Surrogate Adiposity Markers and Mortality

Importance

Body mass index (BMI) is an easily obtained adiposity surrogate. However, there is variability in body composition and adipose tissue distribution between individuals with the same BMI, and there is controversy regarding the BMI associated with the lowest mortality risk.

Objective

To evaluate which of BMI, fat mass index (FMI), and waist-to-hip (WHR) has the strongest and most consistent association with mortality.

Design, Setting, and Participant

This cohort study used incident deaths from the UK Biobank (UKB; 2006-2022), which includes data from 22 clinical assessment centers across the United Kingdom. UKB British participants of British White ancestry (N = 387 672) were partitioned into a discovery cohort (n = 337 078) and validation cohort (n = 50 594), with the latter consisting of 25 297 deaths and 25 297 controls. The discovery cohort was used to derive genetically determined adiposity measures while the validation cohort was used for analyses. Exposure-outcome associations were analyzed through observational and mendelian randomization (MR) analyses.

Exposures

BMI, FMI, and WHR.

Main Outcomes and Measures

All-cause and cause-specific (cancer, cardiovascular disease [CVD], respiratory disease, or other causes) mortality.

Results

There were 387 672 and 50 594 participants in our observational (mean [SD] age, 56.9 [8.0] years; 177 340 [45.9%] male, 210 332 [54.2%], female), and MR (mean [SD] age, 61.6 [6.2] years; 30 031 [59.3%] male, 20 563 [40.6%], female) analyses, respectively. Associations between measured BMI and FMI with all-cause mortality were J-shaped, whereas the association of WHR with all-cause mortality was linear using the hazard ratio (HR) scale (HR per SD increase of WHR, 1.41 [95% CI, 1.38-1.43]). Genetically determined WHR had a stronger association with all-cause mortality than BMI (odds ratio [OR] per SD increase of WHR, 1.51 [95% CI, 1.32-1.72]; OR per SD increase of BMI, 1.29 [95% CI, 1.20-1.38]; P for heterogeneity = .02). This association was stronger in male than female participants (OR, 1.89 [95% CI, 1.54-2.32]; P for heterogeneity = .01). Unlike BMI or FMI, the genetically determined WHR-all-cause mortality association was consistent irrespective of observed BMI.

Conclusions and Relevance

In this cohort study, WHR had the strongest and most consistent association with mortality irrespective of BMI. Clinical recommendations should consider focusing on adiposity distribution compared with mass.

Biomarkers Associated With Severe COVID-19 Among Populations With High Cardiometabolic Risk: A 2-Sample Mendelian Randomization Study

Importance

Cardiometabolic parameters are established risk factors for COVID-19 severity. The identification of causal or protective biomarkers for COVID-19 severity may facilitate the development of novel therapies.

Objective

To identify protein biomarkers that promote or reduce COVID-19 severity and that mediate the association of cardiometabolic risk factors with COVID-19 severity.

Design, Setting, and Participants

This genetic association study using 2-sample mendelian randomization (MR) was conducted in 2022 to investigate associations among cardiometabolic risk factors, circulating biomarkers, and COVID-19 hospitalization. Inputs for MR included genetic and proteomic data from 4147 participants with dysglycemia and cardiovascular risk factors collected through the Outcome Reduction With Initial Glargine Intervention (ORIGIN) trial. Genome-wide association study summary statistics were obtained from (1) 3 additional independent plasma proteome studies, (2) genetic consortia for selected cardiometabolic risk factors (including body mass index [BMI], type 2 diabetes, type 1 diabetes, and systolic blood pressure; all n >10 000), and (3) the COVID-19 Host Genetics Initiative (n = 5773 hospitalized and 15 497 nonhospitalized case participants with COVID-19). Data analysis was performed in July 2022.

Exposures

Genetically determined concentrations of 235 circulating proteins assayed with a multiplex biomarker panel from the ORIGIN trial for the initial analysis.

Main Outcomes and Measures

Hospitalization status of individuals from the COVID-19 Host Genetics Initiative with a positive COVID-19 test result.

Results

Among 235 biomarkers tested in samples totaling 22 101 individuals, MR analysis showed that higher kidney injury molecule-1 (KIM-1) levels reduced the likelihood of COVID-19 hospitalization (odds ratio [OR] per SD increase in KIM-1 levels, 0.86 [95% CI, 0.79-0.93]). A meta-analysis validated the protective association with no observed directional pleiotropy (OR per SD increase in KIM-1 levels, 0.91 [95% CI, 0.88-0.95]). Of the cardiometabolic risk factors studied, only BMI was associated with KIM-1 levels (0.17 SD increase in biomarker level per 1 kg/m2 [95% CI, 0.08-0.26]) and COVID-19 hospitalization (OR per 1-SD biomarker level, 1.33 [95% CI, 1.18-1.50]). Multivariable MR analysis also revealed that KIM-1 partially mitigated the association of BMI with COVID-19 hospitalization, reducing it by 10 percentage points (OR adjusted for KIM-1 level per 1 kg/m2, 1.23 [95% CI, 1.06-1.43]).

Conclusions and Relevance

In this genetic association study, KIM-1 was identified as a potential mitigator of COVID-19 severity, possibly attenuating the increased risk of COVID-19 hospitalization among individuals with high BMI. Further studies are required to better understand the underlying biological mechanisms.

Leveraging related health phenotypes for polygenic prediction of impulsive choice, impulsive action, and impulsive personality traits in 1534 European ancestry community adults

Impulsivity refers to a number of conceptually related phenotypes reflecting self-regulatory capacity that are considered promising endophenotypes for mental and physical health. Measures of impulsivity can be broadly grouped into three domains, namely, impulsive choice, impulsive action, and impulsive personality traits. In a community-based sample of ancestral Europeans (n = 1534), we conducted genome-wide association studies (GWASs) of impulsive choice (delay discounting), impulsive action (behavioral inhibition), and impulsive personality traits (UPPS-P), and evaluated 11 polygenic risk scores (PRSs) of phenotypes previously linked to self-regulation. Although there were no individual genome-wide significant hits, the neuroticism PRS was positively associated with negative urgency (adjusted R²  = 1.61%, p = 3.6 × 10^-7 ) and the educational attainment PRS was inversely associated with delay discounting (adjusted R²  = 1.68%, p = 2.2 × 10^-7 ). There was also evidence implicating PRSs of attention-deficit/hyperactivity disorder, externalizing, risk-taking, smoking cessation, smoking initiation, and body mass index with one or more impulsivity phenotypes (adjusted R² s: 0.35%-1.07%; FDR adjusted ps = 0.05-0.0006). These significant associations between PRSs and impulsivity phenotypes are consistent with established genetic correlations. The combined PRS explained 0.91%-2.46% of the phenotypic variance for individual impulsivity measures, corresponding to 8.7%-32.5% of their reported single-nucleotide polymorphism (SNP)-based heritability, suggesting a non-negligible portion of the SNP-based heritability can be recovered by PRSs. These results support the predictive validity and utility of PRSs, even derived from related phenotypes, to inform the genetics of impulsivity phenotypes.

From 'Omics to Multi-omics Technologies: the Discovery of Novel Causal Mediators

PURPOSE OF REVIEW

'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.

RECENT FINDINGS

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.

ACLY and CKD: A Mendelian Randomization Analysis

Introduction

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.

Methods

We constructed a genetic instrument by selecting variants associated with ACLY expression in the expression quantitative trait loci genetics consortium (eQTLGen) from blood samples from 31,684 participants. In a 2-sample Mendelian randomization analysis, we evaluated the effect of genetically predicted ACLY expression on the risk of CKD, estimated glomerular filtration rate (eGFR), and albumin-to-creatinine ratio (ACR) using the CKD Genetics (CKDGen) consortium, UK Biobank, and the Finnish Genetics (FinnGen) consortium totaling 66,396 CKD cases and 958,517 controls.

Results

ACLY is constitutively expressed in all cell types including in whole blood. The genetic instrument included 13 variants and explained 1.5% of the variation in whole blood ACLY gene expression. A 34% reduction in ACLY expression score was associated with a 0.04 mmol/l reduced low-density lipoprotein (LDL) cholesterol (P = 3.4 × 10^-4) and a 9% reduced risk of CKD (stages 3, 4, 5, dialysis, or eGFR < 60 ml/min per 1.73 m²) (odds ratio [OR] = 0.91, 95% CI: 0.85-0.98, P = 0.008), but no association was observed with either eGFR or ACR.

Conclusion

Mendelian 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.

Elevated Lipoprotein(a) and Risk of Atrial Fibrillation: An Observational and Mendelian Randomization Study

BACKGROUND

Atrial fibrillation (AF) is a cardiac arrhythmia associated with an elevated risk of stroke, heart failure, and mortality. However, preventative therapies are needed with ancillary benefits on its cardiovascular comorbidities. Lipoprotein(a) (Lp[a]) is a recognized risk factor for atherosclerotic cardiovascular disease (ASCVD), which itself increases AF risk, but it remains unknown whether Lp(a) is a causal mediator of AF independent of ASCVD.

OBJECTIVES

This study investigated the role of Lp(a) in AF and whether it is independent of ASCVD.

METHODS

Measured and genetically predicted Lp(a) levels were tested for association with 20,432 cases of incident AF in the UK Biobank (N = 435,579). Mendelian randomization analyses were performed by using summary-level data for AF from publicly available genome-wide association studies (N = 1,145,375).

RESULTS

In the UK Biobank, each 50 nmol/L (23 mg/dL) increase in Lp(a) was associated with an increased risk of incident AF using measured Lp(a) (HR: 1.03; 95% CI: 1.02-1.04 ; P = 1.65 × 10^-8) and genetically predicted Lp(a) (OR: 1.03; 95% CI: 1.02-1.05; P = 1.33 × 10^-5). Mendelian randomization analyses using independent data replicated the effect (OR: 1.04 per 50 nmol/L Lp[a] increase; 95% CI: 1.03-1.05 per 50 nmol/L Lp[a] increase; P = 9.23 × 10^-10). There was no evidence of risk-conferring effect from low-density lipoprotein cholesterol or triglycerides, and only 39% (95% CI: 27%-73%) of Lp(a) risk was mediated through ASCVD, suggesting that Lp(a) partly influences AF independent of its known effects on ASCVD.

CONCLUSIONS

Our findings implicate Lp(a) as a potential causal mediator in the development of AF which show that the effects of Lp(a) extend across myocardial tissues. Ongoing clinical trials for Lp(a)-lowering therapies should evaluate effects on AF prevention.

Mitochondrial DNA Copy Number as a Marker and Mediator of Stroke Prognosis: Observational and Mendelian Randomization Analyses

BACKGROUND AND OBJECTIVES

Low 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.

METHODS

First, 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.

RESULTS

A 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).

DISCUSSION

Buffy coat mtDNA-CN is a novel and robust marker of poststroke prognosis that may also be a causal determinant of poststroke outcomes.

CLASSIFICATION OF EVIDENCE

This 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.

GWAS and ExWAS of blood Mitochondrial DNA copy number identifies 71 loci and highlights a potential causal role in dementia

Background:

Mitochondrial DNA copy number (mtDNA-CN) is an accessible blood-based measurement believed to capture underlying mitochondrial (MT) function. The specific biological processes underpinning its regulation, and whether those processes are causative for disease, is an area of active investigation.

Methods:

We developed a novel method for array-based mtDNA-CN estimation suitable for biobank-scale studies, called ‘automatic mitochondrial copy (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. Finally, we performed two-sample Mendelian randomization to assess whether genetically low mtDNA-CN influenced select MT phenotypes.

Results:

Overall, genetic analyses identified 71 loci for mtDNA-CN, which implicated several genes involved in rare mtDNA depletion disorders, deoxynucleoside triphosphate (dNTP) metabolism, and the MT 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).

Conclusions:

Altogether, our genetic findings indicate that mtDNA-CN is a complex biomarker reflecting specific MT processes related to mtDNA regulation, and that these processes are causally related to human diseases.

Funding:

No funds supported this specific investigation. Awards and positions supporting authors include: Canadian Institutes of Health Research (CIHR) Frederick Banting and Charles Best Canada Graduate Scholarships Doctoral Award (MC, PM); CIHR Post-Doctoral Fellowship Award (RM); Wellcome Trust Grant number: 099313/B/12/A; Crasnow Travel Scholarship; Bongani Mayosi UCT-PHRI Scholarship 2019/2020 (TM); Wellcome Trust Health Research Board Irish Clinical Academic Training (ICAT) Programme Grant Number: 203930/B/16/Z (CJ); European Research Council COSIP Grant Number: 640580 (MO); E.J. Moran Campbell Internal Career Research Award (MP); CISCO Professorship in Integrated Health Systems and Canada Research Chair in Genetic and Molecular Epidemiology (GP)

Our cells are powered by small internal compartments known as mitochondria, which host several copies of their own ‘mitochondrial’ genome. Defects in these semi-autonomous structures are associated with a range of severe, and sometimes fatal conditions: easily checking the health of mitochondria through cheap, quick and non-invasive methods can therefore help to improve human health.

Measuring the concentration of mitochondrial DNA molecules in our blood cells can help to estimate the number of mitochondrial genome copies per cell, which in turn act as a proxy for the health of the compartment. In fact, having lower or higher concentration of mitochondrial DNA molecules is associated with diseases such as cancer, stroke, or cardiac conditions. However, current approaches to assess this biomarker are time and resource-intensive; they also do not work well across people with different ancestries, who have slightly different versions of mitochondrial genomes.

In response, Chong et al. developed a new method for estimating mitochondrial DNA concentration in blood samples. Called AutoMitoC, the automated pipeline is fast, easy to use, and can be used across ethnicities. Applying this method to nearly 400,000 individuals highlighted 71 genetic regions for which slight sequence differences were associated with changes in mitochondrial DNA concentration. Further investigation revealed that these regions contained genes that help to build, maintain, and organize mitochondrial DNA. In addition, the analyses yield preliminary evidence showing that lower concentration of mitochondrial DNA may be linked to a higher risk of dementia.

Overall, the work by Chong et al. demonstrates that AutoMitoC can be used to investigate how mitochondria are linked to health and disease in populations across the world, potentially paving the way for new therapeutic approaches.

Epigenetic Age and the Risk of Incident Atrial Fibrillation

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<0.01) and 15% (adjusted HR, 1.15 [95% CI, 1.05-1.25]; P<0.01) higher hazards of incident AF, respectively. Mendelian randomization analyses for the 5 EAA measures did not reveal statistically significant associations with AF.

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.

Calibrated rare variant genetic risk scores for complex disease prediction using large exome sequence repositories

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.

Effects of lifelong testosterone exposure on health and disease using Mendelian randomization

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.

Global Assessment of Mendelian Stroke Genetic Prevalence in 101 635 Individuals From 7 Ethnic Groups

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.

Metformin-induced increases in GDF15 are important for suppressing appetite and promoting weight loss

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 understood^1-3. 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.

Novel Drug Targets for Ischemic Stroke Identified Through Mendelian Randomization Analysis of the Blood Proteome

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.

A Mendelian Randomization-Based Approach to Identify Early and Sensitive Diagnostic Biomarkers of Disease

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