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'Omics studies provide a comprehensive characterisation of a biological entity, such as the genome, epigenome, transcriptome, proteome, metabolome, or microbiome. This review covers the unique properties of these types of 'omics and their roles as causal mediators in cardiovascular disease. Moreover, applications and challenges of integrating multiple types of 'omics data to increase predictive power, improve causal inference, and elucidate biological mechanisms are discussed.Multi-omics approaches are growing in adoption as they provide orthogonal evidence and overcome the limitations of individual types of 'omics data. Studies with multiple types of 'omics data have improved the diagnosis and prediction of disease states and afforded a deeper understanding of underlying pathophysiological mechanisms, beyond any single type of 'omics data. For instance, disease-associated loci in the genome can be supplemented with other 'omics to prioritise causal genes and understand the function of non-coding variants. Alternatively, techniques, such as Mendelian randomisation, can leverage genetics to provide evidence supporting a causal role for disease-associated molecules, and elucidate their role in disease pathogenesis. As technologies improve, costs for 'omics studies will continue to fall and datasets will become increasingly accessible to researchers. The intrinsically unbiased nature of 'omics data is well-suited to exploratory analyses that discover causal mediators of disease, and multi-omics is an emerging discipline that leverages the strengths of each type of 'omics data to provide insights greater than the sum of its parts.

Adenosine triphosphate-citrate lyase (ACLY) inhibition is a therapeutic strategy under investigation for atherosclerotic cardiovascular disease, nonalcoholic steatohepatitis, and metabolic syndrome. Mouse models suggest that ACLY inhibition could reduce inflammation and kidney fibrosis. Genetic analysis of ACLY in chronic kidney disease (CKD) has not been performed.We constructed a genetic instrument by selecting variants associated withMendelian randomization analyses revealed that genetically reduced ACLY expression was associated with reduced risk of CKD but had no effect on either eGFR or ACR. Further evaluation of ACLY in kidney disease is warranted.

Genetic predisposition is a risk factor for office hypertension. We tested whether genetic background could identify individuals with ambulatory daytime hypertension in a sample of white Europeans from Liechtenstein. We evaluated two measures of predisposition to hypertension: family history and polygenic risk scores (PRS). Our analytic sample contained 1444 participants aged 25 to 41. Of the participants, 12% had office hypertension, while 37% had out-of-office hypertension. The correlation between blood pressure PRS and family history of hypertension was low (R2= 4.96×10−3), but both were strongly associated with ambulatory blood pressure (2.2 mmHg per 1 SD increase [95% CI: 1.6, 2.7] & 2.4 mmHg increase with positive family history [95% CI: 1.3, 3.4], respectively). The PRS provides incremental improvement in predicting ambulatory systolic blood pressure beyond a validated blood pressure prediction score (ΔAIC = - 33), whereas family history does not (ΔAIC = 1). However, the difference in performance between a baseline prediction algorithm for identifying ambulatory systolic daytime hypertension (positive likelihood ratio of 6.87 [95% CI: 5.56, 8.49]; negative likelihood ratio of 0.45 [95% CI: 0.39, 0.51]) and the same model with PRS integrated (positive likelihood ratio of 7.69 [95% CI: 6.18, 9.57]; negative likelihood ratio of 0.43 [95% CI: 0.37, 0.49]) was modest. In conclusion, in a white European sample from Liechtenstein, PRS and family history are distinct constructs that are associated with increased clinical and ambulatory blood pressure. Unlike family history, polygenic risk scores provide incremental information in the identification of individuals with ambulatory hypertension. However, these gains are modest and warrant further development to improve predictive utility at the point-of-care.

ImportanceBody mass index (BMI) is an easily obtainable surrogate for adiposity. However, there is substantial variability in body composition and adipose tissue distribution between individuals with the same BMI. Furthermore, previous literature is conflicting regarding the optimal BMI linked with the lowest mortality risk.ObjectiveTo determine which of BMI, fat mass index (FMI), and waist-to-hip (WHR) is the strongest and most consistent causal predictor for mortality.DesignWe created a case-control cohort using all incident deaths from the UK Biobank (UKB; 2006 to 2022).Setting22 Clinical assessment centres across the United Kingdom.ParticipantsWe partitioned UKB British participants (N= 387,672) into a discovery (N = 337,078) and validation cohort (N = 50,594), the latter consisting of 25,297 deaths and 25,297 randomly selected age- and sex-matched controls. The discovery cohort was used to derive genetically-determined adiposity measures while the validation cohort was used for all other analyses. Relationships between exposures and outcomes were analyzed through both observational and Mendelian randomization (MR) analyses to infer causality.ExposuresBMI, FMI and WHR.Main Outcomes and MeasuresAll-cause mortality; Cause-specific mortality (cancer, cardiovascular disease (CVD), respiratory disease, or other causes).ResultsObservational relationships between measured BMI and FMI with all-cause mortality were J-shaped, whereas the relationship with WHR was linear. Genetically-determined WHR had a stronger association with all-cause mortality compared to BMI or FMI (OR per SD increase of WHR (95% CI): 1.51 (1.32 – 1.72); 1.29 (1.20 – 1.38) for BMI, and 1.45 (1.36 – 1.54) for FMI, heterogeneity PPP > 0.05).Conclusions and RelevanceWHR has the strongest and most consistent causal association with risk of mortality irrespective of BMI, with the effect being stronger in males than females. Clinical recommendations and interventions should prioritize adiposity distribution rather than mass.Key PointsQuestionAmong body mass index (BMI), fat mass index (FMI), or waist-to-hip (WHR) ratio, what is the optimal adiposity measure for predicting mortality outcomes in adults?FindingsIn this Mendelian randomization study consisting of 387,672 British adult participants from the UK Biobank (UKB), WHR was found to have the strongest and most consistent causal relationship with all-cause and cause-specific mortality.MeaningWHR was the most robust predictor of mortality risk and may serve as a more appropriate target for health care intervention.

Background and Purpose— Mendelian stroke confers a high lifetime risk for mutation carriers; however, ethnicity-specific prevalence estimates have been difficult to establish. Methods— Eighteen genes responsible for Mendelian stroke were investigated using the Genome Aggregation Database. Genome Aggregation Database participants belonged to 1 of 7 populations: African/African-American, Latino/Admixed American, Ashkenazi Jewish, East Asian, Finnish European, non-Finnish European, and South Asian. Rare nonsynonymous variants from 101 635 participants free of neurological disease were examined for each ethnicity. Mutations were categorized according to 3 nested classes: pathogenic clinical variants, likely damaging variants based on in silico prediction, and all nonsynonymous variants. Results— ABCC6 , KRIT1 , CECR1 , COL3A1 , COL4A1 , COL4A2 , COLGALT1 , GLA , HTRA1 , NOTCH3 , RNF213 , and TREX1 harbored pathogenic clinical variants in Genome Aggregation Database. Across all 18 genes, total nonsynonymous carrier frequency was found to be high in 5 ethnicities (African/African-American, Latino/Admixed American, East Asian, non-Finnish European, and South Asian; 28.5%–37.5%) while lower total frequencies were estimated for in silico–predicted likely damaging variants (14.9%–19.7%) and pathogenic clinical variants (0.7%–2.8%). Overall, East Asian exhibited the highest total pathogenic clinical mutation carrier frequency (2.8%). ABCC6 pathogenic clinical variants were most prevalent among East Asian (0.8%). Pathogenic NOTCH3 variants, causal for cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, were most frequent among East Asian (1.1%) and South Asian (1.2%). East Asian also demonstrated the highest carrier rate for RNF213 (0.8%). Finnish European exhibited the greatest HTRA1 frequency (0.2%), while COL4A1 pathogenic variants were most prevalent in African/African-American (0.3%). Conclusions— Especially, among pathogenic clinical variants, Mendelian stroke genetic prevalence differed significantly between populations. These prevalence estimates may serve as guides for screening and risk profiling in patients worldwide, particularly for understudied non-European populations.

Background and ObjectivesLow buffy coat mitochondrial DNA copy number (mtDNA-CN) is associated with incident risk of stroke and poststroke mortality; however, its prognostic utility has not been extensively explored. Our goal was to investigate whether low buffy coat mtDNA-CN is a marker and causal determinant of poststroke outcomes using epidemiologic and genetic studies.MethodsFirst, we performed association testing between baseline buffy coat mtDNA-CN measurements and 1-month poststroke outcomes in 3,498 cases of acute, first stroke from 25 countries from the international, multicenter case-control study Importance of Conventional and Emerging Risk Factors of Stroke in Different Regions and Ethnic Groups of the World (INTERSTROKE). Then, we performed 2-sample mendelian randomization analyses to evaluate potential causative effects of low mtDNA-CN on 3-month modified Rankin Scale (mRS) score. Genetic variants associated with mtDNA-CN levels were derived from the UK Biobank study (N = 383,476), and corresponding effects on 3-month mRS score were ascertained from the Genetics of Ischemic Stroke Functional Outcome (GISCOME; N = 6,021) study.ResultsA 1-SD lower mtDNA-CN at baseline was associated with stroke severity (baseline mRS score: odds ratio [OR] 1.27, 95% confidence interval [CI] 1.19–1.36; p = 4.7 × 10−12). Independently of baseline stroke severity, lower mtDNA-CN was associated with increased odds of greater 1-month disability (ordinal mRS score: OR 1.16, 95% CI 1.08–1.24; p = 4.4 × 10−5), poor functional outcome status (mRS score 3–6 vs 0–2: OR 1.21, 95% CI 1.08–1.34; p = 6.9 × 10−4), and mortality (OR 1.35, 95% CI 1.14–1.59; p = 3.9 × 10−4). Subgroup analyses demonstrated consistent effects across stroke type, sex, age, country income level, and education level. In addition, mtDNA-CN significantly improved reclassification of poor functional outcome status (net reclassification index [NRI] score 0.16, 95% CI 0.08–0.23; p = 3.6 × 10−5) and mortality (NRI score 0.31, 95% CI 0.19–0.43; p = 1.7 × 10−7) beyond known prognosticators. With the use of independent datasets, mendelian randomization revealed that a 1-SD decrease in genetically determined mtDNA-CN was associated with increased odds of greater 3-month disability quantified by ordinal mRS score (OR 2.35, 95% CI 1.13–4.90; p = 0.02) and poor functional outcome status (OR 2.68, 95% CI 1.05–6.86; p = 0.04).DiscussionBuffy coat mtDNA-CN is a novel and robust marker of poststroke prognosis that may also be a causal determinant of poststroke outcomes.Classification of EvidenceThis study provides Class II evidence that low buffy coat mtDNA-CN (>1 SD) was associated with worse baseline severity and 1-month outcomes in patients with ischemic or hemorrhagic stroke.

Elevated liver de novo lipogenesis contributes to non-alcoholic steatohepatitis (NASH) and can be inhibited by targeting acetyl-CoA carboxylase (ACC). However, hypertriglyceridemia limits the use of pharmacological ACC inhibitors as a monotherapy. ATP-citrate lyase (ACLY) generates acetyl-CoA and oxaloacetate from citrate, but whether inhibition is effective for treating NASH is unknown. Here, we characterize a new mouse model that replicates many of the pathological and molecular drivers of NASH and find that genetically inhibiting ACLY in hepatocytes reduces liver malonyl-CoA, oxaloacetate, steatosis, and ballooning as well as blood glucose, triglycerides, and cholesterol. Pharmacological inhibition of ACLY mirrors genetic inhibition but has additional positive effects on hepatic stellate cells, liver inflammation, and fibrosis. Mendelian randomization of human variants that mimic reductions in ACLY also associate with lower circulating triglycerides and biomarkers of NASH. These data indicate that inhibiting liver ACLY may be an effective approach for treatment of NASH and dyslipidemia.

Background: The most prominent risk factor for atrial fibrillation (AF) is chronological age; however, underlying mechanisms are unexplained. Algorithms using epigenetic modifications to the human genome effectively predict chronological age. Chronological and epigenetic predicted ages may diverge in a phenomenon referred to as epigenetic age acceleration (EAA), which may reflect accelerated biological aging. We sought to evaluate for associations between epigenetic age measures and incident AF. Methods: Measures for 4 epigenetic clocks (Horvath, Hannum, DNA methylation [DNAm] PhenoAge, and DNAm GrimAge) and an epigenetic predictor of PAI-1 (plasminogen activator inhibitor-1) levels (ie, DNAm PAI-1) were determined for study participants from 3 population-based cohort studies. Cox models evaluated for associations with incident AF and results were combined via random-effects meta-analyses. Two-sample summary-level Mendelian randomization analyses evaluated for associations between genetic instruments of the EAA measures and AF. Results: Among 5600 participants (mean age, 65.5 years; female, 60.1%; Black, 50.7%), there were 905 incident AF cases during a mean follow-up of 12.9 years. Unadjusted analyses revealed all 4 epigenetic clocks and the DNAm PAI-1 predictor were associated with statistically significant higher hazards of incident AF, though the magnitudes of their point estimates were smaller relative to the associations observed for chronological age. The pooled EAA estimates for each epigenetic measure, with the exception of Horvath EAA, were associated with incident AF in models adjusted for chronological age, race, sex, and smoking variables. After multivariable adjustment for additional known AF risk factors that could also potentially function as mediators, pooled EAA measures for 2 clocks remained statistically significant. Five-year increases in EAA measures for DNAm GrimAge and DNAm PhenoAge were associated with 19% (adjusted hazard ratio [HR], 1.19 [95% CI, 1.09–1.31]; P P Conclusions: Our study identified adjusted associations between EAA measures and incident AF, suggesting that biological aging plays an important role independent of chronological age, though a potential underlying causal relationship remains unclear. These aging processes may be modifiable and not constrained by the immutable factor of time.

BackgroundATP-citrate lyase (ACLY) inhibition is a promising therapeutic target for dyslipidemia, atherosclerotic cardiovascular disease, non-alcoholic steatohepatitis, and metabolic syndrome. Genetic analysis of its role in chronic kidney disease (CKD) has not been performed.MethodsWe constructed a genetic instrument by selecting variants associated with ACLY expression level in the expression quantitative trait loci genetics consortium (eQTLGen) that includes blood samples from 31,684 participants. In a two-sample Mendelian randomization analysis, we then evaluated the effect of genetically predicted ACLY expression on risk of CKD, estimated glomerular filtration rate (eGFR), and microalbuminuria using the CKD Genetics consortium (CKDGen), United Kingdom biobank, and the Finnish Genetics consortium (FinnGen) totaling 66,396 CKD cases and 958,517 controls.ResultsACLY is constitutively expressed in all cell types including in whole blood. The genetic instrument included 13 variants and explained 1.5% of variation in whole blood ACLY gene expression. A 34% reduction in genetically predicted ACLY expression was associated with a 0.04 mmol/L reduced low-density lipoprotein cholesterol (P = 3.4 × 10−4) and a 9% reduced risk of CKD (stage 3,4,5, dialysis or eGFR below 60 ml/min/1.73m2) (OR = 0.91, 95% C.I. 0.85-0.98, P = 0.008), but no association was observed with eGFR nor microalbuminuria.ConclusionMendelian Randomization analysis provides cautious optimism regarding the possibility of ACLY as a therapeutic target for CKD.

Metformin is the most commonly prescribed medication for type 2 diabetes, owing to its glucose-lowering effects, which are mediated through the suppression of hepatic glucose production (reviewed in refs. 1-3). However, in addition to its effects on the liver, metformin reduces appetite and in preclinical models exerts beneficial effects on ageing and a number of diverse diseases (for example, cognitive disorders, cancer, cardiovascular disease) through mechanisms that are not fully understood1-3. Given the high concentration of metformin in the liver and its many beneficial effects beyond glycemic control, we reasoned that metformin may increase the secretion of a hepatocyte-derived endocrine factor that communicates with the central nervous system4. Here we show, using unbiased transcriptomics of mouse hepatocytes and analysis of proteins in human serum, that metformin induces expression and secretion of growth differentiating factor 15 (GDF15). In primary mouse hepatocytes, metformin stimulates the secretion of GDF15 by increasing the expression of activating transcription factor 4 (ATF4) and C/EBP homologous protein (CHOP; also known as DDIT3). In wild-type mice fed a high-fat diet, oral administration of metformin increases serum GDF15 and reduces food intake, body mass, fasting insulin and glucose intolerance; these effects are eliminated in GDF15 null mice. An increase in serum GDF15 is also associated with weight loss in patients with type 2 diabetes who take metformin. Although further studies will be required to determine the tissue source(s) of GDF15 produced in response to metformin in vivo, our data indicate that the therapeutic benefits of metformin on appetite, body mass and serum insulin depend on GDF15.

Background: Novel, effective, and safe drugs are warranted for treatment of ischemic stroke. Circulating protein biomarkers with causal genetic evidence represent promising drug targets, but no systematic screen of the proteome has been performed. Methods: First, using Mendelian randomization (MR) analyses, we assessed 653 circulating proteins as possible causal mediators for 3 different subtypes of ischemic stroke: large artery atherosclerosis, cardioembolic stroke, and small artery occlusion. Second, we used MR to assess whether identified biomarkers also affect risk for intracranial bleeding, specifically intracerebral and subarachnoid hemorrhages. Third, we expanded this analysis to 679 diseases to test a broad spectrum of side effects associated with hypothetical therapeutic agents for ischemic stroke that target the identified biomarkers. For all MR analyses, summary-level data from genome-wide association studies (GWAS) were used to ascertain genetic effects on circulating biomarker levels versus disease risk. Biomarker effects were derived by meta-analysis of 5 GWAS (N≤20 509). Disease effects were derived from large GWAS analyses, including MEGASTROKE (N≤322 150) and UK Biobank (N≤408 961) studies. Results: Several biomarkers emerged as causal mediators for ischemic stroke. Causal mediators for cardioembolic stroke included histo-blood group ABO system transferase, coagulation factor XI, scavenger receptor class A5 (SCARA5), and tumor necrosis factor–like weak inducer of apoptosis (TNFSF12). Causal mediators for large artery atherosclerosis included ABO, cluster of differentiation 40, apolipoprotein(a), and matrix metalloproteinase-12. SCARA5 (odds ratio [OR]=0.78; 95% CI, 0.70–0.88; P =1.46×10 −5 ) and TNFSF12 (OR=0.86; 95% CI, 0.81–0.91; P =7.69×10 −7 ) represent novel protective mediators of cardioembolic stroke. TNFSF12 also increased the risk of subarachnoid (OR=1.53; 95% CI, 1.31–1.78; P =3.32×10 −8 ) and intracerebral (OR=1.34; 95% CI, 1.14–1.58; P =4.05×10 −4 ) hemorrhages, whereas SCARA5 decreased the risk of subarachnoid hemorrhage (OR=0.61; 95% CI, 0.47–0.81; P =5.20×10 −4 ). Multiple side effects beyond stroke were identified for 6 of 7 biomarkers, most (75%) of which were beneficial. No adverse side effects were found for coagulation factor XI, apolipoprotein(a), and SCARA5. Conclusions: Through a systematic MR screen of the circulating proteome, causal roles for 5 established and 2 novel biomarkers for ischemic stroke were identified. Side-effect profiles were characterized to help inform drug target prioritization. In particular, SCARA5 represents a promising target for treatment of cardioembolic stroke, with no predicted adverse side effects.

Mitochondrial DNA copy number (mtDNA-CN) is an accessible blood-based measurement believed to capture underlying mitochondrial function. The specific biological processes underpinning its regulation, and whether those processes are causative for disease, is an area of active investigation. We developed a novel method for array-based mtDNA-CN estimation suitable for biobank-scale studies, called “AutoMitoC”. We applied AutoMitoC to 395,781 UKBiobank study participants and performed genome and exome-wide association studies, identifying novel common and rare genetic determinants. Overall, genetic analyses identified 73 loci for mtDNA-CN, which implicated several genes involved in rare mtDNA depletion disorders, dNTP metabolism, and the mitochondrial central dogma. Rare variant analysis identified SAMHD1 mutation carriers as having higher mtDNA-CN (beta=0.23 SDs; 95% CI, 0.18-0.29; P=2.6×10−19), a potential therapeutic target for patients with mtDNA depletion disorders, but at increased risk of breast cancer (OR=1.91; 95% CI, 1.52-2.40; P=2.7×10−8). Finally, Mendelian randomization analyses suggest a causal effect of low mtDNA-CN on dementia risk (OR=1.94 per 1 SD decrease in mtDNA-CN; 95% CI, 1.55-2.32; P=7.5×10−4). Altogether, our genetic findings indicate that mtDNA-CN is a complex biomarker reflecting specific mitochondrial processes related to mtDNA regulation, and that these processes are causally related to human diseases.

Metformin is the most commonly prescribed medication for type 2 diabetes, owing to its glucose-lowering effects, which are mediated through the suppression of hepatic glucose production (reviewed in refs. 1-3). However, in addition to its effects on the liver, metformin reduces appetite and in preclinical models exerts beneficial effects on ageing and a number of diverse diseases (for example, cognitive disorders, cancer, cardiovascular disease) through mechanisms that are not fully understood1-3. Given the high concentration of metformin in the liver and its many beneficial effects beyond glycemic control, we reasoned that metformin may increase the secretion of a hepatocyte-derived endocrine factor that communicates with the central nervous system4. Here we show, using unbiased transcriptomics of mouse hepatocytes and analysis of proteins in human serum, that metformin induces expression and secretion of growth differentiating factor 15 (GDF15). In primary mouse hepatocytes, metformin stimulates the secretion of GDF15 by increasing the expression of activating transcription factor 4 (ATF4) and C/EBP homologous protein (CHOP; also known as DDIT3). In wild-type mice fed a high-fat diet, oral administration of metformin increases serum GDF15 and reduces food intake, body mass, fasting insulin and glucose intolerance; these effects are eliminated in GDF15 null mice. An increase in serum GDF15 is also associated with weight loss in patients with type 2 diabetes who take metformin. Although further studies will be required to determine the tissue source(s) of GDF15 produced in response to metformin in vivo, our data indicate that the therapeutic benefits of metformin on appetite, body mass and serum insulin depend on GDF15.

Testosterone products are prescribed to males for a variety of possible health benefits, but causal effects are unclear. Evidence from randomized trials are difficult to obtain, particularly regarding effects on long-term or rare outcomes. Mendelian randomization analyses were performed to infer phenome-wide effects of free testosterone on 461 outcomes in 161,268 males from the UK Biobank study. Lifelong increased free testosterone had beneficial effects on increased bone mineral density, and decreased body fat; adverse effects on decreased HDL, and increased risks of prostate cancer, androgenic alopecia, spinal stenosis, and hypertension; and context-dependent effects on increased hematocrit and decreased C-reactive protein. No benefit was observed for type 2 diabetes, cardiovascular or cognitive outcomes. Mendelian randomization suggests benefits of long-term increased testosterone should be considered against adverse effects, notably increased prostate cancer and hypertension. Well-powered randomized trials are needed to conclusively address risks and benefits of testosterone treatment on these outcomes., eLife digest Men experience a gradual decline in their testosterone levels as they grow older. However, the effects of testosterone and the consequences of supplementation on the human body have been unclear. Scientists use so-called randomized controlled trials to establish cause-and-effect and to reduce bias. In these experiments, participants are randomly assigned to a either a treatment group (that receives the intervention being tested) or a control group (that either receives an alternative intervention, a dummy or placebo, or no intervention at all). Randomization ensures that both groups are balanced, and any resulting differences can be attributed to the treatment. However, randomized controlled trials are time-consuming and expensive, so trials of testosterone have had relatively small numbers of participants and short follow-up periods. This makes it difficult to draw conclusions about any potential effects of testosterone administration on less common diseases in men. Now, Paré et al. investigated the effects of naturally produced testosterone using Mendelian randomization, which mimics randomized trials by exploiting the fact that parents randomly pass on their unique genetic variants to their children at conception. This random assignment of genetic variants leads to its informal namesake, “nature’s clinical trial”, and provides the ability to study cause-and-effect for any genetically determined factors, such as testosterone levels. Paré et al. studied the long-term effects of testosterone on 22 diseases previously explored in randomized controlled trials, and hundreds of other traits and diseases that have not been investigated in any randomized controlled trials yet. The Mendelian randomization analysis made it possible to examine the effects of lifelong naturally elevated testosterone levels on 469 traits and diseases. Paré et al. found that testosterone increased the density of bone mineral and decreased body fat. However, it also increased the risks of prostate cancer, high blood pressure, baldness and a condition affecting the spine. It also increased the number of red blood cells and decreased a marker of inflammation, which may be beneficial or detrimental depending on the context. This shows that genetic analyses can be powerful methods to prioritize the allocation of limited resources towards investigating the most pressing clinical questions. The results of this study may help inform physicians and patients about the effects of long-term testosterone use. Ultimately, large randomized controlled trials are needed to conclusively address the cause-and-effect on these diseases.

Disease risk varies significantly between ethnic groups, however, the clinical significance and implications of these observations are poorly understood. Investigating ethnic differences within the human proteome may shed light on the impact of ancestry on disease risk. We used admixture mapping to explore the impact of genetic ancestry on 237 cardiometabolic biomarkers in 2,216 Latin Americans within the Outcomes Reduction with an Initial Glargine Intervention (ORIGIN) study. We developed a variance component model in order to determine the proportion of variance explained by inter-ancestry differences, and we applied it to the biomarker panel. Multivariable linear regression was used to identify and localize genetic loci affecting biomarker variability between ethnicities. Variance component analysis revealed that 5% of biomarkers were significantly impacted by genetic admixture (p < 0.05/237), including C-peptide, apolipoprotein-E, and intercellular adhesion molecule 1. We also identified 46 regional associations across 40 different biomarkers (p < 1.13 × 10(−6)). An independent analysis revealed that 34 of these 46 regions were associated at genome-wide significance (p < 5 × 10(−8)) with their respective biomarker in either Europeans or Latin populations. Additional analyses revealed that an admixture mapping signal associated with increased C-peptide levels was also associated with an increase in diabetes risk (odds ratio [OR] = 6.07 per SD, 95% confidence interval [CI] 1.44 to 25.56, p = 0.01) and surrogate measures of insulin resistance. Our results demonstrate the impact of ancestry on biomarker levels, suggesting that some of the observed differences in disease prevalence have a biological basis, and that reference intervals for those biomarkers should be tailored to ancestry. Specifically, our results point to a strong role of ancestry in insulin resistance and diabetes risk.

Rare variants are collectively numerous and may underlie a considerable proportion of complex disease risk. However, identifying genuine rare variant associations is challenging due to small effect sizes, presence of technical artefacts, and heterogeneity in population structure. We hypothesize that rare variant burden over a large number of genes can be combined into a predictive rare variant genetic risk score (RVGRS). We propose a method (RV-EXCALIBER) that leverages summary-level data from a large public exome sequencing database (gnomAD) as controls and robustly calibrates rare variant burden to account for the aforementioned biases. A calibrated RVGRS strongly associates with coronary artery disease (CAD) in European and South Asian populations by capturing the aggregate effect of rare variants through a polygenic model of inheritance. The RVGRS identifies 1.5% of the population with substantial risk of early CAD and confers risk even when adjusting for known Mendelian CAD genes, clinical risk factors, and a common variant genetic risk score., Identifying associations of rare variants with disease is challenging due to small effect sizes, technical artefacts and population structure heterogeneity. Here, the authors present RV-EXCALIBER, a method that uses large summary-level exome data to robustly calibrate rare variant burden.

Metformin is the most commonly prescribed medication for type 2 diabetes, owing to its glucose-lowering effects, which are mediated through the suppression of hepatic glucose production (reviewed in refs.

BACKGROUND Identifying markers of chronic kidney disease (CKD) that occur early in the disease process and are specific to loss of kidney function rather than other underlying causes of disease may allow earlier, more accurate identification of patients who will develop CKD. We therefore sought to identify diagnostic blood markers of early CKD that are caused by loss of kidney function by using an innovative “reverse Mendelian randomization” (MR) approach. METHODS We applied this technique to genetic and biomarker data from 4147 participants in the Outcome Reduction with Initial Glargine Intervention (ORIGIN) trial, all with known type 2 diabetes, impaired fasting glucose, or impaired glucose tolerance. Two-sample MR was conducted using variants associated with creatinine-based eGFR (eGFRcrea) from the CKDGen Consortium (n = 133814) to estimate the effect of genetically decreased eGFRcrea on 238 serum biomarkers. RESULTS With reverse MR, trefoil factor 3 (TFF3) was identified as a protein that is increased owing to decreased eGFRcrea (β = 1.86 SD per SD decrease eGFRcrea; 95% CI, 0.95–2.76; P = 8.0 × 10−5). Reverse MR findings were consistent with epidemiological associations for incident CKD in ORIGIN (OR = 1.28 per SD increase in TFF3; 95% CI, 1.18–1.38; P = 4.58 × 10−10). Addition of TFF3 significantly improved discrimination for incident CKD relative to eGFRcrea alone (net reclassification improvement = 0.211; P = 9.56 × 10−12) and in models including additional risk factors. CONCLUSIONS Our results suggest TFF3 is a valuable diagnostic marker for early CKD in dysglycemic populations and acts as a proof of concept for the application of this novel MR technique to identify diagnostic biomarkers for other chronic diseases. ClinicalTrials.gov Identifier NCT00069784