Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits

Increased brain volume from higher cereal and lower coffee intake: shared genetic determinants and impacts on cognition and metabolism

It is unclear how different diets may affect human brain development and if genetic and environmental factors play a part. We investigated diet effects in the UK Biobank data from 18,879 healthy adults and discovered anticorrelated brain-wide gray matter volume (GMV)-association patterns between coffee and cereal intake, coincidence with their anticorrelated genetic constructs. The Mendelian randomization approach further indicated a causal effect of higher coffee intake on reduced total GMV, which is likely through regulating the expression of genes responsible for synaptic development in the brain. The identified genetic factors may further affect people's lifestyle habits and body/blood fat levels through the mediation of cereal/coffee intake, and the brain-wide expression pattern of gene CPLX3, a dedicated marker of subplate neurons that regulate cortical development and plasticity, may underlie the shared GMV-association patterns among the coffee/cereal intake and cognitive functions. All the main findings were successfully replicated. Our findings thus revealed that high-cereal and low-coffee diets shared similar brain and genetic constructs, leading to long-term beneficial associations regarding cognitive, body mass index (BMI), and other metabolic measures. This study has important implications for public health, especially during the pandemic, given the poorer outcomes of COVID-19 patients with greater BMIs.

Leveraging large observational studies to discover genetic determinants of drug concentrations: A proof-of-concept study

Large, observational genetic studies are commonly used to identify genetic factors associated with diseases and disease‐related traits. Such cohorts have not been commonly used to identify genetic predictors of drug dosing or concentrations, perhaps because of the heterogeneity in drug dosing and formulation, and the random timing of blood sampling. We hypothesized that large sample sizes relative to traditional pharmacokinetic studies would compensate for this variability and enable the identification of pharmacogenetic predictors of drug concentrations. We performed a cross‐sectional, proof‐of‐concept association study to replicate the well‐established association between metoprolol concentrations and CYP2D6 genotype‐inferred metabolizer phenotypes in participants from the Montreal Heart Institute Hospital Cohort undergoing metoprolol therapy. Plasma concentrations of metoprolol and α‐hydroxymetoprolol (α‐OH‐metoprolol) were measured in samples collected randomly regarding the previous metoprolol dose. A total of 999 individuals were included. The metoprolol daily dose ranged from 6.25 to 400 mg (mean 84.3 ± 57.1 mg). CYP2D6‐inferred phenotype was significantly associated with both metoprolol and α‐OH‐metoprolol in unadjusted and adjusted models (all p < 10⁻¹⁴). Models for metoprolol daily dose showed consistent results. Our study suggests that randomly drawn blood samples from biobanks can serve as a new approach to discover genetic associations related to drug concentrations and dosing, with potentially broader implications for genomewide association studies on the pharmacogenomics of drug metabolism.

First genome-wide association study investigating blood pressure and renal traits in domestic cats

Hypertension (HTN) and chronic kidney disease (CKD) are common in ageing cats. In humans, blood pressure (BP) and renal function are complex heritable traits. We performed the first feline genome-wide association study (GWAS) of quantitative traits systolic BP and creatinine and binary outcomes HTN and CKD, testing 1022 domestic cats with a discovery, replication and meta-analysis design. No variants reached experimental significance level in the discovery stage for any phenotype. Follow up of the top 9 variants for creatinine and 5 for systolic BP, one SNP reached experimental-wide significance for association with creatinine in the combined meta-analysis (chrD1.10258177; P = 1.34 × 10^–6). Exploratory genetic risk score (GRS) analyses were performed. Within the discovery sample, GRS of top SNPs from the BP and creatinine GWAS show strong association with HTN and CKD but did not validate in independent replication samples. A GRS including SNPs corresponding to human CKD genes was not significant in an independent subset of cats. Gene-set enrichment and pathway-based analysis (GSEA) was performed for both quantitative phenotypes, with 30 enriched pathways with creatinine. Our results support the utility of GWASs and GSEA for genetic discovery of complex traits in cats, with the caveat of our findings requiring validation.

Associations of Visceral Adipose Tissue, Circulating Protein Biomarkers, and Risk of Cardiovascular Diseases: A Mendelian Randomization Analysis

Aim: To evaluate the genetic associations of visceral adipose tissue (VAT) mass with metabolic risk factors and cardiovascular disease (CVD) endpoints and to construct a network analysis about the underlying mechanism using Mendelian randomization (MR) analysis.

Methods and Results: Using summary statistics from genome-wide association studies (GWAS), we conducted the two-sample MR to assess the effects of VAT mass on 10 metabolic risk factors and 53 CVD endpoints. Genetically predicted VAT mass was associated with metabolic risk factors, including triglyceride (odds ratio, OR, 1.263 [95% confidence interval, CI, 1.203–1.326]), high-density lipoprotein cholesterol (OR, 0.719 [95% CI, 0.678–0.763]), type 2 diabetes (OR, 2.397 [95% CI, 1.965–2.923]), fasting glucose (OR, 1.079 [95% CI, 1.046–1.113]), fasting insulin (OR, 1.194 [95% CI, 1.16–1.229]), and insulin resistance (OR, 1.204 [95% CI, 1.16–1.25]). Genetically predicted VAT mass was associated with CVD endpoints, including atrial fibrillation (OR, 1.414 [95% CI, 1.332 = 1.5]), coronary artery disease (OR, 1.573 [95% CI, 1.439 = 1.72]), myocardial infarction (OR, 1.633 [95% CI, 1.484 =1.796]), heart failure (OR, 1.711 [95% CI, 1.599–1.832]), any stroke (OR, 1.29 [1.193–1.394]), ischemic stroke (OR, 1.292 [1.189–1.404]), large artery stroke (OR, 1.483 [1.206–1.823]), cardioembolic stroke (OR, 1.261 [1.096–1.452]), and intracranial aneurysm (OR, 1.475 [1.235–1.762]). In the FinnGen study, the relevance of VAT mass to coronary heart disease, stroke, cardiac arrhythmia, vascular diseases, hypertensive heart disease, and cardiac death was found. In network analysis to identify the underlying mechanism between VAT and CVDs, VAT mass was positively associated with 23 cardiovascular-related proteins (e.g., Leptin, Hepatocyte growth factor, interleukin-16), and inversely with 6 proteins (e.g., Galanin peptides, Endothelial cell-specific molecule 1). These proteins were further associated with 32 CVD outcomes.

Conclusion: Mendelian randomization analysis has shown that VAT mass was associated with a wide range of CVD outcomes including coronary heart disease, cardiac arrhythmia, vascular diseases, and stroke. A few circulating proteins may be the mediators between VAT and CVDs.

Multi-Trait Genome-Wide Association Study of Atherosclerosis Detects Novel Pleiotropic Loci

Although affecting different arterial territories, the related atherosclerotic vascular diseases coronary artery disease (CAD) and peripheral artery disease (PAD) share similar risk factors and have shared pathobiology. To identify novel pleiotropic loci associated with atherosclerosis, we performed a joint analysis of their shared genetic architecture, along with that of common risk factors. Using summary statistics from genome-wide association studies of nine known atherosclerotic (CAD, PAD) and atherosclerosis risk factors (body mass index, smoking initiation, type 2 diabetes, low density lipoprotein, high density lipoprotein, total cholesterol, and triglycerides), we perform 15 separate multi-trait genetic association scans which resulted in 25 novel pleiotropic loci not yet reported as genome-wide significant for their respective traits. Colocalization with single-tissue eQTLs identified candidate causal genes at 14 of the detected signals. Notably, the signal between PAD and LDL-C at the PCSK6 locus affects PCSK6 splicing in human liver tissue and induced pluripotent derived hepatocyte-like cells. These results show that joint analysis of related atherosclerotic disease traits and their risk factors allowed identification of unified biology that may offer the opportunity for therapeutic manipulation. The signal at PCSK6 represent possible shared causal biology where existing inhibitors may be able to be leveraged for novel therapies.

Smoking behavior might affect allergic rhinitis and vasomotor rhinitis differently: A mendelian randomization appraisal

BACKGROUND

Allergic rhinitis and vasomotor rhinitis are harassing numerous patients and their risk factors have not been well investigated. Here, we try to identify their risk factors and distinguish these 2 diseases.

METHODS

A two-sample Mendelian randomization (MR) study was implemented to discover the risk factors of allergic and vasomotor rhinitis. Based on previous studies, we selected 15 potential risk factors and the genome-wide summary statistics were extracted from the non-FinnGen consortium. The genome-wide summary statistics of rhinitis were obtained from the FinnGen consortium. Both univariable MR and multivariable MR analyses were performed to identify the causal risk factors. The Cochrane's Q value was calculated to appraise the heterogeneity. MR-Egger intercept and MR-RPESSO were utilized to appraise the pleiotropy.

RESULTS

In the univariable model, the number of cigarettes per day can decrease the risk of allergic rhinitis (IVW OR = 0.29[0.18, 0.47], p-value = 2.70 × 10-7) while increasing the risk of vasomotor rhinitis (IVW OR = 1.30[1.04, 1.62], p-value = 0.022). Besides, no other risk factors could affect the risk of either allergic or vasomotor rhinitis. After adjusting for age of smoking initiation and alcohol intake, the cigarettes per day could still decrease the risk of allergic rhinitis (IVW OR = 4.66 × 10-3 [1.99 × 10-4, 0.11], p-value = 0.003) while not affecting the risk of vasomotor rhinitis (IVW OR = 0.92[0.44, 1.96], p-value = 0.834).

CONCLUSION

Smoking can affect the risk of allergic and vasomotor rhinitis differently where it decreases the risk of allergic rhinitis and increases the risk of vasomotor rhinitis.

Elevated blood pressure, antihypertensive medications and bone health in the population: revisiting old hypotheses and exploring future research directions

Blood pressure and bone metabolism appear to share commonalities in their physiologic regulation. Specific antihypertensive drug classes may also influence bone mineral density. However, current evidence from existing observational studies and randomised trials is insufficient to establish causal associations for blood pressure and use of blood pressure-lowering drugs with bone health outcomes, particularly with the risks of osteoporosis and fractures. The availability and access to relevant large-scale biomedical data sources as well as developments in study designs and analytical approaches provide opportunities to examine the nature of the association between blood pressure and bone health more reliably and in greater detail than has ever been possible. It is unlikely that a single source of data or study design can provide a definitive answer. However, with appropriate considerations of the strengths and limitations of the different data sources and analytical techniques, we should be able to advance our understanding of the role of raised blood pressure and its drug treatment on the risks of low bone mineral density and fractures. As elevated blood pressure is highly prevalent and blood pressure-lowering drugs are widely prescribed, even small effects of these exposures on bone health outcomes could be important at a population level.

Robust estimates of heritable coronary disease risk in individuals with type 2 diabetes

Type 2 diabetes (T2D) is an important heritable risk factor for coronary artery disease (CAD), the risk of both diseases being increased by metabolic syndrome (MS). With the availability of large-scale genome-wide association data, we aimed to elucidate the genetic burden of CAD risk in T2D predisposed individuals within the context of MS and their shared genetic architecture. Mendelian randomization (MR) analyses supported a causal relationship between T2D and CAD [odds ratio (OR) = 1.13 per log-odds unit 95% confidence interval (CI): 1.10-1.16; p = 1.59 × 10-17 ]. Simultaneously adjusting MR analyses for the effects of the T2D instrument including blood pressure, dyslipidaemia, and obesity attenuated the association between T2D and CAD (OR = 1.07, 95% CI: 1.04-1.11). Bayesian locus-overlap analysis identified 44 regions with the same causal variant underlying T2D and CAD genetic signals (FDR < 1%) at a posterior probability >0.7; five (MHC, LPL, ABO, RAI1 and MC4R) of these regions contain genome-wide significant (p < 5 × 10-8 ) associations for both traits. Given the small effect sizes observed in genome-wide association studies for complex diseases, even with 44 potential target regions, this has implications for the likely magnitude of CAD risk reduction that might be achievable by pure T2D therapies.

Genetically proxied therapeutic inhibition of antihypertensive drug targets and risk of common cancers: A mendelian randomization analysis

BACKGROUND

Epidemiological studies have reported conflicting findings on the potential adverse effects of long-term antihypertensive medication use on cancer risk. Naturally occurring variation in genes encoding antihypertensive drug targets can be used as proxies for these targets to examine the effect of their long-term therapeutic inhibition on disease outcomes.

METHODS AND FINDINGS

We performed a mendelian randomization analysis to examine the association between genetically proxied inhibition of 3 antihypertensive drug targets and risk of 4 common cancers (breast, colorectal, lung, and prostate). Single-nucleotide polymorphisms (SNPs) in ACE, ADRB1, and SLC12A3 associated (P < 5.0 × 10-8) with systolic blood pressure (SBP) in genome-wide association studies (GWAS) were used to proxy inhibition of angiotensin-converting enzyme (ACE), β-1 adrenergic receptor (ADRB1), and sodium-chloride symporter (NCC), respectively. Summary genetic association estimates for these SNPs were obtained from GWAS consortia for the following cancers: breast (122,977 cases, 105,974 controls), colorectal (58,221 cases, 67,694 controls), lung (29,266 cases, 56,450 controls), and prostate (79,148 cases, 61,106 controls). Replication analyses were performed in the FinnGen consortium (1,573 colorectal cancer cases, 120,006 controls). Cancer GWAS and FinnGen consortia data were restricted to individuals of European ancestry. Inverse-variance weighted random-effects models were used to examine associations between genetically proxied inhibition of these drug targets and risk of cancer. Multivariable mendelian randomization and colocalization analyses were employed to examine robustness of findings to violations of mendelian randomization assumptions. Genetically proxied ACE inhibition equivalent to a 1-mm Hg reduction in SBP was associated with increased odds of colorectal cancer (odds ratio (OR) 1.13, 95% CI 1.06 to 1.22; P = 3.6 × 10-4). This finding was replicated in the FinnGen consortium (OR 1.40, 95% CI 1.02 to 1.92; P = 0.035). There was little evidence of association of genetically proxied ACE inhibition with risk of breast cancer (OR 0.98, 95% CI 0.94 to 1.02, P = 0.35), lung cancer (OR 1.01, 95% CI 0.92 to 1.10; P = 0.93), or prostate cancer (OR 1.06, 95% CI 0.99 to 1.13; P = 0.08). Genetically proxied inhibition of ADRB1 and NCC were not associated with risk of these cancers. The primary limitations of this analysis include the modest statistical power for analyses of drug targets in relation to some less common histological subtypes of cancers examined and the restriction of the majority of analyses to participants of European ancestry.

CONCLUSIONS

In this study, we observed that genetically proxied long-term ACE inhibition was associated with an increased risk of colorectal cancer, warranting comprehensive evaluation of the safety profiles of ACE inhibitors in clinical trials with adequate follow-up. There was little evidence to support associations across other drug target-cancer risk analyses, consistent with findings from short-term randomized controlled trials for these medications.

Promoter DNA Methylation in GWAS-Identified Genes as Potential Functional Elements for Blood Pressure: An Observational and Mendelian Randomization Study

Genome-wide association studies have identified numerous genetic loci for blood pressure (BP). However, the relationships of functional elements inside these loci with BP are not fully understood. This study represented an effort to determine if promoter DNA methylations inside BP-associated loci were associated with BP.We conducted a cross-sectional study investigating the association between promoter DNA methylations of 10 candidate genes and BP in 1,241 Chinese individuals. Twenty-one genomic fragments in the CpG Islands were sequenced. The associations of methylation levels with BP and hypertension were assessed in regression models. Mendelian randomization (MR) analysis was then applied to find supporting evidence for the identified associations.A total of 413 DNA methylation sites were examined in an observational study. Methylation levels of 24 sites in PRDM6, IGFBP3, SYT7, PDE3A, TBX2 and C17orf82 were significantly associated with BP. Methylation levels of PRDM6 and SYT7 were significantly associated with hypertension. Methylation levels of five sites (including cg06713098) in IGFBP3 were significantly associated with DBP. MR analysis found associations between the methylation levels of six CpG sites (cg06713098, cg14228300, cg23193639, cg21268650, cg10677697 and cg04812164) around the IGFBP3 promoter and DBP. Methylation levels of cg14228300 and cg04812164 were associated with SBP. By further applying several MR methods we showed that the associations may not be due to pleiotropy. Association between IGFBP3 mRNA levels in blood cells and BP was also found in MR analysis. This study identified promoter methylation as potential functional element for BP. The identified methylations may be involved in the regulatory pathway linking genetic variants to BP.

Association between Exercise and Blood Pressure in Hypertensive Residents: A Meta-Analysis

BACKGROUND

Exercise is recommended as an effective lifestyle behaviour for adults to prevent and treat hypertension. In this study, a randomized-effect meta-analysis was used to analyse the influence of exercise interventions on blood pressure in patients with hypertension.

METHODS

Candidate papers were retrieved from PubMed, Web of Science, Embase, and Cochrane Library electronic databases, and 46 studies were finally included and analysed.

RESULTS

It was shown that preplanned walking (systolic blood pressure (SBP): WMD (weighted mean difference) = -5.94, 95% CI: -8.57, -3.30; diastolic blood pressure (DBP): WMD = -2.66, 95% CI: -3.66, -1.67), yoga (SBP: WMD = -5.09, 95% CI: -9.28, -0.89; DBP: WMD = -3.06, 95% CI: -5.16, -0.96), aquatic sports (SBP WMD = -7.53, 95% CI: -11.40, -3.65; DBP: WMD = -5.35, 95% CI: -9.00, -1.69), and football (SBP: WMD = -6.06, 95% CI: -9.30, -2.82; DBP: WMD = -5.55, 95% CI: -8.98, -2.13) had significant effects on blood pressure reduction. However, Tai Chi (SBP: WMD = -8.31, 95% CI: -20.39, 3.77; DBP: WMD = -3.05, 95% CI: -6.96, 0.87) and Qigong (SBP: WMD = -4.34, 95% CI: -13.5, 4.82; DBP: WMD = -3.44, 95% CI: -7.89, 1.01) did not significantly reduce blood pressure. The heterogeneity of the meta-analysis was high.

CONCLUSION

Walking, yoga, aquatic sports, and football were feasible and independent lifestyle interventions, and they were effective options for treating hypertension. More scientifically designed randomized controlled trials are needed in the future to further compare different forms of exercise for the treatment of hypertension.

A genome-wide association study of serum proteins reveals shared loci with common diseases

With the growing number of genetic association studies, the genotype-phenotype atlas has become increasingly more complex, yet the functional consequences of most disease associated alleles is not understood. The measurement of protein level variation in solid tissues and biofluids integrated with genetic variants offers a path to deeper functional insights. Here we present a large-scale proteogenomic study in 5,368 individuals, revealing 4,035 independent associations between genetic variants and 2,091 serum proteins, of which 36% are previously unreported. The majority of both cis- and trans-acting genetic signals are unique for a single protein, although our results also highlight numerous highly pleiotropic genetic effects on protein levels and demonstrate that a protein's genetic association profile reflects certain characteristics of the protein, including its location in protein networks, tissue specificity and intolerance to loss of function mutations. Integrating protein measurements with deep phenotyping of the cohort, we observe substantial enrichment of phenotype associations for serum proteins regulated by established GWAS loci, and offer new insights into the interplay between genetics, serum protein levels and complex disease.

Shared genetic influences on resting‐state functional networks of the brain

The amplitude of activation in brain resting state networks (RSNs), measured with resting‐state functional magnetic resonance imaging, is heritable and genetically correlated across RSNs, indicating pleiotropy. Recent univariate genome‐wide association studies (GWASs) explored the genetic underpinnings of individual variation in RSN activity. Yet univariate genomic analyses do not describe the pleiotropic nature of RSNs. In this study, we used a novel multivariate method called genomic structural equation modeling to model latent factors that capture the shared genomic influence on RSNs and to identify single nucleotide polymorphisms (SNPs) and genes driving this pleiotropy. Using summary statistics from GWAS of 21 RSNs reported in UK Biobank (N = 31,688), the genomic latent factor analysis was first conducted in a discovery sample (N = 21,081), and then tested in an independent sample from the same cohort (N = 10,607). In the discovery sample, we show that the genetic organization of RSNs can be best explained by two distinct but correlated genetic factors that divide multimodal association networks and sensory networks. Eleven of the 17 factor loadings were replicated in the independent sample. With the multivariate GWAS, we found and replicated nine independent SNPs associated with the joint architecture of RSNs. Further, by combining the discovery and replication samples, we discovered additional SNP and gene associations with the two factors of RSN amplitude. We conclude that modeling the genetic effects on brain function in a multivariate way is a powerful approach to learn more about the biological mechanisms involved in brain function.

Coding and regulatory variants are associated with serum protein levels and disease

Circulating proteins can be used to diagnose and predict disease-related outcomes. A deep serum proteome survey recently revealed close associations between serum protein networks and common disease. In the current study, 54,469 low-frequency and common exome-array variants were compared to 4782 protein measurements in the serum of 5343 individuals from the AGES Reykjavik cohort. This analysis identifies a large number of serum proteins with genetic signatures overlapping those of many diseases. More specifically, using a study-wide significance threshold, we find that 2021 independent exome array variants are associated with serum levels of 1942 proteins. These variants reside in genetic loci shared by hundreds of complex disease traits, highlighting serum proteins' emerging role as biomarkers and potential causative agents of a wide range of diseases.

Cardiovascular Risk Factors and MRI Markers of Cerebral Small Vessel Disease: A Mendelian Randomization Study

BACKGROUND AND OBJECTIVES

Cardiovascular risk factors have been implicated in the etiology of cerebral small vessel disease (CSVD); however, whether the associations are causal remains unclear in part due to the susceptibility of observational studies to reverse causation and confounding. Here, we use mendelian randomization (MR) to determine which cardiovascular risk factors are likely to be involved in the etiology of CSVD.

METHODS

We used data from large-scale genome-wide association studies of European ancestry to identify genetic proxies for blood pressure, blood lipids, body mass index (BMI), type 2 diabetes, smoking initiation, cigarettes per day, and alcohol consumption. MR was performed to assess their association with 3 neuroimaging features that are altered in CSVD (white matter hyperintensities [WMH], fractional anisotropy [FA], and mean diffusivity [MD]) using genetic summary data from the UK Biobank (N = 31,855). Our primary analysis used inverse-weighted median MR, with validation using weighted median, MR-Egger, and a pleiotropy-minimizing approach. Finally, multivariable MR was performed to study the effects of multiple risk factors jointly.

RESULTS

MR analysis showed consistent associations across all methods for higher genetically proxied systolic and diastolic blood pressures with WMH, FA, and MD and for higher genetically proxied BMI with WMH. There was weaker evidence for associations between total cholesterol, low-density lipoprotein, smoking initiation, pulse pressure, and type 2 diabetes liability and at least 1 CSVD imaging feature, but these associations were not reproducible across all validation methods used. Multivariable MR analysis for blood pressure traits found that the effect was primarily through genetically proxied diastolic blood pressure across all CSVD traits.

DISCUSSION

Genetic predisposition to higher blood pressure, primarily diastolic blood pressure, and to higher BMI is associated with a higher burden of CSVD, suggesting a causal role. Improved management and treatment of these risk factors could reduce the burden of CSVD.

Novel methylation mark and essential hypertension

Background

Essential hypertension (EH) is an important risk factor for various cardiovascular, cerebral and renal disorders. It is a multi-factorial trait which occurs through complex interplay between genetic, epigenetic, and environmental factors. Even after advancement of technology and deciphering the involvement of multiple signalling pathways in blood pressure regulation, it still remains as a huge global concern.

Main body of the abstract

Genome-wide association studies (GWAS) have revealed EH-associated genetic variants but these solely cannot explain the variability in blood pressure indicating the involvement of additional factors. The etiopathogenesis of hypertension has now advanced to the level of epigenomics where aberrant DNA methylation is the most defined epigenetic mechanism to be involved in gene regulation. Though role of DNA methylation in cancer and other mechanisms is deeply studied but this mechanism is in infancy in relation to hypertension. Generally, 5-methylcytosine (5mC) levels are being targeted at both individual gene and global level to find association with the disease. But recently, with advanced sequencing techniques another methylation mark, N6-methyladenine (6mA) was found and studied in humans which was earlier considered to be absent in case of eukaryotes. Relation of aberrant 6mA levels with cancer and stem cell fate has drawn attention to target 6mA levels with hypertension too.

Conclusion

Recent studies targeting hypertension has suggested 6mA levels as novel marker and its demethylase, ALKBH1 as probable therapeutic target to prevent hypertension through epigenetic programming. This review compiles different methylation studies and suggests targeting of both 5mC and 6mA levels to cover role of methylation in hypertension in broader scenario.

A deep learning model for early risk prediction of heart failure with preserved ejection fraction by DNA methylation profiles combined with clinical features

Background

Heart failure with preserved ejection fraction (HFpEF), affected collectively by genetic and environmental factors, is the common subtype of chronic heart failure. Although the available risk assessment methods for HFpEF have achieved some progress, they were based on clinical or genetic features alone. Here, we have developed a deep learning framework, HFmeRisk, using both 5 clinical features and 25 DNA methylation loci to predict the early risk of HFpEF in the Framingham Heart Study Cohort.

Results

The framework incorporates Least Absolute Shrinkage and Selection Operator and Extreme Gradient Boosting-based feature selection, as well as a Factorization-Machine based neural network-based recommender system. Model discrimination and calibration were assessed using the AUC and Hosmer–Lemeshow test. HFmeRisk, including 25 CpGs and 5 clinical features, have achieved the AUC of 0.90 (95% confidence interval 0.88–0.92) and Hosmer–Lemeshow statistic was 6.17 (P = 0.632), which outperformed models with clinical characteristics or DNA methylation levels alone, published chronic heart failure risk prediction models and other benchmark machine learning models. Out of them, the DNA methylation levels of two CpGs were significantly correlated with the paired transcriptome levels (R < −0.3, P < 0.05). Besides, DNA methylation locus in HFmeRisk were associated with intercellular signaling and interaction, amino acid metabolism, transport and activation and the clinical variables were all related with the mechanism of occurrence of HFpEF. Together, these findings give new evidence into the HFmeRisk model.

Conclusion

Our study proposes an early risk assessment framework for HFpEF integrating both clinical and epigenetic features, providing a promising path for clinical decision making.

A multi-omics study of circulating phospholipid markers of blood pressure

High-throughput techniques allow us to measure a wide-range of phospholipids which can provide insight into the mechanisms of hypertension. We aimed to conduct an in-depth multi-omics study of various phospholipids with systolic blood pressure (SBP) and diastolic blood pressure (DBP). The associations of blood pressure and 151 plasma phospholipids measured by electrospray ionization tandem mass spectrometry were performed by linear regression in five European cohorts (n = 2786 in discovery and n = 1185 in replication). We further explored the blood pressure-related phospholipids in Erasmus Rucphen Family (ERF) study by associating them with multiple cardiometabolic traits (linear regression) and predicting incident hypertension (Cox regression). Mendelian Randomization (MR) and phenome-wide association study (Phewas) were also explored to further investigate these association results. We identified six phosphatidylethanolamines (PE 38:3, PE 38:4, PE 38:6, PE 40:4, PE 40:5 and PE 40:6) and two phosphatidylcholines (PC 32:1 and PC 40:5) which together predicted incident hypertension with an area under the ROC curve (AUC) of 0.61. The identified eight phospholipids are strongly associated with triglycerides, obesity related traits (e.g. waist, waist-hip ratio, total fat percentage, body mass index, lipid-lowering medication, and leptin), diabetes related traits (e.g. glucose, insulin resistance and insulin) and prevalent type 2 diabetes. The genetic determinants of these phospholipids also associated with many lipoproteins, heart rate, pulse rate and blood cell counts. No significant association was identified by bi-directional MR approach. We identified eight blood pressure-related circulating phospholipids that have a predictive value for incident hypertension. Our cross-omics analyses show that phospholipid metabolites in the circulation may yield insight into blood pressure regulation and raise a number of testable hypothesis for future research.

Metabolic and lifestyle factors in relation to senile cataract: a Mendelian randomization study

We conducted a Mendelian randomization study to determine the associations of body mass index (BMI), type 2 diabetes (T2D), systolic blood pressure (SBP), coffee and alcohol consumption and smoking initiation with senile cataract. Independent single nucleotide polymorphisms associated with the metabolic and lifestyle factors at the p < 5 × 10^-8 were selected as instrument variables. Summary-level data for senile cataract were obtained from the FinnGen consortium (20,157 cases and 154,905 non-cases) and UK Biobank study (6332 cases and 354,862 non-cases). Higher genetically predicted BMI and SBP and genetic predisposition to T2D and smoking initiation were associated with an increased risk of senile cataract. The combined odds ratios were 1.19 (95% confidence interval (CI) 1.09-1.29; p < 0.001) per one standard deviation increase in BMI (~ 4.8 kg/m²), 1.13 (95% CI 1.04-1.23; p = 0.004) per 10 mmHg increase in SBP, 1.06 (95% CI 1.03-1.09; p < 0.001) per one unit increase in log-transformed odds ratio of T2D, and 1.19 (95% CI 1.10-1.29; p < 0.001) per one standard deviation increase in prevalence of smoking initiation. Genetically predicted coffee consumption showed a suggestive association with senile cataract (odds ratio per 50% increase, 1.18, 95% CI 1.00-1.40; p = 0.050). This study suggests causal roles of obesity, T2D, SBP and smoking in senile cataract.

Genetics of common cerebral small vessel disease

Cerebral small vessel disease (cSVD) is a leading cause of ischaemic and haemorrhagic stroke and a major contributor to dementia. Covert cSVD, which is detectable with brain MRI but does not manifest as clinical stroke, is highly prevalent in the general population, particularly with increasing age. Advances in technologies and collaborative work have led to substantial progress in the identification of common genetic variants that are associated with cSVD-related stroke (ischaemic and haemorrhagic) and MRI-defined covert cSVD. In this Review, we provide an overview of collaborative studies - mostly genome-wide association studies (GWAS) - that have identified >50 independent genetic loci associated with the risk of cSVD. We describe how these associations have provided novel insights into the biological mechanisms involved in cSVD, revealed patterns of shared genetic variation across cSVD traits, and shed new light on the continuum between rare, monogenic and common, multifactorial cSVD. We consider how GWAS summary statistics have been leveraged for Mendelian randomization studies to explore causal pathways in cSVD and provide genetic evidence for drug effects, and how the combination of findings from GWAS with gene expression resources and drug target databases has enabled identification of putative causal genes and provided proof-of-concept for drug repositioning potential. We also discuss opportunities for polygenic risk prediction, multi-ancestry approaches and integration with other omics data.

Higher Circulating Vitamin D Levels Are Associated With Decreased Migraine Risk: A Mendelian Randomization Study

Background

Evidence showed the supplementation of vitamin D might have beneficial effects for migraine patients. We aimed to investigate the causal effects of serum vitamin D levels on migraine risk using two-sample Mendelian randomization (MR) method.

Methods

A total of 184 independent genetic instruments for serum vitamin D levels were selected from a study in 417,580 Europeans from UK biobank. Six variants from an independent study were obtained to perform replication analysis. Summary-level data for migraine were obtained from three studies with 48,975 migraine cases, 28,852 migraine cases and 10,536 migraine cases, respectively.

Results

The estimated odds ratios (ORs) per standard deviation increase in circulating vitamin D levels based on the three migraine datasets were 0.948 (95% CI = 0.883-1.016, p = 0.133), 0.902 (95% confidence intervals [CI] = 0.825-0.986, p = 0.023), and 0.880 (95% CI = 0.786-0.984, p = 0.025), respectively. Using pooled migraine summary data with no sample overlap, MR analysis showed per standard deviation increase in circulating vitamin D levels was significantly associated with a decreased migraine risk (OR = 0.916, 95% CI = 0.859-0.977, p = 0.008). Multivariable MR analyses, sensitivity analyses and replication analysis confirmed the association. MR analyses showed similar estimates for migraine with aura and migraine without aura but with wider 95% CIs. Mediation analysis showed the effect of vitamin D on migraine risk via pathway of serum calcium was corresponding to an OR of 1.003 (95% CI = 1.001-1.005) and a proportion mediated of 3.42%. The reverse MR analysis showed migraine might not affect vitamin D levels.

Conclusion

This two-sample MR study showed genetically determined increased circulating vitamin D levels are associated with decreased migraine risk. The effect seems consistent across different migraine subtypes. In addition, the role of serum calcium in mediating the association between vitamin D and migraine is negligible. Future large well-designed randomized trials are warranted to assess the effects of vitamin D supplementation for migraine patients, especially in those with vitamin D deficiency.

Effects of Gut Microbiota and Metabolites on Heart Failure and Its Risk Factors: A Two-Sample Mendelian Randomization Study

Introduction

Previous observational studies have indicated that gut microbiota and metabolites may contribute to heart failure and its risk factors. However, with the limitation of reverse causality and confounder in observational studies, such relationship remains unclear. This study aims to reveal the causal effect of gut microbiota and metabolites on heart failure and its risk factors.

Methods

This study collected summary statistics regarding gut microbiota and metabolites, heart failure, diabetes, hypertension, chronic kidney disease, myocardial infarction, atrial fibrillation, hypertrophic cardiomyopathy, dilated cardiomyopathy, coronary heart disease, valvular heart disease, and myocarditis. Two-sample Mendelian randomization analysis was performed using MR-Egger, inverse variance weighted (IVW), MR-PRESSO, maximum likelihood, and weighted median.

Results

Results from gene prediction showed that among all gut microbiota, candida, shigella, and campylobacter were not associated with higher incidence of heart failure. However, genetic prediction suggested that for every 1 unit increase in shigella concentration, the relative risk increased by 38.1% for myocarditis and 13.3% for hypertrophic cardiomyopathy. Besides, for every 1 unit increased in candida concentration, the relative risk of chronic kidney disease increased by 7.1%. As for intestinal metabolites, genetic prediction results suggested that for every 1 unit increase in betaine, the relative risk of heart failure and myocardial infarction increased by 1.4% and 1.7%, separately.

Conclusions

This study suggested new evidence of the relationship between gut microbiota and heart failure and its risk factors, which may shed light on designing microbiome- and microbiome-dependent metabolite interventions on heart failure and its risk factors in clinical trials in the future.

Causal Associations of Obesity With Achilles Tendinopathy: A Two-Sample Mendelian Randomization Study

BACKGROUND

Achilles tendinopathy (AT) is associated with severe pain and is the cause of dysfunction and disability that are associated with significant reduction in social and economic benefits. Several potential risk factors have been proposed to be responsible for AT development; however, the results of observational epidemiological studies remain controversial, presumably because the designs of these studies are subject to residual confounding and reverse causality. Mendelian randomization (MR) can infer the causality between exposure and disease outcomes using genetic variants as instrumental variables, and identification of the causal risk factors for AT is beneficial for early intervention. Thus, we employed the MR strategy to evaluate the causal associations between previously reported risk factors (anthropometric parameters, lifestyle factors, blood biomarkers, and systemic diseases) and the risk of AT.

METHODS

Univariable MR was performed to screen for potential causal associations between the putative risk factors and AT. Bidirectional MR was used to infer reverse causality. Multivariable MR was conducted to investigate the body mass index (BMI)-independent causal effect of other obesity-related traits, such as the waist-hip ratio, on AT.

RESULTS

Univariable MR analyses with the inverse-variance weighted method indicated that the genetically predicted BMI was significantly associated with the risk of AT (P=2.0×10^-3), and the odds ratios (95% confidence intervals) is 1.44 (1.14-1.81) per 1-SD increase in BMI. For the other tested risk factors, no causality with AT was identified using any of the MR methods. Bidirectional MR suggested that AT was not causally associated with BMI, and multivariable MR indicated that other anthropometric parameters included in this study were not likely to causally associate with the risk of AT after adjusting for BMI.

CONCLUSIONS

The causal association between BMI and AT risk suggests that weight control is a promising strategy for preventing AT and alleviating the corresponding disease burden.

Investigating a Potential Causal Relationship Between Maternal Blood Pressure During Pregnancy and Future Offspring Cardiometabolic Health

Observational epidemiological studies have reported that higher maternal blood pressure (BP) during pregnancy is associated with increased future risk of offspring cardiometabolic disease. However, it is unclear whether this association represents a causal relationship through intrauterine mechanisms. We used a Mendelian randomization (MR) framework to examine the relationship between unweighted maternal genetic scores for systolic BP and diastolic BP and a range of cardiometabolic risk factors in the offspring of up to 29 708 genotyped mother-offspring pairs from the UKB study (UK Biobank) and the HUNT study (Trøndelag Health). We conducted similar analyses in up to 21 423 father-offspring pairs from the same cohorts. We confirmed that the BP-associated genetic variants from the general population sample also had similar effects on maternal BP during pregnancy in independent cohorts. We did not detect any association between maternal (or paternal) unweighted genetic scores and cardiometabolic offspring outcomes in the meta-analysis of UKB and HUNT after adjusting for offspring genotypes at the same loci. We find little evidence to support the notion that maternal BP is a major causal risk factor for adverse offspring cardiometabolic outcomes in later life.

Associations of maternal blood pressure-raising polygenic risk scores with fetal weight

Maternal blood pressure (BP) is associated with variations in fetal weight, an important determinant of neonatal and adult health. However, the association of BP-raising genetic risk with fetal weight is unknown. We tested the associations of maternal BP-raising polygenic risk scores (PRS) with estimated fetal weights (EFWs) at 13, 20, 27, and 40 weeks of gestation. This study included 622 White, 637 Black, 568 Hispanic, and 238 Asian pregnant women with genotype data from the NICHD Fetal Growth Studies. PRS of systolic (SBP) and diastolic BP (DBP) were calculated for each participant based on summary statistics from a recent genome-wide association study. Linear regression models were used to compare mean EFW differences between the highest versus lowest tertile of PRS, adjusting for maternal age, education, parity, genetic principal components and fetal sex. Hispanics in the highest DBP PRS tertile, compared to those in the lowest, had 8.1 g (95% CI: -15.1, -1.1), 32.4 g (-58.4, -6.4) and 119.4 g (-218.1, -20.7) lower EFW at 20, 27 and 40 weeks, respectively. Similarly, Asians in the highest DBP PRS tertile had 137.2 g (-263.5, -10.8) lower EFW at week 40, and those in the highest tertile of SBP PRS had 3.2 g (-5.8, -0.7), 12.9 g (-23.5, -2.4), and 39.8 g (-76.9, -2.7) lower EFWs at 13, 20, and 27 weeks. The findings showed that pregnant women's genetic susceptibility to high BP contributes to reduced fetal growth, suggesting a potential future clinical application in perinatal health.

Personalizing treatments for patients based on cardiovascular phenotyping

Introduction

Cardiovascular disease persists as the leading cause of death worldwide despite continued advances in diagnostics and therapeutics. Our current approach to patients with cardiovascular disease is rooted in reductionism, which presupposes that all patients share a similar phenotype and will respond the same to therapy; however, this is unlikely as cardiovascular diseases exhibit complex heterogeneous phenotypes.

Areas covered

With the advent of high-throughput platforms for omics testing, phenotyping cardiovascular diseases has advanced to incorporate large-scale molecular data with classical history, physical examination, and laboratory results. Findings from genomics, proteomics, and metabolomics profiling have been used to define more precise cardiovascular phenotypes and predict adverse outcomes in population-based and disease-specific patient cohorts. These molecular data have also been utilized to inform drug efficacy based on a patient's unique phenotype.

Expert opinion

Multiscale phenotyping of cardiovascular disease has revealed diversity among patients that can be used to personalize pharmacotherapies and predict outcomes. Nonetheless, precision phenotyping for cardiovascular disease remains a nascent field that has not yet translated into widespread clinical practice despite its many potential advantages for patient care. Future endeavors that demonstrate improved pharmacotherapeutic responses and associated reduction in adverse events will facilitate mainstream adoption of precision cardiovascular phenotyping.

The role of obesity, type 2 diabetes, and metabolic factors in gout: A Mendelian randomization study

BACKGROUND

Several epidemiological studies have reported a possible correlation between risk of gout and metabolic disorders including type 2 diabetes, insulin resistance, obesity, dyslipidemia, and hypertension. However, it is unclear if this association is causal.

METHODS

We used Mendelian randomization (MR) to evaluate the causal relation between metabolic conditions and gout or serum urate concentration by inverse-variance-weighted (conventional) and weighted median methods. Furthermore, MR-Egger regression and MR-pleiotropy residual sum and outlier (PRESSO) method were used to explore pleiotropy. Genetic instruments for metabolic disorders and outcome (gout and serum urate) were obtained from several genome-wide association studies on individuals of mainly European ancestry.

RESULTS

Conventional MR analysis showed a robust causal association of increasing obesity measured by body mass index (BMI), high-density lipoprotein cholesterol (HDL), and systolic blood pressure (SBP) with risk of gout. A causal relationship between fasting insulin, BMI, HDL, triglycerides (TG), SBP, alanine aminotransferase (ALT), and serum urate was also observed. These results were consistent in weighted median method and MR-PRESSO after removing outliers identified. Our analysis also indicated that HDL and serum urate as well as gout have a bidirectional causal effect on each other.

CONCLUSIONS

Our study suggested causal effects between glycemic traits, obesity, dyslipidemia, blood pressure, liver function, and serum urate as well as gout, which implies that metabolic factors contribute to the development of gout via serum urate, as well as potential benefit of sound management of increased serum urate in patients with obesity, dyslipidemia, hypertension, and liver dysfunction.

Mendelian randomization study supports the causal association between serum cystatin C and risk of diabetic nephropathy

AIMS

Cystatin C, an inhibitor of cysteine protease, has been used as a biomarker for estimating glomerular filtration rate. However, the causal relation between cystatin C and diabetic nephropathy remains uncertain.

METHODS

We assessed the causal effect of cystatin C together with other five serum biomarkers including KIM-1, GDF-15, TBIL, uric acid, and Scr on diabetic nephropathy by Mendelian randomization (MR) analysis. 234 genetic variants were selected as instrumental variables to evaluate the causal effect of cystatin C (N_GWAS=361194) on diabetic nephropathy (Ncase/Ncontrol up to 3283/210463). Multivariable MR (MVMR) was performed to assess the stability of cystatin C's causal relationship. Two-step MR was used to assess the mediation effect of BMI and SBP.

RESULTS

Among the six serum biomarkers, only cystatin C causally associated with diabetic nephropathy (IVW OR: 1.36, 95%CI [1.15, 1.61]). After adjusting for the potential confounders BMI and SBP, cystatin C maintained its causal effect on the DN (OR: 1.17, 95%CI [1.02, 1.33]), which means that the risk of DN increased by 17% with an approximate 1 standard deviation (SD) increment of serum cystatin C level. Two-step MR results indicated that BMI might mediate the causal effect of cystatin C on diabetic nephropathy.

INTERPRETATION

Our findings discovered that cystatin C was a risk factor for diabetic nephropathy independent of BMI and SBP in diabetes mellitus patients. Future research is required to illustrate the underlying mechanism and prove targeting circulating cystatin C could be a potential therapy method.

Causal association of cognitive reserve on Alzheimer's disease with putative sex difference

INTRODUCTION

Sex-dependent risk factors may underlie sex differences in Alzheimer's disease (AD).

METHODS

Using sex-stratified genome-wide association studies (GWAS) of AD, we evaluated associations of 12 traits with AD through polygenic risk scores (PRS) and Mendelian randomization (MR), and explored joint genetic architecture among significant traits by genomic structural equation modeling and network analysis.

RESULTS

AD was associated with lower PRS for premorbid cognitive performance, intelligence, and educational attainment. MR showed a causal role for the cognition-related traits in AD, particularly among females. Their joint genetic components encompassed RNA processing, neuron projection development, and cell cycle pathways that overlap with cellular senescence. Cholesterol and C-reactive protein showed pleiotropy but no causality with AD.

DISCUSSION

Lower cognitive reserve is causally related to AD. The stronger causal link between cognitive performance and AD in females, despite similar PRS between sexes, suggest these differences may result from gene-environmental interactions accumulated over the lifespan.

Cohort profile: Copenhagen Hospital Biobank - Cardiovascular Disease Cohort (CHB-CVDC): Construction of a large-scale genetic cohort to facilitate a better understanding of heart diseases

PURPOSE

The aim of Copenhagen Hospital Biobank-Cardiovascular Disease Cohort (CHB-CVDC) is to establish a cohort that can accelerate our understanding of CVD initiation and progression by jointly studying genetics, diagnoses, treatments and risk factors.

PARTICIPANTS

The CHB-CVDC is a large genomic cohort of patients with CVD. CHB-CVDC currently includes 96 308 patients. The cohort is part of CHB initiated in 2009 in the Capital Region of Denmark. CHB is continuously growing with ~40 000 samples/year. Patients in CHB were included in CHB-CVDC if they were above 18 years of age and assigned at least one cardiovascular diagnosis. Additionally, up-to 110 000 blood donors can be analysed jointly with CHB-CVDC. Linkage with the Danish National Health Registries, Electronic Patient Records, and Clinical Quality Databases allow up-to 41 years of medical history. All individuals are genotyped using the Infinium Global Screening Array from Illumina and imputed using a reference panel consisting of whole-genome sequence data from 8429 Danes along with 7146 samples from North-Western Europe. Currently, 39 539 of the patients are deceased.

FINDINGS TO DATE

Here, we demonstrate the utility of the cohort by showing concordant effects between known variants and selected CVDs, that is, >93% concordance for coronary artery disease, atrial fibrillation, heart failure and cholesterol measurements and 85% concordance for hypertension. Furthermore, we evaluated multiple study designs and the validity of using Danish blood donors as part of CHB-CVDC. Lastly, CHB-CVDC has already made major contributions to studies of sick sinus syndrome and the role of phytosterols in development of atherosclerosis.

FUTURE PLANS

In addition to genetics, electronic patient records, national socioeconomic and health registries extensively characterise each patient in CHB-CVDC and provides a promising framework for improved understanding of risk and protective variants. We aim to include other measurable biomarkers for example, proteins in CHB-CVDC making it a platform for multiomics cardiovascular studies.

Multi-Omic Approaches to Identify Genetic Factors in Metabolic Syndrome

Metabolic syndrome (MetS) is a highly heritable disease and a major public health burden worldwide. MetS diagnosis criteria are met by the simultaneous presence of any three of the following: high triglycerides, low HDL/high LDL cholesterol, insulin resistance, hypertension, and central obesity. These diseases act synergistically in people suffering from MetS and dramatically increase risk of morbidity and mortality due to stroke and cardiovascular disease, as well as certain cancers. Each of these component features is itself a complex disease, as is MetS. As a genetically complex disease, genetic risk factors for MetS are numerous, but not very powerful individually, often requiring specific environmental stressors for the disease to manifest. When taken together, all sequence variants that contribute to MetS disease risk explain only a fraction of the heritable variance, suggesting additional, novel loci have yet to be discovered. In this article, we will give a brief overview on the genetic concepts needed to interpret genome-wide association studies (GWAS) and quantitative trait locus (QTL) data, summarize the state of the field of MetS physiological genomics, and to introduce tools and resources that can be used by the physiologist to integrate genomics into their own research on MetS and any of its component features. There is a wealth of phenotypic and molecular data in animal models and humans that can be leveraged as outlined in this article. Integrating these multi-omic QTL data for complex diseases such as MetS provides a means to unravel the pathways and mechanisms leading to complex disease and promise for novel treatments. © 2022 American Physiological Society. Compr Physiol 12:1-40, 2022.

Heart Failure and Ischemic Stroke: A Bidirectional and Multivariable Mendelian Randomization Study

Background: Heart failure (HF) is a potential cause of ischemic stroke (IS), and previous studies have reported an association between HF and IS. This study aimed to analyze the causal link between HF and IS using bidirectional and multivariable Mendelian randomization (MR) studies.

Methods: Genetic variants significantly associated with HF and IS were selected in the MR analysis from two large genome-wide association studies. Bidirectional and multivariable MR analyses were performed to evaluate the effect of HF on IS or the effect of IS on HF.

Results: Two-sample MR analysis showed causal effects of HF on IS of all causes [odds ratio (OR) = 1.555, 95% confidence interval (CI): 1.343–1.799, p = 3.35 × 10⁻⁹] and large artery atherosclerosis stroke (LAS) (OR = 1.678, 95% CI: 1.044–2.696, p = 3.03 × 10⁻⁵), while there was a suggestive effect of HF on cardioembolic stroke (CES) (OR = 3.355, 95% CI: 1.031–10.919, p = 0.044). Genetically predicted HF was not associated with small artery occlusion stroke. Bidirectional MR analysis showed causal effects of IS of all causes (OR = 1.211, 95% CI: 1.040–1.410, p = 0.014) and CES (OR = 1.277, 95% CI: 1.213–1.344, p = 6.73 × 10⁻²¹) on HF, while there were no causal effects of LAS on HF.

Conclusion: This MR analysis provided evidence of the causal links between genetically predicted HF and IS. Subgroup analysis highlighted the causal or suggestive relationship between genetically predicted HF and LAS or CES. The potential causal links need further investigation with genetic information about other ancestries or etiologies of HF.

Blood pressure and risk of cancer: a Mendelian randomization study

Background

Previous large observational cohort studies showed higher blood pressure (BP) positively associated with cancer. We used Mendelian randomization (MR) to obtain less confounded estimates of BP on total and site-specific cancers.

Methods

We applied replicated genetic instruments for systolic and diastolic BP to summary genetic associations with total cancer (37387 cases, 367856 non-cases) from the UK Biobank, and 17 site-specific cancers (663–17881 cases) from a meta-analysis of the UK Biobank and the Kaiser Permanente Genetic Epidemiology Research on Adult Health and Aging. We used inverse-variance weighting with multiplicative random effects as the main analysis, and sensitivity analyses including the weighted median, MR-Egger and multivariable MR adjusted for body mass index and for smoking. For validation, we included breast (Breast Cancer Association Consortium: 133384 cases, 113789 non-cases), prostate (Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome Consortium: 79194 cases, 61112 non-cases) and lung (International Lung and Cancer Consortium: 10246 cases, 38295 non-cases) cancer from large consortia. We used asthma as a negative control outcome.

Results

Systolic and diastolic BP were unrelated to total cancer (OR 0.98 per standard deviation higher [95% confidence interval (CI) 0.89, 1.07] and OR 1.00 [95% CI 0.92, 1.08]) and to site-specific cancers after accounting for multiple testing, with consistent findings from consortia. BP was nominally associated with melanoma and possibly kidney cancer, and as expected, not associated with asthma. Sensitivity analyses using other MR methods gave similar results.

Conclusions

In contrast to previous observational evidence, BP does not appear to be a risk factor for cancer, although an effect on melanoma and kidney cancer cannot be excluded. Other targets for cancer prevention might be more relevant.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-09067-x.

Genetically Determined Inflammatory Biomarkers and the Risk of Heart Failure: A Mendelian Randomization Study

Background: Positive associations between inflammatory biomarkers and the risk of heart failure (HF) have been reported in conventional observational studies. However, the causal effects of inflammatory biomarkers on HF have not been fully elucidated. We conducted a Mendelian randomization (MR) study to examine the possible etiological roles of inflammatory biomarkers in HF. Methods: Summary statistical data for the associations between single nucleotide polymorphisms (SNPs) and C-reactive protein (CRP), fibrinogen, and components of the interleukin-1 (IL-1)-interleukin-6 (IL-6) inflammatory signaling pathway, namely, interleukin-1β (IL-1β), IL-1 receptor antagonist (IL-1ra), IL-6, and soluble IL-6 receptor (sIL-6r), were obtained from genome-wide association studies (GWASs) for individuals of European descent. The GWAS dataset of 977,323 participants of European ancestry, which included 47,309 HF cases and 930,014 controls, was collected to identify genetic variants underlying HF. A two-sample Mendelian randomization framework was implemented to examine the causality of the association between these inflammatory biomarkers and HF. Results: Our MR analyses found that genetically determined CRP and fibrinogen were not causally associated with HF risk (odds ratio [OR] = 0.93, 95% confidence interval [CI] = 0.84-1.02, p = 0.15; OR = 0.94, 95% CI = 0.55-1.58, p = 0.80, respectively). These findings remained consistent using different Mendelian randomization methods and in sensitivity analyses. For the IL-1-IL-6 pathway, causal estimates for IL-6 (OR = 0.86, 95% CI 0.81-0.91, p < 0.001), but not for IL-1β, IL-1ra, or sIL-6r, were significant. However, the association between genetically determined IL-6 and HF risk became non-significant after excluding SNPs with potential pleiotropy (OR = 0.89, 95% CI = 0.77-1.03, p = 0.12). Conclusion: Our study did not identify convincing evidence to support that CRP and fibrinogen, together with their upstream IL-1-IL-6 signaling pathway, were causally associated with HF risk.

Association of low-frequency and rare coding variants with information processing speed

Measures of information processing speed vary between individuals and decline with age. Studies of aging twins suggest heritability may be as high as 67%. The Illumina HumanExome Bead Chip genotyping array was used to examine the association of rare coding variants with performance on the Digit-Symbol Substitution Test (DSST) in community-dwelling adults participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. DSST scores were available for 30,576 individuals of European ancestry from nine cohorts and for 5758 individuals of African ancestry from four cohorts who were older than 45 years and free of dementia and clinical stroke. Linear regression models adjusted for age and gender were used for analysis of single genetic variants, and the T5, T1, and T01 burden tests that aggregate the number of rare alleles by gene were also applied. Secondary analyses included further adjustment for education. Meta-analyses to combine cohort-specific results were carried out separately for each ancestry group. Variants in RNF19A reached the threshold for statistical significance (p = 2.01 × 10^-6) using the T01 test in individuals of European descent. RNF19A belongs to the class of E3 ubiquitin ligases that confer substrate specificity when proteins are ubiquitinated and targeted for degradation through the 26S proteasome. Variants in SLC22A7 and OR51A7 were suggestively associated with DSST scores after adjustment for education for African-American participants and in the European cohorts, respectively. Further functional characterization of its substrates will be required to confirm the role of RNF19A in cognitive function.

Shared Genetic Liability and Causal Associations Between Major Depressive Disorder and Cardiovascular Diseases

Major depressive disorder (MDD) is phenotypically associated with cardiovascular diseases (CVD). We aim to investigate mechanisms underlying relationships between MDD and CVD in the context of shared genetic variations. Polygenic overlap analysis was used to test genetic correlation and to analyze shared genetic variations between MDD and seven cardiovascular outcomes (coronary artery disease (CAD), heart failure, atrial fibrillation, stroke, systolic blood pressure, diastolic blood pressure, and pulse pressure measurement). Mendelian randomization analysis was used to uncover causal relationships between MDD and cardiovascular traits. By cross-trait meta-analysis, we identified a set of genomic loci shared between the traits of MDD and stroke. Putative causal genes for MDD and stroke were prioritized by fine-mapping of transcriptome-wide associations. Polygenic overlap analysis pointed toward substantial genetic variation overlap between MDD and CVD. Mendelian randomization analysis indicated that genetic liability to MDD has a causal effect on CAD and stroke. Comparison of genome-wide genes shared by MDD and CVD suggests 20q12 as a pleiotropic region conferring risk for both MDD and CVD. Cross-trait meta-analyses and fine-mapping of transcriptome-wide association signals identified novel risk genes for MDD and stroke, including RPL31P12, BORSC7, PNPT11, and PGF. Many genetic variations associated with MDD and CVD outcomes are shared, thus, pointing that genetic liability to MDD may also confer risk for stroke and CAD. Presented results shed light on mechanistic connections between MDD and CVD phenotypes.

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

[Figure: see text].

Mendelian randomization to assess causality between uromodulin, blood pressure and chronic kidney disease

UMOD variants associated with higher levels of urinary uromodulin (uUMOD) increase the risk of chronic kidney disease (CKD) and hypertension. However, uUMOD levels also reflect functional kidney tubular mass in observational studies, questioning the causal link between uromodulin production and kidney damage. We used Mendelian randomization to clarify causality between uUMOD levels, kidney function and blood pressure in individuals of European descent. The link between uUMOD and estimated glomerular filtration rate (eGFR) was first investigated in a population-based cohort of 3851 individuals. In observational data, higher uUMOD associated with higher eGFR. Conversely, when using rs12917707 (an UMOD polymorphism) as an instrumental variable in one-sample Mendelian randomization, higher uUMOD strongly associated with eGFR decline. We next applied two-sample Mendelian randomization on four genome wide association study consortia to explore causal links between uUMOD and eGFR, CKD risk (567,460 individuals) and blood pressure (757,461 individuals). Higher uUMOD levels significantly associated with lower eGFR, higher odds for eGFR decline or CKD, and higher systolic or diastolic blood pressure. Each one standard deviation (SD) increase of uUMOD decreased log-transformed eGFR by -0.15 SD (95% confidence interval -0.17 to -0.13) and increased log-odds CKD by 0.13 SD (0.12 to 0.15). One SD increase of uUMOD increased systolic blood pressure by 0.06 SD (0.03 to 0.09) and diastolic blood pressure by 0.08 SD (0.05 to 0.12). The effect of uUMOD on blood pressure was mediated by eGFR, whereas the effect on eGFR was not mediated by blood pressure. Thus, our data support that genetically driven levels of uromodulin have a direct, causal and adverse effect on kidney function outcome in the general population, not mediated by blood pressure.

UMOD-ulating CKD risk: untangling the relationship between urinary uromodulin, blood pressure, and kidney disease

A new Mendelian randomization study finds evidence that genetically predicted higher levels of urinary uromodulin are associated with lower kidney function and higher blood pressure. Bidirectional and multivariable Mendelian randomization suggests the association with higher blood pressure appears to be partially through decreased kidney function, but blood pressure does not appear to mediate the association of uromodulin with low kidney function. We describe the methods used for the bidirectional and multivariable Mendelian randomization analyses and examine the validity of the assumptions and implications of the results.

Identification of Functional Genetic Determinants of Cardiac Troponin T and I in a Multiethnic Population and Causal Associations With Atrial Fibrillation

BACKGROUND

Elevated cardiac troponin levels in blood are associated with increased risk of cardiovascular diseases and mortality. Cardiac troponin levels are heritable, but their genetic architecture remains elusive.

METHODS

We conducted a transethnic genome-wide association analysis on high-sensitivity cTnT (cardiac troponin T; hs-cTnT) and high-sensitivity cTnI (cardiac troponin I; hs-cTnI) levels in 24 617 and 14 336 participants free of coronary heart disease and heart failure from 6 population-based cohorts, followed by a series of bioinformatic analyses to decipher the genetic architecture of hs-cTnT and hs-cTnI.

RESULTS

We identified 4 genome-wide significant loci for hs-cTnT including a novel locus rs3737882 in PPFIA4 and 3 previously reported loci at NCOA2, TRAM1, and BCL2. One known locus at VCL was replicated for hs-cTnI. One copy of C allele for rs3737882 was associated with a 6% increase in hs-cTnT levels (minor allele frequency, 0.18; P=2.80×10-9). We observed pleiotropic loci located at BAG3 and ANO5. The proportions of variances explained by single-nucleotide polymorphisms were 10.15% and 7.74% for hs-cTnT and hs-cTnI, respectively. Single-nucleotide polymorphisms were colocalized with BCL2 expression in heart tissues and hs-cTnT and with ANO5 expression in artery, heart tissues, and whole blood and both troponins. Mendelian randomization analyses showed that genetically increased hs-cTnT and hs-cTnI levels were associated with higher odds of atrial fibrillation (odds ratio, 1.38 [95% CI, 1.25-1.54] for hs-cTnT and 1.21 [95% CI, 1.06-1.37] for hs-cTnI).

CONCLUSIONS

We identified a novel genetic locus associated with hs-cTnT in a multiethnic population and found that genetically regulated troponin levels were associated with atrial fibrillation.

The association between the Moyamoya disease susceptible gene RNF213 variant and incident cardiovascular disease in a general population: the Nagahama study

OBJECTIVE

An association between the Moyamoya disease susceptible gene ring finger protein 213 (RNF213) variant and ischemic stroke and coronary artery disease has been suggested in case-control studies. We aimed to investigate the possible association between the RNF213 variant and the incidence of cardiovascular disease in a general population.

METHODS

The study participants consisted of 9153 Japanese community residents without history of cardiovascular disease. The clinical parameters employed in this analysis were observed at baseline between 2008 and 2010. The RNF213 p.R4859K variant was determined by TaqMan probe assay and then confirmed by Sanger sequencing.

RESULTS

During 8.52 years follow-up period, we observed 214 incident cases of cardiovascular diseases (99 total stroke cases, 119 major adverse cardiac event cases, including 4 cases of both). The incidence rate was higher for the variant allele carriers (120 cases; incidence rate, 71.0 per 10 000 person-years) than for the homozygotes of the wild-type allele (26.9), and the group differences achieved statistical significance (P = 0.009). Although the RNF213 variant was also associated with systolic blood pressure (dominant model: coefficient of 8.19 mmHg; P < 0.001), the Cox regression analysis adjusted for major covariates including systolic blood pressure identified the RNF213 variant as an independent determinant for cardiovascular disease (hazard ratio of 3.41, P = 0.002) and major adverse cardiac event (hazard ratio of 3.80, P = 0.010) but not with total stroke (P = 0.102).

CONCLUSION

The Moyamoya disease susceptible RNF213 variant was associated with blood pressure and the incidence of cardiovascular disease in a Japanese general population.

Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons.

Hypertension genetics past, present and future applications

Essential hypertension is a complex trait where the underlying aetiology is not completely understood. Left untreated it increases the risk of severe health complications including cardiovascular and renal disease. It is almost 15 years since the first genome-wide association study for hypertension, and after a slow start there are now over 1000 blood pressure (BP) loci explaining ∼6% of the single nucleotide polymorphism-based heritability. Success in discovery of hypertension genes has provided new pathological insights and drug discovery opportunities and translated to the development of BP genetic risk scores (GRSs), facilitating population disease risk stratification. Comparing highest and lowest risk groups shows differences of 12.9 mm Hg in systolic-BP with significant differences in risk of hypertension, stroke, cardiovascular disease and myocardial infarction. GRSs are also being trialled in antihypertensive drug responses. Drug targets identified include NPR1, for which an agonist drug is currently in clinical trials. Identification of variants at the PHACTR1 locus provided insights into regulation of EDN1 in the endothelin pathway, which is aiding the development of endothelin receptor EDNRA antagonists. Drug re-purposing opportunities, including SLC5A1 and canagliflozin (a type-2 diabetes drug), are also being identified. In this review, we present key studies from the past, highlight current avenues of research and look to the future focusing on gene discovery, epigenetics, gene-environment interactions, GRSs and drug discovery. We evaluate limitations affecting BP genetics, including ancestry bias and discuss streamlining of drug target discovery and applications for treating and preventing hypertension, which will contribute to tailored precision medicine for patients.

Cardiovascular health and risk of hospitalization with COVID-19: A Mendelian Randomization study

Background

Susceptibility to and severity of COVID-19 is associated with risk factors for and presence of cardiovascular disease.

Methods

We performed a 2-sample Mendelian randomization to determine whether blood pressure (BP), body mass index (BMI), presence of type 2 diabetes (T2DM) and coronary artery disease (CAD) are causally related to presentation with severe COVID-19. Variant-exposure instrumental variable associations were determined from most recently published genome-wide association and meta-analysis studies (GWAS) with publicly available summary-level GWAS data. Variant-outcome associations were obtained from a recent GWAS meta-analysis of laboratory confirmed diagnosis of COVID-19 with severity determined according to need for hospitalization/death. We also examined reverse causality using exposure as diagnosis of severe COVID-19 causing cardiovascular disease.

Results

We found no evidence for a causal association of cardiovascular risk factors/disease with severe COVID-19 (compared to population controls), nor evidence of reverse causality. Causal odds ratios (OR, by inverse variance weighted regression) for BP (OR for COVID-19 diagnosis 1.00 [95% confidence interval (CI): 0.99-1.01, P = 0.604] per genetically predicted increase in BP) and T2DM (OR for COVID-19 diagnosis to that of genetically predicted T2DM 1.02 [95% CI: 0.9-1.05, P = 0.927], in particular, were close to unity with relatively narrow confidence intervals.

Conclusion

The association between cardiovascular risk factors/disease with that of hospitalization with COVID-19 reported in observational studies could be due to residual confounding by socioeconomic factors and /or those that influence the indication for hospital admission.

Type 2 diabetes mellitus increases risk of erectile dysfunction independent of obesity and dyslipidemia: A Mendelian randomization study

BACKGROUND

The causal effects of individual risk factors of metabolic syndrome on erectile dysfunction (ED) are still unclear.

OBJECTIVES

To evaluate the causal effect of risk factors of metabolic syndrome on ED through Mendelian randomization (MR).

MATERIALS AND METHODS

Data for risk factors were obtained from multiple databases with 173,082-757,601 individuals, and that for ED were collected from a genome-wide association study including 223,805 Europeans. We performed univariate MR analysis using inverse-variance weighted, MR-Egger, weighted-median, weighted mode methods and multivariable MR analysis to evaluate the total and direct causal effects.

RESULTS

The univariable MR supported that type 2 diabetes mellitus (odds ratios [OR] = 1.14, 95% confidence intervals [CI]: 1.08-1.21, p < 0.001) and body mass index (BMI) (OR = 1.27, 95% CI: 1.12-1.44, p < 0.001) were associated with ED. After excluding the SNPs associated with BMI and other risk factors, the results of multivariable MR for T2D (OR = 1.15, 95% CI: 1.05-1.25, p = 0.001) remained consistent. However, the results of multivariable MR provided limited evidence for the causality between BMI and ED (OR = 1.06, 95% CI: 0.88-1.29, p = 0.532). For systolic blood pressure and lipid components (low-density lipoprotein, high-density lipoprotein and triglycerides), both univariable and multivariable MR failed to offer sufficient evidence to confirm their causal effect on ED.

CONCLUSION

T2D showed a direct causal effect on ED independent of obesity and dyslipidemia.

Multi-stage metabolomics and genetic analyses identified metabolite biomarkers of metabolic syndrome and their genetic determinants

Background

Metabolic syndrome (MetS) is a cluster of multiple cardiometabolic risk factors that increase the risk of type 2 diabetes and cardiovascular diseases. Identifying novel biomarkers of MetS and their genetic associations could provide insights into the mechanisms of cardiometabolic diseases.

Methods

Potential MetS-associated metabolites were screened and internally validated by untargeted metabolomics analyses among 693 patients with MetS and 705 controls. External validation was conducted using two well-established targeted metabolomic methods among 149 patients with MetS and 253 controls. The genetic associations of metabolites were determined by linear regression using our previous genome-wide SNP data. Causal relationships were assessed using a one-sample Mendelian Randomization (MR) approach.

Findings

Nine metabolites were ultimately found to be associated with MetS or its components. Five metabolites, including LysoPC(14:0), LysoPC(15:0), propionyl carnitine, phenylalanine, and docosapentaenoic acid (DPA) were selected to construct a metabolite risk score (MRS), which was found to have a dose-response relationship with MetS and metabolic abnormalities. Moreover, MRS displayed a good ability to differentiate MetS and metabolic abnormalities. Three SNPs (rs11635491, rs7067822, and rs1952458) were associated with LysoPC(15:0). Two SNPs, rs1952458 and rs11635491 were found to be marginally correlated with several MetS components. MR analyses showed that a higher LysoPC(15:0) level was causally associated with the risk of overweight/obesity, dyslipidaemia, high uric acid, high insulin and high HOMA-IR.

Interpretation

We identified five metabolite biomarkers of MetS and three SNPs associated with LysoPC(15:0). MR analyses revealed that abnormal LysoPC metabolism may be causally linked the metabolic risk.

Funding

This work was supported by grants from the National Key Research and Development Program of China (2017YFC0907004).

Idéfix: identifying accidental sample mix-ups in biobanks using polygenic scores

MOTIVATION

Identifying sample mix-ups in biobanks is essential to allow the repurposing of genetic data for clinical pharmacogenetics. Pharmacogenetic advice based on the genetic information of another individual is potentially harmful. Existing methods for identifying mix-ups are limited to datasets in which additional omics data (e.g. gene expression) is available. Cohorts lacking such data can only use sex, which can reveal only half of the mix-ups. Here, we describe Idéfix, a method for the identification of accidental sample mix-ups in biobanks using polygenic scores.

RESULTS

In the Lifelines population-based biobank, we calculated polygenic scores (PGSs) for 25 traits for 32 786 participants. We then applied Idéfix to compare the actual phenotypes to PGSs, and to use the relative discordance that is expected for mix-ups, compared to correct samples. In a simulation, using induced mix-ups, Idéfix reaches an AUC of 0.90 using 25 polygenic scores and sex. This is a substantial improvement over using only sex, which has an AUC of 0.75. Subsequent simulations present Idéfix's potential in varying datasets with more powerful PGSs. This suggests its performance will likely improve when more highly powered GWASs for commonly measured traits will become available. Idéfix can be used to identify a set of high-quality participants for whom it is very unlikely that they reflect sample mix-ups, and for these participants we can use genetic data for clinical purposes, such as pharmacogenetic profiles. For instance, in Lifelines, we can select 34.4% of participants, reducing the sample mix-up rate from 0.15% to 0.01%.

AVAILABILITYAND IMPLEMENTATION

Idéfix is freely available at https://github.com/molgenis/systemsgenetics/wiki/Idefix. The individual-level data that support the findings were obtained from the Lifelines biobank under project application number ov16_0365. Data is made available upon reasonable request submitted to the LifeLines Research office (research@lifelines.nl, https://www.lifelines.nl/researcher/how-to-apply/apply-here).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Bench Research Informed by GWAS Results

Scientifically interesting as well as practically important phenotypes often belong to the realm of complex traits. To the extent that these traits are hereditary, they are usually 'highly polygenic'. The study of such traits presents a challenge for researchers, as the complex genetic architecture of such traits makes it nearly impossible to utilise many of the usual methods of reverse genetics, which often focus on specific genes. In recent years, thousands of genome-wide association studies (GWAS) were undertaken to explore the relationships between complex traits and a large number of genetic factors, most of which are characterised by tiny effects. In this review, we aim to familiarise 'wet biologists' with approaches for the interpretation of GWAS results, to clarify some issues that may seem counterintuitive and to assess the possibility of using GWAS results in experiments on various complex traits.