Association of ANK1 variants with new-onset type 2 diabetes in a Han Chinese population from northeast China

Decoding the genetic relationship between Alzheimer's disease and type 2 diabetes: potential risk variants and future direction for North Africa

Introduction

Alzheimer's disease (AD) and Type 2 diabetes (T2D) are both age-associated diseases. Identification of shared genes could help develop early diagnosis and preventive strategies. Although genetic background plays a crucial role in these diseases, we noticed an underrepresentation tendency of North African populations in omics studies.

Materials and methods

First, we conducted a comprehensive review of genes and pathways shared between T2D and AD through PubMed. Then, the function of the identified genes and variants was investigated using annotation tools including PolyPhen2, RegulomeDB, and miRdSNP. Pathways enrichment analyses were performed with g:Profiler and EnrichmentMap. Next, we analyzed variant distributions in 16 worldwide populations using PLINK2, R, and STRUCTURE software. Finally, we performed an inter-ethnic comparison based on the minor allele frequency of T2D-AD common variants.

Results

A total of 59 eligible papers were included in our study. We found 231 variants and 363 genes shared between T2D and AD. Variant annotation revealed six single nucleotide polymorphisms (SNP) with a high pathogenic score, three SNPs with regulatory effects on the brain, and six SNPs with potential effects on miRNA-binding sites. The miRNAs affected were implicated in T2D, insulin signaling pathways, and AD. Moreover, replicated genes were significantly enriched in pathways related to plasma protein binding, positive regulation of amyloid fibril deposition, microglia activation, and cholesterol metabolism. Multidimensional screening performed based on the 363 shared genes showed that main North African populations are clustered together and are divergent from other worldwide populations. Interestingly, our results showed that 49 SNP associated with T2D and AD were present in North African populations. Among them, 11 variants located in DNM3, CFH, PPARG, ROHA, AGER, CLU, BDNF1, CST9, and PLCG1 genes display significant differences in risk allele frequencies between North African and other populations.

Conclusion

Our study highlighted the complexity and the unique molecular architecture of North African populations regarding T2D-AD shared genes. In conclusion, we emphasize the importance of T2D-AD shared genes and ethnicity-specific investigation studies for a better understanding of the link behind these diseases and to develop accurate diagnoses using personalized genetic biomarkers.

Skeletal muscle overexpression of sAnk1.5 in transgenic mice does not predispose to type 2 diabetes

Genome-wide association studies (GWAS) and cis-expression quantitative trait locus (cis-eQTL) analyses indicated an association of the rs508419 single nucleotide polymorphism (SNP) with type 2 diabetes (T2D). rs508419 is localized in the muscle-specific internal promoter (P2) of the ANK1 gene, which drives the expression of the sAnk1.5 isoform. Functional studies showed that the rs508419 C/C variant results in increased transcriptional activity of the P2 promoter, leading to higher levels of sAnk1.5 mRNA and protein in skeletal muscle biopsies of individuals carrying the C/C genotype. To investigate whether sAnk1.5 overexpression in skeletal muscle might predispose to T2D development, we generated transgenic mice (TgsAnk1.5/+) in which the sAnk1.5 coding sequence was selectively overexpressed in skeletal muscle tissue. TgsAnk1.5/+ mice expressed up to 50% as much sAnk1.5 protein as wild-type (WT) muscles, mirroring the difference reported between individuals with the C/C or T/T genotype at rs508419. However, fasting glucose levels, glucose tolerance, insulin levels and insulin response in TgsAnk1.5/+ mice did not differ from those of age-matched WT mice monitored over a 12-month period. Even when fed a high-fat diet, TgsAnk1.5/+ mice only presented increased caloric intake, but glucose disposal, insulin tolerance and weight gain were comparable to those of WT mice fed a similar diet. Altogether, these data indicate that sAnk1.5 overexpression in skeletal muscle does not predispose mice to T2D susceptibility.

Bioinformatics and Next-Generation Data Analysis for Identification of Genes and Molecular Pathways Involved in Subjects with Diabetes and Obesity

Background and Objectives: A subject with diabetes and obesity is a class of the metabolic disorder. The current investigation aimed to elucidate the potential biomarker and prognostic targets in subjects with diabetes and obesity. Materials and Methods: The next-generation sequencing (NGS) data of GSE132831 was downloaded from Gene Expression Omnibus (GEO) database. Functional enrichment analysis of DEGs was conducted with ToppGene. The protein-protein interactions network, module analysis, target gene-miRNA regulatory network and target gene-TF regulatory network were constructed and analyzed. Furthermore, hub genes were validated by receiver operating characteristic (ROC) analysis. A total of 872 DEGs, including 439 up-regulated genes and 433 down-regulated genes were observed. Results: Second, functional enrichment analysis showed that these DEGs are mainly involved in the axon guidance, neutrophil degranulation, plasma membrane bounded cell projection organization and cell activation. The top ten hub genes (MYH9, FLNA, DCTN1, CLTC, ERBB2, TCF4, VIM, LRRK2, IFI16 and CAV1) could be utilized as potential diagnostic indicators for subjects with diabetes and obesity. The hub genes were validated in subjects with diabetes and obesity. Conclusion: This investigation found effective and reliable molecular biomarkers for diagnosis and prognosis by integrated bioinformatics analysis, suggesting new and key therapeutic targets for subjects with diabetes and obesity.

Identification of biomarkers, pathways, and potential therapeutic targets for heart failure using next-generation sequencing data and bioinformatics analysis

BACKGROUND

Heart failure (HF) is the most common cardiovascular diseases and the leading cause of cardiovascular diseases related deaths. Increasing molecular targets have been discovered for HF prognosis and therapy. However, there is still an urgent need to identify novel biomarkers. Therefore, we evaluated biomarkers that might aid the diagnosis and treatment of HF.

METHODS

We searched next-generation sequencing (NGS) dataset (GSE161472) and identified differentially expressed genes (DEGs) by comparing 47 HF samples and 37 normal control samples using limma in R package. Gene ontology (GO) and pathway enrichment analyses of the DEGs were performed using the g: Profiler database. The protein-protein interaction (PPI) network was plotted with Human Integrated Protein-Protein Interaction rEference (HiPPIE) and visualized using Cytoscape. Module analysis of the PPI network was done using PEWCC1. Then, miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed by Cytoscape software. Finally, we performed receiver operating characteristic (ROC) curve analysis to predict the diagnostic effectiveness of the hub genes.

RESULTS

A total of 930 DEGs, 464 upregulated genes and 466 downregulated genes, were identified in HF. GO and REACTOME pathway enrichment results showed that DEGs mainly enriched in localization, small molecule metabolic process, SARS-CoV infections, and the citric acid tricarboxylic acid (TCA) cycle and respiratory electron transport. After combining the results of the PPI network miRNA-hub gene regulatory network and TF-hub gene regulatory network, 10 hub genes were selected, including heat shock protein 90 alpha family class A member 1 (HSP90AA1), arrestin beta 2 (ARRB2), myosin heavy chain 9 (MYH9), heat shock protein 90 alpha family class B member 1 (HSP90AB1), filamin A (FLNA), epidermal growth factor receptor (EGFR), phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), cullin 4A (CUL4A), YEATS domain containing 4 (YEATS4), and lysine acetyltransferase 2B (KAT2B).

CONCLUSIONS

This discovery-driven study might be useful to provide a novel insight into the diagnosis and treatment of HF. However, more experiments are needed in the future to investigate the functional roles of these genes in HF.

The new landscape of differentially expression proteins in placenta tissues of gestational diabetes based on iTRAQ proteomics

INTRODUCTION

Gestational diabetes mellitus (GDM) refers to abnormal glucose tolerance that occurs or is firstly diagnosed during pregnancy. GDM is related to various adverse pregnancy outcomes, but GDM pathogeny has not been fully elucidated. Nevertheless, previous studies have observed that many proteins in the placentas of patients with GDM are dysregulated. The present study aimed to establish a novel differentially expressed protein (DEP) landscape of GDM and normal maternal placentas and to explore the possible connection between DEPs and GDM pathogenesis. This study provides new insights into the mechanism of GDM and should make an important contribution to the development of biomarkers.

METHODS

The morphological characteristics of the placenta were observed on 30 GDM and normal maternal placental tissues stained with haematoxylin and eosin. Isobaric tags for relative and absolute quantitation (iTRAQ) was used in the proteomics screening of the DEPs of the normal and GDM maternal placentas. Bioinformatics analysis was performed on the DEPs, and parallel reaction monitoring (PRM) was performed to verify the DEPs. Finally, the quantitative analysis of iTRAQ and PRM was verified by immunohistochemical assay.

RESULTS

A total of 68 DEPs in the GDM placenta were identified with iTRAQ proteomics experiment, comprising 21 up-regulated and 47 down-regulated DEPs. Bioinformatics analysis showed that the regulation of transport, catabolic process of non-coding RNA, cytoskeleton and cell binding were the most abundant Gene Ontology terms, and RNA degradation was an important pathway for significant enrichment. Protein-protein interaction network analysis showed that heterogeneous nuclear ribonucleoproteins A2/B1 (HNRNPA2B1), heterogeneous nuclear ribonucleoprotein A/B (HNRNPAB), heterogeneous nuclear ribonucleoprotein L (HNRNPL) and heterogeneous nuclear ribonucleoprotein A3 (HNRNPA3) were the cores of the up-regulated proteins. Band 3 anion transport protein (SLC4A1), spectrin beta chain erythrocytic (SPTB), ankyrin-1 (ANK1), spectrin beta chain non-erythrocytic 2 (SPTBN2), D-3-phosphoglycerate dehydrogenase (PHGDH) and exosome complex component RRP42 (EXOSC7) were the cores of the down-regulated proteins. These proteins are involved in the binding, splicing, processing, transport and degradation of RNA and in the formation and maintenance of the cytoskeleton. PRM verification results showed that seven proteins, namely, epiplakin (EPPK1), cold-inducible RNA-binding protein (CIRBP), HNRNPA2B1, HNRNPAB, HNRNPL, Ras-related protein Rab-21 (RAB21) and Ras-related protein Rab-3B (RAB3B), were up-regulated, whereas SPTB and SLC4A1 were down-regulated. The results of immunohistochemical assay also showed that the expression of five proteins, namely EPPK1, HNRNPA2B1, HNRNPAB, CIRBP and RAB21, were significantly higher in GDM placental tissues (P < 0.01). The GDM placentas showed changes in the morphological evaluation, including poor villous maturation, obvious increase in the number of syncytiotrophoblast nodules, thickening of the wall of dry villous arterioles with lumen stenosis, increased fibrinous exudation and excessive filling of villous interstitial vessels.

DISCUSSION

Differentially expressed proteins related to a variety of biological processes in the GDM placenta were found. Fourteen proteins, namely, HNRNPA2B1, HNRNPAB, HNRNPL, HNRNPA3, EPPK1, CIRBP, RAB21, RAB3B, SLC4A1, SPTB, ANK1, SPTBN2, PHGDH and EXOSC7, which were differentially expressed in the placenta, may play an important role in regulating the occurrence and development of gestational diabetes through multi-channel and multi-link regulation.

The SNP rs516946 Interacted in the Association of MetS with Dietary Iron among Chinese Males but Not Females

This study aimed to explore the role of the single nucleotide polymorphism (SNP) rs516946 of the Ankyrin 1 (ANK1) gene in the relationship between dietary iron and metabolic syndrome (MetS) in the Chinese population. A total of 2766 Chinese adults (1284 males and 1482 females) were recruited. A 3-day 24-h dietary recall and weighing of household condiments were used to assess dietary intake. Anthropometric and laboratory measurements were obtained. After adjusting for age, region, years of education, intentional physical exercise, physical activity level, smoking, alcohol use and energy intake, dietary iron and the SNP rs516946 were both correlated with MetS risk and interacted among the male participants. The trend between dietary iron and MetS risk remained among T allele non-carriers of males but not among T allele carriers of males. Both the SNP rs516946 and the ferritin level correlated positively with the aspartate aminotransferase (AST) level. ANK1 SNP rs516946 interacted in the association of MetS with dietary iron among Chinese males while no association was found among females. Periodic blood loss might prevent females from these associations. The SNP rs516946 might correlate with liver function.

Multi-species and multi-tissue methylation clocks for age estimation in toothed whales and dolphins

The development of a precise blood or skin tissue DNA Epigenetic Aging Clock for Odontocete (OEAC) would solve current age estimation inaccuracies for wild odontocetes. Therefore, we determined genome-wide DNA methylation profiles using a custom array (HorvathMammalMethyl40) across skin and blood samples (n = 446) from known age animals representing nine odontocete species within 4 phylogenetic families to identify age associated CG dinucleotides (CpGs). The top CpGs were used to create a cross-validated OEAC clock which was highly correlated for individuals (r = 0.94) and for unique species (median r = 0.93). Finally, we applied the OEAC for estimating the age and sex of 22 wild Norwegian killer whales. DNA methylation patterns of age associated CpGs are highly conserved across odontocetes. These similarities allowed us to develop an odontocete epigenetic aging clock (OEAC) which can be used for species conservation efforts by provide a mechanism for estimating the age of free ranging odontocetes from either blood or skin samples.

Mapping the genetic basis of diabetes mellitus in the Australian Burmese cat (Felis catus)

Diabetes mellitus, a common endocrinopathy affecting domestic cats, shares many clinical and pathologic features with type 2 diabetes in humans. In Australia and Europe, diabetes mellitus is almost four times more common among Burmese cats than in other breeds. As a genetically isolated population, the diabetic Australian Burmese cat provides a spontaneous genetic model for studying diabetes mellitus in humans. Studying complex diseases in pedigreed breeds facilitates tighter control of confounding factors including population stratification, allelic frequencies and environmental heterogeneity. We used the feline SNV array and whole genome sequence data to undertake a genome wide-association study and runs of homozygosity analysis, of a case–control cohort of Australian and European Burmese cats. Our results identified diabetes-associated haplotypes across chromosomes A3, B1 and E1 and selective sweeps across the Burmese breed on chromosomes B1, B3, D1 and D4. The locus on chromosome B1, common to both analyses, revealed coding and splice region variants in candidate genes, ANK1, EPHX2 and LOX2, implicated in diabetes mellitus and lipid dysregulation. Mapping this condition in Burmese cats has revealed a polygenic spectrum, implicating loci linked to pancreatic beta cell dysfunction, lipid dysregulation and insulin resistance in the pathogenesis of diabetes mellitus in the Burmese cat.

A Replication Study Identified Seven SNPs Associated with Quantitative Traits of Type 2 Diabetes among Chinese Population in A Cross-Sectional Study

Genome-wide association studies (GWAS) have identified common variants for quantitative traits (insulin resistance and impaired insulin release) of type 2 diabetes (T2D) across different ethnics including China, but results were inconsistent. The study included 1654 subjects who were selected from the 2010–2012 China National Nutrition and Health Surveillance (CNNHS). Insulin resistance and impaired insulin release were assessed by homeostasis model assessment (HOMA). The study included 64 diabetes-related single nucleotide polymorphisms (SNPs), which were done using Mass ARRAY. A logistic regression model was employed to explore the associations of SNPs with insulin resistance and impaired insulin release by correcting for the confounders. The 5q11.2-rs4432842, RASGRP1-rs7403531, and SEC16B-rs574367 increased the risk of insulin resistance with OR = 1.23 (95% CI: 1.04–1.45, OR = 1.35 (95% CI: 1.13–1.62), OR = 1.34 (95% CI: 1.07–1.67), respectively, while MAEA-rs6815464 decreased the risk of insulin resistance (OR = 0.84, 95% CI: 0.71–1.00). CENTD2-rs1552224, TSPAN8-rs7961581 and ANK1-rs516946 was associated with increased risk of impaired insulin release with OR = 1.47 (95% CI: 1.09–1.99), OR = 1.25 (95% CI: 1.03–1.51), OR = 1.39 (95% CI: 1.07–1.81), respectively. Our findings would provide insight into the pathogenesis of individual SNPs and T2D.

Effects of variants of 50 genes on diabetes risk among the Chinese population born in the early 1960s

BACKGROUND

Genome-wide association studies have identified loci that significantly increase diabetes risk. This study explored the genetic susceptibility in relation to diabetes risk in adulthood among a Chinese population born in the early 1960s.

METHODS

In all, 2129 subjects (833 males, 1296 females) were selected from the cross-sectional 2010 to 2012 China National Nutrition and Health Survey. Fifty diabetes-related single nucleotide polymorphisms (SNPs) were detected. Two diabetes genetic risk scores (GRSs) based on the 50 diabetes-predisposing variants were developed to examine the association of these SNPs with diabetes risk.

RESULTS

Associations were found between diabetes risk and SNPs in the MTNR1B (rs10830963), KLHDC5 (rs10842994), GRK5 (rs10886471), cyclindependentkinase 5 regulatory subunit associated protein 1 (rs10946398), adaptorrelated protein complex 3 subunit sigma 2 (rs2028299), diacylglycerol kinase beta/transmembrane protein 195 (rs2191349), SREBF chaperone (rs4858889), ankyrin1 (rs516946), RAS guanyl releasing protein 1 (rs7403531), and zinc finger AN1-type containing 3 (rs9470794) genes. As a continuous variable, with a 1-point increase in the GRS or weighted (w) GRS, fasting plasma glucose (FPG) increased 0.045 and 0.044 mM, respectively (P < 0.001 for both), after adjusting for confounders. Both GRS and wGRS showed an association with diabetes, with a multivariable-adjusted odds ratio (95% confidence interval) of 1.09 (1.00-1.19) and 1.12 (1.03-1.22), respectively, among all subjects. No significant associations were found between the GRS or wGRS and impaired fasting glucose or impaired glucose tolerance.

CONCLUSIONS

The data suggest the association of 10 SNPs and the GRS or wGRS with diabetes risk. Genetic susceptibility to diabetes may synergistically affect the risk of diabetes in adulthood.