The ADRA2A rs553668 variant is associated with type 2 diabetes and five variants were associated at nominal significance levels in a population-based case-control study from Mexico City

Germline genetic regulation of the colorectal tumor immune microenvironment

OBJECTIVE

To evaluate the contribution of germline genetics to regulating the briskness and diversity of T cell responses in CRC, we conducted a genome-wide association study to examine the associations between germline genetic variation and quantitative measures of T cell landscapes in 2,876 colorectal tumors from participants in the Molecular Epidemiology of Colorectal Cancer Study (MECC).

METHODS

Germline DNA samples were genotyped and imputed using genome-wide arrays. Tumor DNA samples were extracted from paraffin blocks, and T cell receptor clonality and abundance were quantified by immunoSEQ (Adaptive Biotechnologies, Seattle, WA). Tumor infiltrating lymphocytes per high powered field (TILs/hpf) were scored by a gastrointestinal pathologist. Regression models were used to evaluate the associations between each variant and the three T-cell features, adjusting for sex, age, genotyping platform, and global ancestry. Three independent datasets were used for replication.

RESULTS

We identified a SNP (rs4918567) near RBM20 associated with clonality at a genome-wide significant threshold of 5 × 10- 8, with a consistent direction of association in both discovery and replication datasets. Expression quantitative trait (eQTL) analyses and in silico functional annotation for these loci provided insights into potential functional roles, including a statistically significant eQTL between the T allele at rs4918567 and higher expression of ADRA2A (P = 0.012) in healthy colon mucosa.

CONCLUSIONS

Our study suggests that germline genetic variation is associated with the quantity and diversity of adaptive immune responses in CRC. Further studies are warranted to replicate these findings in additional samples and to investigate functional genomic mechanisms.

Influence of Receptor Polymorphisms on the Response to α-Adrenergic Receptor Blockers in Pheochromocytoma Patients

Background: Presurgical treatment with an α-adrenergic receptor blocker is recommended to antagonize the catecholamine-induced α-adrenergic receptor mediated vasoconstriction in patients with pheochromocytoma or sympathetic paraganglioma (PPGL). There is, however, a considerable interindividual variation in the dose-response relationship regarding the magnitude of blood pressure reduction or the occurrence of side effects. We hypothesized that genetically determined differences in α-adrenergic receptor activity contribute to this variability in dose-response relationship. Methods: Thirty-one single-nucleotide polymorphisms (SNPs) of the α1A, α1B, α1D adrenoreceptor (ADRA1A, ADRA1B, ADRA1D) and α2A, α2B adrenoreceptor (ADRA2A, ADRA2B) genes were genotyped in a group of 116 participants of the PRESCRIPT study. Haplotypes were constructed after determining linkage disequilibrium blocks. Results: The ADRA1B SNP rs10515807 and the ADRA2A SNPs rs553668/rs521674 were associated with higher dosages of α-adrenergic receptor blocker (p < 0.05) and with a higher occurrence of side effects (rs10515807) (p = 0.005). Similar associations were found for haplotype block 6, which is predominantly defined by rs10515807. Conclusions: This study suggests that genetic variability of α-adrenergic receptor genes might be associated with the clinically observed variation in beneficial and adverse therapeutic drug responses to α-adrenergic receptor blockers. Further studies in larger cohorts are needed to confirm our observations.

Integrated bioinformatics analysis reveals novel key biomarkers in diabetic nephropathy

Objectives:

The underlying molecular mechanisms of diabetic nephropathy have yet not been investigated clearly. In this investigation, we aimed to identify key genes involved in the pathogenesis and prognosis of diabetic nephropathy.

Methods:

We downloaded next-generation sequencing data set GSE142025 from Gene Expression Omnibus database having 28 diabetic nephropathy samples and nine normal control samples. The differentially expressed genes between diabetic nephropathy and normal control samples were analyzed. Biological function analysis of the differentially expressed genes was enriched by Gene Ontology and REACTOME pathways. Then, we established the protein–protein interaction network, modules, miRNA-differentially expressed gene regulatory network and transcription factor-differentially expressed gene regulatory network. Hub genes were validated by using receiver operating characteristic curve analysis.

Results:

A total of 549 differentially expressed genes were detected including 275 upregulated and 274 downregulated genes. The biological process analysis of functional enrichment showed that these differentially expressed genes were mainly enriched in cell activation, integral component of plasma membrane, lipid binding, and biological oxidations. Analyzing the protein–protein interaction network, miRNA-differentially expressed gene regulatory network and transcription factor-differentially expressed gene regulatory network, we screened hub genes MDFI, LCK, BTK, IRF4, PRKCB, EGR1, JUN, FOS, ALB, and NR4A1 by the Cytoscape software. The receiver operating characteristic curve analysis confirmed that hub genes were of diagnostic value.

Conclusions:

Taken above, using integrated bioinformatics analysis, we have identified key genes and pathways in diabetic nephropathy, which could improve our understanding of the cause and underlying molecular events, and these key genes and pathways might be therapeutic targets for diabetic nephropathy.

Effect of KCNQ1 rs2237892 polymorphism on the predisposition to type 2 diabetes mellitus: An updated meta-analysis

OBJECTIVES

Previous studies have analyzed the potential effect of KCNQ1 rs2237892 polymorphism on the predisposition to type 2 diabetes mellitus, but the findings are inconclusive and the subject of debate. The purpose of our study was to provide further insight into the potential association between KCNQ1 rs2237892 polymorphism and the risk of type 2 diabetes mellitus.

METHODS

In total, 50 articles (60 studies) with 77,276 cases and 76,054 controls were utilized in our analysis. The pooled odds ratio (OR), 95% confidence interval (95% CI), and p value were used to evaluate the significance of our findings. Funnel plots and Beggar's regression tests were utilized to determine the presence of publication bias.

RESULTS

Our meta-analysis results indicated that KCNQ1 rs2237892 polymorphism could be correlated with the risk of type 2 diabetes mellitus under the C allelic, recessive, and dominant genetic models (OR = 1.25, 95% 1.19-1.32, p < 0.001; OR = 1.50, 95% CI 1.34-1.68, p < 0.001; OR = 1.26, 95% CI 1.14-1.40, p < 0.001, respectively). Additionally, ethnicity analysis revealed that the source of control, case size, and Hardy-Weinberg Equilibrium status were correlated to the polymorphism in the three genetic models.

CONCLUSIONS

Our meta-analysis demonstrated significant evidence to support the association between KCNQ1 rs2237892 polymorphism and predisposition to type 2 diabetes mellitus.

Evidence of association between single-nucleotide polymorphisms in lipid metabolism-related genes and type 2 diabetes mellitus in a Chinese population

Background: Type 2 diabetes mellitus (T2DM) is a complex chronic metabolic disorder triggered by insulin resistance in peripheral tissues. Evidence has shown that lipid metabolism and related genetic factors lead to insulin resistance. Hence, it is meaningful to investigate the association between single-nucleotide polymorphisms (SNPs) in lipid metabolism-related genes and T2DM. Methods: A total of 1,194 subjects with T2DM and 1,274 Non-diabetic subjects (NDM) were enrolled. Five SNPs in three genes (rs864745 in JAZF1, rs35767 in IGF1, and rs4376068, rs4402960, and rs6769511 in IGF2BP2) that contribute to insulin resistance involving lipid metabolism were genotyped using the MassArray method in a Chinese population. Results: The allele and genotypes of rs6769511 in IGF2BP2 were associated with T2DM (P=0.009 and P=0.002, respectively). In inheritance model analysis, compared with the T/T-C/T genotype, the C/C genotype of rs6769511 in IGF2BP2 was a risk factor for the development of T2DM (P<0.001, odds ratio [OR] =1.76; 95% confidence interval [CI]: 1.29-2.42). Haplotype analysis revealed associations of the rs4376068-rs4402960-rs6769511 haplotypes in IGF2BP2 with the development of T2DM (P=0.015). Additionally, rs4376068C-rs4402960T-rs6769511C was a risk haplotype for T2DM (OR=1.179; 95% CI: 1.033-1.346). Conclusion: The rs6769511 in IGF2BP2 was associated with T2DM susceptibility, and the rs4376068-rs4402960-rs6769511 haplotypes in IGF2BP2 was associated with the development of T2DM in a Chinese population.

Novel Targets in Glucose Homeostasis and Obesity-Lesson from Rare Mutations

PURPOSE OF REVIEW

Obesity and diabetes have already become the second largest risk factor for cardiovascular disease. During the last decade, remarkable advances have been made in understanding the human genome's contribution to glucose homeostasis disorders and obesity. A few studies on rare mutations of candidate genes provide potential genetic targets for the treatment of diabetes and obesity. In this review, we discussed the detailed findings of these studies and the possible causalities between specific genetic variations and dysfunctions in energy or glucose homeostasis. We are optimistic that novel therapeutic strategies targeting these specific mutants for treating and preventing diabetes and obesity will be developed in the near future.

RECENT FINDINGS

Studies on rare genetic mutation-caused obesity or diabetes have identified potential genetic targets to decrease body weight or reduce the risk of diabetes. Rare mutations observed in lipodystrophy, obese, or diabetic human patients are promising targets in the treatment of diabetes and obesity.

Association study of candidate genes with obesity and metabolic traits in antipsychotic-treated patients with first-episode psychosis over a 2-year period

AIMS

Patients with a first episode of psychosis (FEP) often display different metabolic disturbances even independently of drug therapy. However, antipsychotic (AP) treatment, especially with second-generation APs, is strongly linked to weight gain, which increases patients' risk of developing obesity and other metabolic diseases. There is an important genetic risk component that can contribute to the appearance of these disturbances. The aim of the present study was to evaluate the effect of polymorphisms in selected candidate genes on obesity and other anthropometric and metabolic traits in 320 AP-treated FEP patients over the course of a 2-year follow-up.

METHODS

These patients were recruited in the multicentre PEPs study (Phenotype-genotype and environmental interaction; Application of a predictive model in first psychotic episodes). A total of 127 validated single nucleotide polymorphisms (SNPs) in 18 candidate genes were included in the genetic analysis.

RESULTS

After Bonferroni correction, SNPs in ADRA2A, FTO, CNR1, DRD2, DRD3, LEPR and BDNF were associated with obesity, abdominal circumference, triglycerides, HDL cholesterol, and/or percentage of glycated haemoglobin.

CONCLUSIONS

Although our results should be interpreted as exploratory, they support previous evidence of the impact of these candidate genes on obesity and metabolic status. Further research is required to gain a better knowledge of the genetic variants that can be considered relevant metabolic risk factors. The ability to identify FEP patients at higher risk for these metabolic disturbances would enable clinicians to better select and control their AP treatment.

Maya gene variants related to the risk of type 2 diabetes in a family-based association study

Mexican Maya populations have a notably high prevalence of type 2 diabetes (T2D) as a consequence of the interaction between environmental factors and a genetic component. To assess the impact of 24 single nucleotide variants (SNVs) located in 18 T2D risk genes, we conducted a family-based association evaluation in samples from Maya communities with a high incidence of the disease. A total of four hundred individuals were recruited from three Maya communities with a high T2D incidence. Family pedigrees (100) and 49 nuclear families were included. Genotyping was performed by allelic discrimination with TaqMan probes. This study also included the family-based association test (FBAT) statistic U to assess the genetic associations with T2D, and the multivariate statistical and haplotype analyses. A positive association with TD2 risk was found for WFS1 rs6446482 (p = 0.046, Z = 1.994) under an additive model, and SIRT1 rs7896005 (p = 0.038, Z = 2.073) under the dominant model. Multivariate model analysis, including T2D status, age, and body mass index (BMI), displayed significant covariance in PPARGC-1α rs8192678; SIRT1 rs7896005; TCF7L2 rs7903146 and rs122243326; UCP3 rs3781907; and HHEX rs1111875 with a P < 0.05. This study revealed an association of SIRT1 and WFS1 with T2D risk.

Pleiotropic Effects of a KCNQ1 Variant on Lipid Profiles and Type 2 Diabetes: A Family-Based Study in China

OBJECTIVE

The genetic variant rs2237895, located in the Potassium Voltage-Gated Channel Subfamily Q Member 1 (KCNQ1) gene, has been replicated to be associated with type 2 diabetes mellitus (T2DM) susceptibility, but the relationship with lipids is conflicting. Furthermore, the common genetic predisposition to T2DM and lipids was not fully detected.

METHODS

In total, 5839 individuals (2220 were T2DM patients) across 2885 families were included. The effect of rs2237895 on T2DM and lipids was estimated using linear regression and logistic regression models after adjustment for multiple covariates. Mediation analysis was then used to test whether KCNQ1 participated in T2DM pathogenesis via lipid-mediated pathways.

RESULTS

Per allele-C of rs2237895 was associated with 17% (11-23%, P < 0.001) increased T2DM risk. Moreover, it was correlated with 5% (1-9%, P < 0.001) increased T2DM risk. Moreover, it was correlated with 5% (1-9%, P < 0.001) increased T2DM risk. Moreover, it was correlated with 5% (1-9%, P < 0.001) increased T2DM risk. Moreover, it was correlated with 5% (1-9%, P < 0.001) increased T2DM risk. Moreover, it was correlated with 5% (1-9%, P < 0.001) increased T2DM risk. Moreover, it was correlated with 5% (1-9%.

CONCLUSION

KCNQ1 had pleiotropic effects on lipids and T2DM, and the unexpected genetic effect on association of HDL-C with T2DM was observed, indicating the different pathways to lipids and T2DM. Further research studies are needed to verify potential biological mechanisms.

Data on a genome-wide association study of type 2 diabetes in a Maya population

Maya communities have been shown to exhibit type 2 diabetes (T2D) with high prevalence compared with Mexican mestizo populations. Furthermore, some variants associated with the risk for T2D have been described. In this study, we describe the results of a pilot genome wide association study (GWAS) using 817,823 single nucleotide polymorphisms (SNPs) to identify candidate variants for replication in future studies. Herein, we present the GWAS study data, which were divided into three parts: first, 1289 ancestry informative markers (AIMs) were selected for Latino populations containing European, African, and Native American SNPs obtained from the literature; second, a GWAS hypothesis free to select candidate genes associated with T2D was performed, which identified 24 candidate genes; and third, 39 SNPs previously associated with T2D or related traits were replicated. This article is associated with the original article published in “Gene” under the title “Pilot genome-wide association study identifying novel risk loci for type 2 diabetes in a Maya population”.