The genetic regulation of the gastric transcriptome is associated with metabolic and obesity-related traits and diseases

Tissue-specific gene expression and gene regulation lead to a better understanding of tissue-specific physiology and pathophysiology. We analyzed the transcriptome and genetic regulatory profiles of two distinct gastric sites, corpus and antrum, to identify tissue-specific gene expression and its regulation. Gastric corpus and antrum mucosa biopsies were collected during routine gastroscopies from up to 431 healthy individuals. We obtained genotype and transcriptome data and performed transcriptome profiling and expression quantitative trait locus (eQTL) studies. We further used data from genome-wide association studies (GWAS) of various diseases and traits to partition their heritability and to perform transcriptome-wide association studies (TWAS). The transcriptome data from corpus and antral mucosa highlights the heterogeneity of gene expression in the stomach. We identified enriched pathways revealing distinct and common physiological processes in gastric corpus and antrum. Furthermore, we found an enrichment of the single nucleotide polymorphism (SNP)-based heritability of metabolic, obesity-related, and cardiovascular traits and diseases by considering corpus- and antrum-specifically expressed genes. Particularly, we could prioritize gastric-specific candidate genes for multiple metabolic traits, like NQO1 which is involved in glucose metabolism, MUC1 which contributes to purine and protein metabolism or RAB27B being a regulator of weight and body composition. Our findings show that gastric corpus and antrum vary in their transcriptome and genetic regulatory profiles indicating physiological differences which are mostly related to digestion and epithelial protection. Moreover, our findings demonstrate that the genetic regulation of the gastric transcriptome is linked to biological mechanisms associated with metabolic, obesity-related, and cardiovascular traits and diseases. NEW & NOTEWORTHY We analyzed the transcriptomes and genetic regulatory profiles of gastric corpus and for the first time also of antrum mucosa in 431 healthy individuals. Through tissue-specific gene expression and eQTL analyses, we uncovered unique and common physiological processes across both primary gastric sites. Notably, our findings reveal that stomach-specific eQTLs are enriched in loci associated with metabolic traits and diseases, highlighting the pivotal role of gene expression regulation in gastric physiology and potential pathophysiology.

Elucidation of the genetic causes of bicuspid aortic valve disease

AIMS

The present study aims to characterize the genetic risk architecture of bicuspid aortic valve (BAV) disease, the most common congenital heart defect.

METHODS AND RESULTS

We carried out a genome-wide association study (GWAS) including 2236 BAV patients and 11 604 controls. This led to the identification of a new risk locus for BAV on chromosome 3q29. The single nucleotide polymorphism rs2550262 was genome-wide significant BAV associated (P = 3.49 × 10-08) and was replicated in an independent case-control sample. The risk locus encodes a deleterious missense variant in MUC4 (p.Ala4821Ser), a gene that is involved in epithelial-to-mesenchymal transformation. Mechanistical studies in zebrafish revealed that loss of Muc4 led to a delay in cardiac valvular development suggesting that loss of MUC4 may also play a role in aortic valve malformation. The GWAS also confirmed previously reported BAV risk loci at PALMD (P = 3.97 × 10-16), GATA4 (P = 1.61 × 10-09), and TEX41 (P = 7.68 × 10-04). In addition, the genetic BAV architecture was examined beyond the single-marker level revealing that a substantial fraction of BAV heritability is polygenic and ∼20% of the observed heritability can be explained by our GWAS data. Furthermore, we used the largest human single-cell atlas for foetal gene expression and show that the transcriptome profile in endothelial cells is a major source contributing to BAV pathology.

CONCLUSION

Our study provides a deeper understanding of the genetic risk architecture of BAV formation on the single marker and polygenic level.

Development and validation of a triplex real-time qPCR for sensitive detection and quantification of major rat bite fever pathogen Streptobacillus moniliformis

Streptobacillus (S.) moniliformis is the most important pathogen causing rat bite fever (RBF) worldwide. This zoonotic pathogen is understudied mainly due to difficulties in culturing S. moniliformis as a fastidious microorganism. Therefore, advances in molecular detection techniques are highly needed, especially with regard to the widespread availability of real-time quantitative (q) PCR in laboratories. In this study, we aimed to develop a qPCR for the identification of Streptobacillus species and quantification of S. moniliformis in clinical samples, especially those derived from tissue samples of animal origin. We optimized a previously described PCR protocol in order to develop a qPCR, which can detect different Streptobacillus species with high specificity and is simultaneously able to quantitate S. moniliformis in different clinical matrices. The qPCR exhibited a limit of detection (LOD) of 21 copies/reaction representing ~4-5 streptobacilli, while the limit of quantification (LOQ) was 2.1 × 10³ copies/reaction. It was also more sensitive than conventional PCR by two orders of magnitude and proved to have a substantial agreement (Kappa 0.74) compared to it with a superior detection rate in 374 samples from wild rats, laboratory rats and animals from holdings of wild-trapped rats. To conclude, the qPCR described in this study is an important molecular tool that is able to quantify S. moniliformis in tissue samples of animal origin. It represents a suitable tool for future establishment and evaluation of other molecular assays that are highly needed for a better understanding of epidemiology and pathophysiology of RBF. In experimental studies, it will also be useful for titration purposes since the quantification of the organism using classical plate counting technique is problematic and inaccurate.