Genome-wide Association Study Analysis Research Articles

Genome-wide association study and transcriptome analysis reveal the genetic basis underlying the environmental adaptation of plant height in a woody plant

Studies on plant height have been conducted in several crops. However, the underlying genetic mechanisms in woody plants remain unclear. To improve the genetic understanding of plant height, the genome-wide association study (GWAS) was conducted on the 298 individuals of paper mulberry (Broussonetia papyrifera), and the individuals with the highest and lowest plant heights were selected for comparative transcriptome analysis. The analysis of phenotypic data showed that plant height decreased from low latitude (N: 24°30′) to high latitude (N: 41°00′), ranging from 372 to 150 cm. Furthermore, the plant height of paper mulberry was significantly correlated with environmental factors, such as latitude, frost-free period, hours of sunshine and so on, indicating adaptive phenotypic divergence across environmental gradients. A total of 228 candidate genes were identified through the GWAS, including three genes (Bp10g0547, Bp10g0551 and Bp10g0817) that contained nonsynonymous SNP variations significantly affecting plant height. A total of 2554 differentially expressed genes (DEGs) were identified through RNA sequencing (RNA-seq) analysis, including 28, 5, 3, 20 and 138 DEGs involved in auxin, gibberellin, cytokinin, ubiquitylation and transcription factors, respectively. Besides, there were 13 common genes identified by integrating GWAS and RNA-seq analysis, including Bp10g0817, which encodes COP1 (CONSTITUTIVELY PHOTOMORPHOGENIC 1) and belongs to the RING type E3 ubiquitin ligase gene family. Collectively, this study provides valuable insights into the genetic mechanisms underlying plant height and adaptation of woody plants to diverse environments.

Shared genetic architecture and causality between autism spectrum disorder and irritable bowel syndrome, multisite pain, and fatigue

Autism spectrum disorder (ASD) often co-occurs with functional somatic syndromes (FSS), such as irritable bowel syndrome (IBS), multisite pain, and fatigue. However, the underlying genetic mechanisms and causality have not been well studied. Using large-scale genome-wide association study (GWAS) data, we investigated the shared genetic architecture and causality between ASD and FSS. Specifically, we first estimated genetic correlations and then conducted a multi-trait analysis of GWAS (MTAG) to detect potential novel genetic variants for single traits. Afterwards, polygenic risk scores (PRS) of ASD were derived from GWAS and MTAG to examine the associations with phenotypes in the large Dutch Lifelines cohort. Finally, we performed Mendelian randomization (MR) to evaluate the causality. We observed positive genetic correlations between ASD and FSS (IBS: rg = 0.27, adjusted p = 2.04 × 10−7; multisite pain: rg = 0.13, adjusted p = 1.10 × 10−3; fatigue: rg = 0.33, adjusted p = 5.21 × 10−9). Leveraging these genetic correlations, we identified 3 novel genome-wide significant independent loci for ASD by conducting MTAG, mapped to NEDD4L, MFHAS1, and RP11-10A14.4. PRS of ASD derived from both GWAS and MTAG were associated with ASD and FSS in Lifelines, and MTAG-derived PRS showed a bigger effect size, larger explained variance, and smaller p-values. We did not observe significant causality using MR. Our study found genetic associations between ASD and FSS, specifically with IBS, multisite pain, and fatigue. These findings suggest that a shared genetic architecture may partly explain the co-occurrence between ASD and FSS. Further research is needed to investigate the causality between ASD and FSS due to current limited statistical power of the GWASs.

Genome-wide association analysis provides insights into the molecular etiology of dilated cardiomyopathy.

Dilated cardiomyopathy (DCM) is a leading cause of heart failure and cardiac transplantation. We report a genome-wide association study and multi-trait analysis of DCM (14,256 cases) and three left ventricular traits (36,203 UK Biobank participants). We identified 80 genomic risk loci and prioritized 62 putative effector genes, including several with rare variant DCM associations (MAP3K7, NEDD4L and SSPN). Using single-nucleus transcriptomics, we identify cellular states, biological pathways, and intracellular communications that drive pathogenesis. We demonstrate that polygenic scores predict DCM in the general population and modify penetrance in carriers of rare DCM variants. Our findings may inform the design of genetic testing strategies that incorporate polygenic background. They also provide insights into the molecular etiology of DCM that may facilitate the development of targeted therapeutics.

Protein phosphatase 1 catalytic subunit gamma is a causative gene for meat lightness and redness.

The quality of meat is important to the consumer. Color is a primary indicator of meat quality and is characterized mainly into lightness, redness, and yellowness. Here, we used the genome-wide association study (GWAS) and gene-based association analysis with whole-genome resequencing of 230 fast-growing white-feathered chickens to map genes related to meat lightness and redness to a 6.24 kb QTL region (Chr15: 6298.34-6304.58 kb). This analysis revealed that only the protein phosphatase 1 catalytic subunit gamma (PPP1CC) was associated with meat color (P = 8.65E-08). The causal relationships between PPP1CC expression and meat lightness/redness were further validated through Mendelian randomization analyses (P < 2.9E-12). Inducible skeletal muscle-specific PPP1CC knockout (PPP1CC-SSKO) mice were generated and these mice showed increased lightness and decreased myoglobin content in the limb muscles. In addition, the predominant myofiber shifted from slow-twitch to fast-twitch myofibers. Through transcriptome and targeted metabolome evidence, we found that inhibition of PPP1CC decreased the expression of typical slow-twitch myofiber and myofiber-type specification genes and enhanced the glycolysis pathway. Functional validation through a plasmid reporter assay revealed that a SNP (rs315520807, C > T) located in the intron of PPP1CC could regulate the gene transcription activity. The differences in meat color phenotypes, myoglobin content, frequency of rs315520807 variant, expression of PPP1CC and fast-twitch fiber marker genes were detected between fast-growing white-feathered chickens and local chickens. In this study, PPP1CC was identified as the causative gene for meat color, and the novel target gene and variant that can aid in the innovation of meat improvement technology were detected.

Screening of SNP Loci Related to Leg Length Trait in Leizhou Goats Based on Whole-Genome Resequencing.

Leizhou goats can be classified into tall and short types based on their size and habits. The tall Leizhou goats are well-suited for grazing management due to their robust physique, while the dwarf types are smaller, grow rapidly, and are more appropriate for feeding management systems. In this study, whole-genome resequencing was conducted to identify genomic variants in 15 Tall-legged (TL) and 15 Short-legged (SL) Leizhou goats, yielding 8,641,229 high-quality SNPs in the Leizhou goat genome. Phylogenetic tree and principal component analyses revealed obvious genetic differentiation between the two groups. Fst and θπ analyses identified 420 genes in the TL group and 804 genes in the SL group. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses indicated that the phosphatidylinositol signaling system is associated with growth and development. Additionally, Genome-Wide Association Study (GWAS) analysis identified eight genes linked to leg length, including B4GALT7 and NR1D1. Notably, the NC_030818.1 (g.53666634T > C) variant was significantly associated with leg length traits, where the CC genotype was linked to shorter legs and the TT genotype to longer legs. This study identifies candidate genes and molecular markers, serving as a reference point for breeding and genetic improvement efforts in Leizhou goats and other goat breeds.

Genetic Differences Modify Anesthetic Preconditioning of Traumatic Brain Injury in Drosophila.

Pre-clinical vertebrate models of traumatic brain injury (TBI) routinely use anesthetics for animal welfare; however, humans experience TBI without anesthetics. Therefore, translation of findings from vertebrate models to humans hinges on understanding how anesthetics influence cellular and molecular events that lead to secondary injuries following TBI. To investigate the effects of anesthetics on TBI outcomes, we used an invertebrate Drosophila melanogaster model to compare outcomes between animals exposed or not exposed to anesthetics prior to the same primary injury. Using a common laboratory fly line, w1118, we found that exposure to the volatile anesthetics isoflurane or sevoflurane, but not ether, prior to TBI produced a dose-dependent reduction in mortality within 24 h following TBI. Thus, isoflurane and sevoflurane precondition w1118 flies to deleterious effects of TBI. To examine the effects of genetic differences on anesthetic preconditioning of TBI, we repeated the experiment with the Drosophila Genetic Reference Panel (DGRP) collection of genetically diverse, inbred fly lines. Pre-exposure to either isoflurane or sevoflurane revealed a wide range of preconditioning levels among 171 and 144 DGRP lines, respectively, suggesting a genetic component for variation in anesthetic preconditioning of mortality following TBI. Finally, genome-wide association study analyses identified single-nucleotide polymorphisms in genes associated with isoflurane or sevoflurane preconditioning of TBI. Several of the genes, including the fly ortholog of mammalian Calcium Voltage-Gated Subunit Alpha1 D (CACNA1D), are highly expressed in neurons and are functionally linked to both anesthetics and TBI. These data indicate that anesthetic dose and genetic background should be considered when investigating effects of anesthetics in vertebrate TBI models, and they support use of the fly model for elucidating the mechanisms underlying anesthetic preconditioning of TBI.

A genome-wide association study in Swedish colorectal cancer patients with gastric- and prostate cancer in relatives

BackgroundA complex inheritance has been suggested in families with colorectal-, gastric- and prostate cancer. Therefore, we conducted a genome-wide association study (GWAS) in colorectal cancer patients, who’s relatives had prostate-, and/or gastric cancer.MethodsThe GWAS analysis consisted of 685 cases of colorectal cancer and 4780 healthy controls from Sweden. A sliding window haplotype analysis was conducted using a logistic regression model. Thereafter, we performed sequencing to find candidate variants, finally to be tested in a nested case–control study.ResultsCandidate loci/genes on ten chromosomal regions were suggested with odds ratios between 1.71–3.62 and p-values < 5 × 10–8 in the analysis. The regions suggested were 1q32.2, 3q29, 4q35.1, 4p15.31, 4q26, 8p23.1, 13q33.3, 13q13.3, 16q23.3 and 22q11.21. All regions, except one on 1q32.2, had protein coding genes, many already shown to be involved in cancer, such as ZDHHC19, SYNPO2, PCYT1A, MYO16, TXNRD2, COMT, and CDH13. Sequencing of DNA from 122 colorectal cancer patients with gastric- and/or prostate cancer in their families was performed to search for candidate variants in the haplotype regions. The identified candidate variants were tested in a nested case–control study of similar colorectal cancer cases and controls. There was some support for an increased risk of colorectal-, gastric-, and/or prostate cancer in all the six loci tested.ConclusionsThis study demonstrated a proof of principle strategy to identify risk variants found by GWAS, and identified ten candidate loci that could be associated with colorectal, gastric- and prostate cancer.Graphical

QTL mapping and genome-wide association analysis reveal genetic loci and candidate gene for resistance to gray leaf spot in tropical and subtropical maize germplasm

Key messageUsing QTL mapping and GWAS, two candidate genes (Zm00001d051039 and Zm00001d051147) were consistently identified across the three different environments and BLUP values. GWAS analysis identified the candidate gene, Zm00001d044845. These genes were subsequently validated to exhibit a significant association with maize gray leaf spot (GLS) resistance.Gray leaf spot (GLS) is a major foliar disease of maize (Zea mays L.) that causes significant yield losses worldwide. Understanding the genetic mechanisms underlying gray leaf spot resistance is crucial for breeding high-yielding and disease-resistant varieties. In this study, eight tropical and subtropical germplasms were crossed with the temperate germplasm Ye107 to develop a nested association mapping (NAM) population comprising 1,653 F2:8 RILs, consisting of eight recombinant inbred line (RIL) subpopulations, using the single-seed descent method. The NAM population was evaluated for GLS resistance in three different environments, and genotyping by sequencing of the NAM population generated 593,719 high-quality single-nucleotide polymorphisms (SNPs). Linkage analysis and genome-wide association studies (GWASs) were conducted to identify candidate genes regulating GLS resistance in maize. Both analyses identified 25 QTLs and 149 SNPs that were significantly associated with GLS resistance. Candidate genes were screened 20 Kb upstream and downstream of the significant SNPs, and three novel candidate genes (Zm00001d051039, Zm00001d051147, and Zm00001d044845) were identified. Zm00001d051039 and Zm00001d051147 were located on chromosome 4 and co-localized in both linkage (qGLS4-1 and qGLS4-2) and GWAS analyses. SNP-138,153,206 was located 0.499 kb downstream of the candidate gene Zm00001d051039, which encodes the protein IN2-1 homolog B, a homolog of glutathione S-transferase (GST). GSTs and protein IN2-1 homolog B scavenge reactive oxygen species under various stress conditions, and GSTs are believed to protect plants from a wide range of biotic and abiotic stresses by detoxifying reactive electrophilic compounds. Zm00001d051147 encodes a probable beta-1,4-xylosyltransferase involved in the biosynthesis of xylan in the cell wall, enhancing resistance. SNP-145,813,215 was located 2.69 kb downstream of the candidate gene. SNP-5,043,412 was consistently identified in three different environments and BLUP values and was located 8.788 kb downstream of the candidate gene Zm00001d044845 on chromosome 9. Zm00001d044845 encodes the U-box domain-containing protein 4 (PUB4), which is involved in regulating plant immunity. qRT-PCR analysis showed that the relative expression levels of the three candidate genes were significantly upregulated in the leaves of the TML139 (resistant) parent, indicating that these three candidate genes could be associated with resistance to GLS. The findings of this study are significant for marker-assisted breeding aimed at enhancing resistance to GLS in maize and lay the foundation for further elucidation of the genetic mechanisms underlying resistance to gray leaf spot in maize and breeding of new disease-resistant varieties.

Scalable analysis of large multi-ancestry biobanks by leveraging sparse ancestry-adjusted sample-relatedness.

Linear mixed-effects models (LMMs) and ridge regression are commonly applied in genetic association studies to control for population structure and sample-relatedness. To control for sample-relatedness, the existing methods use empirical genetic relatedness matrices (GRM) either explicitly or conceptually. This works well with mostly homogeneous populations, however, in multi-ancestry heterogeneous populations, GRMs are confounded with population structure which leads to inflated type I error rates, massively increased computation, and reduced power. Here, we propose FastSparseGRM, a scalable pipeline for multi-ancestry Genome-Wide Association studies (GWAS) and Whole Genome Sequencing (WGS) studies. It utilizes a block-diagonal sparse ancestry-adjusted (BDSA) GRM to model sample-relatedness, and ancestry PCs as fixed effects to control for population structure. It is ~ 2540/4100/54 times faster than BOLT-LMM/fast-GWA/REGENIE for fitting the null LMM on 50,000 heterogeneous subjects. Through numerical simulations and both single-variant GWAS and rare variant WGS analyses of five biomarkers (Triglycerides, HDL, LDL, BMI, Total Bilirubin) on the entire UK Biobank data, we demonstrate that our approach scales to nearly half-a-million subjects and provides accurate p-value calibration and improved power compared to the existing methods.

Detection of Candidate Genes and Development of KASP Markers for Pod Length and Pod Width by Combining Genome-Wide Association and Transcriptome Sequencing in Vegetable Soybean

Vegetable soybeans are one of the most important vegetable types in East Asia. The yield of vegetable soybeans is considerably influenced by the size of their pods. To facilitate the understanding of the genetic basis of the pod length and width in vegetable soybeans, we conducted a genome-wide association study (GWAS) and transcriptome sequencing. Four quantitative trait loci, namely, qGPoL1, qGPoL2, qGPoW1, and qGPoW2, were mapped via GWAS analysis. Through the integration of gene function annotation, transcriptome sequencing, and expression pattern analysis, we identified Glyma.06G255000 and Glyma.13G007000 as the key determinants of the pod length and width in vegetable soybeans, respectively. Furthermore, two kompetitive allele-specific polymerase chain reaction (KASP) markers, namely, S06-42138365 (A/T) and S13_628331 (A/T), were developed and effectively validated in 27 vegetable soybean accessions. Overall, our research identified genes that regulate the pod length and width and determined KASP markers for molecular marker-assisted selection breeding. These findings have crucial implications for the improvement of soybean crops and can contribute to the development of efficient breeding strategies.

Mining of Candidate Genes Associated with Leaf Shape Traits in Grapes.

As the most important organ for photosynthesis, leaves provide the main energy source for plant growth. Leaf traits affect light energy utilization and, thus, plant development and biomass. Given the high morphological variability of leaves between and within grape genotypes, phenotypic analysis is challenging. This study first evaluated leaf shape trait parameters using a specific leaf profile and area analyzer, along with genome-wide association study (GWAS) analyses, to identify additional candidate genes related to grape leaf shape traits. In the two-year analysis, 89 single-nucleotide polymorphisms (SNPs) were found to be significantly associated with leaf shape traits. These SNP loci were distributed on 18 chromosomes, of which chromosome 15 had the most relevant SNPs. We found that leaf shape-associated genes included mainly plant hormone-, ubiquitin ligase-, serine/threonine protein kinase-, transcription factor-, and cell wall metabolism-related genes. By analyzing the expression of these candidate genes on the chip, we found that they exhibited diverse expression levels in leaves at different developmental stages (young, mature, and senescent). This suggests that these genes could be considered candidates for grape leaf improvement.

Genetic and functional analyses of CTBP2 in anorexia nervosa and body weight regulation.

The C-terminal binding protein 2 (CTBP2) gene (translational isoforms: CTBP2-L/S, RIBEYE) had been identified by a cross-trait analysis of genome-wide association studies for anorexia nervosa (AN) and body mass index (BMI). Here, we did a mutation analysis in CTBP2 by performing polymerase chain reactions with subsequent Sanger-sequencing to identify variants relevant for AN and body weight regulation and ensued functional studies. Analysis of the coding regions of CTBP2 in 462 female patients with AN(acute or recovered), 490 children and adolescents with severe obesity, 445 healthy-lean adult individuals and 168 healthy adult individuals with normal body weight detected 24 variants located in the specific exon of RIBEYE.In the initial analysis, three of these were rare non-synonymous variants (NSVs) detected heterozygously in patients with AN (p.Arg72Trp - rs146900874; p.Val289Met -rs375685611 and p.Gly362Arg - rs202010294). Four NSVs and one heterozygousframeshift variant were exclusively detected in children and adolescents with severe obesity (p.Pro53Ser - rs150867595; p.Gln175ArgfsTer45 - rs141864737; p.Leu310Val - rs769811964; p.Pro397Ala - rs76134089 and p.Pro402Ser - rs113477585). Ribeye mRNA was detected in mouse hypothalamus. No effect of fasting or overfeeding on murine hypothalamic Ribeye expression was determined. Yet, increased Ribeye expression was detected in hypothalami of leptin-treated Lepob/ob mice. This increase was not related to reduced food intake and leptin-induced weight loss. We detected rare and frequent variants in the RIBEYE specific exon in both patients with AN and in children and adolescents with severe obesity. Our data suggest RIBEYE as a relevant gene for weight regulation.

Genome-wide association study reveals novel QTLs and candidate genes for panicle number in rice.

Panicle number (PN) is one of the three key yield components in rice, maintaining stable tiller and PN is a crucial characteristic of an ideal plant architecture. Understanding the molecular mechanisms underlying PN is essential for breeders aiming to improve rice yield. To dissect the genetic architecture of panicle number, a genome-wide association study (GWAS) was conducted in 411 japonica rice varieties. GWAS analysis was carried out with the mixed linear model using 743,678 high-quality SNPs. Over two experimental years, we detected a total of seven quantitative trait loci (QTLs), located on chromosomes 1, 4, 6, 8, 11, and 12; notably, qPN1.1 and qPN8 were detected consistently in both years. By combining haplotype and expression analyses, OsCKX11 was identified as the candidate gene for qPN8, while LOC_Os01g07870 and LOC_Os01g07950 were identified as candidate genes for qPN1.1. Significant differences were observed among the haplotypes of these candidate genes. Additionally, qRT-PCR results showed that LOC_Os01g07870 expression levels were significantly lower in accessions with high panicle numbers compared to those with low panicle numbers. To understand the natural biological function of these candidate genes, further research involving overexpression or silencing in rice is needed. Despite these challenges, our results will lay the foundation for further study of panicle development and provide valuable genetic resources for developing high-panicle-number rice cultivars using genetic engineering and molecular breeding.

Dissecting genomic regions and underlying candidate genes in groundnut MAGIC population for drought tolerance

BackgroundGroundnut is mainly grown in the semi-arid tropic (SAT) regions worldwide, where abiotic stress like drought is persistent. However, a major research gap exists regarding exploring the genetic and genomic underpinnings of tolerance to drought. In this study, a multi-parent advanced generation inter-cross (MAGIC) population was developed and evaluated for five seasons at two locations for three consecutive years (2018–19, 2019–20 and 2020–21) under drought stress and normal environments.ResultsPhenotyping data of drought tolerance related traits, combined with the high-quality 10,556 polymorphic SNPs, were used to perform multi-locus model genome-wide association study (GWAS) analysis. We identified 37 significant marker-trait associations (MTAs) (Bonferroni-corrected) accounting, 0.91- 9.82% of the phenotypic variance. Intriguingly, 26 significant MTAs overlap on four chromosomes (Ah03, Ah07, Ah10 and Ah18) (harboring 70% of MTAs), indicating genomic hotspot regions governing drought tolerance traits. Furthermore, important candidate genes associated with leaf senescence (NAC transcription factor), flowering (B3 domain-containing transcription factor, Ulp1 protease family, and Ankyrin repeat-containing protein), involved in chlorophyll biosynthesis (FAR1 DNA-binding domain protein), stomatal regulation (Rop guanine nucleotide exchange factor; Galacturonosyltransferases), and associated with yield traits (Fasciclin-like arabinogalactan protein 11 and Fasciclin-like arabinogalactan protein 21) were found in the vicinity of significant MTAs genomic regions.ConclusionThe findings of our investigation have the potential to provide a basis for significant MTAs validation, gene discovery and development of functional markers, which could be employed in genomics-assisted breeding to develop climate-resilient groundnut varieties.

Shared genetic associations and etiology between obstructive sleep apnea and CVDs: A genome-wide cross-trait analysis and bidirectional Mendelian randomization analysis.

To investigate the genetic correlations and potential causal relationships between obstructive sleep apnea (OSA) and various cardiovascular diseases (CVDs), aiming to enhance understanding of shared genetic mechanisms and improve recognition and treatment of OSA in patients with CVDs. Utilizing genome-wide association study (GWAS) data, we analyzed shared genetics between OSA and CVDs using linkage disequilibrium score regression (LDSC), multi-trait analysis of GWAS (MTAG), and genotype-tissue expression analysis (GTEx TSEA). We further investigated causal relationships using Bayesian colocalization tests, bidirectional Mendelian randomization (MR), and latent causal variable (LCV) analysis. We found strong associations between OSA and multiple CVDs: coronary artery disease (CAD), heart failure (HF), myocardial infarction (MI), stroke, and atrial fibrillation (AF). Novel SNPs related to CVDs were identified during single-trait MTAG analysis. By applying cross-trait MTAG, we identified 15 shared loci between OSA and CAD, 25 shared loci between OSA and MI, and 7 shared loci between OSA and HF. Shared genes are primarily expressed in the blood, heart, kidney, liver, muscle, and pancreas. MR analysis indicated a significant causal effect of OSA on HF and AF as a causal factor for OSA. LCV analysis suggested that AF was causally associated with OSA, while HF showed partial causality. Our study suggests strong genetic correlations between OSA and several CVDs. Further research is needed on the associations between OSA and CVDs, as well as the mechanisms of the identified loci.

A Genome-Wide Association Study and Rare Variant Analysis for Dupuytren Disease in a North American Population

Although European genome-wide association studies (GWAS) have aided in defining genetic associations in Dupuytren disease (DD), North American populations have been infrequently analyzed. Additionally, there are a paucity of rare variant analyses (RVA) for DD, which can help define both trait variability and risk for low-frequency variants. Our purpose was to perform a GWAS and RVA for DD using a North American database. The study cohort (cases and controls) consisted of patients from our institutional MyCode Community Health Initiative, an unselected clinical cohort. A GWAS was performed controlling for age, sex and body mass index. For the RVA, sequence kernel association test analysis was performed on the most significant genes from the GWAS. Sequence kernel association test is a regression method to test associations between common and rare genetic variants in a defined region and a specific trait while adjusting for covariates. A total of 1,123 DD cases and 130,822 controls were included. DD cases were significantly older, more likely to be male, and had higher body mass indices. The GWAS yielded variants in two genes with a statistically significant difference between cases and controls: WNT7B and EPDR1. WNT7B variants rs9330811 (odds ratio, 1.96; 95% confidence interval, 1.73-2.23) and rs10448585 (odds ratio, 1.68; 95% confidence interval, 1.44-1.96) were the top hits. Variant rs2122625 in EPDR1 also reached genome-wide significance. The RVA indicated that WNT7B, DUXA, LOXL1, CSMD2, and TACC2 were significantly associated with a diagnosis of DD. In our North American population, GWAS yielded variants in two genes that were significantly associated with DD (WNT7B and EPDR), which likely contribute to abnormal proliferation of fibroblasts. Five rare variants (WNT7B, DUXA, LOXL1, CSMD2, and TACC2) were also significantly associated with DD. As disease-modifying treatments are explored, these data add to a growing body of literature defining genetic variants in DD.

A Mendelian Randomization Study about Causal Associations between Tofu Consumption and Stroke as well as Related Subtypes.

Consuming soy in the diet is beneficial for health, and tofu possess the richest source of dietary soy. However, the specific association with stroke and related subtypes remains controversial. In this study, the genetic causal relationship among tofu and stroke as well as the subtypes was investigated by utilizing the data in a number of genome-wide association study (GWAS) based on population. The tofu intake GWAS analysis is derived from the Medical Research Council (MRC) Integrative Epidemiology Unit at the University of Bristol (MRC-IEU) Consortium. The two-sample Mendelian randomization (MR) study was carried out, utilizing multiple analysis methods to analyze the associations with stroke and related subtypes. The sensitivity, heterogeneity, and potential pleiotropy could be investigated by multiple analysis method. We found that tofu intake had no causal relationship with stroke. However, in stroke subtype, there is a causal relationship among tofu intake with the risk of intracerebral hemorrhage (ICH) (odds ratio, OR = 1.24 × 10-5, 95% CI: 1.54 × 10-8-9.95 × 10-3, p = 9.300 × 10-4), while tofu intake does not affect the risk of ischemic stroke (OR = 1.07 × 10-1, 95% CI: 3.84 × 10-4-2.97 × 101, p = 4.362 × 10-1) and subarachnoid hemorrhage (SAH) (OR = 3.33 × 10-3, 95% CI: 1.79 × 10-6-6.18, p = 1.373 × 10-1). Both the Mendelian randomization PRESSO (MR-PRESSO) global test and Cochran's Q test did not detect any sensitivity and heterogeneity. While tofu consumption is associated with a higher risk of ICH, it does not show a significant relationship with ischemic stroke or SAH. The varying effects of tofu on different stroke subtypes underscore the need for considering potential confounding dietary and lifestyle factors in future studies.

The genetic architecture of exercise-induced ventricular ectopy

Abstract Background Previously, we have shown that the frequency of exercise-induced premature ventricular contractions (PVCs) during and after exercise are associated with increased risk of major adverse cardiovascular events in asymptomatic individuals from the UK Biobank study1. The underlying mechanisms are, however, unclear. Several electrocardiographic markers associated with arrhythmogenesis have a known hereditary component, but the genetic underpinnings of exercise-induced ventricular ectopy have not been investigated. Purpose Our aim was to explore the genetic basis of premature ventricular ectopy during and after exercise and unveil plausible candidate genes and biological mechanisms. Methods We conducted a genome-wide association study (GWAS) for PVC frequency during exercise and recovery in &amp;gt;44,000 asymptomatic individuals of European ancestry without known cardiovascular disease from the UK Biobank study. As the distribution of PVC frequency is highly skewed (e.g. absence of negative values and excess of zero values), we first applied Gaussian transformation. Simulation studies were performed to justify that this approach would lead to valid inference. In the GWAS model, we included sex, age, UK Biobank genotyping array, and the first 10 genetic principal components as covariates. Statistical power was boosted by joint analysis of exercise and recovery PVC traits using multi-trait analysis of GWAS (MTAG)2. Genetic risk scores were constructed in independent samples from UK Biobank (N=341,948) and were tested for association with heart failure and life-threatening ventricular arrhythmias. Results We identified 4 loci for PVC frequency during exercise, and 1 locus for PVC frequency during recovery (Picture 1). Candidate genes included CRIM1, FLNC, and BAG3 for which mutations have been linked in the pathogenesis of (arrhythmogenic) cardiomyopathy. Subjects in the top 10% of the genetic risk scores had a significantly higher risk of heart failure and life-threatening ventricular arrhythmias compared to the bottom 90%, (odds ratio (OR) (95% confidence interval): 1.14 (1.08 – 1.20), p &amp;lt; 0.001; and 1.13 (1.02 – 1.24), p &amp;lt; 0.001, respectively). Conclusions Ventricular ectopic burdens during exercise and recovery have a significant heritable component. Candidate genes highlight a possible shared genetic background with inherited cardiomyopathy and a genetic risk score was associated with heart failure and ventricular arrhythmias. These findings substantial advance our understanding of the genetic basis of exercise-induced ventricular ectopy in a population-based cohort without cardiovascular disease.Miami plot of ventricular ectopic burden

Genome-wide association study of CMR image-based aortic stiffness in 45,789 individuals identifies loci linked with cardiovascular diseases

Abstract Background The use of artificial intelligence on large-scale cardiac magnetic resonance (CMR) imaging data has enabled detailed characterisation of cardiac shape and function for use in genome-wide association studies (GWAS), leading to improved understanding of genetic aetiology of cardiovascular diseases (CVDs). Aortic stiffness is associated with increased risk of cardiovascular events in observational studies. Here, we present a novel CMR-based pressure-independent measure of aortic stiffness, identify genetic associations and explore links with CVDs. Purpose Identify genetic contributions to pressure-independent aortic stiffness and links to CVDs using large-scale GWAS analysis on the UK Biobank cohort. Methods A pre-trained neural network was used to segment CMR images of participants in the UK Biobank to quantify ascending aorta diameter, which together with contemporaneous systolic and diastolic blood pressure measurements (SBP, DBP, respectively) were used to calculate a pressure-independent measure of aortic stiffness (β0). The measurement assumes an exponential relationship between pressure and aortic diameter. We then performed a GWAS on β0 in 45,789 participants of European ancestry without CVDs. A multi-trait-based conditional &amp; joint analysis (mtCOJO) was performed to estimate genetic effects independent of SBP, DBP and aortic area. We mapped the independent lead variants associated with aortic stiffness at P &amp;lt; 5x10-8 to nearest gene, and characterised shared genetic association across CVDs using Open Targets Platform database. Results The GWAS identified 17 independent lead variants, including 6 that remained significant in the conditional analysis. Four of these lead variants, not previously reported in GWAS of other aortic traits, were located near CTD-2203A3.1, MCF2L, CFDP1 and CDH13 genes (red annotations in the Figure). MCF2L, CFDP1 and CDH13 have been associated with coronary artery disease, and CFDP1 with myocardial infarction and coronary atherosclerosis in previous studies. Conclusion A GWAS of CMR-derived aortic stiffness identified 4 loci distinct from other aortic traits that also associate with other CVDs, suggesting genetic links between aortic stiffness and CVDs. Further analyses are required to explore biological mechanisms underlying these genetic associations.Aortic Stiffness Manhattan Plot

A genome-wide association study identifies genetic determinants of hemoglobin glycation index with implications across sex and ethnicity.

We investigated the genetic determinants of variation in the hemoglobin glycation index (HGI), an emerging biomarker for the risk of diabetes complications. We conducted a genome-wide association study (GWAS) for HGI in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial (N = 7,913) using linear regression and additive genotype encoding on variants with minor allele frequency greater than 3%. We conducted replication analyses of top findings in the Atherosclerosis Risk in Communities (ARIC) study with inverse variance-weighted meta-analysis. We followed up with stratified GWAS analyses by sex and self-reported race. In ACCORD, we identified single nucleotide polymorphisms (SNPs) associated with HGI, including a peak with the strongest association at the intergenic SNP rs73407935 (7q11.22) (P = 5.8e-10) with a local replication in ARIC. In black individuals, the variant rs10739419 on chromosome 9 in the Whirlin (WHRN) gene formally replicated (meta-P = 2.2e-9). The SNP-based heritability of HGI was 0.39 (P< 1e-10). HGI had significant sex-specific associations with SNPs in or near GALNT11 in women and HECW2 in men. Finally, in Hispanic participants, we observed genome-wide significant associations with variants near USF1 and NXNL2/SPIN1. Many HGI-associated SNPs were distinct from those associated with fasting plasma glucose or HbA1c, lending further support for HGI as a distinct biomarker of diabetes complications. The results of this first evaluation of the genetic etiology of HGI indicate that it is highly heritable and point to heterogeneity by sex and race.