Understanding Genetic Heterogeneity in Type 2 Diabetes by Delineating Physiological Phenotypes: SIRT1 and its Gene Network in Impaired Insulin Secretion

Proteomic analysis of diabetes genetic risk scores identifies complement C2 and neuropilin-2 as predictors of type 2 diabetes: the Atherosclerosis Risk in Communities (ARIC) Study

AIMS/HYPOTHESIS

Genetic predisposition to type 2 diabetes is well-established, and genetic risk scores (GRS) have been developed that capture heritable liabilities for type 2 diabetes phenotypes. However, the proteins through which these genetic variants influence risk have not been thoroughly investigated. This study aimed to identify proteins and pathways through which type 2 diabetes risk variants may influence pathophysiology.

METHODS

Using a proteomics data-driven approach in a discovery sample of 7241 White participants in the Atherosclerosis Risk in Communities Study (ARIC) cohort and a replication sample of 1674 Black ARIC participants, we interrogated plasma levels of 4870 proteins and four GRS of specific type 2 diabetes phenotypes related to beta cell function, insulin resistance, lipodystrophy, BMI/blood lipid abnormalities and a composite score of all variants combined.

RESULTS

Twenty-two plasma proteins were identified in White participants after Bonferroni correction. Of the 22 protein-GRS associations that were statistically significant, 10 were replicated in Black participants and all but one were directionally consistent. In a secondary analysis, 18 of the 22 proteins were found to be associated with prevalent type 2 diabetes and ten proteins were associated with incident type 2 diabetes. Two-sample Mendelian randomisation indicated that complement C2 may be causally related to greater type 2 diabetes risk (inverse variance weighted estimate: OR 1.65 per SD; p=7.0 × 10-3), while neuropilin-2 was inversely associated (OR 0.44 per SD; p=8.0 × 10-3).

CONCLUSIONS/INTERPRETATION

Identified proteins may represent viable intervention or pharmacological targets to prevent, reverse or slow type 2 diabetes progression, and further research is needed to pursue these targets.

A systems genomics approach to uncover patient-specific pathogenic pathways and proteins in ulcerative colitis

We describe a precision medicine workflow, the integrated single nucleotide polymorphism network platform (iSNP), designed to determine the mechanisms by which SNPs affect cellular regulatory networks, and how SNP co-occurrences contribute to disease pathogenesis in ulcerative colitis (UC). Using SNP profiles of 378 UC patients we map the regulatory effects of the SNPs to a human signalling network containing protein-protein, miRNA-mRNA and transcription factor binding interactions. With unsupervised clustering algorithms we group these patient-specific networks into four distinct clusters driven by PRKCB, HLA, SNAI1/CEBPB/PTPN1 and VEGFA/XPO5/POLH hubs. The pathway analysis identifies calcium homeostasis, wound healing and cell motility as key processes in UC pathogenesis. Using transcriptomic data from an independent patient cohort, with three complementary validation approaches focusing on the SNP-affected genes, the patient specific modules and affected functions, we confirm the regulatory impact of non-coding SNPs. iSNP identified regulatory effects for disease-associated non-coding SNPs, and by predicting the patient-specific pathogenic processes, we propose a systems-level way to stratify patients.

The Regulatory Effect of SIRT1 on Extracellular Microenvironment Remodeling

The sirtuins family is well known by its unique nicotinamide adenine dinucleotide (NAD⁺)-dependent deacetylase function. The most-investigated member of the family, Sirtuin 1 (SIRT1), accounts for deacetylating a broad range of transcription factors and coregulators, such as p53, the Forkhead box O (FOXO), and so on. It serves as a pivotal regulator in various intracellular biological processes, including energy metabolism, DNA damage response, genome stability maintenance and tumorigenesis. Although the most attention has been focused on its intracellular functions, the regulatory effect on extracellular microenvironment remodeling of SIRT1 has been recognized by researchers recently. SIRT1 can regulate cell secretion process and participate in glucose metabolism, neuroendocrine function, inflammation and tumorigenesis. Here, we review the advances in the understanding of SIRT1 on remodeling the extracellular microenvironment, which may provide new ideas for pathogenesis investigation and guidance for clinical treatment.

Metabolomics Signatures in Type 2 Diabetes: A Systematic Review and Integrative Analysis

OBJECTIVE

Metabolic signatures have emerged as valuable signaling molecules in the biochemical process of type 2 diabetes (T2D). To summarize and identify metabolic biomarkers in T2D, we performed a systematic review and meta-analysis of the associations between metabolites and T2D using high-throughput metabolomics techniques.

METHODS

We searched relevant studies from MEDLINE (PubMed), Embase, Web of Science, and Cochrane Library as well as Chinese databases (Wanfang, Vip, and CNKI) inception through 31 December 2018. Meta-analysis was conducted using STATA 14.0 under random effect. Besides, bioinformatic analysis was performed to explore molecule mechanism by MetaboAnalyst and R 3.5.2.

RESULTS

Finally, 46 articles were included in this review on metabolites involved amino acids, acylcarnitines, lipids, carbohydrates, organic acids, and others. Results of meta-analysis in prospective studies indicated that isoleucine, leucine, valine, tyrosine, phenylalanine, glutamate, alanine, valerylcarnitine (C5), palmitoylcarnitine (C16), palmitic acid, and linoleic acid were associated with higher T2D risk. Conversely, serine, glutamine, and lysophosphatidylcholine C18:2 decreased risk of T2D. Arginine and glycine increased risk of T2D in the Western countries subgroup, and betaine was negatively correlated with T2D in nested case-control subgroup. In addition, slight improvements in T2D prediction beyond traditional risk factors were observed when adding these metabolites in predictive analysis. Pathway analysis identified 17 metabolic pathways may alter in the process of T2D and metabolite-related genes were also enriched in functions and pathways associated with T2D.

CONCLUSIONS

Several metabolites and metabolic pathways associated with T2D have been identified, which provide valuable biomarkers and novel targets for prevention and drug therapy.

"H" for Heterogeneity in the Algorithm for Type 2 Diabetes Management

PURPOSE OF REVIEW

Genetic, socioeconomic and clinical features vary considerably among individuals with type 2 diabetes (T2D) influencing disease development, progression and response to therapy. Although a patient-centred approach to pharmacologic therapy of T2D is widely recommended, patients are often treated similarly, irrespective of the differences that may affect therapeutic response. Addressing the heterogeneity of T2D is a major task of diabetes research to lower the high rate of treatment failure as well as to reduce the risk of long-term complications.

RECENT FINDINGS

A pathophysiology-based clustering system seems the most promising to help in the stratification of diabetes in terms of complication risk and response to treatment. This urges for clinical studies looking at novel biomarkers related to the different metabolic pathways of T2D and able to inform about the therapeutic cluster of each patient. Here, we review the main settings of diabetes heterogeneity, to what extent it has been already addressed and the current gaps in knowledge towards a personalized therapeutic approach that considers the distinctive features of each patient.

Recent advances and perspectives in next generation sequencing application to the genetic research of type 2 diabetes

Type 2 diabetes (T2D) mellitus is a common complex disease that currently affects more than 400 million people worldwide and has become a global health problem. High-throughput sequencing technologies such as whole-genome and whole-exome sequencing approaches have provided numerous new insights into the molecular bases of T2D. Recent advances in the application of sequencing technologies to T2D research include, but are not limited to: (1) Fine mapping of causal rare and common genetic variants; (2) Identification of confident gene-level associations; (3) Identification of novel candidate genes by specific scoring approaches; (4) Interrogation of disease-relevant genes and pathways by transcriptional profiling and epigenome mapping techniques; and (5) Investigation of microbial community alterations in patients with T2D. In this work we review these advances in application of next-generation sequencing methods for elucidation of T2D pathogenesis, as well as progress and challenges in implementation of this new knowledge about T2D genetics in diagnosis, prevention, and treatment of the disease.

[The role of endogenous miRNAs in the development of cerebral aneurysms]

Cerebral aneurysms are characterized by pathological expansion and thinning of the wall of vessels on the brain base, which may lead to rupture and subarachnoid hemorrhage (SAH) that is a life-threatening condition. This dictates the need for identification of new biological markers that predict the presence of aneurysms and the risk of their rupture. In the last decade, the role of microRNAs (miRNAs), which are considered to be key regulators of biological processes, has been investigated. miRNAs have been shown to play a role in the development of aneurysms, but today there is little similar data. In this literature review, we analyze the existing data on the role of miRNAs in development, progression, and rupture of cerebral aneurysms. We describe the relationship between miRNA expression profiles and specific molecular and cellular processes leading to the development of aneurysms. Also, we discuss the potential clinical significance of miRNAs for predicting the risk of aneurysm rupture.

Exercise Training-Induced Changes in MicroRNAs: Beneficial Regulatory Effects in Hypertension, Type 2 Diabetes, and Obesity

MicroRNAs are small non-coding RNAs that regulate gene expression post-transcriptionally. They are involved in the regulation of physiological processes, such as adaptation to physical exercise, and also in disease settings, such as systemic arterial hypertension (SAH), type 2 diabetes mellitus (T2D), and obesity. In SAH, microRNAs play a significant role in the regulation of key signaling pathways that lead to the hyperactivation of the renin-angiotensin-aldosterone system, endothelial dysfunction, inflammation, proliferation, and phenotypic change in smooth muscle cells, and the hyperactivation of the sympathetic nervous system. MicroRNAs are also involved in the regulation of insulin signaling and blood glucose levels in T2D, and participate in lipid metabolism, adipogenesis, and adipocyte differentiation in obesity, with specific microRNA signatures involved in the pathogenesis of each disease. Many studies report the benefits promoted by exercise training in cardiovascular diseases by reducing blood pressure, glucose levels, and improving insulin signaling and lipid metabolism. The molecular mechanisms involved, however, remain poorly understood, especially regarding the participation of microRNAs in these processes. This review aimed to highlight microRNAs already known to be associated with SAH, T2D, and obesity, as well as their possible regulation by exercise training.

Role of telomeres and associated maintenance genes in Type 2 Diabetes Mellitus: A review

Type 2 Diabetes Mellitus (T2DM), a multifactorial complex disorder, is emerging as a major cause of morbidity, mortality and socio-economic burden across the world. Despite huge efforts in understanding genetics of T2DM, only ∼10% of the genetic factors have been identified so far. Telomere attrition, a natural phenomenon has recently emerged in understanding the pathophysiology of T2DM. It has been indicated that Telomeres and associated pathways might be the critical components in the disease etiology, though the mechanism(s) involved are not clear. Recent Genome Wide (GWAS) and Candidate Gene Case-Control Association Studies have also indicated an association of Telomere and associated pathways related genes with T2DM. Single Nucleotide Polymorphisms (SNPs) in the telomere maintenance genes: TERT, TERC, TNKS, CSNK2A2, TEP1, ACD, TRF1 and TRF2, have shown strong association with telomere attrition in T2DM and its pathophysiology, in these studies. However, the assessment has been made within limited ethnicities (Caucasians, Han Chinese cohort and Punjabi Sikhs from South Asia), warranting the study of such associations in different ethnic groups. Here, we propose the possible mechanisms, in the light of existing knowledge, to understand the association of T2DM with telomeres and associated pathways.