Improved Detection of Potentially Pleiotropic Genes in Coronary Artery Disease and Chronic Kidney Disease Using GWAS Summary Statistics

Genetic variability in proteoglycan biosynthetic genes reveals new facets of heparan sulfate diversity

Heparan sulfate (HS) and chondroitin sulfate (CS) proteoglycans (PG) consist of a core protein to which the glycosaminoglycan (GAG) chains, HS or CS, are attached through a common linker tetrasaccharide. In the extracellular space, they are involved in the regulation of cell communication, assuring development and homeostasis. The HSPG biosynthetic pathway has documented 51 genes, with many diseases associated to defects in some of them. The phenotypic consequences of this genetic variation in humans, and of genetic ablation in mice, and their expression patterns, led to a phenotypically centered HSPG biosynthetic pathway model. In this model, HS sequences produced by ubiquitous NDST1, HS2ST and HS6ST enzymes are essential for normal development and homeostasis, whereas tissue restricted HS sequences produced by the non-ubiquitous NDST2-4, HS6ST2-3, and HS3ST1-6 enzymes are involved in adaptative behaviors, cognition, tissue responsiveness to stimuli, and vulnerability to disease. The model indicates that the flux through the HSPG/CSPG pathways and its diverse branches is regulated by substrate preferences and protein-protein-interactions. This results in a privileged biosynthesis of HSPG over that of CSPGs, explaining the phenotypes of linkeropathies, disease caused by defects in genes involved in the biosynthesis of the common tetrasaccharide linker. Documented feedback loops whereby cells regulate HS sulfation, and hence the interactions of HS with protein partners, may be similarly implemented, e.g., protein tyrosine sulfation and other posttranslational modifications in enzymes of the HSPG pathway. Together, ubiquitous HS, specialized HS, and their biosynthesis model can facilitate research for a better understanding of HSPG roles in physiology and pathology.

Global Epidemiological Impact of PNPLA3 I148M on Liver Disease

The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) has increased exponentially over the past three decades, in parallel with the global rise in obesity and type 2 diabetes. It is currently the most common cause of liver-related morbidity and mortality. Although obesity has been identified as a key factor in the increased prevalence of MASLD, individual differences in susceptibility are significantly influenced by genetic factors. PNPLA3 I148M (rs738409 C>G) is the variant with the greatest impact on the risk of developing progressive MASLD and likely other forms of steatotic liver disease. This variant is prevalent across the globe, with the risk allele (G) frequency exhibiting considerable variation. Here, we review the contribution of PNPLA3 I148M to global burden and regional differences in MASLD prevalence, focusing on recent evidence emerging from population-based sequencing studies and prevalence assessments. We calculated the population attributable fraction (PAF) as a means of quantifying the impact of the variant on MASLD. Furthermore, we employ quantitative trait locus (QTL) analysis to ascertain the associations between rs738409 and a range of phenotypic traits. This analysis suggests that these QTLs may underpin pleiotropic effects on extrahepatic traits. Finally, we outline potential avenues for further research and identify key areas for investigation in future studies.

Mitochondrial related variants associated with cardiovascular traits

Introduction

Cardiovascular disease (CVD) is responsible for over 30% of mortality worldwide. CVD arises from the complex influence of molecular, clinical, social, and environmental factors. Despite the growing number of autosomal genetic variants contributing to CVD, the cause of most CVDs is still unclear. Mitochondria are crucial in the pathophysiology, development and progression of CVDs; the impact of mitochondrial DNA (mtDNA) variants and mitochondrial haplogroups in the context of CVD has recently been highlighted.

Aims

We investigated the role of genetic variants in both mtDNA and nuclear-encoded mitochondrial genes (NEMG) in CVD, including coronary artery disease (CAD), hypertension, and serum lipids in the UK Biobank, with sub-group analysis for diabetes.

Methods

We investigated 371,542 variants in 2,527 NEMG, along with 192 variants in 32 mitochondrial genes in 381,994 participants of the UK Biobank, stratifying by presence of diabetes.

Results

Mitochondrial variants showed associations with CVD, hypertension, and serum lipids. Mitochondrial haplogroup J was associated with CAD and serum lipids, whereas mitochondrial haplogroups T and U were associated with CVD. Among NEMG, variants within Nitric Oxide Synthase 3 (NOS3) showed associations with CVD, CAD, hypertension, as well as diastolic and systolic blood pressure. We also identified Translocase Of Outer Mitochondrial Membrane 40 (TOMM40) variants associated with CAD; Solute carrier family 22 member 2 (SLC22A2) variants associated with CAD and CVD; and HLA-DQA1 variants associated with hypertension. Variants within these three genes were also associated with serum lipids.

Conclusion

Our study demonstrates the relevance of mitochondrial related variants in the context of CVD. We have linked mitochondrial haplogroup U to CVD, confirmed association of mitochondrial haplogroups J and T with CVD and proposed new markers of hypertension and serum lipids in the context of diabetes. We have also evidenced connections between the etiological pathways underlying CVDs, blood pressure and serum lipids, placing NOS3, SLC22A2, TOMM40 and HLA-DQA1 genes as common nexuses.

Inferring causal direction between two traits using R2 with application to transcriptome-wide association studies

In Mendelian randomization, two single SNP-trait correlation-based methods have been developed to infer the causal direction between an exposure (e.g., a gene) and an outcome (e.g., a trait), called MR Steiger's method and its recent extension called Causal Direction-Ratio (CD-Ratio). Here we propose an approach based on R2, the coefficient of determination, to combine information from multiple (possibly correlated) SNPs to simultaneously infer the presence and direction of a causal relationship between an exposure and an outcome. Our proposed method generalizes Steiger's method from using a single SNP to multiple SNPs as IVs. It is especially useful in transcriptome-wide association studies (TWASs) (and similar applications) with typically small sample sizes for gene expression (or another molecular trait) data, providing a more flexible and powerful approach to inferring causal directions. It can be applied to GWAS summary data with a reference panel. We also discuss the influence of invalid IVs and introduce a new approach called R2S to select and remove invalid IVs (if any) to enhance the robustness. We compared the performance of the proposed method with existing methods in simulations to demonstrate its advantages. We applied the methods to identify causal genes for high/low-density lipoprotein cholesterol (HDL/LDL) using the individual-level GTEx gene expression data and UK Biobank GWAS data. The proposed method was able to confirm some well-known causal genes while identifying some novel ones. Additionally, we illustrated an application of the proposed method to GWAS summary to infer causal relationships between HDL/LDL and stroke/coronary artery disease (CAD).

Large-scale meta-genome-wide association study reveals common genetic factors linked to radiation-induced acute toxicities across cancer types

BACKGROUND

This study was designed to identify common genetic susceptibility and shared genetic variants associated with acute radiation-induced toxicity across 4 cancer types (prostate, head and neck, breast, and lung).

METHODS

A genome-wide association study meta-analysis was performed using 19 cohorts totaling 12 042 patients. Acute standardized total average toxicity (STATacute) was modelled using a generalized linear regression model for additive effect of genetic variants, adjusted for demographic and clinical covariates (rSTATacute). Linkage disequilibrium score regression estimated shared single-nucleotide variation (SNV-formerly SNP)-based heritability of rSTATacute in all patients and for each cancer type.

RESULTS

Shared SNV-based heritability of STATacute among all cancer types was estimated at 10% (SE = 0.02) and was higher for prostate (17%, SE = 0.07), head and neck (27%, SE = 0.09), and breast (16%, SE = 0.09) cancers. We identified 130 suggestive associated SNVs with rSTATacute (5.0 × 10‒8 < P < 1.0 × 10‒5) across 25 genomic regions. rs142667902 showed the strongest association (effect allele A; effect size ‒0.17; P = 1.7 × 10‒7), which is located near DPPA4, encoding a protein involved in pluripotency in stem cells, which are essential for repair of radiation-induced tissue injury. Gene-set enrichment analysis identified 'RNA splicing via endonucleolytic cleavage and ligation' (P = 5.1 × 10‒6, P = .079 corrected) as the top gene set associated with rSTATacute among all patients. In silico gene expression analysis showed that the genes associated with rSTATacute were statistically significantly up-regulated in skin (not sun exposed P = .004 corrected; sun exposed P = .026 corrected).

CONCLUSIONS

There is shared SNV-based heritability for acute radiation-induced toxicity across and within individual cancer sites. Future meta-genome-wide association studies among large radiation therapy patient cohorts are worthwhile to identify the common causal variants for acute radiotoxicity across cancer types.

Identification of potentially common loci between childhood obesity and coronary artery disease using pleiotropic approaches

Childhood obesity remains one of the most important issues in global health, which is implicated in many chronic diseases. Converging evidence suggests that a higher body mass index during childhood (CBMI) is significantly associated with increased coronary artery disease (CAD) susceptibility in adulthood, which may partly arise from the shared genetic determination. Despite genome-wide association studies (GWASs) have successfully identified some loci associated with CBMI and CAD individually, the genetic overlap and common biological mechanism between them remains largely unexplored. Here, relying on the results from the two large-scale GWASs (n = 35,668 for CBMI and n = 547,261 for CAD), linkage disequilibrium score regression (LDSC) was used to estimate the genetic correlation of CBMI and CAD in the first step. Then, we applied different pleiotropy-informed methods including conditional false discovery rate ([Formula: see text]) and genetic analysis incorporating pleiotropy and annotation (GPA) to detect potentially common loci for childhood obesity and CAD. By integrating the genetic information from the existing GWASs summary statistics, we found a significant positive genetic correlation ([Formula: see text] = 0.127, p = 2E-4) and strong pleiotropic enrichment between CBMI and CAD (LRT = 79.352, p = 5.2E-19). Importantly, 28 loci were simultaneously discovered to be associated with CBMI, and 13 of them were identified as potentially pleiotropic loci by [Formula: see text] and GPA. Those corresponding pleiotropic genes were enriched in trait-associated gene ontology (GO) terms "amino sugar catabolic process", "regulation of fat cell differentiation" and "synaptic transmission". Overall, the findings of the pleiotropic loci will help to further elucidate the common molecular mechanisms underlying the association of childhood obesity and CAD, and provide a theoretical direction for early disease prevention and potential therapeutic targets.

ARHGEF19 promotes the growth of breast cancer in vitro and in vivo by the MAPK pathway

OBJECTIVE

To assess the expression of ARHGEF19 in human breast cancer, investigate its role in breast cancer, and clarify the mechanism.

METHODS

Bioinformatics analysis, immunoblot, quantitative PCR, and immunohistochemical (IHC) assays were performed to assess ARHGEF19 expression in breast cancer. CCK-8 and Edu assays were conducted to reveal its role in breast cancer cell proliferation. Flow cytometry (FCM) assays and immunoblot were performed to confirm its effects on breast cancer apoptosis. Immunoblot was also performed to clarify the mechanism. Finally, tumor growth assays were aimed to confirm the role of ARHGEF19 in mice.

RESULTS

We observed that ARHGEF19 was highly expressed in human breast cancer. ARHGEF19 promoted breast cancer cell growth in vitro, and suppressed apoptosis. In addition, we found that ARHGEF19 could activate the MAPK pathway in breast cancer cells. Our findings further confirmed that ARHGEF19 contributed to breast cancer growth in mice.

CONCLUSION

We observed that ARHGEF19 promoted the growth of breast cancer in vitro and in vivo via MAPK pathway, and presume it could serve as a breast cancer therapeutic target.