De novo identification of complex traits associated with asthma.

Introduction: Asthma is a heterogeneous inflammatory disease often associated with other complex phenotypes. Identifying asthma-associated diseases and uncovering the molecular mechanisms mediating their interaction can help detangle the heterogeneity of asthma. Network analysis is a powerful approach for untangling such inter-disease relationships. Methods: Here, we integrated information on physical contacts between common single nucleotide polymorphisms (SNPs) and gene expression with expression quantitative trait loci (eQTL) data from the lung and whole blood to construct two tissue-specific spatial gene regulatory networks (GRN). We then located the asthma GRN (level 0) within each tissue-specific GRN by identifying the genes that are functionally affected by asthma-associated spatial eQTLs. Curated protein interaction partners were subsequently identified up to four edges or levels away from the asthma GRN. The eQTLs spatially regulating genes on levels 0-4 were queried against the GWAS Catalog to identify the traits enriched (hypergeometric test; FDR ≤ 0.05) in each level. Results: We identified 80 and 82 traits significantly enriched in the lung and blood GRNs, respectively. All identified traits were previously reported to be comorbid or associated (positively or negatively) with asthma (e.g., depressive symptoms and lung cancer), except 8 traits whose association with asthma is yet to be confirmed (e.g., reticulocyte count). Our analysis additionally pinpoints the variants and genes that link asthma to the identified asthma-associated traits, a subset of which was replicated in a comorbidity analysis using health records of 26,781 asthma patients in New Zealand. Discussion: Our discovery approach identifies enriched traits in the regulatory space proximal to asthma, in the tissue of interest, without a priori selection of the interacting traits. The predictions it makes expand our understanding of possible shared molecular interactions and therapeutic targets for asthma, where no cure is currently available.

Integrating Multimorbidity into a Whole-Body Understanding of Disease Using Spatial Genomics.

Multimorbidity is characterized by multidimensional complexity emerging from interactions between multiple diseases across levels of biological (including genetic) and environmental determinants and the complex array of interactions between and within cells, tissues and organ systems. Advances in spatial genomic research have led to an unprecedented expansion in our ability to link alterations in genome folding with changes that are associated with human disease. Studying disease-associated genetic variants in the context of the spatial genome has enabled the discovery of transcriptional regulatory programmes that potentially link dysregulated genes to disease development. However, the approaches that have been used have typically been applied to uncover pathological molecular mechanisms occurring in a specific disease-relevant tissue. These forms of reductionist, targeted investigations are not appropriate for the molecular dissection of multimorbidity that typically involves contributions from multiple tissues. In this perspective, we emphasize the importance of a whole-body understanding of multimorbidity and discuss how spatial genomics, when integrated with additional omic datasets, could provide novel insights into the molecular underpinnings of multimorbidity.

The Spectrum of Genetic Variants Associated with the Development of Monogenic Obesity in Qatar.

INTRODUCTION: Monogenic obesity (MO) is a rare genetic disease characterized by severe early-onset obesity in affected individuals. Previous genetic studies revealed 8 definitive genes for monogenic non-syndromic obesity; many were discovered in consanguineous populations. Here, we examined MO in the Qatari population, whose population is largely consanguineous (54%) and characterized by extensive obesity (45%). METHODS: Whole genome sequencing data of Qatar Biobank samples from 250 subjects with obesity and 250 subjects with normal weight, obtained in association with the Qatar Genome Programme, were searched for genetic variants in the genes known to be associated with MO (i.e., LEP, LEPR, POMC, PCSK1, MC3R, MC4R, MRAP2, and ADCY3). The impact of the variants identified was investigated utilizing in silico tools for prediction in combination with protein visualization by PyMOL. RESULTS: We identified potential MO variants in more than 5% of the cases in our cohort. We revealed 11 rare variants in 6 of the genes targeted, including two disease-causing variants in MC4R and MRAP2, all of which were heterozygous. Moreover, enrichment of a heterozygous ADCY3 variant (c.1658C>T; p.A553V) appeared to cause severe obesity in an autosomal dominant manner. CONCLUSION: These findings highlight the importance of implementing routine testing for genetic variants that predispose for MO in Qatar. Clearly, additional studies of this nature on populations not yet examined are required. At the same time, functional investigations, both in vitro and in vivo, are necessary in order to better understand the role of the variants identified in the pathogenesis of obesity.

Hepatitis B Virus Molecular Epidemiology, Host-Virus Interaction, Coinfection, and Laboratory Diagnosis in the MENA Region: An Update.

Hepatitis B virus (HBV) is an enveloped partial double-stranded DNA virus that can cause acute and chronic hepatitis. According to the World Health Organization (WHO) and the Centers for Disease Control and Prevention (CDC), 257 million people are living with HBV. Moreover, 20,900 acute hepatitis B cases were reported in 2016. Hepatitis B is highly prevalent in the African, Western Pacific, Eastern Mediterranean, South-East Asia, and European regions, respectively. Due to the high mutational rate of HBV and lack of reverse transcriptase proofreading activity, ten different genotypes with different geographical distributions have been identified. HBV pathogenesis and severity of infection depend on several host and viral factors, particularly, the genetic variability of both the host and virus. Although HBV infection is a global health concern, there is a lack of adequate studies and reports in the Middle East and North Africa (MENA) region. Here, we provide a review on HBV epidemiology, pathogenesis, host-pathogen interactions, coinfection with selected viruses, and laboratory diagnosis, focusing on studies conducted in the MENA region to determine the current situation of the HBV infection and outline the future study areas.