Expression quantitative trait analyses to identify causal genetic variants for type 2 diabetes susceptibility

The association study between changes in HbA1C with rs2250486 and rs67238751 genetic variants for SLC47A1 in newly diagnosed Iranian patients with type 2 diabetes mellitus: 6 months follow-up study

OBJECTIVES

One of the most well-known oral medications for the treatment of T2DM is metformin. Variants have been found in studies to be useful in detecting new genes connected to T2DM aetiology and affecting metformin's mechanism of action. In this research, we aimed to study two variations of the SLC47A1 gene; rs2250486 and rs67238751, in T2DM patients who had been taking metformin for the first 6 months after the diagnosis in the Iranian population for the first time.

DESIGN AND METHODS

A total of 200 individuals were recruited for the study. According to their glycosylated haemoglobin (HbA1c) levels, the patients were divided into two groups: responders (HbA1c levels were reduced by at least 1% after 6 months of metformin treatment.) and non-responders. DNA was extracted from whole blood and genotyped by Tetra ARMS PCR. High-performance liquid chromatography (HPLC) was used to measure HbA1c levels at the start of the treatment and again 6 months later.

RESULTS

rs2250486 variant in the dominant model reduces the HbA1C levels after 6 months of metformin treatment. In fact, when compared to the T/C + C/C genotypes, the T/T genotype improves HbA1C levels (p-value = .014). Furthermore, in the allelic model, the T allele improves HbA1C levels in comparison to the C allele (p-value = .008). After 6 months of metformin treatment, serum levels of HbA1C in responders were reduced significantly in both groups (T/T and T/C + C/C), (p-value = <.0001). However, the rs67238751 variant did not reveal a meaningful relationship with lower HbA1C levels in any of the models.

CONCLUSIONS

This study found that the rs2250486 variant could be associated with reducing HbA1C levels while the rs67238751 variant, had no relationship.

Iron and the Pathophysiology of Diabetes

High iron is a risk factor for type 2 diabetes mellitus (T2DM) and affects most of its cardinal features: decreased insulin secretion, insulin resistance, and increased hepatic gluconeogenesis. This is true across the normal range of tissue iron levels and in pathologic iron overload. Because of iron's central role in metabolic processes (e.g., fuel oxidation) and metabolic regulation (e.g., hypoxia sensing), iron levels participate in determining metabolic rates, gluconeogenesis, fuel choice, insulin action, and adipocyte phenotype. The risk of diabetes related to iron is evident in most or all tissues that determine diabetes phenotypes, with the adipocyte, beta cell, and liver playing central roles. Molecular mechanisms for these effects are diverse, although there may be integrative pathways at play. Elucidating these pathways has implications not only for diabetes prevention and treatment, but also for the pathogenesis of other diseases that are, like T2DM, associated with aging, nutrition, and iron.

A diet rich in fruit and whole grains is associated with a low risk of type 2 diabetes mellitus: findings from a case-control study in South China

OBJECTIVE

Various foods are associated with or protect against type 2 diabetes mellitus (T2DM). This study was to examine the associations of foods and food patterns with the risk of T2DM in South China.

DESIGN

Case-control study.

SETTING

The dietary patterns were identified by a principal components factor analysis. Univariable and multivariable conditional logistic regression analyses were used to analyse the associations between food groups and dietary patterns and the risk of T2DM.

PARTICIPANTS

A total of 384 patients with T2DM and 768 controls.

RESULTS

After adjustment for total energy intake, the standard intake of grains (228·3 ± 71·9 v. 238·8 ± 73·1 g/d, P = 0·025) and fruits (109 ± 90 v. 145 ± 108 g/d, P < 0·001) were lower in T2DM than in controls. Four dietary patterns were identified: (1) high light-coloured vegetables and low grains, (2) high fruits, (3) high red meat and low grains and (4) high dark-coloured vegetable. After adjustment for covariables, multivariable conditional logistic regression analyses showed significant dose-dependent inverse associations between total fruit intake, whole grains intake and the score of the high-fruit dietary pattern (all Pfor trend < 0·001) and the risk of T2DM. The adjusted OR (95 % CI) for T2DM comparing the extreme quartiles were 0·46 (0·29, 0·76) for total fruits, 0·48(0·31, 0·77) for whole grains and 0·42 (0·26, 0·68) for the high-fruit dietary pattern, respectively. Similar associations were observed for all subgroups of fruits (dark-colour and light-colour).

CONCLUSION

In South China, a diet rich in fruit and whole grains is associated with lower risk of T2DM.

Association of single nucleotide polymorphisms with insulin secretion, insulin sensitivity, and diabetes in women with a history of gestational diabetes mellitus

Background

This study investigated whether single nucleotide polymorphisms (SNPs) reported by previous genome-wide association studies (GWAS) to be associated with impaired insulin secretion, insulin resistance, and/or type 2 diabetes are associated with disposition index, the homeostasis model assessment of insulin resistance (HOMA-IR), and/or development of diabetes following a pregnancy complicated by gestational diabetes mellitus (GDM).

Methods

Seventy-two SNPs were genotyped in 374 women with previous GDM from Southern Sweden. An oral glucose tolerance test was performed 1–2 years postpartum, although data on the diagnosis of diabetes were accessible up to 5 years postpartum. HOMA-IR and disposition index were used to measure insulin resistance and secretion, respectively.

Results

The risk A-allele in the rs11708067 polymorphism of the adenylate cyclase 5 gene (ADCY5) was associated with decreased disposition index (beta = − 0.90, SE 0.38, p = 0.019). This polymorphism was an expression quantitative trait loci (eQTL) in islets for both ADCY5 and its antisense transcript. The risk C-allele in the rs2943641 polymorphism, near the insulin receptor substrate 1 gene (IRS1), showed a trend towards association with increased HOMA-IR (beta = 0.36, SE 0.18, p = 0.050), and the T-allele of the rs4607103 polymorphism, near the ADAM metallopeptidase with thrombospondin type 1 motif 9 gene (ADAMTS9), was associated with postpartum diabetes (OR = 2.12, SE 0.22, p = 0.00055). The genetic risk score (GRS) of the top four SNPs tested for association with the disposition index using equal weights was associated with the disposition index (beta = − 0.31, SE = 0.29, p = 0.00096). In addition, the GRS of the four SNPs studied for association with HOMA-IR using equal weights showed an association with HOMA-IR (beta = 1.13, SE = 0.48, p = 9.72874e−11). All analyses were adjusted for age, body mass index, and ethnicity.

Conclusions

This study demonstrated the genetic susceptibility of women with a history of GDM to impaired insulin secretion and sensitivity and, ultimately, to diabetes development.

Could personalised risk prediction for type 2 diabetes using polygenic risk scores direct prevention, enhance diagnostics, or improve treatment?

Over the past three decades, the number of people globally with diabetes mellitus has more than doubled. It is estimated that by 2030, 439 million people will be suffering from the disease, 90-95% of whom will have type 2 diabetes (T2D). In 2017, 5 million deaths globally were attributable to T2D, placing it in the top 10 global causes of death. Because T2D is a result of both genetic and environmental factors, identification of individuals with high genetic risk can help direct early interventions to prevent progression to more serious complications. Genome-wide association studies have identified ~400 variants associated with T2D that can be used to calculate polygenic risk scores (PRS). Although PRSs are not currently more accurate than clinical predictors and do not yet predict risk with equal accuracy across all ethnic populations, they have several potential clinical uses. Here, we discuss potential usages of PRS for predicting T2D and for informing and optimising interventions. We also touch on possible health inequality risks of PRS and the feasibility of large-scale implementation of PRS in clinical practice. Before PRSs can be used as a therapeutic tool, it is important that further polygenic risk models are derived using non-European genome-wide association studies to ensure that risk prediction is accurate for all ethnic groups. Furthermore, it is essential that the ethical, social and legal implications of PRS are considered before their implementation in any context.

An Integrative Phenotype-Genotype Approach Using Phenotypic Characteristics from the UAE National Diabetes Study Identifies HSD17B12 as a Candidate Gene for Obesity and Type 2 Diabetes

The United Arab Emirates National Diabetes and Lifestyle Study (UAEDIAB) has identified obesity, hypertension, obstructive sleep apnea, and dyslipidemia as common phenotypic characteristics correlated with diabetes mellitus status. As these phenotypes are usually linked with genetic variants, we hypothesized that these phenotypes share single nucleotide polymorphism (SNP)-clusters that can be used to identify causal genes for diabetes. Materials and We explored the National Human Genome Research Institute-European Bioinformatics Institute Catalog of Published Genome-Wide Association Studies (NHGRI-EBI GWAS) to list SNPs with documented association with the UAEDIAB-phenotypes as well as diabetes. The shared chromosomal regions affected by SNPs were identified, intersected, and searched for Enriched Ontology Clustering. The potential SNP-clusters were validated using targeted DNA next-generation sequencing (NGS) in two Emirati diabetic patients. RNA sequencing from human pancreatic islets was used to study the expression of identified genes in diabetic and non-diabetic donors. Eight chromosomal regions containing 46 SNPs were identified in at least four out of the five UAEDIAB-phenotypes. A list of 34 genes was shown to be affected by those SNPs. Targeted NGS from two Emirati patients confirmed that the identified genes have similar SNP-clusters. ASAH1, LRP4, FES, and HSD17B12 genes showed the highest SNPs rate among the identified genes. RNA-seq analysis revealed high expression levels of HSD17B12 in human islets and to be upregulated in type 2 diabetes (T2D) donors. Our integrative phenotype-genotype approach is a novel, simple, and powerful tool to identify clinically relevant potential biomarkers in diabetes. HSD17B12 is a novel candidate gene for pancreatic β-cell function.

The Transcription Factor Nfatc2 Regulates β-Cell Proliferation and Genes Associated with Type 2 Diabetes in Mouse and Human Islets

Human genome-wide association studies (GWAS) have shown that genetic variation at >130 gene loci is associated with type 2 diabetes (T2D). We asked if the expression of the candidate T2D-associated genes within these loci is regulated by a common locus in pancreatic islets. Using an obese F2 mouse intercross segregating for T2D, we show that the expression of ~40% of the T2D-associated genes is linked to a broad region on mouse chromosome (Chr) 2. As all but 9 of these genes are not physically located on Chr 2, linkage to Chr 2 suggests a genomic factor(s) located on Chr 2 regulates their expression in trans. The transcription factor Nfatc2 is physically located on Chr 2 and its expression demonstrates cis linkage; i.e., its expression maps to itself. When conditioned on the expression of Nfatc2, linkage for the T2D-associated genes was greatly diminished, supporting Nfatc2 as a driver of their expression. Plasma insulin also showed linkage to the same broad region on Chr 2. Overexpression of a constitutively active (ca) form of Nfatc2 induced β-cell proliferation in mouse and human islets, and transcriptionally regulated more than half of the T2D-associated genes. Overexpression of either ca-Nfatc2 or ca-Nfatc1 in mouse islets enhanced insulin secretion, whereas only ca-Nfatc2 was able to promote β-cell proliferation, suggesting distinct molecular pathways mediating insulin secretion vs. β-cell proliferation are regulated by NFAT. Our results suggest that many of the T2D-associated genes are downstream transcriptional targets of NFAT, and may act coordinately in a pathway through which NFAT regulates β-cell proliferation in both mouse and human islets.

Genome-wide association studies (GWAS) and linkage studies provide a powerful way to establish a causal connection between a gene locus and a physiological or pathophysiological phenotype. We wondered if candidate genes associated with type 2 diabetes in human populations, in addition to being causal for the disease, could also be intermediate traits in a pathway leading to disease. In addition, we wished to know if there were any regulatory loci that could coordinately drive the expression of these genes in pancreatic islets and thus complete a pathway; i.e. Driver → GWAS candidate expression → type 2 diabetes. Using data from a mouse intercross between a diabetes-susceptible and a diabetes-resistant mouse strain, we found that the expression of ~40% of >130 candidate GWAS genes genetically mapped to a hot spot on mouse chromosome 2. Using a variety of statistical methods, we identified the transcription factor Nfatc2 as the candidate driver. Follow-up experiments showed that overexpression of Nfatc2 does indeed affect the expression of the GWAS genes and regulates β-cell proliferation and insulin secretion. The work shows that in addition to being causal, GWAS candidate genes can be intermediate traits in a pathway leading to disease. Model organisms can be used to explore these novel causal pathways.

Genome-wide association study identifies pharmacogenomic loci linked with specific antihypertensive drug treatment and new-onset diabetes

We conducted a discovery genome-wide association study with expression quantitative trait loci (eQTL) annotation of new-onset diabetes (NOD) among European Americans, who were exposed to a calcium channel blocker-based strategy (CCB strategy) or a β-blocker-based strategy (β-blocker strategy) in the INternational VErapamil SR Trandolapril STudy. Replication of the top signal from the SNP*treatment interaction analysis was attempted in Hispanic and African Americans, and a joint meta-analysis was performed (total 334 NOD cases and 806 matched controls). PLEKHH2 rs11124945 at 2p21 interacted with antihypertensive exposure for NOD (meta-analysis p=5.3×10⁻⁸). rs11124945 G allele carriers had lower odds for NOD when exposed to the β-blocker strategy compared with the CCB strategy [OR=0.38 (0.24-0.60), p=4.0×10⁻⁵], while A/A homozygotes exposed to the β-blocker strategy had increased odds for NOD compared with the CCB strategy [OR=2.02 (1.39-2.92), p=2.0×10⁻⁴]. eQTL annotation of the 2p21 locus provides functional support for regulating gene expression.

A Genome-Wide mQTL Analysis in Human Adipose Tissue Identifies Genetic Variants Associated with DNA Methylation, Gene Expression and Metabolic Traits

Little is known about the extent to which interactions between genetics and epigenetics may affect the risk of complex metabolic diseases and/or their intermediary phenotypes. We performed a genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human adipose tissue of 119 men, where 592,794 single nucleotide polymorphisms (SNPs) were related to DNA methylation of 477,891 CpG sites, covering 99% of RefSeq genes. SNPs in significant mQTLs were further related to gene expression in adipose tissue and obesity related traits. We found 101,911 SNP-CpG pairs (mQTLs) in cis and 5,342 SNP-CpG pairs in trans showing significant associations between genotype and DNA methylation in adipose tissue after correction for multiple testing, where cis is defined as distance less than 500 kb between a SNP and CpG site. These mQTLs include reported obesity, lipid and type 2 diabetes loci, e.g. ADCY3/POMC, APOA5, CETP, FADS2, GCKR, SORT1 and LEPR. Significant mQTLs were overrepresented in intergenic regions meanwhile underrepresented in promoter regions and CpG islands. We further identified 635 SNPs in significant cis-mQTLs associated with expression of 86 genes in adipose tissue including CHRNA5, G6PC2, GPX7, RPL27A, THNSL2 and ZFP57. SNPs in significant mQTLs were also associated with body mass index (BMI), lipid traits and glucose and insulin levels in our study cohort and public available consortia data. Importantly, the Causal Inference Test (CIT) demonstrates how genetic variants mediate their effects on metabolic traits (e.g. BMI, cholesterol, high-density lipoprotein (HDL), hemoglobin A1c (HbA1c) and homeostatic model assessment of insulin resistance (HOMA-IR)) via altered DNA methylation in human adipose tissue. This study identifies genome-wide interactions between genetic and epigenetic variation in both cis and trans positions influencing gene expression in adipose tissue and in vivo (dys)metabolic traits associated with the development of obesity and diabetes.

Mapping adipose and muscle tissue expression quantitative trait loci in African Americans to identify genes for type 2 diabetes and obesity

Relative to European Americans, type 2 diabetes (T2D) is more prevalent in African Americans (AAs). Genetic variation may modulate transcript abundance in insulin-responsive tissues and contribute to risk; yet, published studies identifying expression quantitative trait loci (eQTLs) in African ancestry populations are restricted to blood cells. This study aims to develop a map of genetically regulated transcripts expressed in tissues important for glucose homeostasis in AAs, critical for identifying the genetic etiology of T2D and related traits. Quantitative measures of adipose and muscle gene expression, and genotypic data were integrated in 260 non-diabetic AAs to identify expression regulatory variants. Their roles in genetic susceptibility to T2D, and related metabolic phenotypes, were evaluated by mining GWAS datasets. eQTL analysis identified 1971 and 2078 cis-eGenes in adipose and muscle, respectively. Cis-eQTLs for 885 transcripts including top cis-eGenes CHURC1, USMG5, and ERAP2 were identified in both tissues. 62.1 % of top cis-eSNPs were within ±50 kb of transcription start sites and cis-eGenes were enriched for mitochondrial transcripts. Mining GWAS databases revealed association of cis-eSNPs for more than 50 genes with T2D (e.g. PIK3C2A, RBMS1, UFSP1), gluco-metabolic phenotypes (e.g. INPP5E, SNX17, ERAP2, FN3KRP), and obesity (e.g. POMC, CPEB4). Integration of GWAS meta-analysis data from AA cohorts revealed the most significant association for cis-eSNPs of ATP5SL and MCCC1 genes, with T2D and BMI, respectively. This study developed the first comprehensive map of adipose and muscle tissue eQTLs in AAs (publically accessible at https://mdsetaa.phs.wakehealth.edu ) and identified genetically regulated transcripts for delineating genetic causes of T2D, and related metabolic phenotypes.

Dermatological and musculoskeletal assessment of diabetic foot: A narrative review

AIMS

Diabetic Foot Syndrome (DFS) is the most costly and devastating complication of diabetes mellitus (DM), which early effective assessment can reduce the severity of complications including ulceration and amputations. This study aimed to review dermatological and musculoskeletal assessment of diabetic foot.

MATERIALS AND METHODS

In this review article, we searched for articles published between March 1, 1980 and July 28, 2015 in PubMed, Science Direct, Embase, Web of Science, and Scopus, for both English and non-English language articles with the following keywords: "Diabetic foot syndrome", "Ulceration", "Amputation", "Foot assessment", "Skin disorders" and "Musculoskeletal deformities".

RESULTS

In dermatological dimension, most studies focused on elucidated changes in skin temperature, color, hardiness and turgor as well as common skin disorders such as Diabetic Dermopathy (DD), Necrobiosis Lipoidica Diabeticorum (NLD) and Diabetic Bullae (DB), which are common in diabetic patients and have high potential for leading to limb-threatening problems such as ulceration and infection. In musculoskeletal dimension, most studies focused on range of motion and muscle strength, gait patterns and as well as foot deformities especially Charcot osteoarthropathy (COA), which is the most destructive musculoskeletal complication of diabetes.

CONCLUSION

DFS as a common condition in DM patients lead to ulceration and lower limb amputation frequently unless a prompt and comprehensive assessment was taken. So that dermatological and musculoskeletal assessments are usually neglected in primary health care, these assessments should be done frequently to reduce the high risk of serious complications.

Mining disease genes using integrated protein-protein interaction and gene-gene co-regulation information

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An eQTL-based gene–gene co-regulation network was constructed.

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We adopted a random walk with restart (RWR) algorithm to mine for Alzheimer-disease related genes.

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The integrated HPRD PPI and GGCRN network had faster convergence than using HPRD PPI alone.

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The integrated network also revealed new disease-related genes.

In humans, despite the rapid increase in disease-associated gene discovery, a large proportion of disease-associated genes are still unknown. Many network-based approaches have been used to prioritize disease genes. Many networks, such as the protein–protein interaction (PPI), KEGG, and gene co-expression networks, have been used. Expression quantitative trait loci (eQTLs) have been successfully applied for the determination of genes associated with several diseases. In this study, we constructed an eQTL-based gene–gene co-regulation network (GGCRN) and used it to mine for disease genes. We adopted the random walk with restart (RWR) algorithm to mine for genes associated with Alzheimer disease. Compared to the Human Protein Reference Database (HPRD) PPI network alone, the integrated HPRD PPI and GGCRN networks provided faster convergence and revealed new disease-related genes. Therefore, using the RWR algorithm for integrated PPI and GGCRN is an effective method for disease-associated gene mining.

Integrative network analysis reveals different pathophysiological mechanisms of insulin resistance among Caucasians and African Americans

Background

African Americans (AA) have more pronounced insulin resistance and higher insulin secretion than European Americans (Caucasians or CA) when matched for age, gender, and body mass index (BMI). We hypothesize that physiological differences (including insulin sensitivity [S_I]) between CAs and AAs can be explained by co-regulated gene networks in tissues involved in glucose homeostasis.

Methods

We performed integrative gene network analyses of transcriptomic data in subcutaneous adipose tissue of 99 CA and 37 AA subjects metabolically characterized as non-diabetic, with a range of S_I and BMI values.

Results

Transcripts negatively correlated with S_I in only the CA or AA subjects were enriched for inflammatory response genes and integrin-signaling genes, respectively. A sub-network (module) with TYROBP as a hub enriched for genes involved in inflammatory response (corrected p = 1.7E-26) was negatively correlated with S_I (r = −0.426, p = 4.95E-04) in CA subjects. S_I was positively correlated with transcript modules enriched for mitochondrial metabolism in both groups. Several S_I-associated co-expressed modules were enriched for genes differentially expressed between groups. Two modules involved in immune response to viral infections and function of adherens junction, are significantly correlated with S_I only in CAs. Five modules involved in drug/intracellular transport and oxidoreductase activity, among other activities, are correlated with S_I only in AAs. Furthermore, we identified driver genes of these race-specific S_I-associated modules.

Conclusions

S_I-associated transcriptional networks that were deranged predominantly in one ethnic group may explain the distinctive physiological features of glucose homeostasis among AA subjects.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-015-0078-0) contains supplementary material, which is available to authorized users.