Citations

BACKGROUND: Bicuspid aortic valve (BAV) is a frequent congenital heart defect with a high heritability. Despite this, only a limited number of genes have been associated with the disease, and the molecular mechanisms remain unexplained in most cases. This study aimed to further understand the genetic architecture of BAV. METHODS: A genome-wide association study meta-analysis including 9631 cases among 65 677 participants was performed. Genes were prioritized using transcriptomic analyses based on RNA sequencing in relevant tissues, including human fetal and adult aortic valves. The impact of the knockdown or knockout of 4 candidate genes on cardiac development was verified in zebrafish. A polygenic risk score was developed, its association with BAV was evaluated in an independent cohort, and its association with a wide range of phenotypes (n=976) was evaluated in UK Biobank (n=355 618 individuals). RESULTS: Thirty-six genomic loci were identified, including 32 that were not described previously. Among the prioritized genes, KANK2 and ERBB4 were identified as potentially causal through transcriptomic analyses, colocalization, and Mendelian randomization based on gene expression in human aortic valves (n=484), whereas PRDM6 and STRN were prioritized using similar analyses from aortic (n=326) and left ventricular tissues (n=326), respectively. Targeting 4 candidate genes ( WNT4 , LEF1 , STRN , and KANK2 ) in zebrafish led to disruption in cardiac development. A polygenic risk score was associated with an odds ratio of 2.07 (95% CI, 1.90–2.25; P =5.43×10 -62 ) per SD for BAV and significantly associated with thoracic aortic aneurysm and atrial fibrillation in UK Biobank. CONCLUSIONS: This study supports a significant polygenic contribution to BAV, where the combination of multiple common variants in genes involved in heart morphogenesis disrupts aortic valve development.

Background: Congenitally corrected transposition of the great arteries (ccTGA) is a rare disease of unknown cause. We aimed to better understand familial recurrence patterns. Methods: An international, multicentre, retrospective cohort study was conducted in 29 tertiary hospitals in 6 countries between 1990 and 2018, entailing investigation of 1043 unrelated ccTGA probands. Results: Laterality defects and atrioventricular block at diagnosis were observed in 29.9% and 9.3%, respectively. ccTGA was associated with primary ciliary dyskinesia in 11 patients. Parental consanguinity was noted in 3.4% cases. A congenital heart defect was diagnosed in 81 relatives from 69 families, 58% of them being first-degree relatives, including 28 siblings. The most prevalent defects in relatives were dextro-transposition of the great arteries (28.4%), laterality defects (13.6%), and ccTGA (11.1%); 36 new familial clusters were described, including 8 pedigrees with concordant familial aggregation of ccTGA, 19 pedigrees with familial co-segregation of ccTGA and dextro-transposition of the great arteries, and 9 familial co-segregation of ccTGA and laterality defects. In one family co-segregation of ccTGA, dextro-transposition of the great arteries and heterotaxy syndrome in 3 distinct relatives was found. In another family, twins both displayed ccTGA and primary ciliary dyskinesia. Conclusions: ccTGA is not always a sporadic congenital heart defect. Familial clusters as well as evidence of an association between ccTGA, dextro-transposition of the great arteries, laterality defects and in some cases primary ciliary dyskinesia, strongly suggest a common pathogenetic pathway involving laterality genes in the pathophysiology of ccTGA.

Abstract Aims Mitral valve prolapse (MVP) is a common valvular heart disease with a prevalence of >2% in the general adult population. Despite this high incidence, there is a limited understanding of the molecular mechanism of this disease, and no medical therapy is available for this disease. We aimed to elucidate the genetic basis of MVP in order to better understand this complex disorder. Methods and results We performed a meta-analysis of six genome-wide association studies that included 4884 cases and 434 649 controls. We identified 14 loci associated with MVP in our primary analysis and 2 additional loci associated with a subset of the samples that additionally underwent mitral valve surgery. Integration of epigenetic, transcriptional, and proteomic data identified candidate MVP genes including LMCD1, SPTBN1, LTBP2, TGFB2, NMB, and ALPK3. We created a polygenic risk score (PRS) for MVP and showed an improved MVP risk prediction beyond age, sex, and clinical risk factors. Conclusion We identified 14 genetic loci that are associated with MVP. Multiple analyses identified candidate genes including two transforming growth factor-β signalling molecules and spectrin β. We present the first PRS for MVP that could eventually aid risk stratification of patients for MVP screening in a clinical setting. These findings advance our understanding of this common valvular heart disease and may reveal novel therapeutic targets for intervention.

Abstract Eating disorders and substance use disorders frequently co‐occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [ r g ], twin‐based = 0.23‐0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome‐wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance‐use‐related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism‐based genetic correlations between eating disorder‐ and substance‐use‐related phenotypes. Significant positive genetic associations emerged between AUD and AN ( r g = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN ( r g = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating ( r g = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating ( r gs = −0.19 to −0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co‐varying for major depressive disorder loci. The patterns of association between eating disorder‐ and substance‐use‐related phenotypes highlights the potentially complex and substance‐specific relationships among these behaviors.

KLF11 (TIEG2) is a pancreas-enriched transcription factor that has elicited significant attention because of its role as negative regulator of exocrine cell growth in vitro and in vivo . However, its functional role in the endocrine pancreas remains to be established. Here, we report, for the first time, to our knowledge, the characterization of KLF11 as a glucose-inducible regulator of the insulin gene. A combination of random oligonucleotide binding, EMSA, luciferase reporter, and chromatin immunoprecipitation assays shows that KLF11 binds to the insulin promoter and regulates its activity in beta cells. Genetic analysis of the KLF11 gene revealed two rare variants (Ala347Ser and Thr220Met) that segregate with diabetes in families with early-onset type 2 diabetes, and significantly impair its transcriptional activity. In addition, analysis of 1,696 type 2 diabetes mellitus and 1,776 normoglycemic subjects show a frequent polymorphic Gln62Arg variant that significantly associates with type 2 diabetes mellitus in North European populations (OR = 1.29, P = 0.00033). Moreover, this variant alters the corepressor mSin3A-binding activity of KLF11, impairs the activation of the insulin promoter and shows lower levels of insulin expression in pancreatic beta cells. In addition, subjects carrying the Gln62Arg allele show decreased plasma insulin after an oral glucose challenge. Interestingly, all three nonsynonymous KLF11 variants show increased repression of the catalase 1 promoter, suggesting a role in free radical clearance that may render beta cells more sensitive to oxidative stress. Thus, both functional and genetic analyses reveal that KLF11 plays a role in the regulation of pancreatic beta cell physiology, and its variants may contribute to the development of diabetes.