About this Research Topic
Type 2 diabetes (T2D) is one of the most prevalent chronic diseases, affecting about 415 million people worldwide in 2015. The etiology of T2D involves an interaction between genetic predisposition and lifestyle (e.g. overweight, unhealthy diet, sedentariness).
The past decade has seen fast-paced, technology-driven developments in the field of complex disease genomics. Implementation of the genome wide association study approach has revolutionized our understanding of the genetic underpinnings of T2D, identifying ~70 genetic risk loci for T2D. However, these alone explain less than 10% of overall T2D risk and do not accurately predict T2D.
In the past five years, clinical studies of T2D have increasingly focused on identifying novel serum biomarkers for T2D using cutting-edge ‘omics’ tools, such as metabolomics and proteomics. Metabolomics approaches in particular have been widely adapted to screen blood or other human tissues for changes in metabolites and low-molecular-weight biomolecules such as lipids, sugars, amino acids, organic acids, and nucleotides.
We welcome original and review papers describing current highlights, methods, and challenges in identifying, characterizing, and validating “Novel Biomarkers for Type 2 Diabetes”. We welcome both basic and clinical research articles focusing on experimental data and/or theory including (but not limited to) the following potential topics:
• Identification of biomarkers (e.g. genetic, metabolomic, or proteomic) associated with T2D and related traits
• Prediction of incident T2D and related traits using multivariate models that combine biomarkers and other predictors in data from clinical trials or prospective cohort studies
• Integrative approaches for biomarkers and/or ‘omics’ to improve T2D risk prediction based on existing or new data
The past decade has seen fast-paced, technology-driven developments in the field of complex disease genomics. Implementation of the genome wide association study approach has revolutionized our understanding of the genetic underpinnings of T2D, identifying ~70 genetic risk loci for T2D. However, these alone explain less than 10% of overall T2D risk and do not accurately predict T2D.
In the past five years, clinical studies of T2D have increasingly focused on identifying novel serum biomarkers for T2D using cutting-edge ‘omics’ tools, such as metabolomics and proteomics. Metabolomics approaches in particular have been widely adapted to screen blood or other human tissues for changes in metabolites and low-molecular-weight biomolecules such as lipids, sugars, amino acids, organic acids, and nucleotides.
We welcome original and review papers describing current highlights, methods, and challenges in identifying, characterizing, and validating “Novel Biomarkers for Type 2 Diabetes”. We welcome both basic and clinical research articles focusing on experimental data and/or theory including (but not limited to) the following potential topics:
• Identification of biomarkers (e.g. genetic, metabolomic, or proteomic) associated with T2D and related traits
• Prediction of incident T2D and related traits using multivariate models that combine biomarkers and other predictors in data from clinical trials or prospective cohort studies
• Integrative approaches for biomarkers and/or ‘omics’ to improve T2D risk prediction based on existing or new data
Keywords: Biomarkers, diabetes, genetics, metabolomic
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
