Association of polymorphisms in LEPR with type 2 diabetes and related metabolic traits in a Chinese population

Study on gene expression in the liver at various developmental stages of human embryos

Background

The normal development of the liver during human embryonic stages is critical for the functionality of the adult liver. Despite this, the essential genes, biological processes, and signal pathways that drive liver development in human embryos remain poorly understood.

Methods

In this study, liver samples were collected from human embryos at progressive developmental stages, ranging from 2-month-old to 7-month-old. Highly expressed genes and their associated enrichment processes at various developmental stages of the liver were identified through transcriptomic sequencing.

Results

The findings indicated that genes associated with humoral immune responses and B-cell-mediated immunity were highly expressed during the early developmental stages. Concurrently, numerous genes related to vitamin response, brown adipocyte differentiation, T cell differentiation, hormone secretion, hemostasis, peptide hormone response, steroid metabolism, and hematopoietic regulation exhibited increased expression aligned with liver development. Our results suggest that the liver may possess multiple functions during embryonic stages, beyond serving hematopoietic roles. Moreover, this study elucidated the complex regulatory interactions among genes involved in lymphocyte differentiation, the regulation of hemopoiesis, and liver development. Consequently, the development of human embryonic liver necessitates the synergistic regulation of numerous genes. Notably, alongside conventionally recognized genes, numerous previously uncharacterized genes involved in liver development and function were also identified.

Conclusion

These findings establish a critical foundation for future research on liver development and diseases arising from fetal liver abnormalities.

Leptin and leptin receptor gene polymorphisms and depression treatment response

OBJECTIVE

Associations between leptin (LEP) and leptin receptor (LEPR) gene polymorphisms and mood disorders have been found but not yet confirmed in multiple studies. The aim of our study was to study the associations between LEP and LEPR single nucleotide polymorphisms (SNPs) and treatment response of depression. Associations between leptin levels and depression severity were also investigated.

METHODS

The data included 242 depressed patients in secondary psychiatric care. Symptoms of depression were assessed with the Montgomery–Åsberg Depression Rating Scale (MADRS). Previously found LEP and LEPR SNPs associated with depression and other mood disorders were studied. Furthermore, all available LEP and LEPR SNPs were clumped using proxy SNPs to represent gene areas in r2 > 0.2 linkage disequilibrium and their association with treatment response was analysed with logistic regression.

RESULTS

Two proxy SNPs of LEPR gene, rs12564738 and rs12029311, were associated with MADRS response at 6 weeks (p adjusted = 0.024, p adjusted = 0.024). SNPs from previous studies were not associated with MADRS response, but LEPR rs12145690 from a previous study was strongly associated with rs12564738 (r2 = 0.94). The positive association between leptin levels and MADRS score at baseline after adjusting with age, sex, body mass index (BMI), Alcohol Use Disorders Identification Test score, and smoking was found (p = 0.011).

CONCLUSION

Our findings suggest that LEPR polymorphisms are associated with depression treatment response. We also found associations between leptin levels and depression independently of BMI. Further studies and meta-analyses are needed to confirm the significance of found SNPs and the role of leptin in depression.

Association of rs1137101 with hypertension and type 2 diabetes mellitus of Mongolian and Han Chinese

BACKGROUND

Hypertension (HTN) and type 2 diabetes mellitus (T2DM) are often coincident, and each condition is considered a risk factor for the other. Both occur frequently in the Inner Mongolia region of China. The reasons for differences in risk between Han and Mongolian ethnic groups are not known. The LEPR gene and its polymorphism, rs1137101 (Gln223Arg), are both considered risk factors for HTN and T2DM, but any role of rs1137101 in the occurrence of HTN + T2DM remains unclear for Mongolian and Han populations in the Inner Mongolia region.

AIM

To investigate the relationship between rs1137101 and the occurrence of HTN with T2DM in Mongolian and Han populations in Inner Mongolia.

METHODS

A total of 2652 subjects of Han and Mongolian ethnic origins were enrolled in the current study, including 908 healthy controls, 1061 HTN patients and 683 HTN patients with T2DM.

RESULTS

The association between the rs1137101 polymorphism and HTN with T2DM was analyzed, and differences between Han and Mongolian individuals assessed. There was a significant correlation between rs1137101 and HTN (co-dominant, dominant, over-dominant and log-additive models) and HTN + T2DM (co-dominant, dominant, over-dominant and log-additive models) after adjustment for sex and age in individuals of Mongolian origin. rs1137101 was significantly associated with HTN (co-dominant, recessive and log-additive models) and HTN + T2DM (co-dominant, dominant, over-dominant and log-additive models) in the Han Chinese population.

CONCLUSION

Mongolian and Han subjects from Inner Mongolia with HTN who had rs1137101 were protected against the development of T2DM. Allele A has the opposite impact on the occurrence of HTN in Mongolian and Han Chinese populations.

The genetic susceptibility profile of type 2 diabetes and reflection of its possible role related to reproductive dysfunctions in the southern Indian population of Hyderabad

BACKGROUND

The genetic association studies of type 2 diabetes mellitus (T2DM) hitherto undertaken among the Indian populations are grossly inadequate representation of the ethnic and geographic heterogeneity of the country. In view of this and due to the inconsistent nature of the results of genetic association studies, it would be prudent to undertake large scale studies in different regions of India considering wide spectrum of variants from the relevant pathophysiological pathways. Given the reproductive dysfunctions associated with T2DM, it would be also interesting to explore if some of the reproductive pathway genes are associated with T2DM. The present study is an attempt to examine these aspects in the southern Indian population of Hyderabad.

METHODS

A prioritized panel of 92 SNPs from a large number of metabolic and reproductive pathway genes was genotyped on 500 cases and 500 controls, matched for ethnicity, age and BMI, using AGENA MassARRAYiPLEX™ platform.

RESULTS

The allelic association results suggested 14 SNPs to be significantly associated with T2DM at P ≤ 0.05 and seven of those-rs2241766-G (ADIPOQ), rs6494730-T (FEM1B), rs1799817-A and rs2059806-T (INSR), rs11745088-C (FST), rs9939609-A and rs9940128-A (FTO)-remained highly significant even after correction for multiple testing. A great majority of the significant SNPs were risk in nature. The ROC analysis of the risk scores of the significant SNPs yielded an area under curve of 0.787, suggesting substantial power of our study to confer these genetic variants as predictors of risk for T2DM.

CONCLUSIONS

The associated SNPs of this study are known to be specifically related to insulin signaling, fatty acid metabolism and reproductive pathway genes and possibly suggesting the role of overlapping phenotypic features of insulin resistance, obesity and reproductive dysfunctions inherent in the development of diabetes. Large scale studies involving gender specific approach may be required in order to identify the precise nature of population and gender specific risk profiles for different populations, which might be somewhat distinct.

Association Analysis of LEP Signaling Pathway with Type 2 Diabetes Mellitus in Chinese Han Population from South China

Objective

This study is aimed at analyzing the relationship between leptin (LEP) signaling pathway and type 2 diabetes mellitus (T2DM) and at providing support for molecular genetic research on the pathogenesis of T2DM in Chinese Han population.

Methods

A case-control study was designed, including 1092 cases with T2DM and 1092 healthy controls of Chinese Han origin recruited from ten hospitals in Guangdong Province, Southern China. Twenty-three single nucleotide polymorphisms (SNPs) of 15 genes in LEP signaling pathway were genotyped by SNPscan™ kit. The Pearson chi-square test, Cochran-Armitage trend test, MAX3, and logistic regression were applied to analyze the association between single nucleotide polymorphism (SNP) and T2DM; unconditional logistic regression was used to analyze haplotype in LD block; and SNP set analysis based on logistic kernel machine regression was used to analyze pathway. All statistical analysis was performed by SPSS25.0, R2.14, Haploview4.2, SNPStats, and other statistical software packages.

Results

In association analysis based on SNP, rs2167270 had statistical significance both in the adjusted and unadjusted covariate dominant model and in the unadjusted covariate overdominant model while it had no significant difference in the adjusted covariate overdominant model. Compared to GG genotype, rs2167270 of AG genotype had statistical significance in both the adjusted and unadjusted covariate codominant models. And rs16147 had statistical significance in robust test, stealth model and overdominant model, and adjusting and unadjusting covariate. This study found linkage disequilibrium existed between rs2167270 and rs4731426 of LEP, rs10889502 and rs17127107 of JAK1, rs2970847 and rs6821591 of PPARGC1A, rs249429 and rs3805486 of PRKAA1, rs1342382 and rs6588640 of PRKAA2, rs3766522 and rs6937 of PRKAB2, rs2970847 and rs6821591 of PRKAG2, and rs6436094 and rs645163 of PRKAG3. There was no positive finding with statistical significance from the unconditional logistic regression of the mentioned genes' haplotype of LD block.

Conclusions

LEP signaling pathway association with T2DM remained to be confirmed in Chinese Han population, although rs2167270 and rs16147 were significantly associated with T2DM.

The genome of the naturally evolved obesity-prone Ossabaw miniature pig

The feral pigs of Ossabaw Island (USA) have an outstanding propensity to obesity and develop complete metabolic syndrome (MetS) upon prolonged high energy dieting. We now report the first high quality genome of the Ossabaw pig with Contig N50 of ∼6.03 Mb, significantly higher than most other published pig genomes. Genomic comparison to Duroc reveals that variations including SNPs, INDELs and one ∼2 Mb inversion identified in Ossabaw pig may be related to its "thrifty" phenotype. Finally, an important positively selected gene (PSG) was found to be LEPR (leptin receptor) containing two positively selected sites which may lead to pseudogenization of this gene with possible significant effects on obesity and inflammation development. This work provides the first complete mapping of a genome representing a naturally 'feast and famine' evolved phenotype of MetS, serving as a blueprint to guide the search for new targets and new biomarkers for obesity comorbidities.

NetCore: a network propagation approach using node coreness

We present NetCore, a novel network propagation approach based on node coreness, for phenotype–genotype associations and module identification. NetCore addresses the node degree bias in PPI networks by using node coreness in the random walk with restart procedure, and achieves improved re-ranking of genes after propagation. Furthermore, NetCore implements a semi-supervised approach to identify phenotype-associated network modules, which anchors the identification of novel candidate genes at known genes associated with the phenotype. We evaluated NetCore on gene sets from 11 different GWAS traits and showed improved performance compared to the standard degree-based network propagation using cross-validation. Furthermore, we applied NetCore to identify disease genes and modules for Schizophrenia GWAS data and pan-cancer mutation data. We compared the novel approach to existing network propagation approaches and showed the benefits of using NetCore in comparison to those. We provide an easy-to-use implementation, together with a high confidence PPI network extracted from ConsensusPathDB, which can be applied to various types of genomics data in order to obtain a re-ranking of genes and functionally relevant network modules.

Temporal Leptin to Determine Cardiovascular and Metabolic Fate throughout the Life

Leptin links peripheral adiposity and the central nervous system (CNS) to regulate cardiometabolic physiology. Within the CNS, leptin receptor-expressing cells are a counterpart to circulating leptin, and leptin receptor-mediated neural networks modulate the output of neuroendocrine and sympathetic nervous activity to balance cardiometabolic homeostasis. Therefore, disrupted CNS leptin signaling is directly implicated in the development of metabolic diseases, such as hypertension, obesity, and type 2 diabetes. Independently, maternal leptin also plays a central role in the development and growth of the infant during gestation. Accumulating evidence points to the dynamic maternal leptin environment as a predictor of cardiometabolic fate in their offspring as it is directly associated with infant metabolic parameters at birth. In postnatal life, the degree of serum leptin is representative of the level of body adiposity/weight, a driving factor for cardiometabolic alterations, and therefore, the levels of blood leptin through the CNS mechanism, in a large part, are a strong determinant for future cardiometabolic fate. The current review focuses on highlighting and discussing recent updates for temporal dissection of leptin-associated programing of future cardiometabolic fate throughout the entire life.

LTA, LEP, and TNF-a Gene Polymorphisms are Associated with Susceptibility and Overall Survival of Diffuse Large B-Cell lymphoma in an Arab Population: A Case-Control Study

Objective:

In this study, we aimed to explore the relationship between five selected proinflammatory and immune-mediated genes (TNF rs1800629G>A, rs361525G>A, rs1799964T>C, LTA rs1800683G>A, rs909253A>G, TNFAIP8 rs1042541C>T, LEPR rs1327118G>C, and LEP rs2167270G>A) and the risk and overall survival of DLBCL patients within the Jordanian Arab population.

Methods:

One hundred twenty-five patients (125) diagnosed with DLBCL at the King Abdullah University Hospital (KAUH) between 2013 and 2018 and 238 healthy cancer-free control subjects with similar geographic and ethnic backgrounds to the patients were included in the study. Genomic DNA was extracted from the formalin-fixed paraffin-embedded tissues of the subjects and from peripheral blood samples of the controls. The Sequenom MassARRAY^® sequencer system (iPLEX GOLD) was used. The analyses included assessments of population variability and survival.

Results:

Our study showed significant differences in the distribution of the studied polymorphisms of DLBCL between the patients and controls for TNF rs1800629G>A, LTA rs909253 G>A and LEP rs2167270 G>A. TNF rs1800629G>A (p = 0.01), in which the G allele harbors a higher risk of DLBCL (GG and GA genotypes when compared with AA genotype) (p = 0.044). The LTA rs909253 A>G polymorphism is associated with a higher risk of DLBCL in the allelic model (p = .004). LEP rs2167270 G>A polymorphism is associated with a decreased risk of DLBCL in the recessive mode models (p = .03). Subjects with the dominant model for TNF-a rs1799964 (TT genotype in comparison with the combined TT/TC genotype) and patients with the homozygous genotype (GG) of rs361525 have better overall survival rates.

Conclusion:

Our results confirmed the diversity and the heterogeneity of the disease. Although the study has a limitation because of its relatively small size, it clearly emphasizes the significance of ancestry and genetic composition as the determinants of DLBCL risk and behavior.

Transcriptional Profiling and Biological Pathway(s) Analysis of Type 2 Diabetes Mellitus in a Pakistani Population

The epidemic of type 2 diabetes mellitus (T2DM) is an important global health concern. Our earlier epidemiological investigation in Pakistan prompted us to conduct a molecular investigation to decipher the differential genetic pathways of this health condition in relation to non-diabetic controls. Our microarray studies of global gene expression were conducted on the Affymetrix platform using Human Genome U133 Plus 2.0 Array along with Ingenuity Pathway Analysis (IPA) to associate the affected genes with their canonical pathways. High-throughput qRT-PCR TaqMan Low Density Array (TLDA) was performed to validate the selected differentially expressed genes of our interest, viz., ARNT, LEPR, MYC, RRAD, CYP2D6, TP53, APOC1, APOC2, CYP1B1, SLC2A13, and SLC33A1 using a small population validation sample (n = 15 cases and their corresponding matched controls). Overall, our small pilot study revealed a discrete gene expression profile in cases compared to controls. The disease pathways included: Insulin Receptor Signaling, Type II Diabetes Mellitus Signaling, Apoptosis Signaling, Aryl Hydrocarbon Receptor Signaling, p53 Signaling, Mitochondrial Dysfunction, Chronic Myeloid Leukemia Signaling, Parkinson's Signaling, Molecular Mechanism of Cancer, and Cell Cycle G1/S Checkpoint Regulation, GABA Receptor Signaling, Neuroinflammation Signaling Pathway, Dopamine Receptor Signaling, Sirtuin Signaling Pathway, Oxidative Phosphorylation, LXR/RXR Activation, and Mitochondrial Dysfunction, strongly consistent with the evidence from epidemiological studies. These gene fingerprints could lead to the development of biomarkers for the identification of subgroups at high risk for future disease well ahead of time, before the actual disease becomes visible.

Leptin, cardiovascular diseases and type 2 diabetes mellitus

Leptin, an adipokine that is implicated in the control of food intake via appetite suppression, may also stimulate oxidative stress, inflammation, thrombosis, arterial stiffness, angiogenesis and atherogenesis. These leptin-induced effects may predispose to the development of cardiovascular diseases. In the present review we discuss the evidence linking leptin levels with the presence, severity and/or prognosis of both coronary artery disease and non-cardiac vascular diseases such as stroke, carotid artery disease, peripheral artery disease (PAD) and abdominal aortic aneurysms (AAA) as well as with chronic kidney disease (CKD) and type 2 diabetes mellitus (T2DM). Leptin levels have been positively associated with the presence, severity, extent and lesion complexity of coronary atherosclerosis as well as with the presence, severity and poor clinical outcomes of both ischemic and hemorrhagic strokes. But conflicting results also exist. Furthermore, leptin was reported to independently predict common carotid intima-media thickness and carotid plaque instability. A link between hyperleptinemia and PAD has been reported, whereas limited data were available on the potential association between leptin and AAA. Elevated leptin concentrations have also been related to CKD incidence and progression as well as with insulin resistance, T2DM, micro- and macrovascular diabetic complications. Statins and antidiabetic drugs (including sitagliptin, metformin, pioglitazone, liraglutide and empagliflozin) may affect leptin levels. Further research is needed to establish the potential use (if any) of leptin as a therapeutic target in these diseases.

Insulin dysregulation plays a critical role in colon inflammation: a bioinformatics approach

AIM

Evaluating and screening of genes related to colorectal inflammation of mice for finding critical ones in this disease was the aim of this study.

BACKGROUND

Many studies are shown direct relationship between inflammation and colorectal cancer onset and development. Several molecular aspects of inflammation are investigated to discover molecular mechanism of this disease.

METHODS

Profiles of differentially expressed genes (DEGs) of mice inflamed colorectal tissue in comparison with normal samples are obtained from Gene Expression Omnibus (GEO) database. The significant and characterized DEGs were screened via protein-protein interaction (PPI) network. Hubs of the network were determined and backbone network was constructed. Moreover, action network for the critical nodes was constructed and analyzed.

RESULTS

Eight central genes including IL6, ALB, PRDM10, AKT1, GAPDH, IL8, INS and TNF were determined as hub nodes. Findings indicate that insulin plays critical role in regulation of hub genes. This finding shows association between inflammation and metabolism dysregulation. Except PRDM10 and GAPDH, the other hubs show considerable regulatory effects on each other.

CONCLUSION

Inflammation of colorectal tissue is strongly depended on metabolism especially to insulin function.