PCSK9 genetic variants and risk of vascular and non-vascular diseases in Chinese and UK populations

AIM

Lowering low-density lipoprotein cholesterol (LDL-C) through PCSK9 inhibition represents a new therapeutic approach to preventing and treating cardiovascular disease (CVD). Phenome-wide analyses of PCSK9 genetic variants in large biobanks can help to identify unexpected effects of PCSK9 inhibition.

METHODS

In the prospective China Kadoorie Biobank, we constructed a genetic score using three variants at the PCSK9 locus associated with directly-measured LDL-C (PCSK9-GS). Logistic regression gave estimated odds ratios (ORs) for PCSK9-GS associations with CVD and non-CVD outcomes, scaled to 1SD lower LDL-C.

RESULTS

PCSK9-GS was associated with lower risks of carotid plaque (n=8340 cases; OR=0.61 [95%CI: 0.45-0.83]; P=0.0015), major occlusive vascular events (n=15,752; 0.80 [0.67-0.95]; P=0.011), and ischaemic stroke (n=11,467; 0.80 [0.66-0.98]; P=0.029). However, PCSK9-GS was also associated with higher risk of hospitalisation with chronic obstructive pulmonary disease (COPD: n=6836; 1.38 [1.08-1.76]; P=0.0089), and with even higher risk of fatal exacerbations among individuals with pre-existing COPD (n=730; 3.61 [1.71-7.60]; P=7.3x10-4). We also replicated associations for a PCSK9 variant, reported in UK Biobank, with increased risks of acute upper respiratory tract infection (URTI) (pooled OR after meta-analysis of 1.87 ([1.38-2.54]; P=5.4x10-5) and self-reported asthma (pooled OR 1.17 ([1.04-1.30]; P=0.0071). There was no association of a polygenic LDL-C score with COPD hospitalisation, COPD exacerbation, or URTI.

CONCLUSIONS

LDL-C-lowering PCSK9 genetic variants are associated with lower risk of subclinical and clinical atherosclerotic vascular disease, but higher risks of respiratory diseases. Pharmacovigilance studies may be required to monitor patients treated with therapeutic PCSK9 inhibitors for exacerbations of respiratory diseases or respiratory tract infections.

Central Adiposity Increases Risk of Kidney Stone Disease through Effects on Serum Calcium Concentrations

SIGNIFICANCE STATEMENT

Kidney stone disease is a common disorder with poorly understood pathophysiology. Observational and genetic studies indicate that adiposity is associated with an increased risk of kidney stone disease. However, the relative contribution of general and central adipose depots and the mechanisms by which effects of adiposity on kidney stone disease are mediated have not been defined. Using conventional and genetic epidemiological techniques, we demonstrate that general and central adiposity are independently associated with kidney stone disease. In addition, one mechanism by which central adiposity increases risk of kidney stone disease is by increasing serum calcium concentration. Therapies targeting adipose depots may affect calcium homeostasis and help to prevent kidney stone disease.

BACKGROUND

Kidney stone disease affects approximately 10% of individuals in their lifetime and is frequently recurrent. The disease is linked to obesity, but the mechanisms mediating this association are uncertain.

METHODS

Associations of adiposity and incident kidney stone disease were assessed in the UK Biobank over a mean of 11.6 years/person. Genome-wide association studies and Mendelian randomization (MR) analyses were undertaken in the UK Biobank, FinnGen, and in meta-analyzed cohorts to identify factors that affect kidney stone disease risk.

RESULTS

Observational analyses on UK Biobank data demonstrated that increasing central and general adiposity is independently associated with incident kidney stone formation. Multivariable MR, using meta-analyzed UK Biobank and FinnGen data, established that risk of kidney stone disease increases by approximately 21% per one standard deviation increase in body mass index (BMI, a marker of general adiposity) independent of waist-to-hip ratio (WHR, a marker of central adiposity) and approximately 24% per one standard deviation increase of WHR independent of BMI. Genetic analyses indicate that higher WHR, but not higher BMI, increases risk of kidney stone disease by elevating adjusted serum calcium concentrations (β=0.12 mmol/L); WHR mediates 12%-15% of its effect on kidney stone risk in this way.

CONCLUSIONS

Our study indicates that visceral adipose depots elevate serum calcium concentrations, resulting in increased risk of kidney stone disease. These findings highlight the importance of weight loss in individuals with recurrent kidney stones and suggest that therapies targeting adipose depots may affect calcium homeostasis and contribute to prevention of kidney stone disease.

Plasma Proteomics to Identify Drug Targets for Ischemic Heart Disease

BACKGROUND

Integrated analyses of plasma proteomic and genetic markers in prospective studies can clarify the causal relevance of proteins and discover novel targets for ischemic heart disease (IHD) and other diseases.

OBJECTIVES

The purpose of this study was to examine associations of proteomics and genetics data with IHD in population studies to discover novel preventive treatments.

METHODS

We conducted a nested case-cohort study in the China Kadoorie Biobank (CKB) involving 1,971 incident IHD cases and 2,001 subcohort participants who were genotyped and free of prior cardiovascular disease. We measured 1,463 proteins in the stored baseline samples using the OLINK EXPLORE panel. Cox regression yielded adjusted HRs for IHD associated with individual proteins after accounting for multiple testing. Moreover, cis-protein quantitative loci (pQTLs) identified for proteins in genome-wide association studies of CKB and of UK Biobank were used as instrumental variables in separate 2-sample Mendelian randomization (MR) studies involving global CARDIOGRAM+C4D consortium (210,842 IHD cases and 1,378,170 controls).

RESULTS

Overall 361 proteins were significantly associated at false discovery rate <0.05 with risk of IHD (349 positively, 12 inversely) in CKB, including N-terminal prohormone of brain natriuretic peptide and proprotein convertase subtilisin/kexin type 9. Of these 361 proteins, 212 had cis-pQTLs in CKB, and MR analyses of 198 variants in CARDIOGRAM+C4D identified 13 proteins that showed potentially causal associations with IHD. Independent MR analyses of 307 cis-pQTLs identified in Europeans replicated associations for 4 proteins (FURIN, proteinase-activated receptor-1, Asialoglycoprotein receptor-1, and matrix metalloproteinase-3). Further downstream analyses showed that FURIN, which is highly expressed in endothelial cells, is a potential novel target and matrix metalloproteinase-3 a potential repurposing target for IHD.

CONCLUSIONS

Integrated analyses of proteomic and genetic data in Chinese and European adults provided causal support for FURIN and multiple other proteins as potential novel drug targets for treatment of IHD.

Prediction of Cardiometabolic Health Through Changes in Plasma Proteins With Intentional Weight Loss in the DiRECT and DIADEM-I Randomized Clinical Trials of Type 2 Diabetes Remission

OBJECTIVE

To determine the extent to which changes in plasma proteins, previously predictive of cardiometabolic outcomes, predict changes in two diabetes remission trials.

RESEARCH DESIGN AND METHODS

We applied SomaSignal predictive tests (each derived from ∼5,000 plasma protein measurements using aptamer-based proteomics assay) to baseline and 1-year samples of trial intervention (Diabetes Remission Clinical Trial [DiRECT], n = 118, and Diabetes Intervention Accentuating Diet and Enhancing Metabolism [DIADEM-I], n = 66) and control (DiRECT, n = 144, DIADEM-I, n = 76) group participants.

RESULTS

Mean (SD) weight loss in DiRECT (U.K.) and DIADEM-I (Qatar) was 10.2 (7.4) kg and 12.1 (9.5) kg, respectively, vs. 1.0 (3.7) kg and 4.0 (5.4) kg in control groups. Cardiometabolic SomaSignal test results showed significant improvement (Bonferroni-adjusted P < 0.05) in DiRECT and DIADEM-I (expressed as relative difference, intervention minus control) as follows, respectively: liver fat (-26.4%, -37.3%), glucose tolerance (-36.6%, -37.4%), body fat percentage (-8.6%, -8.7%), resting energy rate (-8.0%, -5.1%), visceral fat (-34.3%, -26.1%), and cardiorespiratory fitness (9.5%, 10.3%). Cardiovascular risk (measured with SomaSignal tests) also improved in intervention groups relative to control, but this was significant only in DiRECT (DiRECT, -44.2%, and DIADEM-I, -9.2%). However, weight loss >10 kg predicted significant reductions in cardiovascular risk, -19.1% (95% CI -33.4 to -4.91) in DiRECT and -33.4% (95% CI -57.3, -9.6) in DIADEM-I. DIADEM-I also demonstrated rapid emergence of metabolic improvements at 3 months.

CONCLUSIONS

Intentional weight loss in recent-onset type 2 diabetes rapidly induces changes in protein-based risk models consistent with widespread cardiometabolic improvements, including cardiorespiratory fitness. Protein changes with greater (>10 kg) weight loss also predicted lower cardiovascular risk, providing a positive outlook for relevant ongoing trials.

Lowering of Circulating Sclerostin May Increase Risk of Atherosclerosis and Its Risk Factors: Evidence From a Genome-Wide Association Meta-Analysis Followed by Mendelian Randomization

OBJECTIVE

In this study, we aimed to establish the causal effects of lowering sclerostin, target of the antiosteoporosis drug romosozumab, on atherosclerosis and its risk factors.

METHODS

A genome-wide association study meta-analysis was performed of circulating sclerostin levels in 33,961 European individuals. Mendelian randomization (MR) was used to predict the causal effects of sclerostin lowering on 15 atherosclerosis-related diseases and risk factors.

RESULTS

We found that 18 conditionally independent variants were associated with circulating sclerostin. Of these, 1 cis signal in SOST and 3 trans signals in B4GALNT3, RIN3, and SERPINA1 regions showed directionally opposite signals for sclerostin levels and estimated bone mineral density. Variants with these 4 regions were selected as genetic instruments. MR using 5 correlated cis-SNPs suggested that lower sclerostin increased the risk of type 2 diabetes mellitus (DM) (odds ratio [OR] 1.32 [95% confidence interval (95% CI) 1.03-1.69]) and myocardial infarction (MI) (OR 1.35 [95% CI 1.01-1.79]); sclerostin lowering was also suggested to increase the extent of coronary artery calcification (CAC) (β = 0.24 [95% CI 0.02-0.45]). MR using both cis and trans instruments suggested that lower sclerostin increased hypertension risk (OR 1.09 [95% CI 1.04-1.15]), but otherwise had attenuated effects.

CONCLUSION

This study provides genetic evidence to suggest that lower levels of sclerostin may increase the risk of hypertension, type 2 DM, MI, and the extent of CAC. Taken together, these findings underscore the requirement for strategies to mitigate potential adverse effects of romosozumab treatment on atherosclerosis and its related risk factors.

Efficacy of metformin targets on cardiometabolic health in the general population and non-diabetic individuals: a Mendelian randomization study

BACKGROUND

Metformin shows beneficial effects on cardiometabolic health in diabetic individuals. However, the beneficial effects in the general population, especially in non-diabetic individuals are unclear. We aim to estimate the effects of perturbation of seven metformin targets on cardiometabolic health using Mendelian randomization (MR).

METHODS

Genetic variants close to metformin-targeted genes associated with expression of the corresponding genes and glycated haemoglobin (HbA1c) level were used to proxy therapeutic effects of seven metformin-related drug targets. Eight cardiometabolic phenotypes under metformin trials were selected as outcomes (average N = 466,947). MR estimates representing the weighted average effects of the seven effects of metformin targets on the eight outcomes were generated. One-sample MR was applied to estimate the averaged and target-specific effects in 338,425 non-diabetic individuals in UK Biobank.

FINDINGS

Genetically proxied averaged effects of five metformin targets, equivalent to a 0.62% reduction of HbA1c level, was associated with 37.8% lower risk of coronary artery disease (CAD) (odds ratio [OR] = 0.62, 95% confidence interval [CI] = 0.46-0.84), lower levels of body mass index (BMI) (β = -0.22, 95% CI = -0.35 to -0.09), systolic blood pressure (SBP) (β = -0.19, 95% CI = -0.28 to -0.09) and diastolic blood pressure (DBP) levels (β = -0.29, 95% CI = -0.39 to -0.19). One-sample MR suggested that the seven metformin targets showed averaged and target-specific beneficial effects on BMI, SBP and DBP in non-diabetic individuals.

INTERPRETATION

This study showed that perturbation of seven metformin targets has beneficial effects on BMI and blood pressure in non-diabetic individuals. Clinical trials are needed to investigate whether similar effects can be achieved with metformin medications.

FUNDING

Funding information is provided in the Acknowledgements.

bubbleHeatmap: an R package for visualization of nightingale health metabolomics datasets

Summary

We present bubbleHeatmap, an R plotting package which combines elements of a bubble plot and heatmap to conveniently display two numerical variables for each data point across a categorical two dimensional grid. This has particular advantages for visualizing the 251 metabolomic measures produced by the automated, high-throughput, 1H-NMR-based platform provided by Nightingale Health, which includes 12 measures repeated across each of 14 lipoprotein subclasses. As these metabolomic profiles are currently available for large biobanks, we provide a figure template to aid the use of bubbleHeatmap in displaying results from analyses using these data.

Availability and implementation

https://cran.r-project.org/web/packages/bubbleHeatmap.

Guidelines for performing Mendelian randomization investigations: update for summer 2023

This paper provides guidelines for performing Mendelian randomization investigations. It is aimed at practitioners seeking to undertake analyses and write up their findings, and at journal editors and reviewers seeking to assess Mendelian randomization manuscripts. The guidelines are divided into ten sections: motivation and scope, data sources, choice of genetic variants, variant harmonization, primary analysis, supplementary and sensitivity analyses (one section on robust statistical methods and one on other approaches), extensions and additional analyses, data presentation, and interpretation. These guidelines will be updated based on feedback from the community and advances in the field. Updates will be made periodically as needed, and at least every 24 months.

Leveraging family history data to disentangle time-varying effects on disease risk using lifecourse mendelian randomization

Lifecourse Mendelian randomization is a causal inference technique which harnesses genetic variants with time-varying effects to develop insight into the influence of age-dependent lifestyle factors on disease risk. Here, we apply this approach to evaluate whether childhood body size has a direct consequence on 8 major disease endpoints by analysing parental history data from the UK Biobank study.Our findings suggest that, whilst childhood body size increases later risk of outcomes such as heart disease (odds ratio (OR) = 1.15, 95% CI = 1.07 to 1.23, P = 7.8 × 10- 5) and diabetes (OR = 1.43, 95% CI = 1.31 to 1.56, P = 9.4 × 10- 15) based on parental history data, these findings are likely attributed to a sustained influence of being overweight for many years over the lifecourse. Likewise, we found evidence that remaining overweight throughout the lifecourse increases risk of lung cancer, which was partially mediated by lifetime smoking index. In contrast, using parental history data provided evidence that being overweight in childhood may have a protective effect on risk of breast cancer (OR = 0.87, 95% CI = 0.78 to 0.97, P = 0.01), corroborating findings from observational studies and large-scale genetic consortia.Large-scale family disease history data can provide a complementary source of evidence for epidemiological studies to exploit, particularly given that they are likely more robust to sources of selection bias (e.g. survival bias) compared to conventional case control studies. Leveraging these data using approaches such as lifecourse Mendelian randomization can help elucidate additional layers of evidence to dissect age-dependent effects on disease risk.

Genetic analyses identify brain structures related to cognitive impairment associated with elevated blood pressure

BACKGROUND AND AIMS

Observational studies have linked elevated blood pressure (BP) to impaired cognitive function. However, the functional and structural changes in the brain that mediate the relationship between BP elevation and cognitive impairment remain unknown. Using observational and genetic data from large consortia, this study aimed to identify brain structures potentially associated with BP values and cognitive function.

METHODS AND RESULTS

Data on BP were integrated with 3935 brain magnetic resonance imaging-derived phenotypes (IDPs) and cognitive function defined by fluid intelligence score. Observational analyses were performed in the UK Biobank and a prospective validation cohort. Mendelian randomisation (MR) analyses used genetic data derived from the UK Biobank, International Consortium for Blood Pressure, and COGENT consortium. Mendelian randomisation analysis identified a potentially adverse causal effect of higher systolic BP on cognitive function [-0.044 standard deviation (SD); 95% confidence interval (CI) -0.066, -0.021] with the MR estimate strengthening (-0.087 SD; 95% CI -0.132, -0.042), when further adjusted for diastolic BP. Mendelian randomisation analysis found 242, 168, and 68 IDPs showing significant (false discovery rate P < 0.05) association with systolic BP, diastolic BP, and pulse pressure, respectively. Most of these IDPs were inversely associated with cognitive function in observational analysis in the UK Biobank and showed concordant effects in the validation cohort. Mendelian randomisation analysis identified relationships between cognitive function and the nine of the systolic BP-associated IDPs, including the anterior thalamic radiation, anterior corona radiata, or external capsule.

CONCLUSION

Complementary MR and observational analyses identify brain structures associated with BP, which may be responsible for the adverse effects of hypertension on cognitive performance.

Distinct metabolic features of genetic liability to type 2 diabetes and coronary artery disease: a reverse Mendelian randomization study

BACKGROUND

Type 2 diabetes (T2D) and coronary artery disease (CAD) both have known genetic determinants, but the mechanisms through which their associated genetic variants lead to disease onset remain poorly understood.

METHODS

We used large-scale metabolomics data in a two-sample reverse Mendelian randomization (MR) framework to estimate effects of genetic liability to T2D and CAD on 249 circulating metabolites in the UK Biobank (N = 118,466). We examined the potential for medication use to distort effect estimates by conducting age-stratified metabolite analyses.

FINDINGS

Using inverse variance weighted (IVW) models, higher genetic liability to T2D was estimated to decrease high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) (e.g.

, HDL-C

 -0.05 SD; 95% CI -0.07 to -0.03, per doubling of liability), whilst increasing all triglyceride groups and branched chain amino acids (BCAAs). IVW estimates for CAD liability suggested an effect on reducing HDL-C as well as raising very-low density lipoprotein cholesterol (VLDL-C) and LDL-C. In pleiotropy-robust models, T2D liability was still estimated to increase BCAAs, but several estimates for higher CAD liability reversed and supported decreased LDL-C and apolipoprotein-B. Estimated effects of CAD liability differed substantially by age for non-HDL-C traits, with higher CAD liability lowering LDL-C only at older ages when statin use was common.

INTERPRETATION

Overall, our results support largely distinct metabolic features of genetic liability to T2D and CAD, illustrating both challenges and opportunities for preventing these commonly co-occurring diseases.

FUNDING

Wellcome Trust [218495/Z/19/Z], UK MRC [MC_UU_00011/1; MC_UU_00011/4], the University of Bristol, Diabetes UK [17/0005587], World Cancer Research Fund [IIG_2019_2009].

Disentangling the relationship between depression and chronic widespread pain: A Mendelian randomisation study

OBJECTIVE

Depression and chronic widespread pain (CWP) frequently coexist, but whether depression is an independent causal risk factor for CWP, and/or vice versa, remains unclear. We investigated the bidirectional causal relationship between depression and CWP.

METHODS

We performed a two-sample Mendelian randomisation (MR) study to estimate the causal relationship between genetically predicted depression (170,756 cases, 329,443 controls) and risk of CWP (6,914 cases, 242,929 controls), and the effect of CWP on depression susceptibility, using large population-level genetic data. We used a new MR method, Causal Analysis Using Summary Effect estimates (CAUSE), which allows for sample overlap, in addition to traditional MR and sensitivity analyses.

RESULTS

For each doubling in odds of genetic liability to depression, the risk of chronic widespread pain was increased (OR 1.004, 95% credible interval 1.003-1.005; p = 7.3 × 10^-5 that the causal model is a better fit than non-causal model). There was bidirectional evidence of causality, with genetic liability to chronic widespread pain increasing depression susceptibility (OR 2.31; 95%CrI 1.57, 3.40; p = 0.0026 that the causal model is a better fit). Other MR methods produced concordant results.

CONCLUSIONS

This study provides evidence in support of a bidirectional causal relationship between depression and increased risk of chronic widespread pain, whilst overcoming the major limitations of previous epidemiological studies. Interventions for depression may be an effective strategy to prevent or reduce the burden of chronic widespread pain and vice versa.

Circulating insulin-like growth factors and risks of overall, aggressive and early-onset prostate cancer: a collaborative analysis of 20 prospective studies and Mendelian randomization analysis

BACKGROUND

Previous studies had limited power to assess the associations of circulating insulin-like growth factors (IGFs) and IGF-binding proteins (IGFBPs) with clinically relevant prostate cancer as a primary endpoint, and the association of genetically predicted IGF-I with aggressive prostate cancer is not known. We aimed to investigate the associations of IGF-I, IGF-II, IGFBP-1, IGFBP-2 and IGFBP-3 concentrations with overall, aggressive and early-onset prostate cancer.

METHODS

Prospective analysis of biomarkers using the Endogenous Hormones, Nutritional Biomarkers and Prostate Cancer Collaborative Group dataset (up to 20 studies, 17 009 prostate cancer cases, including 2332 aggressive cases). Odds ratios (OR) and 95% confidence intervals (CI) for prostate cancer were estimated using conditional logistic regression. For IGF-I, two-sample Mendelian randomization (MR) analysis was undertaken using instruments identified using UK Biobank (158 444 men) and outcome data from PRACTICAL (up to 85 554 cases, including 15 167 aggressive cases). Additionally, we used colocalization to rule out confounding by linkage disequilibrium.

RESULTS

In observational analyses, IGF-I was positively associated with risks of overall (OR per 1 SD = 1.09: 95% CI 1.07, 1.11), aggressive (1.09: 1.03, 1.16) and possibly early-onset disease (1.11: 1.00, 1.24); associations were similar in MR analyses (OR per 1 SD = 1.07: 1.00, 1.15; 1.10: 1.01, 1.20; and 1.13; 0.98, 1.30, respectively). Colocalization also indicated a shared signal for IGF-I and prostate cancer (PP4: 99%). Men with higher IGF-II (1.06: 1.02, 1.11) and IGFBP-3 (1.08: 1.04, 1.11) had higher risks of overall prostate cancer, whereas higher IGFBP-1 was associated with a lower risk (0.95: 0.91, 0.99); these associations were attenuated following adjustment for IGF-I.

CONCLUSIONS

These findings support the role of IGF-I in the development of prostate cancer, including for aggressive disease.

Fibroblast Growth Factor-23 and Risk of Cardiovascular Diseases: A Mendelian Randomization Study

BACKGROUND

Fibroblast growth factor-23 (FGF-23) is associated with a range of cardiovascular and noncardiovascular diseases in conventional epidemiological studies, but substantial residual confounding may exist. Mendelian randomization approaches can help control for such confounding.

METHODS

SCALLOP Consortium data of 19,195 participants were used to generate an FGF-23 genetic score. Data from 337,448 UK Biobank participants were used to estimate associations between higher genetically predicted FGF-23 concentration and the odds of any atherosclerotic cardiovascular disease (n=26,266 events), nonatherosclerotic cardiovascular disease (n=12,652), and noncardiovascular diseases previously linked to FGF-23. Measurements of carotid intima-media thickness and left ventricular mass were available in a subset. Associations with cardiovascular outcomes were also tested in three large case-control consortia: CARDIOGRAMplusC4D (coronary artery disease, n=181,249 cases), MEGASTROKE (stroke, n=34,217), and HERMES (heart failure, n=47,309).

RESULTS

We identified 34 independent variants for circulating FGF-23, which formed a validated genetic score. There were no associations between genetically predicted FGF-23 and any of the cardiovascular or noncardiovascular outcomes. In UK Biobank, the odds ratio (OR) for any atherosclerotic cardiovascular disease per 1-SD higher genetically predicted logFGF-23 was 1.03 (95% confidence interval [95% CI], 0.98 to 1.08), and for any nonatherosclerotic cardiovascular disease, it was 1.01 (95% CI, 0.94 to 1.09). The ORs in the case-control consortia were 1.00 (95% CI, 0.97 to 1.03) for coronary artery disease, 1.01 (95% CI, 0.95 to 1.07) for stroke, and 1.00 (95% CI, 0.95 to 1.05) for heart failure. In those with imaging, logFGF-23 was not associated with carotid or cardiac abnormalities.

CONCLUSIONS

Genetically predicted FGF-23 levels are not associated with atherosclerotic and nonatherosclerotic cardiovascular diseases, suggesting no important causal link.

PODCAST

This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/CJASN/2023_01_10_CJN05080422.mp3.

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

BACKGROUND

Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery.

RESULTS

To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism.

CONCLUSIONS

Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.

The impact of fatty acids biosynthesis on the risk of cardiovascular diseases in Europeans and East Asians: a Mendelian randomization study

Despite early interest, the evidence linking fatty acids to cardiovascular diseases (CVDs) remains controversial. We used Mendelian randomization to explore the involvement of polyunsaturated (PUFA) and monounsaturated (MUFA) fatty acids biosynthesis in the etiology of several CVD endpoints in up to 1 153 768 European (maximum 123 668 cases) and 212 453 East Asian (maximum 29 319 cases) ancestry individuals. As instruments, we selected single nucleotide polymorphisms mapping to genes with well-known roles in PUFA (i.e. FADS1/2 and ELOVL2) and MUFA (i.e. SCD) biosynthesis. Our findings suggest that higher PUFA biosynthesis rate (proxied by rs174576 near FADS1/2) is related to higher odds of multiple CVDs, particularly ischemic stroke, peripheral artery disease and venous thromboembolism, whereas higher MUFA biosynthesis rate (proxied by rs603424 near SCD) is related to lower odds of coronary artery disease among Europeans. Results were unclear for East Asians as most effect estimates were imprecise. By triangulating multiple approaches (i.e. uni-/multi-variable Mendelian randomization, a phenome-wide scan, genetic colocalization and within-sibling analyses), our results are compatible with higher low-density lipoprotein (LDL) cholesterol (and possibly glucose) being a downstream effect of higher PUFA biosynthesis rate. Our findings indicate that PUFA and MUFA biosynthesis are involved in the etiology of CVDs and suggest LDL cholesterol as a potential mediating trait between PUFA biosynthesis and CVDs risk.

Constructing an atlas of associations between polygenic scores from across the human phenome and circulating metabolic biomarkers

Background

Polygenic scores (PGS) are becoming an increasingly popular approach to predict complex disease risk, although they also hold the potential to develop insight into the molecular profiles of patients with an elevated genetic predisposition to disease.

Methods

We sought to construct an atlas of associations between 125 different PGS derived using results from genome-wide association studies and 249 circulating metabolites in up to 83,004 participants from the UK Biobank.

Results

As an exemplar to demonstrate the value of this atlas, we conducted a hypothesis-free evaluation of all associations with glycoprotein acetyls (GlycA), an inflammatory biomarker. Using bidirectional Mendelian randomization, we find that the associations highlighted likely reflect the effect of risk factors, such as adiposity or liability towards smoking, on systemic inflammation as opposed to the converse direction. Moreover, we repeated all analyses in our atlas within age strata to investigate potential sources of collider bias, such as medication usage. This was exemplified by comparing associations between lipoprotein lipid profiles and the coronary artery disease PGS in the youngest and oldest age strata, which had differing proportions of individuals undergoing statin therapy. Lastly, we generated all PGS-metabolite associations stratified by sex and separately after excluding 13 established lipid-associated loci to further evaluate the robustness of findings.

Conclusions

We envisage that the atlas of results constructed in our study will motivate future hypothesis generation and help prioritize and deprioritize circulating metabolic traits for in-depth investigations. All results can be visualized and downloaded at http://mrcieu.mrsoftware.org/metabolites_PRS_atlas.

Funding

This work is supported by funding from the Wellcome Trust, the British Heart Foundation, and the Medical Research Council Integrative Epidemiology Unit.

Constructing an atlas of associations between polygenic scores from across the human phenome and circulating metabolic biomarkers

BACKGROUND

Polygenic scores (PGS) are becoming an increasingly popular approach to predict complex disease risk, although they also hold the potential to develop insight into the molecular profiles of patients with an elevated genetic predisposition to disease.

METHODS

We sought to construct an atlas of associations between 125 different PGS derived using results from genome-wide association studies and 249 circulating metabolites in up to 83,004 participants from the UK Biobank.

RESULTS

As an exemplar to demonstrate the value of this atlas, we conducted a hypothesis-free evaluation of all associations with glycoprotein acetyls (GlycA), an inflammatory biomarker. Using bidirectional Mendelian randomization, we find that the associations highlighted likely reflect the effect of risk factors, such as adiposity or liability towards smoking, on systemic inflammation as opposed to the converse direction. Moreover, we repeated all analyses in our atlas within age strata to investigate potential sources of collider bias, such as medication usage. This was exemplified by comparing associations between lipoprotein lipid profiles and the coronary artery disease PGS in the youngest and oldest age strata, which had differing proportions of individuals undergoing statin therapy. Lastly, we generated all PGS-metabolite associations stratified by sex and separately after excluding 13 established lipid-associated loci to further evaluate the robustness of findings.

CONCLUSIONS

We envisage that the atlas of results constructed in our study will motivate future hypothesis generation and help prioritize and deprioritize circulating metabolic traits for in-depth investigations. All results can be visualized and downloaded at http://mrcieu.mrsoftware.org/metabolites_PRS_atlas.

FUNDING

This work is supported by funding from the Wellcome Trust, the British Heart Foundation, and the Medical Research Council Integrative Epidemiology Unit.

Effects of general and central adiposity on circulating lipoprotein, lipid, and metabolite levels in UK Biobank: A multivariable Mendelian randomization study

Background

The direct effects of general adiposity (body mass index (BMI)) and central adiposity (waist-to-hip-ratio (WHR)) on circulating lipoproteins, lipids, and metabolites are unknown.

Methods

We used new metabolic data from UK Biobank (N=109,532, a five-fold higher N over previous studies). EDTA-plasma was used to quantify 249 traits with nuclear-magnetic-resonance spectroscopy including subclass-specific lipoprotein concentrations and lipid content, plus pre-glycemic and inflammatory metabolites. We used univariable and multivariable two-stage least-squares regression models with genetic risk scores for BMI and WHR as instruments to estimate total (unadjusted) and direct (mutually-adjusted) effects of BMI and WHR on metabolic traits; plus effects on statin use and interaction by sex, statin use, and age (proxy for medication use).

Findings

Higher BMI decreased apolipoprotein B and low-density lipoprotein cholesterol (LDL-C) before and after WHR-adjustment, whilst BMI increased triglycerides only before WHR-adjustment. These effects of WHR were larger and BMI-independent. Direct effects differed markedly by sex, e.g., triglycerides increased only with BMI among men, and only with WHR among women. Adiposity measures increased statin use and showed metabolic effects which differed by statin use and age. Among the youngest (38-53y, statins-5%), BMI and WHR (per-SD) increased LDL-C (total effects: 0.04-SD, 95%CI=-0.01,0.08 and 0.10-SD, 95%CI=0.02,0.17 respectively), but only WHR directly. Among the oldest (63-73y, statins-29%), BMI and WHR directly lowered LDL-C (-0.19-SD, 95%CI=-0.27,-0.11 and -0.05-SD, 95%CI=-0.16,0.06 respectively).

Interpretation

Excess adiposity likely raises atherogenic lipid and metabolite levels exclusively via adiposity stored centrally, particularly among women. Apparent effects of adiposity on lowering LDL-C are likely explained by an effect of adiposity on statin use.

Funding

UK Medical Research Council; British Heart Foundation; Novo Nordisk; National Institute for Health Research; Wellcome Trust; Cancer Research UK.

Circulating free testosterone and risk of aggressive prostate cancer: Prospective and Mendelian randomisation analyses in international consortia

Previous studies had limited power to assess the associations of testosterone with aggressive disease as a primary endpoint. Further, the association of genetically predicted testosterone with aggressive disease is not known. We investigated the associations of calculated free and measured total testosterone and sex hormone-binding globulin (SHBG) with aggressive, overall and early-onset prostate cancer. In blood-based analyses, odds ratios (OR) and 95% confidence intervals (CI) for prostate cancer were estimated using conditional logistic regression from prospective analysis of biomarker concentrations in the Endogenous Hormones, Nutritional Biomarkers and Prostate Cancer Collaborative Group (up to 25 studies, 14 944 cases and 36 752 controls, including 1870 aggressive prostate cancers). In Mendelian randomisation (MR) analyses, using instruments identified using UK Biobank (up to 194 453 men) and outcome data from PRACTICAL (up to 79 148 cases and 61 106 controls, including 15 167 aggressive cancers), ORs were estimated using the inverse-variance weighted method. Free testosterone was associated with aggressive disease in MR analyses (OR per 1 SD = 1.23, 95% CI = 1.08-1.40). In blood-based analyses there was no association with aggressive disease overall, but there was heterogeneity by age at blood collection (OR for men aged <60 years 1.14, CI = 1.02-1.28; Phet  = .0003: inverse association for older ages). Associations for free testosterone were positive for overall prostate cancer (MR: 1.20, 1.08-1.34; blood-based: 1.03, 1.01-1.05) and early-onset prostate cancer (MR: 1.37, 1.09-1.73; blood-based: 1.08, 0.98-1.19). SHBG and total testosterone were inversely associated with overall prostate cancer in blood-based analyses, with null associations in MR analysis. Our results support free testosterone, rather than total testosterone, in the development of prostate cancer, including aggressive subgroups.

Evaluating the efficacy and mechanism of metformin targets on reducing Alzheimer's disease risk in the general population: a Mendelian randomisation study

AIMS/HYPOTHESIS

Metformin use has been associated with reduced incidence of dementia in diabetic individuals in observational studies. However, the causality between the two in the general population is unclear. This study uses Mendelian randomisation (MR) to investigate the causal effect of metformin targets on Alzheimer's disease and potential causal mechanisms in the brain linking the two.

METHODS

Genetic proxies for the effects of metformin drug targets were identified as variants in the gene for the corresponding target that associated with HbA1c level (N=344,182) and expression level of the corresponding gene (N≤31,684). The cognitive outcomes were derived from genome-wide association studies comprising 527,138 middle-aged Europeans, including 71,880 with Alzheimer's disease or Alzheimer's disease-by-proxy. MR estimates representing lifelong metformin use on Alzheimer's disease and cognitive function in the general population were generated. Effect of expression level of 22 metformin-related genes in brain cortex (N=6601 donors) on Alzheimer's disease was further estimated.

RESULTS

Genetically proxied metformin use, equivalent to a 6.75 mmol/mol (1.09%) reduction on HbA1c, was associated with 4% lower odds of Alzheimer's disease (OR 0.96 [95% CI 0.95, 0.98], p=1.06×10-4) in non-diabetic individuals. One metformin target, mitochondrial complex 1 (MCI), showed a robust effect on Alzheimer's disease (OR 0.88, p=4.73×10-4) that was independent of AMP-activated protein kinase. MR of expression in brain cortex tissue showed that decreased MCI-related gene (NDUFA2) expression was associated with lower Alzheimer's disease risk (OR 0.95, p=4.64×10-4) and favourable cognitive function.

CONCLUSIONS/INTERPRETATION

Metformin use may cause reduced Alzheimer's disease risk in the general population. Mitochondrial function and the NDUFA2 gene are plausible mechanisms of action in dementia protection.

Correction: Obesity and risk of female reproductive conditions: A Mendelian randomisation study

[This corrects the article DOI: 10.1371/journal.pmed.1003679.].

A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids

A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.

Genetic and observational evidence: No independent role for cholesterol efflux over static high-density lipoprotein concentration measures in coronary heart disease risk assessment

BACKGROUND

Observational findings for high-density lipoprotein (HDL)-mediated cholesterol efflux capacity (HDL-CEC) and coronary heart disease (CHD) appear inconsistent, and knowledge of the genetic architecture of HDL-CEC is limited.

OBJECTIVES

A large-scale observational study on the associations of HDL-CEC and other HDL-related measures with CHD and the largest genome-wide association study (GWAS) of HDL-CEC.

PARTICIPANTS/METHODS

Six independent cohorts were included with follow-up data for 14,438 participants to investigate the associations of HDL-related measures with incident CHD (1,570 events). The GWAS of HDL-CEC was carried out in 20,372 participants.

RESULTS

HDL-CEC did not associate with CHD when adjusted for traditional risk factors and HDL cholesterol (HDL-C). In contradiction, almost all HDL-related concentration measures associated consistently with CHD after corresponding adjustments. There were no genetic loci associated with HDL-CEC independent of HDL-C and triglycerides.

CONCLUSION

HDL-CEC is not unequivocally associated with CHD in contrast to HDL-C, apolipoprotein A-I, and most of the HDL subclass particle concentrations.

Role of circulating polyunsaturated fatty acids on cardiovascular diseases risk: analysis using Mendelian randomization and fatty acid genetic association data from over 114,000 UK Biobank participants

BACKGROUND

Despite early interest in the health effects of polyunsaturated fatty acids (PUFA), there is still substantial controversy and uncertainty on the evidence linking PUFA to cardiovascular diseases (CVDs). We investigated the effect of plasma concentration of omega-3 PUFA (i.e. docosahexaenoic acid (DHA) and total omega-3 PUFA) and omega-6 PUFA (i.e. linoleic acid and total omega-6 PUFA) on the risk of CVDs using Mendelian randomization.

METHODS

We conducted the largest genome-wide association study (GWAS) of circulating PUFA to date including a sample of 114,999 individuals and incorporated these data in a two-sample Mendelian randomization framework to investigate the involvement of circulating PUFA on a wide range of CVDs in up to 1,153,768 individuals of European ancestry (i.e. coronary artery disease, ischemic stroke, haemorrhagic stroke, heart failure, atrial fibrillation, peripheral arterial disease, aortic aneurysm, venous thromboembolism and aortic valve stenosis).

RESULTS

GWAS identified between 46 and 64 SNPs for the four PUFA traits, explaining 4.8-7.9% of circulating PUFA variance and with mean F statistics >100. Higher genetically predicted DHA (and total omega-3 fatty acids) concentration was related to higher risk of some cardiovascular endpoints; however, these findings did not pass our criteria for multiple testing correction and were attenuated when accounting for LDL-cholesterol through multivariable Mendelian randomization or excluding SNPs in the vicinity of the FADS locus. Estimates for the relation between higher genetically predicted linoleic acid (and total omega-6) concentration were inconsistent across different cardiovascular endpoints and Mendelian randomization methods. There was weak evidence of higher genetically predicted linoleic acid being related to lower risk of ischemic stroke and peripheral artery disease when accounting by LDL-cholesterol.

CONCLUSIONS

We have conducted the largest GWAS of circulating PUFA to date and the most comprehensive Mendelian randomization analyses. Overall, our Mendelian randomization findings do not support a protective role of circulating PUFA concentration on the risk of CVDs. However, horizontal pleiotropy via lipoprotein-related traits could be a key source of bias in our analyses.

Circulating proteins and risk of pancreatic cancer: a case-subcohort study among Chinese adults

BACKGROUND

Pancreatic cancer has a very poor prognosis. Biomarkers that may help predict or diagnose pancreatic cancer may lead to earlier diagnosis and improved survival.

METHODS

The prospective China Kadoorie Biobank (CKB) recruited 512 891 adults aged 30-79 years during 2004-08, recording 702 incident cases of pancreatic cancer during 9 years of follow-up. We conducted a case-subcohort study measuring 92 proteins in 610 cases and a subcohort of 623 individuals, using the OLINK immuno-oncology panel in stored baseline plasma samples. Cox regression with the Prentice pseudo-partial likelihood was used to estimate adjusted hazard ratios (HRs) for risk of pancreatic cancer by protein levels.

RESULTS

Among 1233 individuals (including 610 cases), several chemokines, interleukins, growth factors and membrane proteins were associated with risk of pancreatic cancer, with adjusted HRs per 1 standard deviation (SD) of 0.86 to 1.86, including monocyte chemotactic protein 3 (MCP3/CCL7) {1.29 [95% CI (confidence interval) (1.10, 1.51)]}, angiopoietin-2 (ANGPT2) [1.27 (1.10, 1.48)], interleukin-18 (IL18) [1.24 (1.07, 1.43)] and interleukin-6 (IL6) [1.21 (1.06, 1.38)]. Associations between some proteins [e.g. matrix metalloproteinase-7 (MMP7), hepatocyte growth factor (HGF) and tumour necrosis factor receptor superfamily member 9 [TNFRSF9)] and risk of pancreatic cancer were time-varying, with higher levels associated with higher short-term risk. Within the first year, the discriminatory ability of a model with known risk factors (age, age squared, sex, region, smoking, alcohol, education, diabetes and family history of cancer) was increased when several proteins were incorporated (weighted C-statistic changed from 0.85 to 0.99; P for difference = 4.5 × 10-5), although only a small increase in discrimination (0.77 to 0.79, P = 0.04) was achieved for long-term risk.

CONCLUSIONS

Several plasma proteins were associated with subsequent diagnosis of pancreatic cancer. The potential clinical utility of these biomarkers warrants further investigation.

The impact of education inequality on rheumatoid arthritis risk is mediated by smoking and body mass index: Mendelian randomization study

OBJECTIVE

To estimate the causal relationship between educational attainment-as a proxy for socioeconomic inequality-and risk of RA, and quantify the roles of smoking and BMI as potential mediators.

METHODS

Using the largest genome-wide association studies (GWAS), we performed a two-sample Mendelian randomization (MR) study of genetically predicted educational attainment (instrumented using 1265 variants from 766 345 individuals) and RA (14 361 cases, 43 923 controls). We used two-step MR to quantify the proportion of education's effect on RA mediated by smoking exposure (as a composite index capturing duration, heaviness and cessation, using 124 variants from 462 690 individuals) and BMI (517 variants, 681 275 individuals), and multivariable MR to estimate proportion mediated by both factors combined.

RESULTS

Each s.d. increase in educational attainment (4.2 years of schooling) was protective of RA (odds ratio 0.37; 95% CI: 0.31, 0.44). Higher educational attainment was also protective for smoking exposure (β = -0.25 s.d.; 95% CI: -0.26, -0.23) and BMI [β = -0.27 s.d. (∼1.3 kg/m2); 95% CI: -0.31, -0.24]. Smoking mediated 24% (95% CI: 13%, 35%) and BMI 17% (95% CI: 11%, 23%) of the total effect of education on RA. Combined, the two risk factors explained 47% (95% CI: 11%, 82%) of the total effect.

CONCLUSION

Higher educational attainment has a protective effect on RA risk. Interventions to reduce smoking and excess adiposity at a population level may reduce this risk, but a large proportion of education's effect on RA remains unexplained. Further research into other risk factors that act as potentially modifiable mediators are required.

A phenome-wide bidirectional Mendelian randomization analysis of atrial fibrillation

Background

The prevalence of atrial fibrillation (AF) is increasing with an aging worldwide population, yet a comprehensive understanding of its causes and consequences remains limited. We aim to assess the causes and consequences of AF via a bidirectional Mendelian randomization (MR) analysis.

Methods

We used publicly available genome-wide association study (GWAS) summary data, centralized and harmonized by an open GWAS database. We assessed the genetically predicted effects of 5048 exposures on risk of AF, and the genetically predicted effects of genetic liability to AF, on 10 308 outcomes via two-sample MR analysis. Multivariable MR analysis was further conducted to explore the comparative roles of identified risk factors.

Results

MR analysis suggested that 55 out of 5048 exposure traits, including four proteins, play a causal role in AF (P <1e-5 allowing for multiple comparisons). Multivariable analysis suggested that higher body mass index, height and systolic blood pressure as well as genetic liability to coronary artery diseases independently cause AF. Three out of the four proteins (DUSP13, TNFSF12 and IL6R) had a drug prioritizing score for atrial fibrillation of 0.26, 0.38 and 0.88, respectively (values closer to 1 indicating stronger evidence of the protein as a potential drug target). Genetic liability to AF was linked to a higher risk of cardio-embolic ischaemic stroke.

Conclusions

Our results suggest body mass index, height, systolic blood pressure and genetic liability to coronary artery disease are independent causal risk factors for AF. Several proteins, including DUSP13, IL-6R and TNFSF12, may have therapeutic potential for AF.

Adiposity, metabolomic biomarkers, and risk of nonalcoholic fatty liver disease: a case-cohort study

BACKGROUND

Globally, the burden of obesity and associated nonalcoholic fatty liver disease (NAFLD) are rising, but little is known about the role that circulating metabolomic biomarkers play in mediating their association.

OBJECTIVES

We aimed to examine the observational and genetic associations of adiposity with metabolomic biomarkers and the observational associations of metabolomic biomarkers with incident NAFLD.

METHODS

A case-subcohort study within the prospective China Kadoorie Biobank included 176 NAFLD cases and 180 subcohort individuals and measured 1208 metabolites in stored baseline plasma using a Metabolon assay. In the subcohort the observational and genetic associations of BMI with biomarkers were assessed using linear regression, with adjustment for multiple testing. Cox regression was used to estimate adjusted HRs for NAFLD associated with biomarkers.

RESULTS

In observational analyses, BMI (kg/m2; mean: 23.9 in the subcohort) was associated with 199 metabolites at a 5% false discovery rate. The effects of genetically elevated BMI with specific metabolites were directionally consistent with the observational associations. Overall, 35 metabolites were associated with NAFLD risk, of which 15 were also associated with BMI, including glutamate (HR per 1-SD higher metabolite: 1.95; 95% CI: 1.48, 2.56), cysteine-glutathione disulfide (0.44; 0.31, 0.62), diaclyglycerol (C32:1) (1.71; 1.24, 2.35), behenoyl dihydrosphingomyelin (C40:0) (1.92; 1.42, 2.59), butyrylcarnitine (C4) (1.91; 1.38, 2.35), 2-hydroxybehenate (1.81; 1.34, 2.45), and 4-cholesten-3-one (1.79; 1.27, 2.54). The discriminatory performance of known risk factors was increased when 28 metabolites were also considered simultaneously in the model (weighted C-statistic: 0.84 to 0.90; P  < 0.001).

CONCLUSIONS

Among relatively lean Chinese adults, a range of metabolomic biomarkers are associated with NAFLD risk and these biomarkers may lie on the pathway between adiposity and NAFLD.

Genetic Predisposition to Diabetes and Abdominal Aortic Aneurysm: A Two Stage Mendelian Randomisation Study

OBJECTIVE

Observational studies demonstrate an inverse association between type II diabetes and abdominal aortic aneurysm (AAA) for reasons that are unclear. The aim of this study was to clarify the causal association between type II diabetes predisposition and AAA using Mendelian randomisation.

METHODS

Effect estimates for single nucleotide polymorphisms (SNPs) associated with diabetes were obtained from the DIAbetes Meta-ANalysis of Trans-Ethnic association studies (DIAMANTE) consortium to construct a genetic instrumental variable. Corresponding effect estimates for associations of these SNPs with AAA were obtained from the International Aneurysm Consortium comprising six separate AAA genomewide association studies (4 972 cases and 99 858 controls). Mendelian randomisation estimates were calculated using inverse variance, weighted median, and MR-Egger methods, and compared against recently published observational estimates.

RESULTS

A genetic risk score was constructed from 206 SNPs associated with diabetes. All three Mendelian randomisation models showed no effect of genetic liability to diabetes and risk of AAA (inverse variance: odds ratio 1.04 per unit higher log odds, 95% 0.98 - 1.11, p = .19; MR-Egger slope p = .33; weighted median p = .50). Results were similar after excluding the TCF7L2 locus (inverse variance p = .075). Findings from the Mendelian randomisation analysis differed from previous observational reports of an inverse association (pdif < .001).

CONCLUSION

Lifelong genetic predisposition to diabetes does not appear to protect against AAA. These findings differ from traditional epidemiological studies showing an inverse association between diabetes and AAA, for reasons that remain unclear.

Mendelian randomization

Mendelian randomization (MR) is a term that applies to the use of genetic variation to address causal questions about how modifiable exposures influence different outcomes. The principles of MR are based on Mendel's laws of inheritance and instrumental variable estimation methods, which enable the inference of causal effects in the presence of unobserved confounding. In this Primer, we outline the principles of MR, the instrumental variable conditions underlying MR estimation and some of the methods used for estimation. We go on to discuss how the assumptions underlying an MR study can be assessed and give methods of estimation that are robust to certain violations of these assumptions. We give examples of a range of studies in which MR has been applied, the limitations of current methods of analysis and the outlook for MR in the future. The difference between the assumptions required for MR analysis and other forms of non-interventional epidemiological studies means that MR can be used as part of a triangulation across multiple sources of evidence for causal inference.

Obesity and risk of female reproductive conditions: A Mendelian randomisation study

BACKGROUND

Obesity is observationally associated with altered risk of many female reproductive conditions. These include polycystic ovary syndrome (PCOS), abnormal uterine bleeding, endometriosis, infertility, and pregnancy-related disorders. However, the roles and mechanisms of obesity in the aetiology of reproductive disorders remain unclear. Thus, we aimed to estimate observational and genetically predicted causal associations between obesity, metabolic hormones, and female reproductive disorders.

METHODS AND FINDINGS

Logistic regression, generalised additive models, and Mendelian randomisation (MR) (2-sample, non-linear, and multivariable) were applied to obesity and reproductive disease data on up to 257,193 women of European ancestry in UK Biobank and publicly available genome-wide association studies (GWASs). Body mass index (BMI), waist-to-hip ratio (WHR), and WHR adjusted for BMI were observationally (odds ratios [ORs] = 1.02-1.87 per 1-SD increase in obesity trait) and genetically (ORs = 1.06-2.09) associated with uterine fibroids (UF), PCOS, heavy menstrual bleeding (HMB), and pre-eclampsia. Genetically predicted visceral adipose tissue (VAT) mass was associated with the development of HMB (OR [95% CI] per 1-kg increase in predicted VAT mass = 1.32 [1.06-1.64], P = 0.0130), PCOS (OR [95% CI] = 1.15 [1.08-1.23], P = 3.24 × 10-05), and pre-eclampsia (OR [95% CI] = 3.08 [1.98-4.79], P = 6.65 × 10-07). Increased waist circumference posed a higher genetic risk (ORs = 1.16-1.93) for the development of these disorders and UF than did increased hip circumference (ORs = 1.06-1.10). Leptin, fasting insulin, and insulin resistance each mediated between 20% and 50% of the total genetically predicted association of obesity with pre-eclampsia. Reproductive conditions clustered based on shared genetic components of their aetiological relationships with obesity. This study was limited in power by the low prevalence of female reproductive conditions among women in the UK Biobank, with little information on pre-diagnostic anthropometric traits, and by the susceptibility of MR estimates to genetic pleiotropy.

CONCLUSIONS

We found that common indices of overall and central obesity were associated with increased risks of reproductive disorders to heterogenous extents in a systematic, large-scale genetics-based analysis of the aetiological relationships between obesity and female reproductive conditions. Our results suggest the utility of exploring the mechanisms mediating the causal associations of overweight and obesity with gynaecological health to identify targets for disease prevention and treatment.

Characterising metabolomic signatures of lipid-modifying therapies through drug target mendelian randomisation

Large-scale molecular profiling and genotyping provide a unique opportunity to systematically compare the genetically predicted effects of therapeutic targets on the human metabolome. We firstly constructed genetic risk scores for 8 drug targets on the basis that they primarily modify low-density lipoprotein (LDL) cholesterol (HMGCR, PCKS9, and NPC1L1), high-density lipoprotein (HDL) cholesterol (CETP), or triglycerides (APOC3, ANGPTL3, ANGPTL4, and LPL). Conducting mendelian randomisation (MR) provided strong evidence of an effect of drug-based genetic scores on coronary artery disease (CAD) risk with the exception of ANGPTL3. We then systematically estimated the effects of each score on 249 metabolic traits derived using blood samples from an unprecedented sample size of up to 115,082 UK Biobank participants. Genetically predicted effects were generally consistent among drug targets, which were intended to modify the same lipoprotein lipid trait. For example, the linear fit for the MR estimates on all 249 metabolic traits for genetically predicted inhibition of LDL cholesterol lowering targets HMGCR and PCSK9 was r² = 0.91. In contrast, comparisons between drug classes that were designed to modify discrete lipoprotein traits typically had very different effects on metabolic signatures (for instance, HMGCR versus each of the 4 triglyceride targets all had r² < 0.02). Furthermore, we highlight this discrepancy for specific metabolic traits, for example, finding that LDL cholesterol lowering therapies typically had a weak effect on glycoprotein acetyls, a marker of inflammation, whereas triglyceride modifying therapies assessed provided evidence of a strong effect on lowering levels of this inflammatory biomarker. Our findings indicate that genetically predicted perturbations of these drug targets on the blood metabolome can drastically differ, despite largely consistent effects on risk of CAD, with potential implications for biomarkers in clinical development and measuring treatment response.

Associations between body composition, fat distribution and metabolic consequences of excess adiposity with severe COVID-19 outcomes: observational study and Mendelian randomisation analysis

Background

Higher body mass index (BMI) and metabolic consequences of excess weight are associated with increased risk of severe COVID-19, though their mediating pathway is unclear.

Methods

A prospective cohort study included 435,504 UK Biobank participants. A two-sample Mendelian randomisation (MR) study used the COVID-19 Host Genetics Initiative in 1.6 million participants. We examined associations of total adiposity, body composition, fat distribution and metabolic consequences of excess weight, particularly type 2 diabetes, with incidence and severity of COVID-19, assessed by test positivity, hospital admission, intensive care unit (ICU) admission and death.

Results

BMI and body fat were associated with COVID-19 in the observational and MR analyses but muscle mass was not. The observational study suggested the association with central fat distribution was stronger than for BMI, but there was little evidence from the MR analyses than this was causal. There was evidence that strong associations of metabolic consequences with COVID-19 outcomes in observational but not MR analyses. Type 2 diabetes was strongly associated with COVID-19 in observational but not MR analyses. In adjusted models, the observational analysis showed that the association of BMI with COVID-19 diminished, while central fat distribution and metabolic consequences of excess weight remained strongly associated. In contrast, MR showed the reverse, with only BMI retaining a direct effect on COVID-19.

Conclusions

Excess total adiposity is probably casually associated with severe COVID-19. Mendelian randomisation data do not support causality for the observed associations of central fat distribution or metabolic consequences of excess adiposity with COVID-19.

Contributions of obesity to kidney health and disease: insights from Mendelian randomization and the human kidney transcriptomics

AIMS

Obesity and kidney diseases are common complex disorders with an increasing clinical and economic impact on healthcare around the globe. Our objective was to examine if modifiable anthropometric obesity indices show putatively causal association with kidney health and disease and highlight biological mechanisms of potential relevance to the association between obesity and the kidney.

METHODS AND RESULTS

We performed observational, one-sample, two-sample Mendelian randomization (MR) and multivariable MR studies in ∼300 000 participants of white-British ancestry from UK Biobank and participants of predominantly European ancestry from genome-wide association studies. The MR analyses revealed that increasing values of genetically predicted body mass index and waist circumference were causally associated with biochemical indices of renal function, kidney health index (a composite renal outcome derived from blood biochemistry, urine analysis, and International Classification of Disease-based kidney disease diagnoses), and both acute and chronic kidney diseases of different aetiologies including hypertensive renal disease and diabetic nephropathy. Approximately 13-16% and 21-26% of the potentially causal effect of obesity indices on kidney health were mediated by blood pressure and type 2 diabetes, respectively. A total of 61 pathways mapping primarily onto transcriptional/translational regulation, innate and adaptive immunity, and extracellular matrix and metabolism were associated with obesity measures in gene set enrichment analysis in up to 467 kidney transcriptomes.

CONCLUSIONS

Our data show that a putatively causal association of obesity with renal health is largely independent of blood pressure and type 2 diabetes and uncover the signatures of obesity on the transcriptome of human kidney.

Metabolic Biomarker Discovery for Risk of Peripheral Artery Disease Compared With Coronary Artery Disease: Lipoprotein and Metabolite Profiling of 31 657 Individuals From 5 Prospective Cohorts

Background Peripheral artery disease (PAD) and coronary artery disease (CAD) represent atherosclerosis in different vascular beds. We used detailed metabolic biomarker profiling to identify common and discordant biomarkers and clarify pathophysiological differences for these vascular diseases. Methods and Results We used 5 prospective cohorts from Finnish population (FINRISK 1997, 2002, 2007, and 2012, and Health 2000; n=31 657; median follow-up time of 14 years) to estimate associations between >200 metabolic biomarkers and incident PAD and CAD. Metabolic biomarkers were measured with nuclear magnetic resonance, and disease events were obtained from nationwide hospital records. During the follow-up, 498 incident PAD and 2073 incident CAD events occurred. In age- and sex-adjusted Cox models, apolipoproteins and cholesterol measures were robustly associated with incident CAD (eg, hazard ratio [HR] per SD for higher apolipoprotein B/A-1 ratio, 1.30; 95% CI, 1.25-1.36), but not with incident PAD (HR per SD for higher apolipoprotein B/A-1 ratio, 1.04; 95% CI, 0.95-1.14; P_{heterogeneity}<0.001). In contrast, triglyceride levels in low-density lipoprotein and high-density lipoprotein were associated with both end points (P_{heterogeneity}>0.05). Lower proportion of polyunsaturated fatty acids relative to total fatty acids, and higher concentrations of monounsaturated fatty acids, glycolysis-related metabolites, and inflammatory protein markers were strongly associated with incident PAD, and many of these associations were stronger for PAD than for CAD (P_{heterogeneity}<0.001). Most differences in metabolic profiles for PAD and CAD remained when adjusting for traditional risk factors. Conclusions The metabolic biomarker profile for future PAD risk is distinct from that of CAD. This may represent pathophysiological differences.

Longitudinal trajectories of blood lipid levels in an ageing population sample of Russian Western-Siberian urban population

This study investigated 12-year blood lipid trajectories and whether these trajectories are modified by smoking and lipid lowering treatment in older Russians. To do so, we analysed data on 9,218 Russian West-Siberian Caucasians aged 45-69 years at baseline participating in the international HAPIEE cohort study. Mixed-effect multilevel models were used to estimate individual level lipid trajectories across the baseline and two follow-up examinations (16,445 separate measurements over 12 years). In all age groups, we observed a reduction in serum total cholesterol (TC), LDL-C and non-HDL-C over time even after adjusting for sex, statin treatment, hypertension, diabetes, social factors and mortality (P<0.01). In contrast, serum triglyceride (TG) values increased over time in younger age groups, reached a plateau and decreased in older age groups (> 60 years at baseline). In smokers, TC, LDL-C, non-HDL-C and TG decreased less markedly than in non-smokers, while HDL-C decreased more rapidly while the LDL-C/HDL-C ratio increased. In subjects treated with lipid-lowering drugs, TC, LDL-C and non-HDL-C decreased more markedly and HDL-C less markedly than in untreated subjects while TG and LDL-C/HDL-C remained stable or increased in treatment naïve subjects. We conclude, that in this ageing population we observed marked changes in blood lipids over a 12 year follow up, with decreasing trajectories of TC, LDL-C and non-HDL-C and mixed trajectories of TG. The findings suggest that monitoring of age-related trajectories in blood lipids may improve prediction of CVD risk beyond single measurements.

Response to comment on "Evaluating the cardiovascular safety of sclerostin inhibition using evidence from meta-analysis of clinical trials and human genetics"

Triangulation of evidence from clinical trials and human genetics suggests a potential excess risk of cardiovascular disease events arising from therapeutic inhibition of sclerostin.

The power of genetic diversity in genome-wide association studies of lipids

Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4-23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.

The genomics of heart failure: design and rationale of the HERMES consortium

Aims

The HERMES (HEart failure Molecular Epidemiology for Therapeutic targetS) consortium aims to identify the genomic and molecular basis of heart failure.

Methods and results

The consortium currently includes 51 studies from 11 countries, including 68 157 heart failure cases and 949 888 controls, with data on heart failure events and prognosis. All studies collected biological samples and performed genome‐wide genotyping of common genetic variants. The enrolment of subjects into participating studies ranged from 1948 to the present day, and the median follow‐up following heart failure diagnosis ranged from 2 to 116 months. Forty‐nine of 51 individual studies enrolled participants of both sexes; in these studies, participants with heart failure were predominantly male (34–90%). The mean age at diagnosis or ascertainment across all studies ranged from 54 to 84 years. Based on the aggregate sample, we estimated 80% power to genetic variant associations with risk of heart failure with an odds ratio of ≥1.10 for common variants (allele frequency ≥ 0.05) and ≥1.20 for low‐frequency variants (allele frequency 0.01–0.05) at P < 5 × 10⁻⁸ under an additive genetic model.

Conclusions

HERMES is a global collaboration aiming to (i) identify the genetic determinants of heart failure; (ii) generate insights into the causal pathways leading to heart failure and enable genetic approaches to target prioritization; and (iii) develop genomic tools for disease stratification and risk prediction.

Association of physical activity with risk of hepatobiliary diseases in China: a prospective cohort study of 0.5 million people

OBJECTIVE

There is limited prospective evidence on the association of physical activity with hepatobiliary cancer subtypes and other major hepatobiliary diseases, especially in China. We aimed to quantify the associations with risk of these diseases.

METHODS

The study population involved 460 937 participants of the prospective China Kadoorie Biobank aged 30-79 years from 10 diverse areas in China without history of cancer or hepatobiliary disease at baseline. Cox regression was used to estimate adjusted hazard ratios (HRs) for each disease associated with self-reported total and domain-specific physical activity (occupational and non-occupational, ie, leisure time, household and commuting).

RESULTS

During ~10 years of follow-up, 22 012 incident cases of hepatobiliary diseases were recorded. The overall mean (SD) total physical activity was 21.2 (13.9) metabolic equivalent of task (MET)-hours/day, with 62% from occupational activity. Total physical activity was inversely associated with hospitalised non-alcoholic fatty liver disease (HR comparing top vs bottom quintile: 0.62, 95% confidence interval (CI) 0.53 to 0.72), viral hepatitis (0.73, 95% CI 0.62 to 0.87), cirrhosis (0.76, 95% CI 0.66 to 0.88) and liver cancer (0.81, 95% CI 0.71 to 0.93), as well as gallstone disease (0.86, 95% CI 0.81 to 0.90), gallbladder cancer (0.51, 95% CI 0.32 to 0.80) and biliary tract cancer (0.55, 95% CI 0.38 to 0.78). The associations for occupational physical activity were similar to those for total physical activity, but for non-occupational physical activity they differed by disease subtype. For leisure-time physical activity, there was an inverse association with liver cancer and an inverse trend for gallstone disease (HR comparing ≥7.5 MET-hours/day with none: 0.83, 95% CI 0.75 to 0.91 and 0.82, 95% CI 0.66 to 1.01).

CONCLUSION

Among Chinese adults, high total physical activity, particularly occupational physical activity, was inversely associated with risk of major hepatobiliary cancers and diseases, including non-alcoholic fatty liver disease, cirrhosis and certain types of cancer.

Body muscle gain and markers of cardiovascular disease susceptibility in young adulthood: A cohort study

BACKGROUND

The potential benefits of gaining body muscle for cardiovascular disease (CVD) susceptibility, and how these compare with the potential harms of gaining body fat, are unknown. We compared associations of early life changes in body lean mass and handgrip strength versus body fat mass with atherogenic traits measured in young adulthood.

METHODS AND FINDINGS

Data were from 3,227 offspring of the Avon Longitudinal Study of Parents and Children (39% male; recruited in 1991-1992). Limb lean and total fat mass indices (kg/m2) were measured using dual-energy X-ray absorptiometry scans performed at age 10, 13, 18, and 25 y (across clinics occurring from 2001-2003 to 2015-2017). Handgrip strength was measured at 12 and 25 y, expressed as maximum grip (kg or lb/in2) and relative grip (maximum grip/weight in kilograms). Linear regression models were used to examine associations of change in standardised measures of these exposures across different stages of body development with 228 cardiometabolic traits measured at age 25 y including blood pressure, fasting insulin, and metabolomics-derived apolipoprotein B lipids. SD-unit gain in limb lean mass index from 10 to 25 y was positively associated with atherogenic traits including very-low-density lipoprotein (VLDL) triglycerides. This pattern was limited to lean gain in legs, whereas lean gain in arms was inversely associated with traits including VLDL triglycerides, insulin, and glycoprotein acetyls, and was also positively associated with creatinine (a muscle product and positive control). Furthermore, this pattern for arm lean mass index was specific to SD-unit gains occurring between 13 and 18 y, e.g., -0.13 SD (95% CI -0.22, -0.04) for VLDL triglycerides. Changes in maximum and relative grip from 12 to 25 y were both positively associated with creatinine, but only change in relative grip was also inversely associated with atherogenic traits, e.g., -0.12 SD (95% CI -0.18, -0.06) for VLDL triglycerides per SD-unit gain. Change in fat mass index from 10 to 25 y was more strongly associated with atherogenic traits including VLDL triglycerides, at 0.45 SD (95% CI 0.39, 0.52); these estimates were directionally consistent across sub-periods, with larger effect sizes with more recent gains. Associations of lean, grip, and fat measures with traits were more pronounced among males. Study limitations include potential residual confounding of observational estimates, including by ectopic fat within muscle, and the absence of grip measures in adolescence for estimates of grip change over sub-periods.

CONCLUSIONS

In this study, we found that muscle strengthening, as indicated by grip strength gain, was weakly associated with lower atherogenic trait levels in young adulthood, at a smaller magnitude than unfavourable associations of fat mass gain. Associations of muscle mass gain with such traits appear to be smaller and limited to gains occurring in adolescence. These results suggest that body muscle is less robustly associated with markers of CVD susceptibility than body fat and may therefore be a lower-priority intervention target.

Using Mendelian Randomization to Improve the Design of Randomized Trials

Randomized controlled trials and Mendelian randomization studies are two study designs that provide randomized evidence in human biological and medical research. Both exploit the power of randomization to provide unconfounded estimates of causal effect. However, randomized trials and Mendelian randomization studies have very different study designs and scientific objectives. As a result, despite sometimes being referred to as "nature's randomized trial," a Mendelian randomization study cannot be used to replace a randomized trial but instead provides complementary information. In this review, we explain the similarities and differences between randomized trials and Mendelian randomization studies, and suggest several ways that Mendelian randomization can be used to directly inform and improve the design of randomized trials illustrated with practical examples. We conclude by describing how Mendelian randomization studies can employ the principles of trial design to be framed as "naturally randomized trials" that can provide a template for the design of future randomized trials evaluating therapies directed against genetically validated targets.

Type 2 Diabetes, Metabolic Traits, and Risk of Heart Failure: A Mendelian Randomization Study

OBJECTIVE

The aim of this study was to use Mendelian randomization (MR) techniques to estimate the causal relationships between genetic liability to type 2 diabetes (T2D), glycemic traits, and risk of heart failure (HF).

RESEARCH DESIGN AND METHODS

Summary-level data were obtained from genome-wide association studies of T2D, insulin resistance (IR), glycated hemoglobin, fasting insulin and glucose, and HF. MR was conducted using the inverse-variance weighted method. Sensitivity analyses included the MR-Egger method, weighted median and mode methods, and multivariable MR conditioning on potential mediators.

RESULTS

Genetic liability to T2D was causally related to higher risk of HF (odds ratio [OR] 1.13 per 1-log unit higher risk of T2D; 95% CI 1.11-1.14; P < 0.001); however, sensitivity analysis revealed evidence of directional pleiotropy. The relationship between T2D and HF was attenuated when adjusted for coronary disease, BMI, LDL cholesterol, and blood pressure in multivariable MR. Genetically instrumented higher IR was associated with higher risk of HF (OR 1.19 per 1-log unit higher risk of IR; 95% CI 1.00-1.41; P = 0.041). There were no notable associations identified between fasting insulin, glucose, or glycated hemoglobin and risk of HF. Genetic liability to HF was causally linked to higher risk of T2D (OR 1.49; 95% CI 1.01-2.19; P = 0.042), although again with evidence of pleiotropy.

CONCLUSIONS

These findings suggest a possible causal role of T2D and IR in HF etiology, although the presence of both bidirectional effects and directional pleiotropy highlights potential sources of bias that must be considered.

Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development

Drug development in cardiovascular disease is stagnating, with lack of efficacy and adverse effects being barriers to innovation. Human genetics can provide compelling evidence of causation through approaches such as Mendelian randomization, with genetic support for causation increasing the probability of a clinical trial succeeding. Mendelian randomization applied to quantitative traits can identify risk factors for disease that are both causal and amenable to therapeutic modification. However, important differences exist between genetic investigations of a biomarker (such as HDL cholesterol) and a drug target aimed at modifying the same biomarker of interest (such as cholesteryl ester transfer protein), with implications for the methodology, interpretation and application of Mendelian randomization to drug development. Differences include the comparative nature of the genetic architecture - that is, biomarkers are typically polygenic, whereas protein drug targets are influenced by either cis-acting or trans-acting genetic variants - and the potential for drug targets to show disease associations that might differ from those of the biomarker that they are intended to modify (target-mediated pleiotropy). In this Review, we compare and contrast the use of Mendelian randomization to evaluate potential drug targets versus quantitative traits. We explain how genetic epidemiological studies can be used to assess the aetiological roles of biomarkers in disease and to prioritize drug targets, including designing their evaluation in clinical trials.

Effects of apolipoprotein B on lifespan and risks of major diseases including type 2 diabetes: a mendelian randomisation analysis using outcomes in first-degree relatives

BACKGROUND

Apolipoprotein B (apoB) is emerging as the crucial lipoprotein trait for the role of lipoprotein lipids in the aetiology of coronary heart disease. In this study, we evaluated the effects of genetically predicted apoB on outcomes in first-degree relatives.

METHODS

Data on lipoprotein lipids and disease outcomes in first-degree relatives were obtained from the UK Biobank study. We did a univariable mendelian randomisation analysis using a weighted genetic instrument for apoB. For outcomes with which apoB was associated at a false discovery rate (FDR) of less than 5%, multivariable mendelian randomisation analyses were done, including genetic instruments for LDL cholesterol and triglycerides. Associations between apoB and self-reported outcomes in first-degree relatives were characterised for 12 diseases (including heart disease, stroke, and hypertension) and parental vital status together with age at death. Estimates were inferred causal effects per 1 SD elevated lipoprotein trait (for apoB, 1 SD=0·24 g/L). Replication of estimates for lifespan and type 2 diabetes was done using conventional two-sample mendelian randomisation with summary estimates from genome-wide association study consortia.

FINDINGS

In univariable mendelian randomisation, genetically elevated apoB in participants was identified to lead to a shorter lifespan in parents (fathers: 0·89 years of life lost per 1 SD higher apoB in offspring, 95% CI 0·63-1·16, FDR-adjusted p=4·0 × 10-10; mothers: 0·48 years of life lost per 1 SD higher apoB in offspring, 0·25-0·71, FDR-adjusted p=1·7 × 10-4). The effects were strengthened to around 2 years of life lost in multivariable mendelian randomisation and were replicated in conventional two-sample mendelian randomisation (odds ratio [OR] of surviving to the 90th centile of lifespan: 0·38 per 1 SD higher apoB in offspring, 95% CI 0·22-0·65). Genetically elevated apoB caused higher risks of heart disease in all first-degree relatives and a higher risk of stroke in mothers. Findings in first-degree relatives were replicated in two-sample multivariable mendelian randomisation, which identified apoB to increase (OR 2·32 per 1 SD higher apoB, 95% CI 1·49-3·61) and LDL cholesterol to decrease (0·34 per 1 SD higher LDL cholesterol, 0·21-0·54) the risk of type 2 diabetes.

INTERPRETATION

Higher apoB shortens lifespan, increases risks of heart disease and stroke, and in multivariable analyses that account for LDL cholesterol, increases risk of diabetes.

FUNDING

British Heart Foundation, UK Medical Research Council, and UK Research and Innovation.