Variation in adiposity is associated with cardiometabolic disease outcomes, but mechanisms leading from this exposure to disease are unclear. This study aimed to estimate effects of body mass index ...(BMI) on an extensive set of circulating proteins.
We used SomaLogic proteomic data from up to 2737 healthy participants from the INTERVAL study. Associations between self-reported BMI and 3622 unique plasma proteins were explored using linear regression. These were complemented by Mendelian randomisation (MR) analyses using a genetic risk score (GRS) comprised of 654 BMI-associated polymorphisms from a recent genome-wide association study (GWAS) of adult BMI. A disease enrichment analysis was performed using DAVID Bioinformatics 6.8 for proteins which were altered by BMI.
Observationally, BMI was associated with 1576 proteins (P < 1.4 × 10
), with particularly strong evidence for a positive association with leptin and fatty acid-binding protein-4 (FABP4), and a negative association with sex hormone-binding globulin (SHBG). Observational estimates were likely confounded, but the GRS for BMI did not associate with measured confounders. MR analyses provided evidence for a causal relationship between BMI and eight proteins including leptin (0.63 standard deviation (SD) per SD BMI, 95% CI 0.48-0.79, P = 1.6 × 10
), FABP4 (0.64 SD per SD BMI, 95% CI 0.46-0.83, P = 6.7 × 10
) and SHBG (-0.45 SD per SD BMI, 95% CI -0.65 to -0.25, P = 1.4 × 10
). There was agreement in the magnitude of observational and MR estimates (R
= 0.33) and evidence that proteins most strongly altered by BMI were enriched for genes involved in cardiovascular disease.
This study provides evidence for a broad impact of adiposity on the human proteome. Proteins strongly altered by BMI include those involved in regulating appetite, sex hormones and inflammation; such proteins are also enriched for cardiovascular disease-related genes. Altogether, results help focus attention onto new proteomic signatures of obesity-related disease.
Fructosamine is a measure of short-term glycemic control, which has been suggested as a useful complement to glycated hemoglobin (HbA1c) for the diagnosis and monitoring of diabetes. To date, a ...single genome-wide association study (GWAS) including 8,951 U.S. White and 2,712 U.S. Black individuals without a diabetes diagnosis has been published. Results in Whites and Blacks yielded different association loci, near RCN3 and CNTN5, respectively. In this study, we performed a GWAS on 20,731 European-ancestry blood donors and meta-analyzed our results with previous data from U.S. White participants from the Atherosclerosis Risk in Communities (ARIC) study (Nmeta = 29,685). We identified a novel association near GCK (rs3757840, βmeta = 0.0062; minor allele frequency MAF = 0.49; Pmeta = 3.66 × 10-8) and confirmed the association near RCN3 (rs113886122, βmeta = 0.0134; MAF = 0.17; Pmeta = 5.71 × 10-18). Colocalization analysis with whole-blood expression quantitative trait loci data suggested FCGRT as the effector transcript at the RCN3 locus. We further showed that fructosamine has low heritability (h2 = 7.7%), has no significant genetic correlation with HbA1c and other glycemic traits in individuals without a diabetes diagnosis (P > 0.05), but has evidence of shared genetic etiology with some anthropometric traits (Bonferroni-corrected P < 0.0012). Our results broaden knowledge of the genetic architecture of fructosamine and prioritize FCGRT for downstream functional studies at the established RCN3 locus.
Objective
Cushing's syndrome is characterized by hypercortisolaemia and is frequently accompanied by comorbidities such as type 2 diabetes, hypertension, osteoporosis, depression and schizophrenia. ...It is unclear whether moderate but lifelong hypercortisolaemia is causally associated with these diseases in the general population. We aimed to address this research gap using a Mendelian randomization approach.
Methods
We used three cortisol‐associated genetic variants in the SERPINA6/SERPINA1 region as genetic instruments in a two‐sample, inverse‐variance‐weighted Mendelian randomization analysis. We obtained summary‐level statistics for cortisol and disease outcomes from publicly available genetic consortia, and meta‐analysed them as appropriate. We conducted a multivariable Mendelian randomization analysis to assess potential mediating effects.
Results
A 1 standard deviation higher genetically predicted plasma cortisol was associated with greater odds of hypertension (odds ratio: 1.12; 95% confidence interval CI: 1.05–1.18) as well as higher systolic blood pressure (mean difference MD: 0.03 SD change; 95% CI: 0.01–0.05) and diastolic blood pressure (MD: 0.03 SD change; 95% CI: 0.01–0.04). There was no evidence of association with type 2 diabetes, osteoporosis, depression and schizophrenia. The association with hypertension was attenuated upon adjustment for waist circumference, suggesting potential mediation through central obesity.
Conclusion
There is strong evidence for a causal association between plasma cortisol and greater risk for hypertension, potentially mediated by obesity.
Higher body mass index (BMI) is a risk factor for thrombosis. Platelets are essential for hemostasis but contribute to thrombosis when activated pathologically. We hypothesized that higher BMI leads ...to changes in platelet characteristics, thereby increasing thrombotic risk. The effect of BMI on platelet traits (measured by Sysmex) was explored in 33 388 UK blood donors (INTERVAL study). Linear regression showed that higher BMI was positively associated with greater plateletcrit (PCT), platelet count (PLT), immature platelet count (IPC), and side fluorescence (SFL, a measure of mRNA content used to derive IPC). Mendelian randomization (MR), applied to estimate a causal effect with BMI proxied by a genetic risk score, provided causal estimates for a positive effect of BMI on both SFL and IPC, but there was little evidence for a causal effect of BMI on PCT or PLT. Follow-up analyses explored the functional relevance of platelet characteristics in a pre-operative cardiac cohort (COPTIC). Linear regression provided observational evidence for a positive association between IPC and agonist-induced whole blood platelet aggregation. Results indicate that higher BMI raises the number of immature platelets, which is associated with greater whole blood platelet aggregation in a cardiac cohort. Higher IPC could therefore contribute to obesity-related thrombosis.
Abstract
Aim
To investigate the associations between major foods and dietary fibre with subtypes of stroke in a large prospective cohort.
Methods and results
We analysed data on 418 329 men and women ...from nine European countries, with an average of 12.7 years of follow-up. Diet was assessed using validated country-specific questionnaires which asked about habitual intake over the past year, calibrated using 24-h recalls. Multivariable-adjusted Cox regressions were used to estimate hazard ratios (HRs) for ischaemic and haemorrhagic stroke associated with consumption of red and processed meat, poultry, fish, dairy foods, eggs, cereals, fruit and vegetables, legumes, nuts and seeds, and dietary fibre. For ischaemic stroke (4281 cases), lower risks were observed with higher consumption of fruit and vegetables combined (HR; 95% CI per 200 g/day higher intake, 0.87; 0.82–0.93, P-trend < 0.001), dietary fibre (per 10 g/day, 0.77; 0.69–0.86, P-trend < 0.001), milk (per 200 g/day, 0.95; 0.91–0.99, P-trend = 0.02), yogurt (per 100 g/day, 0.91; 0.85–0.97, P-trend = 0.004), and cheese (per 30 g/day, 0.88; 0.81–0.97, P-trend = 0.008), while higher risk was observed with higher red meat consumption which attenuated when adjusted for the other statistically significant foods (per 50 g/day, 1.07; 0.96–1.20, P-trend = 0.20). For haemorrhagic stroke (1430 cases), higher risk was associated with higher egg consumption (per 20 g/day, 1.25; 1.09–1.43, P-trend = 0.002).
Conclusion
Risk of ischaemic stroke was inversely associated with consumption of fruit and vegetables, dietary fibre, and dairy foods, while risk of haemorrhagic stroke was positively associated with egg consumption. The apparent differences in the associations highlight the importance of examining ischaemic and haemorrhagic stroke subtypes separately.
Metabolite levels measured in the human population are endophenotypes for biological processes. We combined sequencing data for 3,924 (whole-exome sequencing, WES, discovery) and 2,805 (whole-genome ...sequencing, WGS, replication) donors from a prospective cohort of blood donors in England. We used multiple approaches to select and aggregate rare genetic variants (minor allele frequency MAF < 0.1%) in protein-coding regions and tested their associations with 995 metabolites measured in plasma by using ultra-high-performance liquid chromatography–tandem mass spectrometry. We identified 40 novel associations implicating rare coding variants (27 genes and 38 metabolites), of which 28 (15 genes and 28 metabolites) were replicated. We developed algorithms to prioritize putative driver variants at each locus and used mediation and Mendelian randomization analyses to test directionality at associations of metabolite and protein levels at the ACY1 locus. Overall, 66% of reported associations implicate gene targets of approved drugs or bioactive drug-like compounds, contributing to drug targets' validating efforts.
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Excess bodyweight and related metabolic perturbations have been implicated in kidney cancer aetiology, but the specific molecular mechanisms underlying these relationships are poorly understood. In ...this study, we sought to identify circulating metabolites that predispose kidney cancer and to evaluate the extent to which they are influenced by body mass index (BMI).
We assessed the association between circulating levels of 1,416 metabolites and incident kidney cancer using pre-diagnostic blood samples from up to 1,305 kidney cancer case-control pairs from 5 prospective cohort studies. Cases were diagnosed on average 8 years after blood collection. We found 25 metabolites robustly associated with kidney cancer risk. In particular, 14 glycerophospholipids (GPLs) were inversely associated with risk, including 8 phosphatidylcholines (PCs) and 2 plasmalogens. The PC with the strongest association was PC ae C34:3 with an odds ratio (OR) for 1 standard deviation (SD) increment of 0.75 (95% confidence interval CI: 0.68 to 0.83, p = 2.6 × 10-8). In contrast, 4 amino acids, including glutamate (OR for 1 SD = 1.39, 95% CI: 1.20 to 1.60, p = 1.6 × 10-5), were positively associated with risk. Adjusting for BMI partly attenuated the risk association for some-but not all-metabolites, whereas other known risk factors of kidney cancer, such as smoking and alcohol consumption, had minimal impact on the observed associations. A mendelian randomisation (MR) analysis of the influence of BMI on the blood metabolome highlighted that some metabolites associated with kidney cancer risk are influenced by BMI. Specifically, elevated BMI appeared to decrease levels of several GPLs that were also found inversely associated with kidney cancer risk (e.g., -0.17 SD change ßBMI in 1-(1-enyl-palmitoyl)-2-linoleoyl-GPC (P-16:0/18:2) levels per SD change in BMI, p = 3.4 × 10-5). BMI was also associated with increased levels of glutamate (ßBMI: 0.12, p = 1.5 × 10-3). While our results were robust across the participating studies, they were limited to study participants of European descent, and it will, therefore, be important to evaluate if our findings can be generalised to populations with different genetic backgrounds.
This study suggests a potentially important role of the blood metabolome in kidney cancer aetiology by highlighting a wide range of metabolites associated with the risk of developing kidney cancer and the extent to which changes in levels of these metabolites are driven by BMI-the principal modifiable risk factor of kidney cancer.
Genetic, lifestyle, and environmental factors can lead to perturbations in circulating lipid levels and increase the risk of cardiovascular and metabolic diseases. However, how changes in individual ...lipid species contribute to disease risk is often unclear. Moreover, little is known about the role of lipids on cardiovascular disease in Pakistan, a population historically underrepresented in cardiovascular studies.
We characterised the genetic architecture of the human blood lipidome in 5662 hospital controls from the Pakistan Risk of Myocardial Infarction Study (PROMIS) and 13,814 healthy British blood donors from the INTERVAL study. We applied a candidate causal gene prioritisation tool to link the genetic variants associated with each lipid to the most likely causal genes, and Gaussian Graphical Modelling network analysis to identify and illustrate relationships between lipids and genetic loci.
We identified 253 genetic associations with 181 lipids measured using direct infusion high-resolution mass spectrometry in PROMIS, and 502 genetic associations with 244 lipids in INTERVAL. Our analyses revealed new biological insights at genetic loci associated with cardiometabolic diseases, including novel lipid associations at the LPL, MBOAT7, LIPC, APOE-C1-C2-C4, SGPP1, and SPTLC3 loci.
Our findings, generated using a distinctive lipidomics platform in an understudied South Asian population, strengthen and expand the knowledge base of the genetic determinants of lipids and their association with cardiometabolic disease-related loci.
Garrod's concept of 'chemical individuality' has contributed to comprehension of the molecular origins of human diseases. Untargeted high-throughput metabolomic technologies provide an in-depth ...snapshot of human metabolism at scale. We studied the genetic architecture of the human plasma metabolome using 913 metabolites assayed in 19,994 individuals and identified 2,599 variant-metabolite associations (P < 1.25 × 10
) within 330 genomic regions, with rare variants (minor allele frequency ≤ 1%) explaining 9.4% of associations. Jointly modeling metabolites in each region, we identified 423 regional, co-regulated, variant-metabolite clusters called genetically influenced metabotypes. We assigned causal genes for 62.4% of these genetically influenced metabotypes, providing new insights into fundamental metabolite physiology and clinical relevance, including metabolite-guided discovery of potential adverse drug effects (DPYD and SRD5A2). We show strong enrichment of inborn errors of metabolism-causing genes, with examples of metabolite associations and clinical phenotypes of non-pathogenic variant carriers matching characteristics of the inborn errors of metabolism. Systematic, phenotypic follow-up of metabolite-specific genetic scores revealed multiple potential etiological relationships.
Background Older age is the most powerful risk factor for adverse coronavirus disease-19 (COVID-19) outcomes. It is uncertain whether leucocyte telomere length (LTL), previously proposed as a marker ...of biological age, is also associated with COVID-19 outcomes.
Methods We associated LTL values obtained from participants recruited into UK Biobank (UKB) during 2006–2010 with adverse COVID-19 outcomes recorded by 30 November 2020, defined as a composite of any of the following: hospital admission, need for critical care, respiratory support, or mortality. Using information on 130 LTL-associated genetic variants, we conducted exploratory Mendelian randomisation (MR) analyses in UKB to evaluate whether observational associations might reflect cause-and-effect relationships.
Findings Of 6775 participants in UKB who tested positive for infection with SARS-CoV-2 in the community, there were 914 (13.5%) with adverse COVID-19 outcomes. The odds ratio (OR) for adverse COVID-19 outcomes was 1·17 (95% CI 1·05–1·30; P = 0·004) per 1-SD shorter usual LTL, after adjustment for age, sex and ethnicity. Similar ORs were observed in analyses that: adjusted for additional risk factors; disaggregated the composite outcome and reduced the scope for selection or collider bias. In MR analyses, the OR for adverse COVID-19 outcomes was directionally concordant but non-significant.
Interpretation Shorter LTL is associated with higher risk of adverse COVID-19 outcomes, independent of several major risk factors for COVID-19 including age. Further data are needed to determine whether this association reflects causality.
Funding UK Medical Research Council, Biotechnology and Biological Sciences Research Council and British Heart Foundation.