‘Omics’‐driven discoveries in prevention and treatment of type 2 diabetes

Abstract

Glucose-based methods are currently gold standards for identifying individuals at risk of type 2 diabetes. Obviously, these methods only consider one of many pathologies of impaired glucose metabolism and they all suffer from a poor specificity as type 2 diabetes risk assessment tools. Recently, however, panels of multiple biomarkers reflecting several pre-diabetic pathologies have been developed. Their specificity and potentials for future risk stratification are discussed. As a multifactorial disorder type 2 diabetes calls for a multifactorial treatment approach targeting multiple but modifiable vascular risk factors. The same holds for pre-diabetic states and prevention hereof. In addition, type 2 diabetes and pre-diabetes show major heterogeneity between affected individuals in pathology, risk of organ damages, progression rate and responsiveness to treatment or prevention. Despite the heterogeneity and uniqueness of type 2 diabetes and pre-diabetes most affected individuals are currently offered interventions as if they all have the same disease or risk of disease and will respond similarly. The complex origin and course of type 2 diabetes combined with uniformity and non-specificity of current interventions may explain the high rate of treatment failures and the relative poor prognosis of many diabetes patients. Given this situation, the present review also explores the perspectives of selected examples within applied genomics and metagenomics for improving patient care by facilitating interventions tailored to specific subpopulations.

Diabetes and Risk of Arterial Stiffness: A Mendelian Randomization Analysis

“…Given that the current T2D susceptibility loci identified from GWAS are mostly associated with b-cell dysfunction (47,48), our findings were expected. However, the large meta-analysis GWAS focused on IR was spare, only several validated loci associated with IR have been reported.…”

Proteomic interrogation of the gut microbiota: potential clinical impact

“…At present, most holistic approaches for analysing the intestinal microbial community rely on 16S rRNA gene sequencing, a proven method to determine taxonomic composition of communities [2]. However, amplicon sequencing only provides information on who is present and not what they are doing.…”

Nutrigenomics Coupling with other OMICS Platform Enhance Personalized Health Care in Metabolic Disorders

“…T2D also known as hyperglycemia result from compromised insulin utilization (insulin resistance-IR) linked with insuffi cient compensatory insulin production. Long term consequence and comorbidities of T2D are nephropathy, neuropathy, retinopathy, hypertension, cardiovascular disease, dyslipidemia, cerebrovascular and peripheral vascular disease [1][2][3].…”

“…Since diets and genes changes one's health and susceptibility to diseases therefore, identifying T2D, as a polygenic, multifactorial disease can serve as a model for cancer, obesity, cardiovascular disease and other chronic diseases that are infl uenced by diet and environmrntal factors. Epidemiological studies showed that about 90% of T2D are as a result of fi ve major lifestyles which include diet, physical activity, smoking, obesity and alcohol consumption [1][2][3]. But among these diet is essentially given that T2D disease rooted in dysfunctional metabolism and energy fuel utilization.…”