

Background: The association between major depressive disorder (MDD) and irritable bowel syndrome (IBS) has been found in observational research; however, the causative relationship between MDD and IBS remains uncertain. Using the two‐sample Mendelian randomization (MR) approach, we attempted to examine the causal effect of MDD on IBS. Methods: Independent genetic variants for MDD identified by Howard et al. based on a genome‐wide meta‐analysis were selected for this study. Gene‐Outcome associations for IBS were gathered from UK Biobank and FinnGen databases. The MR analysis included inverse variance weighted (IVW), MR‐Egger regression, weighted median, weighted mode, and MR‐PRESSO sensitivity analyses. Results: FinnGen database subjected to inverse variance weighted (IVW) analysis revealed that MDD may be a risk factor for the development of IBS (OR = 1.356, 95% CI: 1.125–1.632, p = 0.0013). The same finding was reached in UK Biobank for IVW (OR = 1.011, 95% CI: 1.006–1.015, p = 3.18 × 10−7), MR‐Egger progression (OR = 1.030, 95% CI: 1.008–1.051, p = 0.007), and weighted median (OR = 1.011, 95% CI: 1.005–1.016, p = 0.0001). Conclusion: Our findings supported a causal relationship between MDD and IBS, which may have implications for the clinical management of IBS in individuals with MDD. [ABSTRACT FROM AUTHOR]

Background: Telomere length is a critical metric linked to aging, health, and disease. Currently, the exploration of target proteins related to telomere length is usually limited to the context of aging and specific diseases, which limits the discovery of more relevant drug targets. This study integrated large-scale plasma cis-pQTLs data and telomere length GWAS datasets. We used Mendelian randomization(MR) to identify drug target proteins for telomere length, providing essential clues for future precision therapy and targeted drug development. Methods: Using plasma cis-pQTLs data from a previous GWAS study (3,606 Pqtls associated with 2,656 proteins) and a GWAS dataset of telomere length (sample size: 472,174; GWAS ID: ieu-b-4879) from UK Biobank, using MR, external validation, and reverse causality testing, we identified essential drug target proteins for telomere length. We also performed co-localization, Phenome-wide association studies and enrichment analysis, protein-protein interaction network construction, search for existing intervening drugs, and potential drug/compound prediction for these critical targets to strengthen and expand our findings. Results: After Bonferron correction (p < 0.05/734), RPN1 (OR: 0.96; 95%CI: (0.95, 0.97)), GDI2 (OR: 0.94; 95%CI: (0.92, 0.96)), NT5C (OR: 0.97; 95%CI: (0.95, 0.98)) had a significant negative causal association with telomere length; TYRO3 (OR: 1.11; 95%CI: (1.09, 1.15)) had a significant positive causal association with telomere length. GDI2 shared the same genetic variants with telomere length (coloc.abf-PPH 4 > 0.8). Conclusion: Genetically determined plasma RPN1, GDI2, NT5C, and TYRO3 have significant causal effects on telomere length and can potentially be drug targets. Further exploration of the role and mechanism of these proteins/genes in regulating telomere length is needed. [ABSTRACT FROM AUTHOR]

Genomics has been forecasted to revolutionise human health by improving medical treatment through a better understanding of the molecular mechanisms of human diseases. Despite great successes of the last decade's genome-wide association studies (GWAS), the results have been translated to genomic medicine to a limited extent. One route to get closer to improved medical treatment could be by understanding the genetics of medication use. Current medication profiles from 335,744 individuals from the UK Biobank were obtained, and a GWAS was conducted to identify common genetic variants associated with current medication use. In total, 59 independent loci were identified for medication use, and approximately 18% of the total variation was attributable to common genetic variation. The largest fraction of genetic variance for current medication use was captured by variants with low-to-medium minor allele frequency, with coding, conserved genomic regions and transcription start sites being enriched for associated variants. The average correlation (R) between medication use and the polygenic score was 0.14. The results further demonstrated that individuals with higher polygenic burden for medication use were, on average, sicker and had a higher risk for adverse drug reactions. These results provide an insight into the genetic contribution of medication use and pave the way for developments of novel multiple trait polygenic scores, which include the genetically informed medication use. [ABSTRACT FROM AUTHOR]

Background Recent cases of clinical failure in malaria patients in the United Kingdom (UK) treated with artemether-lumefantrine have implications for malaria chemotherapy worldwide. Methods Parasites were isolated from an index case of confirmed Plasmodium falciparum treatment failure after standard treatment, and from comparable travel-acquired UK malaria cases. Drug susceptibility in vitro and genotypes at 6 resistance-associated loci were determined for all parasite isolates and compared with clinical outcomes for each parasite donor. Results A traveler, who returned to the UK from Uganda in 2022 with Plasmodium falciparum malaria, twice failed treatment with full courses of artemether-lumefantrine. Parasites from the patient exhibited significantly reduced susceptibility to artemisinin (ring-stage survival, 17.3% [95% confidence interval {CI}, 13.6%–21.1%]; P <.0001) and lumefantrine (effective concentration preventing 50% of growth = 259.4 nM [95% CI, 130.6–388.2 nM]; P =.001). Parasite genotyping identified an allele of pfk13 encoding both the A675V variant in the Pfk13 propeller domain and a novel L145V nonpropeller variant. In vitro susceptibility testing of 6 other P. falciparum lines of Ugandan origin identified reduced susceptibility to artemisinin and lumefantrine in 1 additional line, also from a 2022 treatment failure case. These parasites did not harbor a pfk13 propeller domain variant but rather the novel nonpropeller variant T349I. Variant alleles of pfubp1 , pfap2mu , and pfcoronin were also identified among the 7 parasite lines. Conclusions We confirm, in a documented case of artemether-lumefantrine treatment failure imported from Uganda, the presence of pfk13 mutations encoding L145V and A675V. Parasites with reduced susceptibility to both artemisinin and lumefantrine may be emerging in Uganda. [ABSTRACT FROM AUTHOR]

Mechanisms through which most known Alzheimer's disease (AD) loci operate to increase AD risk remain unclear. Although Apolipoprotein E (APOE) is known to regulate lipid homeostasis, the effects of broader AD genetic liability on non-lipid metabolites remain unknown, and the earliest ages at which metabolic perturbations occur and how these change over time are yet to be elucidated. We examined the effects of AD genetic liability on the plasma metabolome across the life course. Using a reverse Mendelian randomization framework in two population-based cohorts [Avon Longitudinal Study of Parents and Children (ALSPAC, n = 5648) and UK Biobank (n ≤ 118,466)], we estimated the effects of genetic liability to AD on 229 plasma metabolites, at seven different life stages, spanning 8 to 73 years. We also compared the specific effects of APOE ε4 and APOE ε2 carriage on metabolites. In ALSPAC, AD genetic liability demonstrated the strongest positive associations with cholesterol-related traits, with similar magnitudes of association observed across all age groups including in childhood. In UK Biobank, the effect of AD liability on several lipid traits decreased with age. Fatty acid metabolites demonstrated positive associations with AD liability in both cohorts, though with smaller magnitudes than lipid traits. Sensitivity analyses indicated that observed effects are largely driven by the strongest AD instrument, APOE, with many contrasting effects observed on lipids and fatty acids for both ε4 and ε2 carriage. Our findings indicate pronounced effects of the ε4 and ε2 genetic variants on both pro- and anti-atherogenic lipid traits and sphingomyelins, which begin in childhood and either persist into later life or appear to change dynamically. [ABSTRACT FROM AUTHOR]

Background: Genetic variants can contribute differently to trait heritability by their functional categories, and recent studies have shown that incorporating functional annotation can improve the predictive performance of polygenic risk scores (PRSs). In addition, when only a small proportion of variants are causal variants, PRS methods that employ a Bayesian framework with shrinkage can account for such sparsity. It is possible that the annotation group level effect is also sparse. However, the number of PRS methods that incorporate both annotation information and shrinkage on effect sizes is limited. We propose a PRS method, PRSbils, which utilizes the functional annotation information with a bilevel continuous shrinkage prior to accommodate the varying genetic architectures both on the variant-specific level and on the functional annotation level. Results: We conducted simulation studies and investigated the predictive performance in settings with different genetic architectures. Results indicated that when there was a relatively large variability of group-wise heritability contribution, the gain in prediction performance from the proposed method was on average 8.0% higher AUC compared to the benchmark method PRS-CS. The proposed method also yielded higher predictive performance compared to PRS-CS in settings with different overlapping patterns of annotation groups and obtained on average 6.4% higher AUC. We applied PRSbils to binary and quantitative traits in three real world data sources (the UK Biobank, the Michigan Genomics Initiative (MGI), and the Korean Genome and Epidemiology Study (KoGES)), and two sources of annotations: ANNOVAR, and pathway information from the Kyoto Encyclopedia of Genes and Genomes (KEGG), and demonstrated that the proposed method holds the potential for improving predictive performance by incorporating functional annotations. Conclusions: By utilizing a bilevel shrinkage framework, PRSbils enables the incorporation of both overlapping and non-overlapping annotations into PRS construction to improve the performance of genetic risk prediction. The software is available at https://github.com/styvon/PRSbils. [ABSTRACT FROM AUTHOR]

Intersex people suffer human rights abuses and harms because of non-consensual early medical interventions. They have historically been rendered outside of welfare regimes and equality, diversity and inclusion policies, or forcibly subsumed within sex-binaried institutions. This article draws on critical intersex studies to interrogate the policy silences and collusions that have taken place regarding intersex people's suffering. Using Ireland and England as case studies, we show that current formations of equality and diversity policies are inadequate in relation to intersex issues. Analysis of policy documents from Ireland and the UK using Bacchi's method reveals the erasure and/or marginalisation of intersex people, despite some stated commitments to gender and sexual equality. We conclude that there is a pressing need for social policy work around intersex issues and for reform to support intersex people's equality, diversity and inclusion. [ABSTRACT FROM AUTHOR]

Genetic relationships between blood eosinophil count (BEC), asthma susceptibility, and severity are unclear. We sought to identify the genetic difference between type 2 (T2) and nontype 2 (non-T2) asthma (defined by BEC) and investigate genetic relationships between high BEC, asthma susceptibility, and severity. Genome-wide association studies (GWASs) were performed for T2 (n = 9,064; BEC ≥ 300 cells/μL) versus non-T2 asthma (n = 14,379; BEC < 150 cells/μL) and asthma susceptibility (37,227 asthmatics vs. 124,132 nonasthma controls) in the UK Biobank and asthma severity (moderate-to-severe asthma [n = 2,153] vs. mild asthma [n = 5165]) in the All of Us Research Program (AoURP). Genetic causality between BEC, asthma susceptibility, and severity were dissected using Mendelian randomization (MR). High BEC was associated with asthma and decreased pulmonary function. GWASs revealed four sets of genetic variants (p < 5 × 10−8): genes associated with only BEC or asthma and genes associated with high BEC and asthma in the same or opposite direction. The C allele of rs653178 in ATXN2 was associated with high BEC, risk for autoimmune diseases, and protection for asthma. Genetic variants associated with BEC or asthma were not associated with asthma severity. MR indicated high BEC and asthma were in bidirectional causal relationship (p <.001); however, they were not causal for asthma severity. Genetic variants associated with asthma or BEC and asthma severity are distinctive. High BEC is a risk factor for asthma; however, it is neither necessary nor sufficient for asthma susceptibility and severity. [ABSTRACT FROM AUTHOR]

Experimental models suggest an important role for mitochondrial dysfunction in the pathogenesis of chronic kidney disease (CKD) and acute kidney injury (AKI), but little is known regarding the impact of common mitochondrial genetic variation on kidney health. We sought to evaluate associations of inherited mitochondrial DNA (mtDNA) variation with risk of CKD and AKI in a large population-based cohort. We categorized UK Biobank participants who self-identified as white into eight distinct mtDNA haplotypes, which were previously identified based on their associations with phenotypes associated with mitochondrial DNA copy number, a measure of mitochondrial function. We used linear and logistic regression models to evaluate associations of these mtDNA haplotypes with estimated glomerular filtration rate by serum creatinine and cystatin C (eGFRCr-CysC, N = 362,802), prevalent (N = 416 cases) and incident (N = 405 cases) end-stage kidney disease (ESKD), AKI defined by diagnostic codes (N = 14,170 cases), and urine albumin/creatinine ratio (ACR, N = 114,662). The mean age was 57 ± 8 years and the mean eGFR was 90 ± 14 ml/min/1.73 m2. MtDNA haplotype was significantly associated with eGFR (p = 2.8E−12), but not with prevalent ESKD (p = 5.9E−2), incident ESKD (p = 0.93), AKI (p = 0.26), or urine ACR (p = 0.54). The association of mtDNA haplotype with eGFR remained significant after adjustment for diabetes mellitus and hypertension (p = 1.2E−10). When compared to the reference haplotype, mtDNA haplotypes I (β = 0.402, standard error (SE) = 0.111; p = 2.7E−4), IV (β = 0.430, SE = 0.073; p = 4.2E−9), and V (β = 0.233, SE = 0.050; p = 2.7E−6) were each associated with higher eGFR. Among self-identified white UK Biobank participants, mtDNA haplotype was associated with eGFR, but not with ESKD, AKI or albuminuria. [ABSTRACT FROM AUTHOR]

The use of lipid-lowering drugs is still highly controversial in patients with amyotrophic lateral sclerosis (ALS). We performed a drug-target Mendelian randomization (MR) analysis to investigate the effect of targeted lipid-lowering drugs on the risk of ALS. First, we evaluated the causal relationship between HMG-CoA (3-hydroxy-3-methylglutaryl coenzyme A) reductase (HMGCR) inhibitors-taking trait and ALS using a bidirectional two-sample MR study. Second, we investigated the causal relationship between lipid-lowering drugs and ALS through a drug-target MR approach. The summary data for HMGCR inhibitors-taking traits were extracted from a genome-wide association study (GWAS) of medication use and associated disease in the UK Biobank. The summary data for low-density lipoprotein cholesterol and apolipoprotein B (apoB) were extracted from a meta-analysis of GWAS in individuals of European ancestry in the UKB. The GWAS summary data of ALS were obtained from the Project MinE. Our bidirectional two-sample MR showed that genetically determined increased HMGCR inhibitors-taking trait was an independent risk factor for ALS (odds ratio [OR] = 1.090, 95% confidence interval [CI] = 1.035–1.150, p = 0.001). The results of drug-target MR showed that the increased expression of the HMGCR gene in blood with the higher risk of ALS (OR = 1.21, 95% CI = 1.01–1.46; p = 0.042) through SMR method and the apoB level mediated by the APOB gene increased the risk of ALS (OR = 1.15; 95% CI =1.05–1.25; p = 0.001) through inverse-variance weighted MR method. This present study provides genetic support for a positive causal effect of HMGCR inhibitors-taking trait and ALS. The reason for this may be due to the underlying disease condition behind the medication, rather than the medication itself. Our findings also suggested that HMGCR and apoB inhibitors may have potential protective effects on ALS. [ABSTRACT FROM AUTHOR]

Background: The immune system has a central role in preventing carcinogenesis. Alteration of systemic immune cell levels may increase cancer risk. However, the extent to which common genetic variation influences blood traits and cancer risk remains largely undetermined. Here, we identify pleiotropic variants and predict their underlying molecular and cellular alterations. Methods: Multivariate Cox regression was used to evaluate associations between blood traits and cancer diagnosis in cases in the UK Biobank. Shared genetic variants were identified from the summary statistics of the genome-wide association studies of 27 blood traits and 27 cancer types and subtypes, applying the conditional/conjunctional false-discovery rate approach. Analysis of genomic positions, expression quantitative trait loci, enhancers, regulatory marks, functionally defined gene sets, and bulk- and single-cell expression profiles predicted the biological impact of pleiotropic variants. Plasma small RNAs were sequenced to assess association with cancer diagnosis. Results: The study identified 4093 common genetic variants, involving 1248 gene loci, that contributed to blood–cancer pleiotropism. Genomic hotspots of pleiotropism include chromosomal regions 5p15-TERT and 6p21-HLA. Genes whose products are involved in regulating telomere length are found to be enriched in pleiotropic variants. Pleiotropic gene candidates are frequently linked to transcriptional programs that regulate hematopoiesis and define progenitor cell states of immune system development. Perturbation of the myeloid lineage is indicated by pleiotropic associations with defined master regulators and cell alterations. Eosinophil count is inversely associated with cancer risk. A high frequency of pleiotropic associations is also centered on the regulation of small noncoding Y-RNAs. Predicted pleiotropic Y-RNAs show specific regulatory marks and are overabundant in the normal tissue and blood of cancer patients. Analysis of plasma small RNAs in women who developed breast cancer indicates there is an overabundance of Y-RNA preceding neoplasm diagnosis. Conclusions: This study reveals extensive pleiotropism between blood traits and cancer risk. Pleiotropism is linked to factors and processes involved in hematopoietic development and immune system function, including components of the major histocompatibility complexes, and regulators of telomere length and myeloid lineage. Deregulation of Y-RNAs is also associated with pleiotropism. Overexpression of these elements might indicate increased cancer risk. [ABSTRACT FROM AUTHOR]

Background: Observational studies and randomized controlled trials have found evidence that higher maternal circulating cortisol levels in pregnancy are associated with lower offspring birth weight. However, it is possible that the observational associations are due to residual confounding. Methods: We performed two-sample Mendelian Randomisation (MR) using a single genetic variant (rs9989237) associated with morning plasma cortisol (GWAS; sample 1; N = 25,314). The association between this maternal genetic variant and offspring birth weight, adjusted for fetal genotype, was obtained from the published EGG Consortium and UK Biobank meta-analysis (GWAS; sample 2; N = up to 406,063) and a Wald ratio was used to estimate the causal effect. We also performed an alternative analysis using all GWAS reported cortisol variants that takes account of linkage disequilibrium. We also tested the genetic variant's effect on pregnancy cortisol and performed PheWas to search for potential pleiotropic effects. Results: The estimated effect of maternal circulating cortisol on birth weight was a 50 gram (95% CI, -109 to 10) lower birth weight per 1 SD higher log-transformed maternal circulating cortisol levels, using a single variant. The alternative analysis gave similar results (-33 grams (95% CI, -77 to 11)). The effect of the cortisol variant on pregnancy cortisol was 2-fold weaker than in the original GWAS, and evidence was found of pleiotropy. Conclusions: Our findings provide some evidence that higher maternal morning plasma cortisol causes lower birth weight. Identification of more independent genetic instruments for morning plasma cortisol are necessary to explore the potential bias identified. [ABSTRACT FROM AUTHOR]

Because human same-sex sexual behavior (SSB) is heritable and leads to fewer offspring, how SSB-associated alleles have persisted and whether they will remain in human populations are of interest. Using the UK Biobank, we address these questions separately for bisexual behavior (BSB) and exclusive SSB (eSSB) after confirming their genetic distinction. We discover that male BSB is genetically positively correlated with the number of offspring. This unexpected phenomenon is attributable to the horizontal pleiotropy of male risk-taking behavior-associated alleles because male risk-taking behavior is genetically positively correlated with both BSB and the number of offspring and because genetically controlling male risk-taking behavior abolishes the genetic correlation between male BSB and the number of offspring. By contrast, eSSB is genetically negatively correlated with the number of offspring. Our results suggest that male BSB-associated alleles are likely reproductively advantageous, which may explain their past persistence and predict their future maintenance, and that eSSB-associated alleles are likely being selected against at present. [ABSTRACT FROM AUTHOR]

Motivation Multi-trait analysis has been shown to have greater statistical power than single-trait analysis. Most of the existing multi-trait analysis methods only work with a limited number of traits and usually prioritize high statistical power over identifying relevant traits, which heavily rely on domain knowledge. Results To handle diseases and traits with obscure etiology, we developed TraitScan, a powerful and fast algorithm that identifies potential pleiotropic traits from a moderate or large number of traits (e.g. dozens to thousands) and tests the association between one genetic variant and the selected traits. TraitScan can handle either individual-level or summary-level GWAS data. We evaluated TraitScan using extensive simulations and found that it outperformed existing methods in terms of both testing power and trait selection when sparsity was low or modest. We then applied it to search for traits associated with Ewing Sarcoma, a rare bone tumor with peak onset in adolescence, among 754 traits in UK Biobank. Our analysis revealed a few promising traits worthy of further investigation, highlighting the use of TraitScan for more effective multi-trait analysis as biobanks emerge. We also extended TraitScan to search and test association with a polygenic risk score and genetically imputed gene expression. Availability and implementation Our algorithm is implemented in an R package "TraitScan" available at https://github.com/RuiCao34/TraitScan. [ABSTRACT FROM AUTHOR]

Background: Valproate is a candidate for ischemic stroke prevention due to its anti-atherosclerotic effects in vivo. Although valproate use is associated with decreased ischemic stroke risk in observational studies, confounding by indication precludes causal conclusions. Aims: We applied Mendelian randomization to determine whether genetic variants that influence seizure response among valproate users associate with ischemic stroke. Methods: We derived a genetic score for valproate response using genome-wide association data of seizure response after valproate intake from the Epilepsy Pharmacogenomics Consortium. We then tested this score among valproate users of the UK Biobank for association with incident and recurrent ischemic stroke using Cox proportional hazard models. As replication, we tested found associations in an independent cohort of valproate users of the Mass General Brigham Biobank. Results: Among 2150 valproate users (mean 56 years, 54% females), 82 ischemic strokes occurred over a mean 12 year follow-up. Higher valproate response genetic score was associated with higher serum valproate levels (+5.78 µg/ml per 1 standard deviation (SD), 95% confidence interval (CI) (3.45, 8.11)). After adjusting for age and sex, higher valproate response genetic score was associated with lower ischemic stroke risk (hazard ratio (HR) per 1 SD 0.73, 95% CI (0.58, 0.91)) with a halving of absolute risk in the highest compared to the lowest score tertile (4.8% vs 2.5%, p trend = 0.027). Among 194 valproate users with prevalent stroke at baseline, a higher valproate response genetic score was associated with lower recurrent ischemic stroke risk (HR per 1 SD 0.53, 95% CI (0.32, 0.86)) with reduced absolute risk in the highest compared to the lowest score tertile (3/51, 5.9% vs 13/71, 18.3%, p trend = 0.026). The valproate response genetic score was not associated with ischemic stroke among the 427,997 valproate non-users (p = 0.61), suggesting minimal pleiotropy. In 1241 valproate users of the Mass General Brigham Biobank with 99 ischemic stroke events over 6.5 years follow-up, we replicated our observed associations between the valproate response genetic score and ischemic stroke (HR per 1 SD 0.77, 95% CI (0.61, 0.97)). Conclusion: These results demonstrate that a genetically predicted favorable seizure response to valproate is associated with higher serum valproate levels and reduced ischemic stroke risk among valproate users, providing causal support for valproate effectiveness in ischemic stroke prevention. The strongest effect was found for recurrent ischemic stroke, suggesting potential dual-use benefits of valproate for post-stroke epilepsy. Clinical trials will be required in order to identify populations that may benefit most from valproate for stroke prevention. Data access statement: UK Biobank participant data are available after approval of a research proposal. The weights of the used genetic scores are available in the Supplemental Tables. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) have successfully revealed many disease-associated genetic variants. For a case-control study, the adequate power of an association test can be achieved with a large sample size, although genotyping large samples is expensive. A cost-effective strategy to boost power is to integrate external control samples with publicly available genotyped data. However, the naive integration of external controls may inflate the type I error rates if ignoring the systematic differences (batch effect) between studies, such as the differences in sequencing platforms, genotype-calling procedures, population stratification, and so forth. To account for the batch effect, we propose an approach by integrating External Controls into the Association Test by Regression Calibration (iECAT-RC) in case-control association studies. Extensive simulation studies show that iECAT-RC not only can control type I error rates but also can boost statistical power in all models. We also apply iECAT-RC to the UK Biobank data for M72 Fibroblastic disorders by considering genotype calling as the batch effect. Four SNPs associated with fibroblastic disorders have been detected by iECAT-RC and the other two comparison methods, iECAT-Score and Internal. However, our method has a higher probability of identifying these significant SNPs in the scenario of an unbalanced case-control association study. [ABSTRACT FROM AUTHOR]

The stoma care nurse (SCN) assesses peristomal skin during each patient intervention. Living in a diverse multicultural society, the SCN needs to consider dark skin tones and how these are documented. This article looks at how the literature on peristomal skin assessment and available tools discuss skin colour, and compare this with the tissue viability literature. Stoma care and peristomal skin literature features very little about skin colour. Registered nurses are often unaware of the differences when assessing light skin tones versus dark skin tones. The article discusses how to assess for, identify and document problems around peristomal skin with patients who have dark skin tones. The differences in skin breakdown between light skin tones and dark skin tones are highlighted. There needs to be further research and development of tools to assist clinicians in identification and documentation relating to skin tone, thus providing consistency in assessment. [ABSTRACT FROM AUTHOR]

We examined more than 97,000 families from four neurodevelopmental disease cohorts and the UK Biobank to identify phenotypic and genetic patterns in parents contributing to neurodevelopmental disease risk in children. We identified within- and cross-disorder correlations between six phenotypes in parents and children, such as obsessive-compulsive disorder (R = 0.32–0.38, p < 10−126). We also found that measures of sub-clinical autism features in parents are associated with several autism severity measures in children, including biparental mean Social Responsiveness Scale scores and proband Repetitive Behaviors Scale scores (regression coefficient = 0.14, p = 3.38 × 10−4). We further describe patterns of phenotypic similarity between spouses, where spouses show correlations for six neurological and psychiatric phenotypes, including a within-disorder correlation for depression (R = 0.24–0.68, p < 0.001) and a cross-disorder correlation between anxiety and bipolar disorder (R = 0.09–0.22, p < 10−92). Using a simulated population, we also found that assortative mating can lead to increases in disease liability over generations and the appearance of "genetic anticipation" in families carrying rare variants. We identified several families in a neurodevelopmental disease cohort where the proband inherited multiple rare variants in disease-associated genes from each of their affected parents. We further identified parental relatedness as a risk factor for neurodevelopmental disorders through its inverse relationship with variant pathogenicity and propose that parental relatedness modulates disease risk by increasing genome-wide homozygosity in children (R = 0.05–0.26, p < 0.05). Our results highlight the utility of assessing parent phenotypes and genotypes toward predicting features in children who carry rare variably expressive variants and implicate assortative mating as a risk factor for increased disease severity in these families. [Display omitted] Many rare genetic variants are variably expressive, conferring risk for a range of clinical features with incomplete penetrance. We implicate assortative mating as a risk factor for disease in families carrying these variants by increasing genetic disease liability over generations, leading to the "genetic anticipation" observed in these families. [ABSTRACT FROM AUTHOR]

LDpred2 is a widely used Bayesian method for building polygenic scores (PGSs). LDpred2-auto can infer the two parameters from the LDpred model, the SNP heritability h 2 and polygenicity p , so that it does not require an additional validation dataset to choose best-performing parameters. The main aim of this paper is to properly validate the use of LDpred2-auto for inferring multiple genetic parameters. Here, we present a new version of LDpred2-auto that adds an optional third parameter α to its model, for modeling negative selection. We then validate the inference of these three parameters (or two, when using the previous model). We also show that LDpred2-auto provides per-variant probabilities of being causal that are well calibrated and can therefore be used for fine-mapping purposes. We also introduce a formula to infer the out-of-sample predictive performance r 2 of the resulting PGS directly from the Gibbs sampler of LDpred2-auto. Finally, we extend the set of HapMap3 variants recommended to use with LDpred2 with 37% more variants to improve the coverage of this set, and we show that this new set of variants captures 12% more heritability and provides 6% more predictive performance, on average, in UK Biobank analyses. This study extends the utility of LDpred2-auto, a widely used method for deriving predictive polygenic scores. It validates the use of the latest version of LDpred2-auto for inferring key genetic parameters that inform us about the genetic architecture of traits, for identifying causal genetic variants, and for estimating predictive performance. [ABSTRACT FROM AUTHOR]

LEGAL ASPECTS RELATING TO PRENATAL DIAGNOSIS The guidance also clarifies legal aspects in relation to termination of pregnancy for a germline cancer susceptibility gene variant. Prenatal and pre-implantation genetic testing for monogenic disorders for germline cancer susceptibility gene variants: UK joint consensus guidance Although it is anticipated that there would be fewer requests for prenatal diagnosis or PGT-M for moderate penetrance genes and sex-specific variable penetrance genes, sensitive reproductive counselling by an appropriately trained genetic/genomic healthcare professional and case discussion in multidisciplinary forums is recommended. Testing for germline pathogenic variants in cancer susceptibility genes is now commonplace and routine practice, in order to guide management of individuals with cancer and to determine surveillance and risk-reduction options for those at increased genetic risk. [Extracted from the article]

This account presents information on all aspects of the biology of Geranium pratense L. (Meadow Crane's‐Bill). The main topics are presented within the standard framework of the Biological Flora of Britain and Ireland : distribution, habitat, communities, responses to biotic factors, responses to environment, structure and physiology, phenology, floral and seed characters, herbivores and disease, history and conservation.Geranium pratense is a perennial gynodioecious forb of neutral grassland. In Britain and Ireland, it is particularly abundant on roadside verges, railway embankments, the margins of watercourses and woodland rides. It is generally intolerant of grazing and is absent or scarce in livestock‐grazed grassland. Geranium pratense is widespread in England, Wales and Scotland but is scarce in Ireland. It has an extensive native range in Europe and Asia, extending eastwards to Russia, north‐western China and Mongolia. It has been widely introduced to new sites within its native range and has been introduced to Canada, the USA and New Zealand.Geranium pratense usually occurs on free‐draining soils but also infrequently where drainage is impeded. The soils are often nutrient‐rich and weakly acidic to weakly alkaline. The underlying geology is usually non‐acidic sedimentary rocks or superficial deposits.Geranium pratense is protandrous and is pollinated by various insects of the orders Hymenoptera, Diptera and Lepidoptera, particularly bumblebees, solitary bees, hoverflies and butterflies. Eleven species of phytophagous insect have been recorded on G. pratense in Britain and Ireland.Geranium pratense has little or no capacity for vegetative spread. Primary seed dispersal is ballistic and seeds may be flung over distances of up to several metres. The species has a transient seed bank, that is germination typically takes place in the winter and spring after seed production, after the physically dormant seeds have become permeable. Seedling establishment is higher in vegetation‐free gaps than in undisturbed grassland vegetation.There has been no significant change in its distribution between the late 1950s and 2019, although since 2000, it has expanded its range, mainly via introductions, in northern and western Scotland, west Wales and in Ireland. Alien sites have increased markedly since the 1960s due to introductions from wildflower seed sowing and spread from gardens. [ABSTRACT FROM AUTHOR]

Background: C‐reactive protein (CRP) is a sensitive biomarker of inflammation with moderate heritability. The role of rare functional genetic variants in relation to serum CRP is understudied. We aimed to examine gene mutation burden of protein‐altering (PA) and loss‐of‐function (LOF) variants in association with serum CRP, and to further explore the clinical relevance. Methods: We included 161,430 unrelated participants of European ancestry from the UK Biobank. Of the rare (minor allele frequency <0.1%) and functional variants, 1,776,249 PA and 266,226 LOF variants were identified. Gene‐based burden tests, linear regressions, and logistic regressions were performed to identify the candidate mutations at the gene and variant levels, to estimate the potential interaction effect between the identified PA mutation and obesity, and to evaluate the relative risk of 16 CRP‐associated diseases. Results: At the gene level, PA mutation burdens of the CRP (β = −0.685, p = 2.87e‐28) and G6PC genes (β = 0.203, p = 1.50e‐06) were associated with reduced and increased serum CRP concentration, respectively. At the variant level, seven PA alleles in the CRP gene decreased serum CRP, of which the per‐allele effects were approximately three to seven times greater than that of a common variant in the same locus. The effects of obesity and central obesity on serum CRP concentration were smaller among the PA mutation carriers in the CRP (pinteraction = 0.008) and G6PC gene (pinteraction = 0.034) compared to the corresponding non‐carriers. Conclusion: PA mutation burdens in the CRP and G6PC genes are strongly associated with decreased serum CRP concentrations. As serum CRP and obesity are important predictors of cardiovascular risks in clinics, our observations suggest taking rare genetic factors into consideration might improve the delivery of precision medicine. [ABSTRACT FROM AUTHOR]

Background: Atopic dermatitis (AD) accounts for a large proportion of the burden of skin disease, with a prevalence of around 10% among adults worldwide. In addition, systematic reviews and meta‐analyses have found that AD is associated with cancer risk at several sites; if found to be causal this could highlight potential treatment targets to reduce cancer risk. Objectives: To assess the potential causative link between AD and 14 site‐specific cancers in a two‐sample randomization study. Methods: From the largest genome‐wide association study (GWAS) of AD (10,788 cases and 30,047 non‐cases), genetic variants highly associated (p < 5 × 10−8) with AD in the European population were selected as instrumental variables (IVs). Data from large cancer consortia, as well as the UK Biobank study (n = 442,239) and the FinnGen study (n = 218,792), were employed to assess genetic associations with 14 site‐specific cancers and overall cancer. A set of complementary approaches and sensitivity analyses were carried out to examine the robustness of our results. In addition, associations for the same cancer site from different data sources were combined using meta‐analyses. Results: We discovered no strong causal evidence of AD on the risk of overall cancer, with effect estimates close to zero. After the Benjamini–Hochberg correction, the inverse‐variance weighted method indicated no association between AD and overall cancer risk in both the UK Biobank (OR, 1.00; 95% CI, 0.94–1.06; FDR, 0.98) and FinnGen studies (OR, 0.96; 95% CI, 0.92–1.02; FDR, 0.68). No strong evidence of an association was found between genetically predicted AD and the risk of any site‐specific cancers. Conclusions: Our MR investigation does not support a causal effect of AD on cancer risk. This finding has important implications for the prevention and management of both AD and cancer, as it reduces the concern of potential adverse effects of AD on cancer outcomes. [ABSTRACT FROM AUTHOR]

Background: Common and rare variants contribute to the etiology of complex traits. However, the extent to which the phenotypic effects of common and rare variants involve shared molecular mediators remains poorly understood. The question is essential to the basic and translational goals of the science of genomics, with critical basic-science, methodological, and clinical consequences. Methods: Leveraging the latest release of whole-exome sequencing (WES, for rare variants) and genome-wide association study (GWAS, for common variants) data from the UK Biobank, we developed a metric, the COmmon variant and RAre variant Convergence (CORAC) signature, to quantify the convergence for a broad range of complex traits. We characterized the relationship between CORAC and effective sample size across phenome-wide association studies. Results: We found that the signature is positively correlated with effective sample size (Spearman ρ = 0.594, P < 2.2e − 16), indicating increased functional convergence of trait-associated genetic variation, across the allele frequency spectrum, with increased power. Sensitivity analyses, including accounting for heteroskedasticity and varying the number of detected association signals, further strengthened the validity of the finding. In addition, consistent with empirical data, extensive simulations showed that negative selection, in line with enhancing polygenicity, has a dampening effect on the convergence signature. Methodologically, leveraging the convergence leads to enhanced association analysis. Conclusions: The presented framework for the convergence signature has important implications for fine-mapping strategies and drug discovery efforts. In addition, our study provides a blueprint for the expectation from future large-scale whole-genome sequencing (WGS)/WES and sheds methodological light on post-GWAS studies. [ABSTRACT FROM AUTHOR]

Background: Whether serum vitamin D mediate vascular diseases in prediabetic populations remains unclear. This study aimed to determine the associations between circulating 25-hydroxyvitamin D [25(OH)D] levels and vitamin D receptor (VDR) polymorphisms with the risk of macrovascular complications, including myocardial infarction and stroke, and microvascular complications such as diabetic nephropathy and retinopathy, among adults with prediabetes. Methods: Participants with prediabetes in UK Biobank were included (N = 56,387). Multivariable dose–response and Cox proportion models were used to explore the relationship of serum 25(OH)D status and the risks of vascular complications. The interaction of VDR polymorphisms with serum 25(OH)D level on risks of vascular events was also assessed. Results: During a median follow-up of 12 years, higher levels of 25(OH)D were significantly and nonlinearly associated with a lower risk of macrovascular diseases among prediabetic individuals. The adjusted hazard ratios (95% confidential interval) of serum 25(OH)D levels of ≥ 75.0 nmol/L versus < 25 nmol/L were 0.75 (0.63–0.88) for myocardial infarction, 0.74 (0.55–1.00) for stroke, 1.02 (0.60–1.74) for diabetic nephropathy, and 1.30 (0.92–1.84) for diabetic retinopathy, respectively. The rs2228570 (FokI) polymorphisms significantly interacted with 25(OH)D on incident myocardial infarction (P-interaction = 0.042) and stroke (P-interaction = 0.033). The individuals with serum 25(OH)D level of 50.0–74.9 nmol/L and rs2228570 (FokI) homozygotes had the lowest risks of vascular complications. Conclusions: Lower serum 25(OH)D levels are significantly and nonlinearly associated with an increased risk of cardiocerebrovascular diseases in prediabetic individuals, with VDR polymorphisms of rs2228570 (FokI) modify such associations. Monitoring a safe 25(OH)D concentration is suggested to prevent the vascular complications for prediabetes. [ABSTRACT FROM AUTHOR]

Background: Whether serum vitamin D mediate vascular diseases in prediabetic populations remains unclear. This study aimed to determine the associations between circulating 25-hydroxyvitamin D [25(OH)D] levels and vitamin D receptor (VDR) polymorphisms with the risk of macrovascular complications, including myocardial infarction and stroke, and microvascular complications such as diabetic nephropathy and retinopathy, among adults with prediabetes. Methods: Participants with prediabetes in UK Biobank were included (N = 56,387). Multivariable dose–response and Cox proportion models were used to explore the relationship of serum 25(OH)D status and the risks of vascular complications. The interaction of VDR polymorphisms with serum 25(OH)D level on risks of vascular events was also assessed. Results: During a median follow-up of 12 years, higher levels of 25(OH)D were significantly and nonlinearly associated with a lower risk of macrovascular diseases among prediabetic individuals. The adjusted hazard ratios (95% confidential interval) of serum 25(OH)D levels of ≥ 75.0 nmol/L versus < 25 nmol/L were 0.75 (0.63–0.88) for myocardial infarction, 0.74 (0.55–1.00) for stroke, 1.02 (0.60–1.74) for diabetic nephropathy, and 1.30 (0.92–1.84) for diabetic retinopathy, respectively. The rs2228570 (FokI) polymorphisms significantly interacted with 25(OH)D on incident myocardial infarction (P-interaction = 0.042) and stroke (P-interaction = 0.033). The individuals with serum 25(OH)D level of 50.0–74.9 nmol/L and rs2228570 (FokI) homozygotes had the lowest risks of vascular complications. Conclusions: Lower serum 25(OH)D levels are significantly and nonlinearly associated with an increased risk of cardiocerebrovascular diseases in prediabetic individuals, with VDR polymorphisms of rs2228570 (FokI) modify such associations. Monitoring a safe 25(OH)D concentration is suggested to prevent the vascular complications for prediabetes. [ABSTRACT FROM AUTHOR]