Metabolic syndrome (MetS) is a set of co-morbidities that collectively increase an individual’s risk of developing cardiovascular disease, stroke, and type 2 diabetes mellitus (T2D). Per the World Health Organization (WHO), MetS is typically characterized by obesity, insulin resistance, hypertension and hyperlipidemia. Building on this point, some of the major risk factors for development of MetS include increased weight or an obese phenotype, lack of physical activity, and genetics. Interestingly, the last decade has witnessed a deluge of Genome-Wide Association Studies (GWAS) that have linked hundreds of genomic with both collective MetS traits, as well as individual metabolic disorders sitting within it. Currently, in the post-GWAS era, the focus has shifted to characterization of these novel genomic to establish causality and disease relevance. This is being pursued by way of functional validation such as gain- and loss-of-function studies, investigating resulting metabolic phenotypes, mechanisms and pathways underlying these phenotypes, their prevalence and potential for risk stratification across populations , and finally, identification of therapeutic targets for pharmacological intervention.
The major goal of this article collection is to highlight the role of novel genetic variants in the pathophysiology of metabolic diseases sitting within MetS. This collection will include articles in any format, ie. original contributions, review and mini review to focus on the following sub-categories of MetS:
• Non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH)
• Obesity
• T2D and insulin resistance
• Cardiovascular and cardiometabolic traits
• Fetal environment (Birth weight/Gestational period/maternal smoking etc.)
Within these disease areas, special emphasis may be laid on:
• Rare coding and non-coding risk variants: impact on disease pathogenesis, progression and treatment of disease
• Gaps in knowledge: causality and functional validations studies
• Phenotypes and mechanisms: phenotype specificity or endophenotypes, differential mechanisms and pathways involved in order to map complex disease traits
• Nexus between variants and epigenetics
• Frequency/prevalence of occurrence in populations and transethnic comparisons
• Therapeutic potential for alleviation of disease load: identification of potential drug targets; eg. GWAS and personalized therapy or drug response studies/ intervention trials
• Diagnostic relevance, polygenic risk scores and combined algorithms with other non-invasive biomarkers
• Multi-Omics: importance/need to Combine Genomics with other omics such as proteomics, metabolomics and transcriptomics
• Limitations/challenges of GWAS
Despite several challenges, GWAS-backed exploration of disease biology has vastly improved our understanding of the genetic basis of human disease. With this article collection, we hope to continue the quest for identifying genetic variants and their role in metabolic diseases, all the way from functional validation to therapeutic potential.
Metabolic syndrome (MetS) is a set of co-morbidities that collectively increase an individual’s risk of developing cardiovascular disease, stroke, and type 2 diabetes mellitus (T2D). Per the World Health Organization (WHO), MetS is typically characterized by obesity, insulin resistance, hypertension and hyperlipidemia. Building on this point, some of the major risk factors for development of MetS include increased weight or an obese phenotype, lack of physical activity, and genetics. Interestingly, the last decade has witnessed a deluge of Genome-Wide Association Studies (GWAS) that have linked hundreds of genomic with both collective MetS traits, as well as individual metabolic disorders sitting within it. Currently, in the post-GWAS era, the focus has shifted to characterization of these novel genomic to establish causality and disease relevance. This is being pursued by way of functional validation such as gain- and loss-of-function studies, investigating resulting metabolic phenotypes, mechanisms and pathways underlying these phenotypes, their prevalence and potential for risk stratification across populations , and finally, identification of therapeutic targets for pharmacological intervention.
The major goal of this article collection is to highlight the role of novel genetic variants in the pathophysiology of metabolic diseases sitting within MetS. This collection will include articles in any format, ie. original contributions, review and mini review to focus on the following sub-categories of MetS:
• Non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH)
• Obesity
• T2D and insulin resistance
• Cardiovascular and cardiometabolic traits
• Fetal environment (Birth weight/Gestational period/maternal smoking etc.)
Within these disease areas, special emphasis may be laid on:
• Rare coding and non-coding risk variants: impact on disease pathogenesis, progression and treatment of disease
• Gaps in knowledge: causality and functional validations studies
• Phenotypes and mechanisms: phenotype specificity or endophenotypes, differential mechanisms and pathways involved in order to map complex disease traits
• Nexus between variants and epigenetics
• Frequency/prevalence of occurrence in populations and transethnic comparisons
• Therapeutic potential for alleviation of disease load: identification of potential drug targets; eg. GWAS and personalized therapy or drug response studies/ intervention trials
• Diagnostic relevance, polygenic risk scores and combined algorithms with other non-invasive biomarkers
• Multi-Omics: importance/need to Combine Genomics with other omics such as proteomics, metabolomics and transcriptomics
• Limitations/challenges of GWAS
Despite several challenges, GWAS-backed exploration of disease biology has vastly improved our understanding of the genetic basis of human disease. With this article collection, we hope to continue the quest for identifying genetic variants and their role in metabolic diseases, all the way from functional validation to therapeutic potential.
