Type 2 diabetes susceptibility genes on chromosome 1q21-24

Dual-specificity phosphatase 12 attenuates oxidative stress injury and apoptosis in diabetic cardiomyopathy via the ASK1-JNK/p38 signaling pathway

Diabetic cardiomyopathy (DCM) is ventricular dysfunction that occurs in patients with diabetes mellitus (DM), independent of recognized risk factors, such as coronary artery disease, hypertension, and valvular heart disease. Dual-specificity phosphatase 12 (DUSP12) is a dual-specificity phosphatase expressed in all tissues. Genome-wide linkage studies have found an association between DUSP12 and type 2 diabetes (T2D). However, the role of DUSP12 in DCM remains largely unknown. Ubiquitously expressed DUSP12 is involved in nonalcoholic fatty liver disease, bacterial infection, and myocardial hypertrophy and plays a critical role in tumorigenesis. Herein, we observed an increased expression of DUSP12 in a hyperglycemia cell model and a high-fat diet (HFD) mouse model. Heart-specific DUSP12-deficient mice showed severe cardiac dysfunction and remodeling induced by an HFD. DUSP12 deficiency exacerbated oxidative stress injury and apoptosis, whereas DUSP12 overexpression had the opposite effect. At the molecular level, DUSP12 physically bound to apoptotic signal-regulated kinase 1 (ASK1), promoted its dephosphorylation, and inhibited its action on c-Jun N-terminal kinase and p38 mitogen-activated protein kinase. Rescue experiments have shown that oxidative stress injury and apoptosis, exacerbated by DUSP12 deficiency, are alleviated by ASK1 inhibition. Therefore, we consider DUSP12 an important signaling pathway in DCM.

Association between functional genetic variants in retinoid X receptor-α/γ and the risk of gestational diabetes mellitus in a southern Chinese population

To clarify the effect of retinoid X receptor-α/γ (RXR-α/γ) genes functional genetic variants (RXR-α rs4842194 G>A, RXR-γ rs100537 A>G and rs2134095 T>C) on the risk of gestational diabetes mellitus (GDM), a case–control study with 573 GDM patients and 740 pregnant women with normal glucose tolerance was performed in Guangxi area of China. An odds ratio (OR) with its corresponding 95% confidence interval (CI) was used to assess the strengths of the association between genetic variation and GDM. After adjustment of age and pre-BMI, the logistic regression analysis showed that the rs2134095 was significantly associated with GDM risk (CC vs. TT/TC: adjusted OR = 0.71, 95% CI = 0.56–0.90) in all subjects, and this result remained highly significant after Bonferroni’s correction for multiple testing (P=0.004). The stratified analysis showed that rs2134095 was significantly associated with the risk of GDM among age > 30 years (adjusted OR = 0.61, 95% CI = 0.39–0.97), BMI > 22 kg/m² (adjusted OR = 0.46, 95% CI = 0.30–0.70), systolic blood pressure (SBP) > 120 mmHg (adjusted OR = 1.96, 95% CI = 1.14–3.36), glycosylated hemoglobin A1c (HbA1c) < 6.5% (adjusted OR = 1.41, 95% CI = 1.11–1.78), TG ≤ 1.7 mmol/l (adjusted OR = 2.57, 95% CI = 1.45–4.53), TC ≤ 5.18 mmol/l (adjusted OR = 1.58, 95% CI = 1.13–2.22), high-density lipoprotein cholesterol (HDL-c) ≤ 1.5 mmol/l (adjusted OR = 1.70, 95% CI = 1.16–2.49) and low-density lipoprotein cholesterol (LDL-c) > 3.12 mmol/l (adjusted OR = 1.47, 95% CI = 1.08–2.00) subjects, under the recessive genetic model. We also found that rs2134095 interacted with age (P_interaction=0.039), pre-BMI (P_interaction=0.040) and TG (P_interaction=0.025) influencing individual’s genetic susceptibility to GDM. The rs2134095 T>C is significantly associated with the risk of GDM by effect of a single locus and/or complex joint gene–gene and gene–environment interactions. Larger sample-size and different population studies are required to confirm the findings.

Natural products as modulators of the nuclear receptors and metabolic sensors LXR, FXR and RXR

Nuclear receptors (NRs) represent attractive targets for the treatment of metabolic syndrome-related diseases. In addition, natural products are an interesting pool of potential ligands since they have been refined under evolutionary pressure to interact with proteins or other biological targets. This review aims to briefly summarize current basic knowledge regarding the liver X (LXR) and farnesoid X receptors (FXR) that form permissive heterodimers with retinoid X receptors (RXR). Natural product-based ligands for these receptors are summarized and the potential of LXR, FXR and RXR as targets in precision medicine is discussed.

Identification of Four Mouse Diabetes Candidate Genes Altering β-Cell Proliferation

Beta-cell apoptosis and failure to induce beta-cell regeneration are hallmarks of type 2-like diabetes in mouse models. Here we show that islets from obese, diabetes-susceptible New Zealand Obese (NZO) mice, in contrast to diabetes-resistant C57BL/6J (B6)-ob/ob mice, do not proliferate in response to an in-vivo glucose challenge but lose their beta-cells. Genome-wide RNAseq based transcriptomics indicated an induction of 22 cell cycle-associated genes in B6-ob/ob islets that did not respond in NZO islets. Of all genes differentially expressed in islets of the two strains, seven mapped to the diabesity QTL Nob3, and were hypomorphic in either NZO (Lefty1, Apoa2, Pcp4l1, Mndal, Slamf7, Pydc3) or B6 (Ifi202b). Adenoviral overexpression of Lefty1, Apoa2, and Pcp4l1 in primary islet cells increased proliferation, whereas overexpression of Ifi202b suppressed it. We conclude that the identified genes in synergy with obesity and insulin resistance participate in adaptive islet hyperplasia and prevention from severe diabetes in B6-ob/ob mice.

Complex genetic determinants contribute to an inherent susceptibility of type 2 diabetes, characterized by insulin resistance, a dysfunction and loss of insulin-producing beta-cells. We compared the islet expression profile and the genome of two obese mouse strains that react differently when receiving a caloric enriched diet. One mouse (B6-ob/ob) is able to compensate by increasing the beta-cell mass, whereas the other (NZO) develops hyperglycemia due to beta-cells loss. Focusing on differentially expressed genes that are located in susceptibility locus for diabetes and obesity on chromosome 1 we found 6 genes to be only expressed in islets of the diabetes-resistant mouse and one to be exclusively present in islets of the diabetes-prone mouse. Among these, the overexpression of 3 genes (Lefty1, Apoa2, and Pcp4l1) increased and that of Ifi202b decreased the division of primary islet cells. In summary, our data provide new insights into genes inducing or inhibiting islet size and thereby participate in the pathogenesis of type 2 diabetes.

Functional validation of GWAS gene candidates for abnormal liver function during zebrafish liver development

Genome-wide association studies (GWAS) have revealed numerous associations between many phenotypes and gene candidates. Frequently, however, further elucidation of gene function has not been achieved. A recent GWAS identified 69 candidate genes associated with elevated liver enzyme concentrations, which are clinical markers of liver disease. To investigate the role of these genes in liver homeostasis, we narrowed down this list to 12 genes based on zebrafish orthology, zebrafish liver expression and disease correlation. To assess the function of gene candidates during liver development, we assayed hepatic progenitors at 48 hours post fertilization (hpf) and hepatocytes at 72 hpf using in situ hybridization following morpholino knockdown in zebrafish embryos. Knockdown of three genes (pnpla3, pklr and mapk10) decreased expression of hepatic progenitor cells, whereas knockdown of eight genes (pnpla3, cpn1, trib1, fads2, slc2a2, pklr, mapk10 and samm50) decreased cell-specific hepatocyte expression. We then induced liver injury in zebrafish embryos using acetaminophen exposure and observed changes in liver toxicity incidence in morphants. Prioritization of GWAS candidates and morpholino knockdown expedites the study of newly identified genes impacting liver development and represents a feasible method for initial assessment of candidate genes to instruct further mechanistic analyses. Our analysis can be extended to GWAS for additional disease-associated phenotypes.

Association between the APOA2 promoter polymorphism and body weight in Mediterranean and Asian populations: replication of a gene-saturated fat interaction

OBJECTIVE

The APOA2 gene has been associated with obesity and insulin resistance (IR) in animal and human studies with controversial results. We have reported an APOA2-saturated fat interaction determining body mass index (BMI) and obesity in American populations. This work aims to extend our findings to European and Asian populations.

METHODS

Cross-sectional study in 4602 subjects from two independent populations: a high-cardiovascular risk Mediterranean population (n = 907 men and women; aged 67 ± 6 years) and a multiethnic Asian population (n = 2506 Chinese, n = 605 Malays and n = 494 Asian Indians; aged 39 ± 12 years) participating in a Singapore National Health Survey. Anthropometric, clinical, biochemical, lifestyle and dietary variables were determined. Homeostasis model assessment of insulin resistance was used in Asians. We analyzed gene-diet interactions between the APOA2 -265T>C polymorphism and saturated fat intake (<or ≥ 22 g per day) on anthropometric measures and IR.

RESULTS

Frequency of CC (homozygous for the minor allele) subjects differed among populations (1-15%). We confirmed a recessive effect of the APOA2 polymorphism and replicated the APOA2-saturated fat interaction on body weight. In Mediterranean individuals, the CC genotype was associated with a 6.8% greater BMI in those consuming a high (P = 0.018), but not a low (P = 0.316) saturated fat diet. Likewise, the CC genotype was significantly associated with higher obesity prevalence in Chinese and Asian Indians only, with a high-saturated fat intake (P = 0.036). We also found a significant APOA2-saturated fat interaction in determining IR in Chinese and Asian Indians (P = 0.026).

CONCLUSION

The influence of the APOA2 -265T>C polymorphism on body-weight-related measures was modulated by saturated fat in Mediterranean and Asian populations.

Meta-analysis of inter-species liver co-expression networks elucidates traits associated with common human diseases

Co-expression networks are routinely used to study human diseases like obesity and diabetes. Systematic comparison of these networks between species has the potential to elucidate common mechanisms that are conserved between human and rodent species, as well as those that are species-specific characterizing evolutionary plasticity. We developed a semi-parametric meta-analysis approach for combining gene-gene co-expression relationships across expression profile datasets from multiple species. The simulation results showed that the semi-parametric method is robust against noise. When applied to human, mouse, and rat liver co-expression networks, our method out-performed existing methods in identifying gene pairs with coherent biological functions. We identified a network conserved across species that highlighted cell-cell signaling, cell-adhesion and sterol biosynthesis as main biological processes represented in genome-wide association study candidate gene sets for blood lipid levels. We further developed a heterogeneity statistic to test for network differences among multiple datasets, and demonstrated that genes with species-specific interactions tend to be under positive selection throughout evolution. Finally, we identified a human-specific sub-network regulated by RXRG, which has been validated to play a different role in hyperlipidemia and Type 2 diabetes between human and mouse. Taken together, our approach represents a novel step forward in integrating gene co-expression networks from multiple large scale datasets to leverage not only common information but also differences that are dataset-specific.

Two important aspects of drug development are drug target identification and biomarker discovery for early disease detection, disease progression, drug efficacy and drug toxicity, etc. Recently, many single nucleotide polymorphisms (SNPs) associated with human diseases are discovered through large genome-wide association studies (GWAS). However, it is still largely unclear how these candidate SNPs may cause human diseases. The ultimate aim of this paper is to put these GWAS candidate SNPs and their associated genes into a network context to understand their mechanism of action in human diseases. In addition to large-scale human data sets that are often heterogeneous in terms of genetic and environmental factors, many high quality data sets in rodents exist and are frequently used to model human diseases. To leverage such information, we developed a method for combining and contrasting gene networks between human and rodents, specifically to elucidate how GWAS candidate SNPs may contribute to human diseases. By identifying mechanisms that are conserved or divergent between human and rodents, we can also predict which disease causal genes can be studied using rodent models and which ones may not.

Retinoid X receptor heterodimer variants and cardiovascular risk factors

Nuclear receptors are transcription factors that can be activated by specific ligands. Recent progress has shown that retinoid X receptor (RXR) and its heterodimerization partners, including peroxisome proliferator-activated receptors, regulate many important genes involved in energy homeostasis and atherosclerosis, and should be promising therapeutic targets of metabolic syndrome. RXR heterodimers regulate a number of complex cellular processes, and genetic studies of RXR heterodimers have provided important clinical information in addition to knowledge gained from basic research. Genetic variants of RXR heterodimers were screened and investigated, and some variants were shown to have a considerable impact on metabolic disorders, including phenotypic components of familial combined hyperlipidemia. The combined efforts of basic and clinical science regarding nuclear receptors have achieved significant progress in unraveling the inextricably linked control system of energy expenditure, lipid and glucose homeostasis, inflammation, and atherosclerosis.This review summarizes the current understanding regarding RXR heterodimers based on their human genetic variants, which will provide new clues to uncover the background of multifactorial disease, such as metabolic syndrome or familial combined hyperlipidemia.

Genome-wide linkage and admixture mapping of type 2 diabetes in African American families from the American Diabetes Association GENNID (Genetics of NIDDM) Study Cohort

OBJECTIVE

We used a single nucleotide polymorphism (SNP) map in a large cohort of 580 African American families to identify regions linked to type 2 diabetes, age of type 2 diabetes diagnosis, and BMI.

RESEARCH DESIGN AND METHODS

After removing outliers and problematic samples, we conducted linkage analysis using 5,914 SNPs in 1,344 individuals from 530 families. Linkage analysis was conducted using variance components for type 2 diabetes, age of type 2 diabetes diagnosis, and BMI and nonparametric linkage analyses. Ordered subset analyses were conducted ranking on age of type 2 diabetes diagnosis, BMI, waist circumference, waist-to-hip ratio, and amount of European admixture. Admixture mapping was conducted using 4,486 markers not in linkage disequilibrium.

RESULTS

The strongest signal for type 2 diabetes (logarithm of odds [LOD] 4.53) was a broad peak on chromosome 2, with weaker linkage to age of type 2 diabetes diagnosis (LOD 1.82). Type 2 diabetes and age of type 2 diabetes diagnosis were linked to chromosome 13p (3-22 cM; LOD 2.42 and 2.46, respectively). Age of type 2 diabetes diagnosis was linked to 18p (66 cM; LOD 2.96). We replicated previous reports on chromosome 7p (79 cM; LOD 2.93). Ordered subset analysis did not overlap with linkage of unselected families. The best admixture score was on chromosome 12 (90 cM; P = 0.0003).

CONCLUSIONS

The linkage regions on chromosomes 7 (27-78 cM) and 18p overlap prior reports, whereas regions on 2p and 13p linkage are novel. Among potential candidate genes implicated are TCF7L1, VAMP5, VAMP8, CDK8, INSIG2, IPF1, PAX8, IL18R1, members of the IL1 and IL1 receptor families, and MAP4K4. These studies provide a complementary approach to genome-wide association scans to identify causative genes for African American diabetes.

Lack of association between PKLR rs3020781 and NOS1AP rs7538490 and type 2 diabetes, overweight, obesity and related metabolic phenotypes in a Danish large-scale study: case-control studies and analyses of quantitative traits

Background

Several studies in multiple ethnicities have reported linkage to type 2 diabetes on chromosome 1q21-25. Both PKLR encoding the liver pyruvate kinase and NOS1AP encoding the nitric oxide synthase 1 (neuronal) adaptor protein (CAPON) are positioned within this chromosomal region and are thus positional candidates for the observed linkage peak. The C-allele of PKLR rs3020781 and the T-allele of NOS1AP rs7538490 are reported to strongly associate with type 2 diabetes in various European-descent populations comprising a total of 2,198 individuals with a combined odds ratio (OR) of 1.33 [1.16–1.54] and 1.53 [1.28–1.81], respectively. Our aim was to validate these findings by investigating the impact of the two variants on type 2 diabetes and related quantitative metabolic phenotypes in a large study sample of Danes. Further, we intended to expand the analyses by examining the effect of the variants in relation to overweight and obesity.

Methods

PKLR rs3020781 and NOS1AP rs7538490 were genotyped, using TaqMan allelic discrimination, in a combined study sample comprising a total of 16,801 and 16,913 individuals, respectively. The participants were ascertained from four different study groups; the population-based Inter99 cohort (n_PKLR = 5,962, n_NOS1AP = 6,008), a type 2 diabetic patient group (n_PKLR = 1,873, n_NOS1AP = 1,874) from Steno Diabetes Center, a population-based study sample (n_PKLR = 599, n_NOS1AP = 596) from Steno Diabetes Center and the ADDITION Denmark screening study cohort (n_PKLR = 8,367, n_NOS1AP = 8,435).

Results

In case-control studies we evaluated the potential association between rs3020781 and rs7538490 and type 2 diabetes and obesity. No significant associations were observed for type 2 diabetes (rs3020781: p_AF = 0.49, OR = 1.02 [0.96–1.10]; rs7538490: p_AF = 0.84, OR = 0.99 [0.93–1.06]). Neither did we show association with overweight or obesity. Additionally, the PKLR and the NOS1AP genotypes were demonstrated not to have a major influence on diabetes-related quantitative metabolic phenotypes.

Conclusion

We failed to provide evidence of an association between PKLR rs3020781 and NOS1AP rs7538490 and type 2 diabetes, overweight, obesity or related quantitative metabolic phenotypes in large-scale studies of Danes.