Two novel type 2 diabetes loci revealed through integration of TCF7L2 DNA occupancy and SNP association data

LncRNA and mRNA expression profiles in brown adipose tissue of obesity-prone and obesity-resistant mice

Obesity-prone or obesity-resistant phenotypes can exist in individuals who consume the same diet type. Brown adipose tissue functions to dissipate energy in response to cold exposure or overfeeding. Long noncoding RNAs play important roles in a wide range of biological processes. However, systematic examination of lncRNAs in phenotypically divergent mice has not yet been reported. Here, the lncRNA expression profiles in BAT of HFD-induced C57BL/6J mice were investigated by high-throughput RNA sequencing. Genes that play roles in thermogenesis and related pathways were identified. We found lncRNA (Gm44502) may play a thermogenic role in obesity resistance by interacting with six mRNAs. Our results also indicated that seven differentially expressed lncRNAs (4930528G23Rik, Gm39490, Gm5627, Gm15551, Gm16083, Gm36860, Gm42002) may play roles in reducing heat production in obesity susceptibility by interacting with seven differentially expressed mRNAs. The screened lncRNAs may participate in the pathogenesis of weight regulation and provide insight into obesity therapy.

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First lncRNA profiles in BAT of OR and OP mice via bioinformatic analysis

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Gm44502 may play a thermogenic role by interacting with 6 mRNAs

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7 DElncRNAs may reduce thermogenesis by interacting with 7 DEmRNAs

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Validation of expression changes of candidate genes in BAT by in vivo or in vitro

CPPED1-targeting microRNA-371a-5p expression in human placenta associates with spontaneous delivery

MicroRNAs (miRNAs) are important regulators of gene expression, and their expression is associated with many physiological conditions. Here, we investigated potential associations between expression levels of miRNAs in human placenta and the onset of spontaneous term birth. Using RNA sequencing, we identified 54 miRNAs differentially expressed during spontaneous term labor compared to elective term births. Expression levels of 23 miRNAs were upregulated, whereas 31 were downregulated at least 1.5-fold. The upregulated miRNA miR-371a-5p putatively targets CPPED1, expression of which decreases during spontaneous birth. We used a luciferase reporter–based assay to test whether a miR-371a-5p mimic affected translation when it bound to the 3′ untranslated region of CPPED1. In this setting, the miR-371a-5p mimic resulted in lower luciferase activity, which suggests that miR-371a-5p regulates levels of CPPED1. In conclusion, inversely correlated levels of miR-371a-5p and CPPED1 suggest a role for both in spontaneous delivery.

Association between the UBE2Z rs46522 and TCF7L2 rs7903146 polymorphisms with type 2 diabetes in south western Iran

BACKGROUND

Transcription factor 7-like 2 Protein (TCF7L2) has a strong role in the pathogenesis of type 2 diabetes mellitus (T2DM). Association between rs7903146 and T2D risk reported in some of populations. Also many loci such as UBE2Z rs46522 are affecting by TCF7L2 transcription factor have been found associated with T2D. The present study aimed to evaluate association of the SNPs with risk of T2D among our population.

METHODS

This case-control study was conducted on 150 T2D patients and 150 healthy people (as a control group) in south western Iran. Genotyping was performed by PCR-RFLP.

RESULTS

The frequency of genotypes showed no remarkable difference between T2DM patients and control group. The odds ratios of rs7903146 (C/T) polymorphism for CC and TC genotypes were 1.9 (95% CI, 0.85 to 4.24; P=0.12) and 0.81 (95% CI, 0.47 to 1.38; P=0.43) compared with the TT genotype, respectively. The odds ratios of rs46522 (C/T) polymorphism for TT and TC genotypes were 1.75 (95% CI, 0.86 to 3.59; P=0.13) and 1.38 (95% CI, 0.81to 2.35; P=0.24) compared with the CC genotype, respectively.

CONCLUSION

Our study indicates no association of T2D in south western Iran with the rs7903146 and rs46522 variants.

Structural Analysis of G1691S Variant in the Human Filamin B Gene Responsible for Larsen Syndrome: A Comparative Computational Approach

Larsen syndrome (LRS) is a rare genetic disease associated with variable manifestations including skeletal malformations, dislocations of the large joints, and notable changes in facial and limb features. Genetic variants in the Filamin B (FLNB) gene are associated with the development of LRS. We searched two literature databases (OMIM and PubMed) and three gene variant databases (HGMD, UniProt, & dbSNP) to capture all the possible variants associated with LRS phenotype, which may have an impact on the FLNB function. Our search yielded 77 variants that might impact the FLNB protein function in patients with LRS. We performed rigorous computational analysis such as conservational, biochemical, pathogenicity, and structural computational analyses to understand the deleterious effect of the G1691S variant. Further, the structural changes of the G1691S variant was compared with a null variant (G1691A) and the native protein through a molecular dynamic simulation study of 50 ns. We found that the variant G1691S was highly deleterious and destabilize the protein when compared to the native and variant G1691A. This might be due to the physicochemical changes in the variant G1691S when compared to the native and variant G1691A. The destabilization was further supported by transformation of bend to coil in variant G1691S whereas bend was retained in native and variant G1691A through molecular dynamics analysis. Our study shed light on the importance of computational methods to understand the molecular nature of genetic variants and structural insights on the function of the FLNB protein. J. Cell. Biochem. 118: 1900-1910, 2017. © 2017 Wiley Periodicals, Inc.

Rs46522 in the Ubiquitin-Conjugating Enzyme E2Z Gene Is Associated with the Risk of Coronary Artery Disease in Individuals of Chinese Han Population with Type 2 Diabetes

AIMS

We investigated the association between ubiquitin-conjugating enzyme E2Z (UBE2Z) gene SNP rs46522 and the risk of CAD in a Chinese Han population with type 2 diabetes and explored a possible interactive effect with environmental risk factors of CAD.

METHODS

665 patients with T2D were enrolled; 390 were CAD patients and 275 were non-CAD patients. Genotype analysis of rs46522 (T>C) was performed using PCR-RFLP.

RESULTS

The SNP rs47522 was associated with the risk of CAD supposing recessive inheritance model (TT versus CC+CT, OR' = 1.277, 95%CI' 1.039-1.570, p' = 0.020) and codominant model (TT versus CT, OR' = 1.673, 95%CI' 1.088-2.570, p' = 0.019) after adjustment for confounders of CAD. A synergistic effect of rs46522 and BMI was discovered (β = 0.012, p for interreaction = 0.028). In subgroup analysis, minor allele T was significantly associated with CAD in overweight and obesity subgroup (p = 0.034), and the association was also proved in recessive model (OR = 1.537, 95%CI 1.075-2.196, p = 0.018). Smokers with genotype TT had threefold risk of CAD in comparison to nonsmokers with genotype TC or CC (p < 0.001).

CONCLUSIONS

The SNP rs46522 in UBE2Z gene is associated with the risk of CAD in the individuals of Chinese Han descent with type 2 diabetes and is of synergistic effect with BMI.

A Powerful Procedure for Pathway-Based Meta-analysis Using Summary Statistics Identifies 43 Pathways Associated with Type II Diabetes in European Populations

Meta-analysis of multiple genome-wide association studies (GWAS) has become an effective approach for detecting single nucleotide polymorphism (SNP) associations with complex traits. However, it is difficult to integrate the readily accessible SNP-level summary statistics from a meta-analysis into more powerful multi-marker testing procedures, which generally require individual-level genetic data. We developed a general procedure called Summary based Adaptive Rank Truncated Product (sARTP) for conducting gene and pathway meta-analysis that uses only SNP-level summary statistics in combination with genotype correlation estimated from a panel of individual-level genetic data. We demonstrated the validity and power advantage of sARTP through empirical and simulated data. We conducted a comprehensive pathway-based meta-analysis with sARTP on type 2 diabetes (T2D) by integrating SNP-level summary statistics from two large studies consisting of 19,809 T2D cases and 111,181 controls with European ancestry. Among 4,713 candidate pathways from which genes in neighborhoods of 170 GWAS established T2D loci were excluded, we detected 43 T2D globally significant pathways (with Bonferroni corrected p-values < 0.05), which included the insulin signaling pathway and T2D pathway defined by KEGG, as well as the pathways defined according to specific gene expression patterns on pancreatic adenocarcinoma, hepatocellular carcinoma, and bladder carcinoma. Using summary data from 8 eastern Asian T2D GWAS with 6,952 cases and 11,865 controls, we showed 7 out of the 43 pathways identified in European populations remained to be significant in eastern Asians at the false discovery rate of 0.1. We created an R package and a web-based tool for sARTP with the capability to analyze pathways with thousands of genes and tens of thousands of SNPs.

Current Understanding on Role of the Wnt Signaling Pathway Effector TCF7L2 in Glucose Homeostasis

The role of the Wnt signaling pathway in metabolic homeostasis has drawn our intensive attention, especially after the genome-wide association study discovery that certain polymorphisms of its key effector TCF7L2 are strongly associated with the susceptibility to type 2 diabetes. For a decade, great efforts have been made in determining the function of TCF7L2 in various metabolic organs, which have generated both considerable achievements and disputes. In this review, I will briefly introduce the canonical Wnt signaling pathway, focusing on its effector β-catenin/TCF, including emphasizing the bidirectional feature of TCFs and β-catenin post-translational modifications. I will then summarize the observations on the association between TCF7L2 polymorphisms and type 2 diabetes risk. The main content, however, is on the intensive functional exploration of the metabolic role of TCF7L2, including the disputes generated on determining its role in the pancreas and liver with various transgenic mouse lines. Finally, I will discuss those achievements and disputes and present my future perspectives.

Multi-label multi-instance transfer learning for simultaneous reconstruction and cross-talk modeling of multiple human signaling pathways

BACKGROUND

Signaling pathways play important roles in the life processes of cell growth, cell apoptosis and organism development. At present the signal transduction networks are far from complete. As an effective complement to experimental methods, computational modeling is suited to rapidly reconstruct the signaling pathways at low cost. To our knowledge, the existing computational methods seldom simultaneously exploit more than three signaling pathways into one predictive model for the discovery of novel signaling components and the cross-talk modeling between signaling pathways.

RESULTS

In this work, we propose a multi-label multi-instance transfer learning method to simultaneously reconstruct 27 human signaling pathways and model their cross-talks. Computational results show that the proposed method demonstrates satisfactory multi-label learning performance and rational proteome-wide predictions. Some predicted signaling components or pathway targeted proteins have been validated by recent literature. The predicted signaling components are further linked to pathways using the experimentally derived PPIs (protein-protein interactions) to reconstruct the human signaling pathways. Thus the map of the cross-talks via common signaling components and common signaling PPIs is conveniently inferred to provide valuable insights into the regulatory and cooperative relationships between signaling pathways. Lastly, gene ontology enrichment analysis is conducted to gain statistical knowledge about the reconstructed human signaling pathways.

CONCLUSIONS

Multi-label learning framework has been demonstrated effective in this work to model the phenomena that a signaling protein belongs to more than one signaling pathway. As results, novel signaling components and pathways targeted proteins are predicted to simultaneously reconstruct multiple human signaling pathways and the static map of their cross-talks for further biomedical research.