Mendelian randomization for studying the effects of perturbing drug targets

HMG-CoA reductase is a potential therapeutic target for migraine: a mendelian randomization study

Statins are thought to have positive effects on migraine but existing data are inconclusive. We aimed to evaluate the causal effect of such drugs on migraines using Mendelian randomization. We used four types of genetic instruments as proxies for HMG-CoA reductase inhibition. We included the expression quantitative trait loci of the HMG-CoA reductase gene and genetic variation within or near the HMG-CoA reductase gene region. Variants were associated with low-density lipoprotein cholesterol, apolipoprotein B, and total cholesterol. Genome-wide association study summary data for the three lipids were obtained from the UK Biobank. Comparable data for migraine were obtained from the International Headache Genetic Consortium and the FinnGen Consortium. Inverse variance weighting method was used for the primary analysis. Additional analyses included pleiotropic robust methods, colocalization, and meta-analysis. Genetically determined high expression of HMG-CoA reductase was associated with an increased risk of migraines (OR = 1.55, 95% CI 1.30-1.84, P = 6.87 × 10-7). Similarly, three genetically determined HMG-CoA reductase-mediated lipids were associated with an increased risk of migraine. These conclusions were consistent across meta-analyses. We found no evidence of bias caused by pleiotropy or genetic confounding factors. These findings support the hypothesis that statins can be used to treat migraine.

Evaluation of Plasma Biomarkers for Causal Association With Peripheral Artery Disease

BACKGROUND

Hundreds of biomarkers for peripheral artery disease (PAD) have been reported in the literature; however, the observational nature of these studies limits causal inference due to the potential of reverse causality and residual confounding. We sought to evaluate the potential causal impact of putative PAD biomarkers identified in human observational studies through genetic causal inference methods.

METHODS

Putative circulating PAD biomarkers were identified from human observational studies through a comprehensive literature search based on terms related to PAD using PubMed, Cochrane, and Embase. Genetic instruments were generated from publicly available genome-wide association studies of circulating biomarkers. Two-sample Mendelian randomization was used to test the association of genetically determined biomarker levels with PAD using summary statistics from a genome-wide association study of 31 307 individuals with and 211 753 individuals without PAD in the Veterans Affairs Million Veteran Program and replicated in data from FinnGen comprised of 11 924 individuals with and 288 638 individuals without PAD.

RESULTS

We identified 204 unique circulating biomarkers for PAD from the observational literature, of which 173 were genetically instrumented using genome-wide association study results. After accounting for multiple testing (false discovery rate, <0.05), 10 of 173 (5.8%) biomarkers had significant associations with PAD. These 10 biomarkers represented categories including plasma lipoprotein regulation, lipid homeostasis, and protein-lipid complex remodeling. Observational literature highlighted different pathways including inflammatory response, negative regulation of multicellular organismal processes, and regulation of response to external stimuli.

CONCLUSIONS

Integrating human observational studies and genetic causal inference highlights several key pathways in PAD pathophysiology. This work demonstrates that a substantial portion of biomarkers identified in observational studies are not well supported by human genetic evidence and emphasizes the importance of triangulating evidence to understand PAD pathophysiology. Although the identified biomarkers offer insights into atherosclerotic development in the lower limb, their specificity to PAD compared with more widespread atherosclerosis requires further study.

Genetically Determined Circulating Lactase/Phlorizin Hydrolase Concentrations and Risk of Colorectal Cancer: A Two-Sample Mendelian Randomization Study

Previous research has found that milk is associated with a decreased risk of colorectal cancer (CRC). However, it is unclear whether the milk digestion by the enzyme lactase-phlorizin hydrolase (LPH) plays a role in CRC susceptibility. Our study aims to investigate the direct causal relationship of CRC risk with LPH levels by applying a two-sample Mendelian Randomization (MR) strategy. Genetic instruments for LPH were derived from the Fenland Study, and CRC-associated summary statistics for these instruments were extracted from the FinnGen Study, PLCO Atlas Project, and Pan-UK Biobank. Primary MR analyses focused on a cis-variant (rs4988235) for LPH levels, with results integrated via meta-analysis. MR analyses using all variants were also undertaken. This analytical approach was further extended to assess CRC subtypes (colon and rectal). Meta-analysis across the three datasets illustrated an inverse association between genetically predicted LPH levels and CRC risk (OR: 0.92 [95% CI, 0.89-0.95]). Subtype analyses revealed associations of elevated LPH levels with reduced risks for both colon (OR: 0.92 [95% CI, 0.89-0.96]) and rectal cancer (OR: 0.92 [95% CI, 0.87, 0.98]). Consistency was observed across varied analytical methods and datasets. Further exploration is warranted to unveil the underlying mechanisms and validate LPH's potential role in CRC prevention.

Mendelian Randomization Applied to Neurology: Promises and Challenges

The Mendelian randomization (MR) paradigm allows for causal inferences to be drawn using genetic data. In recent years, the expansion of well-powered publicly available genetic association data related to phenotypes such as brain tissue gene expression, brain imaging, and neurologic diseases offers exciting opportunities for the application of MR in the field of neurology. In this review, we discuss the basic principles of MR, its myriad applications to research in neurology, and potential pitfalls of injudicious applications. Throughout, we provide examples where MR-informed findings have shed light on long-standing epidemiologic controversies, provided insights into the pathophysiology of neurologic conditions, prioritized drug targets, and informed drug repurposing opportunities. With the ever-expanding availability of genome-wide association data, we project MR to become a key driver of progress in the field of neurology. It is therefore paramount that academics and clinicians within the field are familiar with the approach.

Genetic insights into repurposing statins for hyperthyroidism prevention: a drug-target Mendelian randomization study

Background

Current therapeutic measures for thyroid dysfunction are limited and often accompanied by adverse effects. The use of lipid-lowering drugs like statins has recently been associated with lower thyroid eye diseases risk.

Objective

To investigate the implications of genetically proxied lipid-lowering drugs on thyroid dysfunction.

Methods

In this drug-target Mendelian randomization (MR) study, we utilized genetic variants within drug target genes associated with low-density lipoprotein (LDL) or triglyceride (TG), derived from a genome-wide association study (GWAS) meta-analysis (N ≤ 188,577), to simulate lifelong drug interventions. Genetic summary statistics for thyroid dysfunction outcomes were retrieved from GWAS datasets of Thyroid Omics Consortium (N ≤ 54,288) and UK Biobank (N = 484,598). Inverse-variance-weighted MR (IVW-MR) method was performed as primary analysis, followed by validation in colocalization analysis. A subsequent two-step MR analysis was conducted to identify biomarkers mediating the identified drug-outcome association.

Results

In IVW-MR analysis, genetic mimicry of 3-hydroxy-3-methylglutarylcoenzyme reductase (HMGCR) inhibitors (e.g. statins) was significantly associated with lower risk of hyperthyroidism in two independent datasets (OR1, 0.417 per 1-mmol/L lower in LDL-C; 95% CI 0.262 to 0.664; P1 = 2.262 × 10-4; OR2 0.996; 95% CI 0.993-0.998; P2 = 0.002). Two-step MR analysis revealed eighteen biomarkers linked to genetic mimicry of HMGCR inhibition, and identified insulin-like growth factor 1 (IGF-1) levels mediating 2.108% of the negative causal relationship between HMGCR inhibition and hyperthyroidism.

Conclusion

This study supports HMGCR inhibition as a promising therapeutic strategy for hyperthyroidism and suggests its underlying mechanisms may extend beyond lipid metabolism. Further investigations through laboratory studies and clinical trials are necessary to confirm and elucidate these findings.

Incorporating biological and clinical insights into variant choice for Mendelian randomisation: examples and principles

Mendelian randomisation is an accessible and valuable epidemiological approach to provide insight into the causal nature of relationships between risk factor exposures and disease outcomes. However, if performed without critical thought, we may simply have replaced one set of implausible assumptions (no unmeasured confounding or reverse causation) with another set of implausible assumptions (no pleiotropy or other instrument invalidity). The most critical decision to avoid pleiotropy is which genetic variants to use as instrumental variables. Two broad strategies for instrument selection are a biologically motivated strategy and a genome-wide strategy; in general, a biologically motivated strategy is preferred. In this review, we discuss various ways of implementing a biologically motivated selection strategy: using variants in a coding gene region for the exposure or a gene region that encodes a regulator of exposure levels, using a positive control variable and using a biomarker as the exposure rather than its behavioural proxy. In some cases, a genome-wide analysis can provide important complementary evidence, even when its reliability is questionable. In other cases, a biologically-motivated analysis may not be possible. The choice of genetic variants must be informed by biological and functional considerations where possible, requiring collaboration to combine biological and clinical insights with appropriate statistical methodology.

The citrate transporter SLC13A5 as a therapeutic target for kidney disease: evidence from Mendelian randomization to inform drug development

BACKGROUND

Solute carrier family 13 member 5 (SLC13A5) is a Na+-coupled citrate co-transporter that mediates entry of extracellular citrate into the cytosol. SLC13A5 inhibition has been proposed as a target for reducing progression of kidney disease. The aim of this study was to leverage the Mendelian randomization paradigm to gain insight into the effects of SLC13A5 inhibition in humans, towards prioritizing and informing clinical development efforts.

METHODS

The primary Mendelian randomization analyses investigated the effect of SLC13A5 inhibition on measures of kidney function, including creatinine and cystatin C-based measures of estimated glomerular filtration rate (creatinine-eGFR and cystatin C-eGFR), blood urea nitrogen (BUN), urine albumin-creatinine ratio (uACR), and risk of chronic kidney disease and microalbuminuria. Secondary analyses included a paired plasma and urine metabolome-wide association study, investigation of secondary traits related to SLC13A5 biology, a phenome-wide association study (PheWAS), and a proteome-wide association study. All analyses were compared to the effect of genetically predicted plasma citrate levels using variants selected from across the genome, and statistical sensitivity analyses robust to the inclusion of pleiotropic variants were also performed. Data were obtained from large-scale genetic consortia and biobanks, with sample sizes ranging from 5023 to 1,320,016 individuals.

RESULTS

We found evidence of associations between genetically proxied SLC13A5 inhibition and higher creatinine-eGFR (p = 0.002), cystatin C-eGFR (p = 0.005), and lower BUN (p = 3 × 10-4). Statistical sensitivity analyses robust to the inclusion of pleiotropic variants suggested that these effects may be a consequence of higher plasma citrate levels. There was no strong evidence of associations of genetically proxied SLC13A5 inhibition with uACR or risk of CKD or microalbuminuria. Secondary analyses identified evidence of associations with higher plasma calcium levels (p = 6 × 10-13) and lower fasting glucose (p = 0.02). PheWAS did not identify any safety concerns.

CONCLUSIONS

This Mendelian randomization analysis provides human-centric insight to guide clinical development of an SLC13A5 inhibitor. We identify plasma calcium and citrate as biologically plausible biomarkers of target engagement, and plasma citrate as a potential biomarker of mechanism of action. Our human genetic evidence corroborates evidence from various animal models to support effects of SLC13A5 inhibition on improving kidney function.

A drug target for erectile dysfunction to help improve fertility, sexual activity, and wellbeing: mendelian randomisation study

OBJECTIVE

To investigate the association of genetically proxied (using a surrogate biomarker) inhibition of phosphodiesterase 5 (PDE5), an established drug target for erectile dysfunction, with fertility, sexual behaviour, and subjective wellbeing.

DESIGN

Two sample cis-mendelian randomisation study.

SETTING

Summary data on genetic associations obtained from the International Consortium for Blood Pressure and UK Biobank.

PARTICIPANTS

Individuals of European ancestry from the International Consortium for Blood Pressure (n=757 601) for estimating PDE5 inhibition (using the surrogate biomarker of diastolic blood pressure reduction), and UK Biobank (n=211 840) for estimating the fertility, sexual behaviour, and subjective wellbeing outcomes in male participants.

INTERVENTION

Genetically proxied PDE5 inhibition.

MAIN OUTCOME MEASURES

Number of children fathered, number of sexual partners, probability of never having had sexual intercourse, and subjective wellbeing.

RESULTS

Genetically proxied PDE5 inhibition was associated with male participants having 0.28 (95% confidence interval 0.16 to 0.39) more children (false discovery rate corrected P<0.001). This association was not identified in female participants. No evidence was found of an association between genetically proxied PDE5 inhibition and number of sexual partners, probability of never having had sexual intercourse, or self-reported wellbeing in male participants.

CONCLUSIONS

The findings of this study provide genetic support for PDE5 inhibition potentially increasing the number of children fathered by male individuals. Absence of this association in female participants supports increased propensity for sustained and robust penile erections as a potential underlying mechanism. Further studies are required to confirm this, however, and these findings should not promote indiscriminate use of PDE5 inhibitors, which can also have harmful adverse effects.

Genetic association of lipids and lipid-lowering drugs with sepsis: a Mendelian randomization and mediation analysis

Background

The impact of lipid-lowering medications on sepsis is still not well defined. A Mendelian randomization (MR) study was carried out to probe the causal connections between genetically determined lipids, lipid-reducing drugs, and the risk of sepsis.

Materials and methods

Data on total serum cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A-I (ApoA-I), apolipoprotein B (ApoB), and triglycerides (TG) were retrieved from the MR-Base platform and the Global Lipids Genetics Consortium in 2021 (GLGC2021). Our study categorized sepsis into two groups: total sepsis and 28-day mortality of sepsis patients (sepsis28). The inverse-variance weighted (IVW) method was the primary method used in MR analysis. Cochran's Q test and the MR-Egger intercept method were used to assess the heterogeneity and pleiotropy.

Results

In the MR analysis, we found that ApoA-I played a suggestively positive role in protecting against both total sepsis (OR, 0.863 per SD increase in ApoA-I; 95% CI, 0.780-0.955; P = 0.004) and sepsis28 (OR, 0.759; 95% CI, 0.598-0.963; P = 0.023). HDL-C levels were also found to suggestively reduce the incidence of total sepsis (OR, 0.891 per SD increase in HDL-C; 95% CI, 0.802-0.990; P = 0.031). Reverse-MR showed that sepsis28 led to a decrease in HDL-C level and an increase in TG level. In drug-target MR, we found that HMGCR inhibitors positively protected against total sepsis (1 OR , 0.719 per SD reduction in LDL-C; 95% CI, 0.540-0.958; P = 0.024). LDL-C and HDL-C proxied CETP inhibitors were found to have a protective effect on total sepsis, with only LDL-C proxied CETP inhibitors showing a suggestively protective effect on sepsis28. In Mediated-MR, BMI exhibited a negative indirect effect in HMGCR inhibitors curing sepsis. The indirect impact of ApoA-I explained over 50% of the curative effects of CETP inhibitors in sepsis.

Conclusions

Our MR study suggested that ApoA-I and HDL-C protected against sepsis, while HMGCR and CETP inhibitors showed therapeutic potential beyond lipid-lowering effects. ApoA-I explained the effects of CETP inhibitors. Our study illuminates how lipids affect sepsis patients and the effectiveness of new drugs, opening new avenues for sepsis treatment.

Repurposing antidiabetic drugs for rheumatoid arthritis: results from a two-sample Mendelian randomization study

Despite increasing therapeutic options to treat rheumatoid arthritis (RA), many patients fail to reach treatment targets. The use of antidiabetic drugs like thiazolidinediones has been associated with lower RA risk. We aimed to explore the repurposing potential of antidiabetic drugs in RA prevention by assessing associations between genetic variation in antidiabetic drug target genes and RA using Mendelian randomization (MR). A two-sample MR design was used to estimate the association between the antidiabetic drug and RA risk using summary statistics from genome-wide association studies (GWAS). We selected independent genetic variants from the gene(s) that encode the target protein(s) of the investigated antidiabetic drug as instruments. We extracted the associations of instruments with blood glucose concentration and RA from the UK Biobank and a GWAS meta-analysis of clinically diagnosed RA, respectively. The effect of genetic variation in the drug target(s) on RA risk was estimated by the Wald ratio test or inverse-variance weighted method. Insulin and its analogues, thiazolidinediones, and sulfonylureas had valid genetic instruments (n = 1, 1, and 2, respectively). Genetic variation in thiazolidinedione target (gene: PPARG) was inversely associated with RA risk (odds ratio [OR] 0.38 per 0.1mmol/L glucose lowering, 95% confidence interval [CI] 0.20-0.73). Corresponding ORs (95%CIs) were 0.83 (0.44-1.55) for genetic variation in the targets of insulin and its analogues (gene: INSR), and 1.12 (0.83, 1.49) 1.25 (0.78-2.00) for genetic variation in the sulfonylurea targets (gene: ABCC8 and KCNJ11). In conclusion, genetic variation in the thiazolidinedione target is associated with a lower RA risk. The underlying mechanisms warrant further exploration.

Circulatory proteins relate cardiovascular disease to cognitive performance: A mendelian randomisation study

Background and objectives: Mechanistic research suggests synergistic effects of cardiovascular disease (CVD) and dementia pathologies on cognitive decline. Interventions targeting proteins relevant to shared mechanisms underlying CVD and dementia could also be used for the prevention of cognitive impairment. Methods: We applied Mendelian randomisation (MR) and colocalization analysis to investigate the causal relationships of 90 CVD-related proteins measured by the Olink CVD I panel with cognitive traits. Genetic instruments for circulatory protein concentrations were obtained using a meta-analysis of genome-wide association studies (GWAS) from the SCALLOP consortium (N = 17,747) based on three sets of criteria: 1) protein quantitative trait loci (pQTL); 2) cis-pQTL (pQTL within ±500 kb from the coding gene); and 3) brain-specific cis-expression QTL (cis-eQTL) which accounts for coding gene expression based on GTEx8. Genetic associations of cognitive performance were obtained from GWAS for either: 1) general cognitive function constructed using Principal Component Analysis (N = 300,486); or, 2) g Factor constructed using genomic structural equation modelling (N = 11,263-331,679). Findings for candidate causal proteins were replicated using a separate protein GWAS in Icelanders (N = 35,559). Results: A higher concentration of genetically predicted circulatory myeloperoxidase (MPO) was nominally associated with better cognitive performance (p < 0.05) using different selection criteria for genetic instruments. Particularly, brain-specific cis-eQTL predicted MPO, which accounts for protein-coding gene expression in brain tissues, was associated with general cognitive function (βWald = 0.22, PWald = 2.4 × 10-4). The posterior probability for colocalization (PP.H4) of MPO pQTL with the g Factor was 0.577. Findings for MPO were replicated using the Icelandic GWAS. Although we did not find evidence for colocalization, we found that higher genetically predicted concentrations of cathepsin D and CD40 were associated with better cognitive performance and a higher genetically predicted concentration of CSF-1 was associated with poorer cognitive performance. Conclusion: We conclude that these proteins are involved in shared pathways between CVD and those for cognitive reserve or affecting cognitive decline, suggesting therapeutic targets able to reduce genetic risks conferred by cardiovascular disease.

Statistical methods for cis-Mendelian randomization with two-sample summary-level data

Mendelian randomization (MR) is the use of genetic variants to assess the existence of a causal relationship between a risk factor and an outcome of interest. Here, we focus on two-sample summary-data MR analyses with many correlated variants from a single gene region, particularly on cis-MR studies which use protein expression as a risk factor. Such studies must rely on a small, curated set of variants from the studied region; using all variants in the region requires inverting an ill-conditioned genetic correlation matrix and results in numerically unstable causal effect estimates. We review methods for variable selection and estimation in cis-MR with summary-level data, ranging from stepwise pruning and conditional analysis to principal components analysis, factor analysis, and Bayesian variable selection. In a simulation study, we show that the various methods have comparable performance in analyses with large sample sizes and strong genetic instruments. However, when weak instrument bias is suspected, factor analysis and Bayesian variable selection produce more reliable inferences than simple pruning approaches, which are often used in practice. We conclude by examining two case studies, assessing the effects of low-density lipoprotein-cholesterol and serum testosterone on coronary heart disease risk using variants in the HMGCR and SHBG gene regions, respectively.

Associations of genetically predicted IL-6 signaling with cardiovascular disease risk across population subgroups

BACKGROUND

Interleukin 6 (IL-6) signaling is being investigated as a therapeutic target for atherosclerotic cardiovascular disease (CVD). While changes in circulating high-sensitivity C-reactive protein (hsCRP) are used as a marker of IL-6 signaling, it is not known whether there is effect heterogeneity in relation to baseline hsCRP levels or other cardiovascular risk factors. The aim of this study was to explore the association of genetically predicted IL-6 signaling with CVD risk across populations stratified by baseline hsCRP levels and cardiovascular risk factors.

METHODS

Among 397,060 White British UK Biobank participants without known CVD at baseline, we calculated a genetic risk score for IL-6 receptor (IL-6R)-mediated signaling, composed of 26 variants at the IL6R gene locus. We then applied linear and non-linear Mendelian randomization analyses exploring associations with a combined endpoint of incident coronary artery disease, ischemic stroke, peripheral artery disease, aortic aneurysm, and cardiovascular death stratifying by baseline hsCRP levels and cardiovascular risk factors.

RESULTS

The study participants (median age 59 years, 53.9% females) were followed-up for a median of 8.8 years, over which time a total of 46,033 incident cardiovascular events occurred. Genetically predicted IL-6R-mediated signaling activity was associated with higher CVD risk (hazard ratio per 1-mg/dL increment in absolute hsCRP levels: 1.11, 95% CI: 1.06-1.17). The increase in CVD risk was linearly related to baseline absolute hsCRP levels. There was no evidence of heterogeneity in the association of genetically predicted IL-6R-mediated signaling with CVD risk when stratifying the population by sex, age, body mass index, estimated glomerular filtration rate, or systolic blood pressure, but there was evidence of greater associations in individuals with low-density lipoprotein cholesterol ≥ 160 mg/dL.

CONCLUSIONS

Any benefit of inhibiting IL-6 signaling for CVD risk reduction is likely to be proportional to absolute reductions in hsCRP levels. Therapeutic inhibition of IL-6 signaling for CVD risk reduction should therefore prioritize those individuals with the highest baseline levels of hsCRP.

Using genetics to assess the association of commonly used antihypertensive drugs with diabetes, glycaemic traits and lipids: a trans-ancestry Mendelian randomisation study

AIMS/HYPOTHESIS

Diabetes and hyperlipidaemia are common comorbidities in people with hypertension. Despite similar protective effects on CVD, different classes of antihypertensive drugs have different effects on CVD risk factors, including diabetes, glucose metabolism and lipids. However, these pleiotropic effects have not been assessed in long-term, large randomised controlled trials, especially for East Asians.

METHODS

We used Mendelian randomisation to obtain unconfounded associations of ACE inhibitors, β-blockers (BBs) and calcium channel blockers (CCBs). Specifically, we used genetic variants in drug target genes and related to systolic BP in Europeans and East Asians, and applied them to the largest available genome-wide association studies of diabetes (74,124 cases and 824,006 controls in Europeans, 77,418 cases and 356,122 controls in East Asians), blood glucose levels, HbA_1c, and lipids (LDL-cholesterol, HDL-cholesterol and triacylglycerols) (approximately 0.5 million Europeans and 0.1 million East Asians). We used coronary artery disease (CAD) as a control outcome and used different genetic instruments and analysis methods as sensitivity analyses.

RESULTS

As expected, genetically proxied ACE inhibition, BBs and CCBs were related to lower risk of CAD in both ancestries. Genetically proxied ACE inhibition was associated with a lower risk of diabetes (OR 0.85, 95% CI 0.78-0.93), and genetic proxies for BBs were associated with a higher risk of diabetes (OR 1.05, 95% CI 1.02-1.09). The estimates were similar in East Asians, and were corroborated by systematic review and meta-analyses of randomised controlled trials. In both ancestries, genetic proxies for BBs were associated with lower HDL-cholesterol and higher triacylglycerols, and genetic proxies for CCBs were associated with higher LDL-cholesterol. The estimates were robust to the use of different genetic instruments and analytical methods.

CONCLUSIONS/INTERPRETATION

Our findings suggest protective association of genetically proxied ACE inhibition with diabetes, while genetic proxies for BBs and CCBs possibly relate to an unfavourable metabolic profile. Developing a deeper understanding of the pathways underlying these diverse associations would be worthwhile, with implications for drug repositioning as well as optimal CVD prevention and treatment strategies in people with hypertension, diabetes and/or hyperlipidaemia.

Morning Cortisol and Circulating Inflammatory Cytokine Levels: A Mendelian Randomisation Study

Cortisol exerts a broad anti-inflammatory effect on the immune system. Inflammatory cytokines contribute to the molecular signalling pathways implicated in various autoimmune and inflammatory conditions. However, the mechanisms by which cortisol modulates such signalling pathways remain uncertain. Leveraging summary-level data from the CORtisol NETwork (CORNET, n = 25,314) and FINRISK (n = 8293) genome-wide association studies, we used two-sample Mendelian randomisation to investigate the causal effect of genetically proxied morning cortisol levels on 42 circulating cytokines. We found that increased genetically proxied morning cortisol levels were associated with reduced levels of IL-8 and increased levels of MIF. These results provide mechanistic insight into the immunomodulatory effects of endogenous cortisol and the therapeutic effects of exogenous corticosteroids. Clinically, our findings underline the therapeutic importance of steroids in inflammatory conditions where IL-8 and MIF play a central pathophysiological role in the onset and progression of disease.

Mendelian Randomization: Concepts and Scope

Mendelian randomization (MR) is a method of studying the causal effects of modifiable exposures (i.e., potential risk factors) on health, social, and economic outcomes using genetic variants associated with the specific exposures of interest. MR provides a more robust understanding of the influence of these exposures on outcomes because germline genetic variants are randomly inherited from parents to offspring and, as a result, should not be related to potential confounding factors that influence exposure-outcome associations. The genetic variant can therefore be used as a tool to link the proposed risk factor and outcome, and to estimate this effect with less confounding and bias than conventional epidemiological approaches. We describe the scope of MR, highlighting the range of applications being made possible as genetic data sets and resources become larger and more freely available. We outline the MR approach in detail, covering concepts, assumptions, and estimation methods. We cover some common misconceptions, provide strategies for overcoming violation of assumptions, and discuss future prospects for extending the clinical applicability, methodological innovations, robustness, and generalizability of MR findings.

Leveraging human genetic data to investigate the cardiometabolic effects of glucose-dependent insulinotropic polypeptide signalling

AIMS/HYPOTHESIS

The aim of this study was to leverage human genetic data to investigate the cardiometabolic effects of glucose-dependent insulinotropic polypeptide (GIP) signalling.

METHODS

Data were obtained from summary statistics of large-scale genome-wide association studies. We examined whether genetic associations for type 2 diabetes liability in the GIP and GIPR genes co-localised with genetic associations for 11 cardiometabolic outcomes. For those outcomes that showed evidence of co-localisation (posterior probability >0.8), we performed Mendelian randomisation analyses to estimate the association of genetically proxied GIP signalling with risk of cardiometabolic outcomes, and to test whether this exceeded the estimate observed when considering type 2 diabetes liability variants from other regions of the genome.

RESULTS

Evidence of co-localisation with genetic associations of type 2 diabetes liability at both the GIP and GIPR genes was observed for five outcomes. Mendelian randomisation analyses provided evidence for associations of lower genetically proxied type 2 diabetes liability at the GIP and GIPR genes with lower BMI (estimate in SD units -0.16, 95% CI -0.30, -0.02), C-reactive protein (-0.13, 95% CI -0.19, -0.08) and triacylglycerol levels (-0.17, 95% CI -0.22, -0.12), and higher HDL-cholesterol levels (0.19, 95% CI 0.14, 0.25). For all of these outcomes, the estimates were greater in magnitude than those observed when considering type 2 diabetes liability variants from other regions of the genome.

CONCLUSIONS/INTERPRETATION

This study provides genetic evidence to support a beneficial role of sustained GIP signalling on cardiometabolic health greater than that expected from improved glycaemic control alone. Further clinical investigation is warranted.

DATA AVAILABILITY

All data used in this study are publicly available. The scripts for the analysis are available at: https://github.com/vkarhune/GeneticallyProxiedGIP .

Growth Factors and Their Roles in Multiple Sclerosis Risk

Background

Previous studies have suggested essential roles of growth factors on the risk of Multiple Sclerosis (MS), but it remains undefined whether the effects are causal.

Objective

We applied Mendelian randomization (MR) approaches to disentangle the causal relationship between genetically predicted circulating levels of growth factors and the risk of MS.

Methods

Genetic instrumental variables for fibroblast growth factor (FGF) 23, growth differentiation factor 15 (GDF15), insulin growth factor 1 (IGF1), insulin-like growth factor binding proteins 3 (IGFBP3) and vascular endothelial growth factor (VEGF) were obtained from up-to-date genome-wide association studies (GWAS). Summary-level statistics of MS were obtained from the International Multiple Sclerosis Genetics Consortium, incorporating 14,802 subjects with MS and 26,703 healthy controls of European ancestry. Inverse-variance weighted (IVW) MR was used as the primary method and multiple sensitivity analyses were employed in this study.

Results

Genetically predicted circulating levels of FGF23 were associated with risk of MS. The odds ratio (OR) of IVW was 0.63 (95% confidence interval [CI], 0.49-0.82; p < 0.001) per one standard deviation increase in circulating FGF23 levels. Weighted median estimators also suggested FGF23 associated with lower MS risk (OR = 0.67; 95% CI, 0.51-0.87; p = 0.003). While MR-Egger approach provided no evidence of horizontal pleiotropy (intercept = -0.003, p = 0.95). Results of IVW methods provided no evidence for causal roles of GDF1, IGF1, IGFBP3 and VEGF on MS risks, and additional sensitivity analyses confirmed the robustness of these null findings.

Conclusion

Our results implied a causal relationship between FGF23 and the risk of MS. Further studies are warranted to confirm FGF23 as a genetically valid target for MS.

Using Human Genetics to Understand Mechanisms in Ischemic Stroke Outcome: From Early Brain Injury to Long-Term Recovery

There is a critical need to elucidate molecular mechanisms underlying brain injury, repair, and recovery following ischemic stroke-a global health problem with major social and economic impact. Despite 5 decades of intensive research, there are no widely accepted neuroprotective drugs that mitigate ischemic brain injury, or neuroreparative drugs, or personalized approaches that guide therapies to enhance recovery. We here explore novel reverse translational approaches that will complement traditional forward translational methods in identifying mechanisms relevant to human stroke outcome. Although genome-wide association studies have yielded over 30 genetic loci that influence ischemic stroke risk, only a few genome-wide association studies have been performed for stroke outcome. We discuss important considerations for genetic studies of ischemic stroke outcome-including carefully designed phenotypes that capture injury/recovery mechanisms, anchored in time to stroke onset. We also address recent genome-wide association studies that provide insight into mechanisms underlying brain injury and repair. There are several ongoing initiatives exploring genomic associations with novel phenotypes related to stroke outcome. To improve the understanding of the genetic architecture of ischemic stroke outcome, larger studies using standardized phenotypes, preferably embedded in standard-of-care measures, are needed. Novel techniques beyond genome-wide association studies-including exploiting informatics, multi-omics, and novel analytics-promise to uncover genetic and molecular pathways from which drug targets and other new interventions may be identified.

Mendelian Randomization in Stroke: A Powerful Approach to Causal Inference and Drug Target Validation

Stroke is a leading cause of death and disability worldwide. However, our understanding of its underlying biology and the number of available treatment options remain limited. Mendelian randomization (MR) offers a powerful approach to identify novel biological pathways and therapeutic targets for this disease. Around ~100 MR studies have been conducted so far to explore, confirm, and quantify causal relationships between several exposures and risk of stroke. In this review, we summarize the current evidence arising from these studies, including those investigating ischemic stroke, hemorrhagic stroke, or both. We highlight the different types of exposures that are currently under study, ranging from well-known cardiovascular risk factors to less established inflammation-related mechanisms. Finally, we provide an overview of future avenues of research and novel approaches, including drug target validation MR, which is poised to have a substantial impact on drug development and drug repurposing.

Prioritizing the Role of Major Lipoproteins and Subfractions as Risk Factors for Peripheral Artery Disease

BACKGROUND

Lipoprotein-related traits have been consistently identified as risk factors for atherosclerotic cardiovascular disease, largely on the basis of studies of coronary artery disease (CAD). The relative contributions of specific lipoproteins to the risk of peripheral artery disease (PAD) have not been well defined. We leveraged large-scale genetic association data to investigate the effects of circulating lipoprotein-related traits on PAD risk.

METHODS

Genome-wide association study summary statistics for circulating lipoprotein-related traits were used in the mendelian randomization bayesian model averaging framework to prioritize the most likely causal major lipoprotein and subfraction risk factors for PAD and CAD. Mendelian randomization was used to estimate the effect of apolipoprotein B (ApoB) lowering on PAD risk using gene regions proxying lipid-lowering drug targets. Genes relevant to prioritized lipoprotein subfractions were identified with transcriptome-wide association studies.

RESULTS

ApoB was identified as the most likely causal lipoprotein-related risk factor for both PAD (marginal inclusion probability, 0.86; P=0.003) and CAD (marginal inclusion probability, 0.92; P=0.005). Genetic proxies for ApoB-lowering medications were associated with reduced risk of both PAD (odds ratio,0.87 per 1-SD decrease in ApoB [95% CI, 0.84-0.91]; P=9×10-10) and CAD (odds ratio,0.66 [95% CI, 0.63-0.69]; P=4×10-73), with a stronger predicted effect of ApoB lowering on CAD (ratio of effects, 3.09 [95% CI, 2.29-4.60]; P<1×10-6). Extra-small very-low-density lipoprotein particle concentration was identified as the most likely subfraction associated with PAD risk (marginal inclusion probability, 0.91; P=2.3×10-4), whereas large low-density lipoprotein particle concentration was the most likely subfraction associated with CAD risk (marginal inclusion probability, 0.95; P=0.011). Genes associated with extra-small very-low-density lipoprotein particle and large low-density lipoprotein particle concentration included canonical ApoB pathway components, although gene-specific effects were variable. Lipoprotein(a) was associated with increased risk of PAD independently of ApoB (odds ratio, 1.04 [95% CI, 1.03-1.04]; P=1.0×10-33).

CONCLUSIONS

ApoB was prioritized as the major lipoprotein fraction causally responsible for both PAD and CAD risk. However, ApoB-lowering drug targets and ApoB-containing lipoprotein subfractions had diverse associations with atherosclerotic cardiovascular disease, and distinct subfraction-associated genes suggest possible differences in the role of lipoproteins in the pathogenesis of PAD and CAD.