Identification of Genetic Variants Associated with Severe Myocardial Bridging through Whole-Exome Sequencing.

Myocardial bridging (MB) is a congenital coronary artery anomaly and an important cause of angina. The genetic basis of MB is currently unknown. This study used a whole-exome sequencing technique and analyzed genotypic differences. Eight coronary angiography-confirmed cases of severe MB and eight age- and sex-matched control patients were investigated. In total, 139 rare variants that are potentially pathogenic for severe MB were identified in 132 genes. Genes with multiple rare variants or co-predicted by ClinVar and CADD/REVEL for severe MB were collected, from which heart-specific genes were selected under the guidance of tissue expression levels. Functional annotation indicated significant genetic associations with abnormal skeletal muscle mass, cardiomyopathies, and transmembrane ion channels. Candidate genes were reviewed regarding the functions and locations of each individual gene product. Among the gene candidates for severe MB, rare variants in DMD, SGCA, and TTN were determined to be the most crucial. The results suggest that altered anchoring proteins on the cell membrane and intracellular sarcomere unit of cardiomyocytes play a role in the development of the missed trajectory of coronary vessels. Additional studies are required to support the diagnostic application of cardiac sarcoglycan and dystroglycan complexes in patients with severe MB.

Application of Whole Exome Sequencing and Functional Annotations to Identify Genetic Variants Associated with Marfan Syndrome.

Marfan syndrome (MFS) is a rare disease that affects connective tissue, which causes abnormalities in several organ systems including the heart, eyes, bones, and joints. The autosomal dominant disorder was found to be strongly associated with FBN1, TGFBR1, and TGFBR2 mutations. Although multiple genetic mutations have been reported, data from Asian populations are still limited. As a result, we utilized the whole exome sequencing (WES) technique to identify potential pathogenic variants of MFS in a Taiwan cohort. In addition, a variety of annotation databases were applied to identify the biological functions as well as the potential mechanisms of candidate genes. In this study, we confirmed the pathogenicity of FBN1 to MFS. Our results indicated that TTN and POMT1 may be likely related to MFS phenotypes. Furthermore, we found nine unique variants highly shared in a MFS family cohort, of which eight are novel variants worthy of further investigation.

Identification of Druggable Genes for Asthma by Integrated Genomic Network Analysis.

Asthma is a common and heterogeneous disease characterized by chronic airway inflammation. Currently, the two main types of asthma medicines are inhaled corticosteroids and long-acting ß2-adrenoceptor agonists (LABAs). In addition, biological drugs provide another therapeutic option, especially for patients with severe asthma. However, these drugs were less effective in preventing severe asthma exacerbation, and other drug options are still limited. Herein, we extracted asthma-associated single nucleotide polymorphisms (SNPs) from the genome-wide association studies (GWAS) and phenome-wide association studies (PheWAS) catalog and prioritized candidate genes through five functional annotations. Genes enriched in more than two categories were defined as "biological asthma risk genes." Then, DrugBank was used to match target genes with FDA-approved medications and identify candidate drugs for asthma. We discovered 139 biological asthma risk genes and identified 64 drugs targeting 22 of these genes. Seven of them were approved for asthma, including reslizumab, mepolizumab, theophylline, dyphylline, aminophylline, oxtriphylline, and enprofylline. We also found 17 drugs with clinical or preclinical evidence in treating asthma. In addition, eleven of the 40 candidate drugs were further identified as promising asthma therapy. Noteworthy, IL6R is considered a target for asthma drug repurposing based on its high target scores. Through in silico drug repurposing approach, we identified sarilumab and satralizumab as the most promising drug for asthma treatment.

Whole-Exome Sequencing Identifies Genetic Variants for Severe Adolescent Idiopathic Scoliosis in a Taiwanese Population.

Adolescent idiopathic scoliosis (AIS) is a three-dimensional spinal curvature deformity that appears in the adolescent period. In this study, we performed whole-exome sequencing on 11 unrelated Taiwanese patients with a Cobb's angle greater than 40 degrees. Our results identified more than 200 potential pathogenic rare variants, however, most of which were carried only by one individual. By in silico pathogenicity annotation studies, we found that TTN, CLCN1, and SOX8 were the most important genes, as multiple pathogenic variants were within these genes. Furthermore, biological functional annotation indicated critical roles of these AIS candidate genes in the skeletal muscle. Importantly, a pathogenic variant on SOX8 was shared by over 35% of the patients. These results highlighted TTN, CLCN1, and SOX8 as the most likely susceptibility genes for severe AIS.

Drug Repurposing for Atopic Dermatitis by Integration of Gene Networking and Genomic Information.

Atopic Dermatitis (AD) is a chronic and relapsing skin disease. The medications for treating AD are still limited, most of them are topical corticosteroid creams or antibiotics. The current study attempted to discover potential AD treatments by integrating a gene network and genomic analytic approaches. Herein, the Single Nucleotide Polymorphism (SNPs) associated with AD were extracted from the GWAS catalog. We identified 70 AD-associated loci, and then 94 AD risk genes were found by extending to proximal SNPs based on r2 > 0.8 in Asian populations using HaploReg v4.1. Next, we prioritized the AD risk genes using in silico pipelines of bioinformatic analysis based on six functional annotations to identify biological AD risk genes. Finally, we expanded them according to the molecular interactions using the STRING database to find the drug target genes. Our analysis showed 27 biological AD risk genes, and they were mapped to 76 drug target genes. According to DrugBank and Therapeutic Target Database, 25 drug target genes overlapping with 53 drugs were identified. Importantly, dupilumab, which is approved for AD, was successfully identified in this bioinformatic analysis. Furthermore, ten drugs were found to be potentially useful for AD with clinical or preclinical evidence. In particular, we identified filgotinub and fedratinib, targeting gene JAK1, as potential drugs for AD. Furthermore, four monoclonal antibody drugs (lebrikizumab, tralokinumab, tocilizumab, and canakinumab) were successfully identified as promising for AD repurposing. In sum, the results showed the feasibility of gene networking and genomic information as a potential drug discovery resource.