Computational analyses of type 2 diabetes-associated loci identified by genome-wide association studies

Understanding the role of corneal biomechanics-associated genetic variants by bioinformatic analyses

PURPOSE

To analyze functions of corneal biomechanical properties (CBP)-related variants as corneal resistance factor (CRF) and corneal hysteresis (CH).

METHODS

Related single nucleotide polymorphisms (SNPs) and genes were identified from NHGRI-EBI GWAS catalog, GWASdb v2 and possible data in published studies. HaploReg v4.1 was used to find linkage SNPs. Functional annotations were performed by GWAVA, CADD and RegulomeDB. GTEx Portal database was used to find out expression quantitative trait locus (eQTL) association. Enrichr was used to annotate the function of GWAS gene and the associated signal pathway. STING (v11.0) database was utilized for protein interaction and network construction.

RESULTS

The integration of 302 CH-associated and 420 CRF-associated lead SNPs has produced 531 CBP-associated lead SNPs. A total of 5,324 proxy variants identified using the HaploReg v4.1 and lead SNPs were functionally annotated. Based on the threshold (CADD ≥ 10, GWAVA ≥ 0.4 and RegulomeDB < rank 3), 23 prioritized putative regulatory SNPs were identified. Eight prioritized eQTL variants (rs75203695, rs34861673, rs846766, rs11024102, rs1377416, rs3829492, rs9934438 and rs197912) were found with strong potential of CBP regulation. It was indicated that CBP-associated genes were significantly enriched in extracellular matrix receptor interaction pathway, closely related to the phenotype of corneal dystrophy and keratoconus. COL1A1, SMAD3, BMP4 and RUNX2 occupied the core position in the co-expression network.

CONCLUSIONS

Data integrative analysis can evaluate CBP variations and explore collagen and extracellular matrix pathways in CBP regulation, which is a promising tool to investigate biological process of corneal diseases.

Identification of EP300 as a Key Gene Involved in Antipsychotic-Induced Metabolic Dysregulation Based on Integrative Bioinformatics Analysis of Multi-Tissue Gene Expression Data

Antipsychotics (APs) are associated with weight gain and other metabolic abnormalities such as hyperglycemia, dyslipidemia and metabolic syndrome. This translational study aimed to uncover the underlying molecular mechanisms and identify the key genes involved in AP-induced metabolic effects. An integrative gene expression analysis was performed in four different mouse tissues (striatum, liver, pancreas and adipose) after risperidone or olanzapine treatment. The analytical approach combined the identification of the gene co-expression modules related to AP treatment, gene set enrichment analysis and protein-protein interaction network construction. We found several co-expression modules of genes involved in glucose and lipid homeostasis, hormone regulation and other processes related to metabolic impairment. Among these genes, EP300, which encodes an acetyltransferase involved in transcriptional regulation, was identified as the most important hub gene overlapping the networks of both APs. Then, we explored the genetically predicted EP300 expression levels in a cohort of 226 patients with first-episode psychosis who were being treated with APs to further assess the association of this gene with metabolic alterations. The EP300 expression levels were significantly associated with increases in body weight, body mass index, total cholesterol levels, low-density lipoprotein cholesterol levels and triglyceride concentrations after 6 months of AP treatment. Taken together, our analysis identified EP300 as a key gene in AP-induced metabolic abnormalities, indicating that the dysregulation of EP300 function could be important in the development of these side effects. However, more studies are needed to disentangle the role of this gene in the mechanism of action of APs.

FOXA1 Suppresses SATB1 Transcription and Inactivates the Wnt/β-Catenin Pathway to Alleviate Diabetic Nephropathy in a Mouse Model

OBJECTIVE

Diabetic nephropathy (DN) represents the most common diabetic complication that may lead to end-stage renal disease. This work focused on the effect of FOXA1 on the DN development and the molecular mechanism.

METHODS

A mouse model of DN was induced by high-fat diets and streptozotocin. The concentrations of blood glucose and urinary protein in mice, and the pathological changes in mouse kidney tissues were determined. A podocyte cell line MPC-5 was treated with high glucose (HG) to mimic a DN-like condition in vitro. FOXA1 and SATB1 were overexpressed in HG-treated MPC-5 cells and in DN mice to explore their effects on cell proliferation and apoptosis, and on pathological changes in mouse kidney tissues. The binding relationship between FOXA1 and STAB1 was predicted and validated. Activation of the Wnt/β-catenin pathway was detected.

RESULTS

FOXA1 was poorly expressed in the kidney tissues of DN mice. Overexpression of FOXA1 reduced the concentrations of fasting blood glucose and 24-h urinary protein in mice. It also suppressed the accumulation of glomerular mesangial matrix and hyperplasia of glomerular basement membrane, and reduced collagen deposition and interstitial fibrosis in mouse kidney. Also, FOXA1 reduced HG-induced apoptosis of MPC-5 cells. FOXA1 bound to the promoter region of SATB1 for transcription suppression. Overexpression of SATB1 activated the Wnt/β-catenin pathway and blocked the protective roles of FOXA1 in DN mice and in HG-treated MPC-5 cells.

CONCLUSION

This study demonstrated that FOXA1 transcriptionally suppresses SATB1 expression and inactivates the Wnt/β-catenin signaling pathway, thereby inhibiting podocyte apoptosis and DN progression.

Clinical and genetic analysis of two wolfram syndrome families with high occurrence of wolfram syndrome and diabetes type II: a case report

Background

Mutations of the WFS1 gene are responsible for most cases of Wolfram syndrome (WS), a rare, recessively inherited neurodegenerative disorder characterized by juvenile-onset non-autoimmune diabetes mellitus and optic atrophy. Variants of WFS1 are also associated with non-syndromic hearing loss and type-2 diabetes mellitus (T2DM). Our study adds to literature significant associations between WS and T2DM.

Case presentation

In this study, we analyzed the clinical and genetic data of two families with high prevalence of WS and T2DM. Genetic linkage analysis and DNA sequencing were exploited to identify pathogenic variants. One novel pathogenic variant (c.2243-2244insC) and one known pathogenic (c.1232_1233delCT) (frameshift) variant were identified in exon eight of WFS1 gene.

Conclusions

The mutational and phenotypic spectrum of WS is broadened by our report of novel WFS1 mutation. Our results reveal the value of molecular analysis of WFS1 in the improvement of clinical diagnostics for WS. This study also confirms the role of WFS1 in T2DM.

Computational and functional analyses of T2D GWAS SNPs for transcription factor binding

Genome-wide association studies (GWASs) have successfully identified numerous non-coding genetic variants for type 2 diabetes (T2D), but the functional roles underlying these non-coding variants remain largely unknown. The effects of T2D GWAS lead SNPs on transcriptional factors binding motifs were firstly analyzed via JASPAR, followed by functional validations including dual-luciferase reporter assays, biotin-based DNA pull-down assays, real-time quantitative PCR, and western blotting. The results showed that GWAS SNP rs4430796 conferred T allele specific transcriptional enhancer activity via a PAX6 binding element, and upregulated the expression of HNF1B. GWAS SNP rs4607103 showed a bidirectional modulation of ADAMTS9-AS2 and ADAMTS9 by TCF7L2 in a T allele-specific manner. GWAS SNP rs849135 conferred C allele-specific bidirectional transcriptional enhancer activity via a CREB1 binding element. Our findings have uncovered the functional mechanisms of three T2D GWAS SNPs via affecting the binding of transcription factors, providing new insights into the genetics and molecular pathogenesis of T2D.

Crosstalk of Genetic Variants, Allele-Specific DNA Methylation, and Environmental Factors for Complex Disease Risk

Over the past decades, genome-wide association studies (GWAS) have identified thousands of phenotype-associated DNA sequence variants for potential explanations of inter-individual phenotypic differences and disease susceptibility. However, it remains a challenge for translating the associations into causative mechanisms for complex diseases, partially due to the involved variants in the noncoding regions and the inconvenience of functional studies in human population samples. So far, accumulating evidence has suggested a complex crosstalk among genetic variants, allele-specific binding of transcription factors (ABTF), and allele-specific DNA methylation patterns (ASM), as well as environmental factors for disease risk. This review aims to summarize the current studies regarding the interactions of the aforementioned factors with a focus on epigenetic insights. We present two scenarios of single nucleotide polymorphisms (SNPs) in coding regions and non-coding regions for disease risk, via potentially impacting epigenetic patterns. While a SNP in a coding region may confer disease risk via altering protein functions, a SNP in non-coding region may cause diseases, via SNP-altering ABTF, ASM, and allele-specific gene expression (ASE). The allelic increases or decreases of gene expression are key for disease risk during development. Such ASE can be achieved via either a "SNP-introduced ABTF to ASM" or a "SNP-introduced ASM to ABTF." Together with our additional in-depth review on insulator CTCF, we are convinced to propose a working model that the small effect of a SNP acts through altered ABTF and/or ASM, for ASE and eventual disease outcome (named as a "SNP intensifier" model). In summary, the significance of complex crosstalk among genetic factors, epigenetic patterns, and environmental factors requires further investigations for disease susceptibility.

Epigenetics of chronic inflammatory diseases

Chronic, noncommunicable, and inflammation-associated diseases remain the largest cause of morbidity and mortality globally and within the United States. This is mainly due to our limited understanding of the molecular mechanisms that underlie these complex pathologies. The available evidence indicates that studies of epigenetics (traditionally defined as the heritable changes to gene expression that are independent of changes to DNA) are significantly advancing our knowledge of these inflammatory conditions. This review will focus on epigenetic studies of three diseases, that are among the most burdensome globally: cardiovascular disease, the number one cause of deaths worldwide, type 2 diabetes and, Alzheimer’s disease. The current status of epigenetic research, including the ability to predict disease risk, and key pathophysiological defects are discussed. The significance of defining the contribution of epigenetic defects to nonresolving inflammation and aging, each associated with these diseases, is highlighted, as these are likely to provide new insights into inflammatory disease pathogenesis.

Ethnicity-Specific Association Between Ghrelin Leu72Met Polymorphism and Type 2 Diabetes Mellitus Susceptibility: An Updated Meta-Analysis

Background: The Leu72Met polymorphism of ghrelin gene has been associated with genetic predisposition to type 2 diabetes mellitus (T2DM), while conclusions remain conflicting. Hence, we performed this updated meta-analysis to clarify the association between Leu72Met polymorphism and T2DM susceptibility. Methods: Six electronic databases were consulted for articles published before 1 January, 2018. Pooled odds ratios (OR) and 95% confidence intervals (CI) were calculated under five genetic models to assess this association. We used I ²-test and Q statistics to measure heterogeneity across the included studies. Subgroup analyses and publication bias were also performed. Results: Thirteen case-control studies involving 4720 T2DM patients and 4206 controls were included in this meta-analysis. The overall results using fixed-effects models showed that Leu72Met polymorphism was significantly associated with an increased risk of T2DM under homozygous model (OR = 1.307, 95%CI 1.001-1.705, p = 0.049). Further subgroup analyses stratified by ethnicity revealed that the risk for T2DM was only increased in Asians (homozygous model: OR = 1.335, 95%CI 1.014-1.758, p = 0.040), while decreased in Caucasians (dominant model: OR = 0.788, 95%CI 0.635-0.978, p = 0.030; heterozygous model: OR = 0.779, 95%CI 0.626-0.969, p = 0.025; allelic model: OR = 0.811, 95%CI 0.661-0.995, p = 0.045). Funnel plots were basically symmetrical, and all p-values of Egger's test under five genetic models were >0.050, which indicated no evidence of publication bias. Conclusions: Our results demonstrate that the Leu72Met polymorphism of ghrelin gene may be protective against T2DM in Caucasians, while predisposing to T2DM in Asians.

Computational analyses of obesity associated loci generated by genome-wide association studies

OBJECTIVES

Genome-wide association studies (GWASs) have discovered associations of numerous SNPs and genes with obesity. However, the underlying molecular mechanisms through which these SNPs and genes affect the predisposition to obesity remain not fully understood. Aims of our study are to comprehensively characterize obesity GWAS SNPs and genes through computational approaches.

METHODS

For obesity GWAS identified SNPs, functional annotation, effects on miRNAs binding and impact on protein phosphorylation were performed via RegulomeDB and 3DSNP, miRNASNP, and the PhosSNP 1.0 database, respectively. For obesity associated genes, protein-protein interaction network construction, gene ontology and pathway enrichment analyses were performed by STRING, PANTHER and STRING, respectively.

RESULTS

A total of 445 SNPs are significantly associated with obesity related phenotypes at threshold P < 5×10-8. A number of SNPs were eQTLs for obesity associated genes, some SNPs located at binding sites of obesity related transcription factors. SNPs that might affect miRNAs binding and protein phosphorylation were identified. Protein-protein interaction network analysis identified the highly-interconnected "hub" genes. Obesity associated genes mainly involved in metabolic process and catalytic activity, and significantly enriched in 15 signal pathways.

CONCLUSIONS

Our results provided the targets for follow-up experimental testing and further shed new light on obesity pathophysiology.

Proteasomal degradation of the histone acetyl transferase p300 contributes to beta-cell injury in a diabetes environment

In type 2 diabetes, amyloid oligomers, chronic hyperglycemia, lipotoxicity, and pro-inflammatory cytokines are detrimental to beta-cells, causing apoptosis and impaired insulin secretion. The histone acetyl transferase p300, involved in remodeling of chromatin structure by epigenetic mechanisms, is a key ubiquitous activator of the transcriptional machinery. In this study, we report that loss of p300 acetyl transferase activity and expression leads to beta-cell apoptosis, and most importantly, that stress situations known to be associated with diabetes alter p300 levels and functional integrity. We found that proteasomal degradation is the mechanism subserving p300 loss in beta-cells exposed to hyperglycemia or pro-inflammatory cytokines. We also report that melatonin, a hormone produced in the pineal gland and known to play key roles in beta-cell health, preserves p300 levels altered by these toxic conditions. Collectively, these data imply an important role for p300 in the pathophysiology of diabetes.

Proteomic analysis and prediction of amino acid variations that influence protein posttranslational modifications

Accumulative studies have indicated that amino acid variations through changing the type of residues of the target sites or key flanking residues could directly or indirectly influence protein posttranslational modifications (PTMs) and bring about a detrimental effect on protein function. Computational mutation analysis can greatly narrow down the efforts on experimental work. To increase the utilization of current computational resources, we first provide an overview of computational prediction of amino acid variations that influence protein PTMs and their functional analysis. We also discuss the challenges that are faced while developing novel in silico approaches in the future. The development of better methods for mutation analysis-related protein PTMs will help to facilitate the development of personalized precision medicine.

Functional annotation of Alzheimer's disease associated loci revealed by GWASs

Genome-wide association studies (GWASs) discovered a number of SNPs and genes associated with Alzheimer's disease (AD). However, how these SNPs and genes influence the liability to AD is not fully understood. We deployed computational approaches to explore the function and action mechanisms of AD -related SNPs and genes identified by GWASs, including the effects of 195 GWAS lead SNPs and 338 proxy SNPs on miRNAs binding and protein phosphorylation, their RegulomeDB and 3DSNP scores, and gene ontology, pathway enrichment and protein-protein interaction network of 126 AD-associated genes. Our computational analysis identified 6 lead SNPs (rs10119, rs1048699, rs148763909, rs610932, rs6857 and rs714948) and 2 proxy SNPs (rs12539172 and rs2847655) that potentially impacted the miRNA binding. Lead SNP rs2296160 and proxy SNPs rs679620 and rs2228145 were identified as PhosSNPs potentially influencing protein phosphorylation. AD-associated genes showed enrichment of “regulation of beta-amyloid formation”, “regulation of neurofibrillary tangle assembly”, “leukocyte mediated immunity” and “protein-lipid complex assembly” signaling pathway. Protein-protein interaction network and functional module analyses identified highly-interconnected “hub” genes (APOE, PICALM, BIN1, ABCA7, CD2AP, CLU, CR1, MS4A4E and MS4A6A) and bottleneck genes (APOE, TOMM40, NME8, PICALM, CD2AP, ZCWPW1, FAM180B, GAB2 and PTK2B) that created three tight subnetworks. Our results provided the targets for further experimental assessment and further insight on AD pathophysiology.