The association between leptin receptor gene polymorphisms and type 2 diabetes mellitus: A systematic review and meta-analysis

Genetic predisposition of LEPR (rs1137101) gene polymorphism related to type 2 diabetes mellitus - a meta-analysis

Background: Type 2 diabetes mellitus (T2DM) is a multifaceted disease appropriate to elevated blood glucose levels resulting from decreased insulin and beta-cell activity. Using a case-control methodology, researchers have examined the relationship between polymorphisms in LEPR and T2DM in a population from south India.Materials and Methods: We conducted a genetic analysis of 311 participants, and results were accomplished using a case-control study, a meta-analysis of previous studies on LEPR was conducted, and type 2 diabetes genotype distribution across various geographical regions Malaysians, Chinese Han, Kuwait, Iran, Mongolia, and Han Chinese, Greece, Saudi, India (North India, Punjabi), (South India, Tamilnadu). The study involved 254 prospective investigations, and nine association studies were preferred according to preset criteria. Studies were assessed for quality using the Hardy-Weinberg equilibrium (HWE) and the Newcastle-Ottawa Scale (NOS). An analysis of the genetic models was conducted to determine their relationship, statistical analysis was utilized to calculate odds ratios (ORs) and matching 95% confidence intervals (CIs).Results: The LEPR-rs1137101 polymorphism in the case-control study was associated with a significant increase in the risk of type 2 diabetes. A meta-analysis revealed a connection between LEPR gene polymorphism (rs1137101) and type 2 diabetes risk. Investigators might gain a more profound thought on the significance of the identified genetic variation and its impact on the chance of developing type 2 diabetes by verifying and strengthening previously reported findings. The model of fixed effects was chosen due to the low heterogeneity, and significant associations were observed in the allelic (OR = 0.79, 95% CI [0.70-0.87]), homozygote (OR = 0.58, 95% CI [0.46-0.72]), dominant (OR = 0.66, 95% CI [0.56-0.79]), and recessive (OR = 0.83, 95% CI [0.71-0.96]) genetic models. A Begg's funnel plot and Egger's test indicated no publication bias. These findings suggest that the rs1137101 variant in the LEPR gene has been linked to a higher risk of T2DM.Conclusions: A larger sample size, however, is required for further research, and consideration of potential confounding factors is needed to validate these associations. Understanding the implications of LEPR gene polymorphisms in T2DM susceptibility may contribute to personalized treatment strategies for patients with T2DM.

Association of TNF-α 308G/A and LEPR Gln223Arg Polymorphisms with the Risk of Type 2 Diabetes Mellitus

The objective of the present study was to identify the association of the TNF-α- 308G/A and leptin receptor (LEPR) Gln223Arg polymorphisms with the risk of development of type 2 diabetes mellitus (T2DM). Methods: A total of 160 volunteers were studied: 108 with T2DM and 52 participants as control, who served as the control group. Polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) for the genomic region of TNF-α- 308G/A and LEPR Gln223Arg were carried out. Results: The frequency of LEPR Gln223Arg genotypes in T2DM and control groups showed significant differences in the distribution of genotypes (p < 0.05). The frequency also of TNF-α- 308G/A genotypes in T2DM and control subjects showed significant differences in the distribution of genotypes (p < 0.05). Conclusion: Our results indicate that there are significant differences in the distribution of genotypes and alleles between the individuals with T2DM and control subjects (p < 0.05).

A network analysis framework of genetic and nongenetic risks for type 2 diabetes

Both genetic and nongenetic factors have been found to be associated with type 2 diabetes, however, the correlation between them is still unclear. In the present study, we aimed to fully decipher the nongenetic and genetic factor association network for type 2 diabetes. We identified risk factors for type 2 diabetes by systematically searching for related meta-analyses and genome-wide association studies (GWAS) database. Among a total of 27,822 studies screened, 202 articles were eligible, from which 174 nongenetic factors and 210 genetic factors associated with type 2 diabetes were identified. Then, we obtained 584 associations between the nongenetic and genetic factors of type 2 diabetes, based on which a risk factor association network was conducted. The nongenetic factors could be classified into seven categories according to the Global Burden of Diseases (GBD). Of these seven categories of nongenetic factors, five were found to be correlated with genes associated with type 2 diabetes, including environmental risks, behavioral risks, metabolic risks, related disease of type 2 diabetes, and treatments. Specifically, air pollutants of environmental risks, alcohol using of behavioral risks, obesity of metabolic risks, rheumatoid arthritis of related disease risk, and simvastatin of treatment was correlated with the largest number of genes. In summary, the correlation between genetic factors and nongenetic factors identified in this study indicates that there is a common phenotype-genotype association in type 2 diabetes, with the combinations of genotypes ("genetic signature") clustering in phenotypes related to type 2 diabetes. Thus, we should take a systematic approach to explore the relationship of various factors for type 2 diabetes, as well as other noncommunicable diseases.

Contrasting association of Leptin receptor polymorphisms and haplotypes with polycystic ovary syndrome in Bahraini and Tunisian women: a case-control study

BACKGROUND

The present study examined the contribution of ethnicity to the association of leptin receptor gene (LEPR) gene variants with polycystic ovary syndrome (PCOS) in Tunisian and Bahraini Arabic-speaking women.

METHODS

Subjects consisted of 320 women with PCOS, and 446 eumenorrhic women from Tunisia, and 242 women with PCOS and 238 controls from Bahrain. Genotyping of (exonic) rs1137100 and rs1137101 and (intronic) rs2025804 LEPR variants was done by allelic exclusion.

RESULTS

The minor allele frequencies (MAFs) of rs1137100 and rs1137101 were significantly different between PCOS cases and control women from Bahrain but not Tunisia, and LEPR rs1137101 was associated with increased PCOS susceptibility only in Bahraini subjects. Furthermore, rs1137100 was associated with decreased PCOS risk among Bahrainis under codominant and recessive models; rs1137100 was negatively associated with PCOS in Tunisians after controlling for testosterone. In addition, rs2025804 was associated with increased PCOS risk among Tunisian but not Bahraini women, after adjusting for key covariates. Negative correlation was seen between rs1137101 and triglycerides in Tunisians, while homeostasis model assessment of insulin resistance (HOMA-IR) and insulin correlated with rs2025804 and rs1137101 among Bahraini subjects, and rs1137101 correlated with estradiol and prolactin. Taking TAG haplotype as common, positive association of TAA and negative association of TGG haplotype with PCOS was seen among Bahraini women; no three-locus PCOS-associated haplotypes were found in Tunisians.

CONCLUSIONS

The present study is the first to demonstrate the contribution of ethnicity to the association of LEPR gene variants with PCOS, thereby highlighting the significance of controlling for ethnicity in gene association investigations.

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.

Shared genetic architecture and casual relationship between leptin levels and type 2 diabetes: large-scale cross-trait meta-analysis and Mendelian randomization analysis

OBJECTIVE

We aimed to estimate genetic correlation, identify shared loci and test causality between leptin levels and type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

Our study consists of three parts. First, we calculated the genetic correlation of leptin levels and T2D or glycemic traits by using linkage disequilibrium score regression analysis. Second, we conducted a large-scale genome-wide cross-trait meta-analysis using cross-phenotype association to identify shared loci between trait pairs that showed significant genetic correlations in the first part. In the end, we carried out a bidirectional MR analysis to find out whether there is a causal relationship between leptin levels and T2D or glycemic traits.

RESULTS

We found positive genetic correlations between leptin levels and T2D (R_g=0.3165, p=0.0227), fasting insulin (FI) (R_g=0.517, p=0.0076), homeostasis model assessment-insulin resistance (HOMA-IR) (R_g=0.4785, p=0.0196), as well as surrogate estimates of β-cell function (HOMA-β) (R_g=0.4456, p=0.0214). We identified 12 shared loci between leptin levels and T2D, 1 locus between leptin levels and FI, 1 locus between leptin levels and HOMA-IR, and 1 locus between leptin levels and HOMA-β. We newly identified eight loci that did not achieve genome-wide significance in trait-specific genome-wide association studies. These shared genes were enriched in pancreas, thyroid gland, skeletal muscle, placenta, liver and cerebral cortex. In addition, we found that 1-SD increase in HOMA-IR was causally associated with a 0.329 ng/mL increase in leptin levels (β=0.329, p=0.001).

CONCLUSIONS

Our results have shown the shared genetic architecture between leptin levels and T2D and found causality of HOMA-IR on leptin levels, shedding light on the molecular mechanisms underlying the association between leptin levels and T2D.

Obstructive sleep apnea and hypertriglyceridaemia share common genetic background: Results of a twin study

Obstructive sleep apnea is associated with an increased risk of hypertension, diabetes and dyslipidaemia. Both obstructive sleep apnea and its comorbidities are at least partly heritable, suggesting a common genetic background. Our aim was to analyse the heritability of the relationship between obstructive sleep apnea and its comorbidities using a twin study. Forty-seven monozygotic and 22 dizygotic adult twin pairs recruited from the Hungarian Twin Registry (mean age 51 ± 15 years) attended an overnight diagnostic sleep study. A medical history was taken, blood pressure was measured, and blood samples were taken for fasting glucose, total cholesterol, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol and lipoprotein (a). To evaluate the heritability of obstructive sleep apnea and its comorbidities bivariate analysis was performed with an adjustment for age, gender, body mass index (BMI) and smoking after false discovery rate correction and following exclusion of patients on lipid-lowering and antidiabetic medications. There was a significant correlation between indices of obstructive sleep apnea severity, such as the apnea-hypopnea index, oxygen desaturation index and percentage of sleep time spent with oxygen saturation below 90%, as well as blood pressure, serum triglyceride, lipoprotein (a) and glucose levels (all p < .05). The bivariate analysis revealed a common genetic background for the correlations between serum triglyceride and the oxygen desaturation index (r = .63, p = .03), as well as percentage of sleep time spent with oxygen saturation below 90% (r = .58, p = .03). None of the other correlations were significantly genetically or environmentally determined. This twin study demonstrates that the co-occurrence of obstructive sleep apnea with hypertriglyceridaemia has a genetic influence and heritable factors play an important role in the pathogenesis of dyslipidaemia in obstructive sleep apnea.

Associations between cytotoxic T-lymphocyte-associated antigen 4 gene polymorphisms and diabetes mellitus: a meta-analysis of 76 case-control studies

Background: Several genetic association studies already investigated potential roles of cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) gene polymorphisms in diabetes mellitus (DM), with inconsistent results. Therefore, we performed this meta-analysis to better assess the relationship between CTLA-4 gene polymorphisms and DM in a larger pooled population.

Methods: PubMed, Embase, Web of Science, and CNKI were systematically searched for eligible studies. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to estimate the strength of associations between CTLA-4 gene polymorphisms and DM in all possible genetic models.

Results: A total of 76 studies were finally included in our analyses. Significant associations with susceptibility to type 1 diabetes mellitus (T1DM) were detected for rs231775 (dominant model: P=0.008, OR = 0.83, 95%CI 0.73–0.95; recessive model: P=0.003, OR = 1.27, 95%CI 1.09–1.50; allele model: P=0.004, OR = 0.85, 95%CI 0.77–0.95) and rs5742909 (recessive model: P=0.02, OR = 1.50, 95%CI 1.05–2.13) polymorphisms in overall population. Further subgroup analyses revealed that rs231775 polymorphism was significantly associated with susceptibility to T1DM in Caucasians and South Asians, and rs5742909 polymorphism was significantly associated with susceptibility to T1DM in South Asians. Moreover, rs231775 polymorphism was also found to be significantly associated with susceptibility to type 2 diabetes mellitus (T2DM) in East Asians and South Asians.

Conclusions: Our findings indicated that rs231775 and rs5742909 polymorphisms may serve as genetic biomarkers of T1DM, and rs231775 polymorphism may also serve as a genetic biomarker of T2DM.

Systematic Meta-analysis Revealed an Association of PGC-1α rs8192678 Polymorphism in Type 2 Diabetes Mellitus

Background

Genome-wide association study (GWAS) provides an unprecedented opportunity to reveal substantial genetic contribution to type 2 diabetes mellitus (T2DM) and glycemic identification of allelic heterogeneity and population-specific genetic variants, yet it also faces difficulty due to the vast amount of potential confounding factors and limited availability of clinical data. To identify responsible susceptibility loci and genomic polymorphism for T2DM and glycemic traits, we have systematically investigated a genome-wide association study related to T2DM. Although GWAS has captured many common genetic variations, which are related to T2DM, each risk allele (RA) of single-nucleotide polymorphisms (SNPs) at these loci is not conclusive. Therefore, it is common to present a combination of several SNPs to infer T2DM risk, yet it is still insufficient to be deterministic. To streamline the identification of a deterministic genetic variation in T2DM, we developed this meta-analysis as a showcase to comprehensively identify the association between cumulative RAs and T2DM risk by combining different studies in reported literature and databases. After all, we identified that PGC-1α rs8192678 polymorphism can be considered as a potentially deterministic biomarker in T2DM risk. Previous studies have potentially linked PGC-1α rs8192678 polymorphism to type 2 diabetes mellitus (T2DM) risk, but the results remain inconsistent in different populations and are not conclusive. We developed a new meta-analysis approach to systematically identify the association between PGC-1α rs8192678 polymorphism and T2DM, and we have comprehensively assessed different ethnic groups to validate our findings.

Methods

We performed comprehensive information retrieval and knowledge discovery meta-analysis by searching extensively published literature and different electronic databases to acquire eligible studies for the above association study. We developed a method to use pooled odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) in five genetic models (allelic, dominant, recessive, homozygous, and heterozygous genetic models) to identify the relationship among ethnicity subgroup analyses comprehensively.

Results

We identified 20 eligible studies consisting of 16,182 subjects (8,038 cases and 8,144 controls) in our meta-analysis. PGC-1α rs8192678 polymorphisms of all subjects showed a significant association with T2DM susceptibility under all genetic models: allelic (OR: 1.24, 95% CI: 1.13-1.35), dominant (OR: 1.27, 95% CI: 1.14-1.42), recessive (OR: 1.24, 95% CI: 1.14-1.36), homozygous (OR: 1.40, 95% CI: 1.20-1.64), and heterozygous (OR: 1.20, 95% CI: 1.06-1.35). In the subgroup analysis, we identified a significant association between PGC-1α rs8192678 polymorphism and T2DM in the Caucasian and Indian populations under all genetic models we investigated. This is the most comprehensive study of the subject to date.

Conclusion

Our development of meta-analysis revealed that the minor allele (A) carriers, especially AA genotype carriers, can lead to risk of T2DM in the Caucasian and Indian populations. This is the first report that such risk has been confirmed. Our finding shed new light into the genetic alteration in T2DM.

Genetic associations between Transcription Factor 7 Like 2 rs7903146 polymorphism and type 2 diabetes mellitus: a meta-analysis of 115,809 subjects

BACKGROUND

Some genetic association studies tried to investigate potential associations of Transcription Factor 7 Like 2 (TCF7L2) rs7903146 polymorphism with type 2 diabetes mellitus (T2DM). However, the results of these studies were not consistent. Thus, we performed the present meta-analysis to explore associations between TCF7L2 rs7903146 polymorphism and T2DM in a larger pooled population.

METHODS

Systematic literature research of PubMed, Web of Science and Embase was performed to identify eligible studies for pooled analyses. I² statistics were employed to assess between-study heterogeneities. If I² was greater than 50%, random-effect models (REMs) would be used to pool the data. Otherwise, fixed-effect models (FEMs) would be applied for synthetic analyses.

RESULTS

Totally 68 studies with 115,809 subjects were included for analyses. The pooled analyses showed that TCF7L2 rs7903146 (dominant model: p < 0.0001; recessive model: p < 0.0001; over-dominant model: p < 0.0001; allele model: p < 0.0001) polymorphism was significantly associated with susceptibility to T2DM in overall population. Further subgroup analyses revealed similar significant findings in both Asians and Caucasians.

CONCLUSIONS

In conclusion, our findings supported that TCF7L2 rs7903146 polymorphism could be used to identify individuals at high risk of developing T2DM in Asians and Caucasians.

Association of type 2 diabetes susceptible genes GCKR, SLC30A8, and FTO polymorphisms with gestational diabetes mellitus risk: a meta-analysis

PURPOSE

Current studies have detected the correlation of polymorphisms in type 2 diabetes susceptible genes GCKR, SLC30A8 and FTO with gestational diabetes mellitus (GDM) risk. However, findings of these studies were incongruous. Hence, we performed an integrated review and meta-analysis for the researches regarding the association of single nucleotide polymorphisms (SNPs) in GCKR, SLC30A8 and FTO genes and GDM risk.

METHODS

Eligible publications were selected on the basis of several inclusion and exclusion criteria. Correlation between each SNP and GDM risk was estimated by computing odds ratios (ORs) with 95% confidence intervals (95%CIs).

RESULTS

Consequently, 19 case-control studies (from 16 citations) including 3636 GDM cases and 7229 GDM-free controls were participated in a meta-analysis of seven prevalent SNPs (GCKR rs1260326 and rs780094; SLC30A8 rs13266634 and rs11558471; FTO rs8050136, rs1421085 and rs9939609). Our results demonstrated that the rs780094, rs13266634 and rs9939609 SNPs were significantly associated with GDM risk. In stratified analysis, correlations of rs780094 and rs13266634 SNPs could be observed in Asian and Caucasian subgroups. Moreover, association between rs9939609 SNP and GDM risk was detected in Caucasian subgroup.

CONCLUSIONS

The GCKR rs780094, SLC30A8 rs13266634 and FTO rs9939609 SNPs were demonstrated to be the potential biomarkers for GDM risk prediction.

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.

Secure Communication through MultiAgent System-Based Diabetes Diagnosing and Classification

The main objective of the research is to provide a multi-agent data mining system for diagnosing diabetes. Here, we use multi-agents for diagnosing diabetes such as user agent, connection agent, updation agent, and security agent, in which each agent performs their own task under the coordination of the connection agent. For secure communication, the user symptoms are encrypted with the help of Elliptic Curve Cryptography and Optimal Advanced Encryption Standard. In Optimal Advanced Encryption Standard algorithm, the key values are optimally selected by means of differential evaluation algorithm. After receiving the encrypted data, the suggested method needs to find the diabetes level of the user through multiple kernel support vector machine algorithm. Based on that, the agent prescribes the drugs for the corresponding user. The performance of the proposed technique is evaluated by classification accuracy, sensitivity, specificity, precision, recall, execution time and memory value. The proposed method will be implemented in JAVA platform.

Differential Transcriptome Analysis of Early Postnatal Developing Longissimus Dorsi Muscle from Two Pig Breeds Characterized in Divergent Myofiber Traits and Fatness

Meat quality traits (MQTs) are very important in the porcine industry, which are mainly determined by skeletal muscle fiber composition, extra-muscular and/or intramuscular fat content. To identify the differentially expressed candidate genes affecting the meat quality traits, first we compared the MQTs and skeletal muscle fiber characteristics in the longissimus dorsi muscle (LDM) of the Northeast Min pig (NM) and the Changbaishan wild boar (CW) with their body weight approaching 90 kg. The significant divergences in the skeletal muscle fiber phenotypes and fatness traits between the two porcine breeds established an ideal model system for further identifying potential key functional genes that dominated MQTs. Further, a transcriptome profile analysis was performed using the Illumina sequencing method in early postnatal developing LDM from the two breeds at the ages of 42 days. Comparative analysis between these two cDNA libraries showed that there were 17,653 and 22,049 unambiguous tag-mapped sense transcripts detected from NM and CW, respectively. 4522 differentially expressed genes (DEGs) were revealed between the two tissue samples, of them, 4176 genes were found as having been upregulated and 346 genes were identified as having been downregulated in the NM library. By pathway enrichment analysis, a set of significantly enriched pathways were identified for the DEGs, which are potentially involved in myofiber development, differentiation and growth, lipogenesis and lipolysis in porcine skeletal muscle. The expression levels of 30 out of the DEGs were validated by real-time quantitative reverse transcriptase PCR (qRT-PCR) and the observed result was consistent noticeably with the Illumina transcriptome profiles. The findings from this study can contribute to future investigations of skeletal muscle growth and development mechanism and to establishing molecular approaches to improve meat quality traits in pig breeding.

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

Background

Leptin acts as a mediator of inflammation and energy homeostasis by activating leptin receptor (LEPR). We conducted this study to explore the association of polymorphisms in LEPR with type 2 diabetes mellitus (T2DM) and its related metabolic traits.

Methods

We performed a case–control study to investigate the association of polymorphisms in LEPR with T2DM and related metabolic traits in a Chinese population, with a total of 922 T2DM patients and 1031 nondiabetic subjects. Polymorphisms were genotyped using MassARRAY assay.

Results

The G allele of rs1327118 was associated with a decreased risk of T2DM in men (P = 0.044, odds ratio = 0.707, 95% confidence interval = 0.504–0.991) and the G allele of rs3806318 was associated with increased systolic blood pressure (SBP) in men with T2DM. Besides, the women patients carrying the G allele of rs1327118 showed increased SBP and diastolic blood pressure (DBP) levels, but decreased high density lipoprotein cholesterol (HDL-C) level.

Conclusion

Our results suggest that rs1327118 may be associated with SBP, DBP and HDL-C levels in women with T2DM, and rs3806318 may be associated with T2DM and SBP level in men with T2DM. Further studies with larger sample size or functional experiments focused on exact mechanism are required to verify our observations.

A meta-analysis of associations of LEPR Q223R and K109R polymorphisms with Type 2 diabetes risk

Background

Leptin receptor (LEPR) plays a pivotal role in the control of body weight, energy metabolism, and insulin sensitivity. Various genetic association studies were performed to evaluate associations of LEPR genetic variants with type 2 diabetes (T2D) susceptibility.

Methods

A comprehensive search was conducted to identify all eligible case-control studies for examining the associations of LEPR single nucleotide polymorphisms (SNPs) Q223R (rs1137101) and K109R (rs1137100) with T2D risk. Odds ratios (OR) and corresponding 95% confidence intervals (CIs) were used to measure the magnitudes of association.

Results

For Q223R, 13 studies (11 articles) consisting of a total of 4030 cases and 2844 controls, and for K109R 7 studies (7 articles) consisting of 3319 cases and 2465 controls were available. Under an allele model, Q223R was not significantly associated with T2D risk (OR = 1.09, 95% CI: 0.80–1.48, P-value = 0.5989), which was consistent with results obtained under four genotypic models (ranges: ORs 1.08–1.20, 95% CIs: 0.58–2.02 to 0.64–2.26; P-values, 0.3650–0.8177, which all exceeded multiplicity-adjusted α = 0.05/5 = 0.01). In addition, no significant association was found between K109R and T2D risk based on either an allele model (OR = 0.93, 95% CI: 0.85–1.03, P-value = 0.1868) or four genotypic models (ranges: ORs 0.81–0.99, 95% CIs: 0.67–0.86 to 0.97–1.26, P-values, 0.0207–0.8804 which all exceeded multiplicity-adjusted α of 0.01). The magnitudes of association for these two SNPs were not dramatically changed in subgroup analyses by ethnicity or sensitivity analyses. Funnel plot inspections as well as Begg and Mazumdar adjusted rank correlation test and Egger linear regression test did not reveal significant publication biases in main and subgroup analyses. Bioinformatics analysis predicted that both missense SNPs were functionally neutral and benign.

Conclusions

The present meta-analysis did not detect significant genetic associations between LEPR Q223R and K109R polymorphisms and T2D risk.

LEPR gene polymorphism and plasma soluble leptin receptor levels are associated with polycystic ovary syndrome in Han Chinese women

Aim: To investigate the association of LEPR polymorphisms and plasma leptin and soluble leptin receptor (sOB-R) levels with polycystic ovary syndrome (PCOS) in Chinese women. Patients & methods: LEPR Lys109Arg (rs1137100) and Gln223Arg (rs1137101) polymorphisms of PCOS patients and the controls were genotyped. Plasma leptin and sOB-R levels of two groups were measured. Results: The genotypic distributions of Lys109Arg (rs1137100) differed between the PCOS and control groups. Plasma sOB-R levels increased significantly in PCOS patients and were associated with PCOS independent of BMI. Furthermore, luteinizing hormone, triglyceride and fasting blood glucose correlated significantly to PCOS patients’ sOB-R levels. Conclusion: LEPR Lys109Arg (rs1137100) was associated with PCOS susceptibility and genotype AA was deduced to be a protective factor for PCOS; sOB-R levels might be recognized as a new indicator for the severity of PCOS.

LEPR gene Gln223Arg polymorphism and type 2 diabetes mellitus: a meta-analysis of 3,367 subjects

Background

The Leptin receptor (LEPR) Gln223Arg gene polymorphism has been associated with an increased susceptibility to Type 2 diabetes mellitus (T2DM). Results from various studies, however, are inconsistent.

Objective and methods

To better elucidate the association of LEPR Gln223Arg gene polymorphism with T2DM in the Chinese population, a meta-analysis of 3,367 subjects from seven independent studies was performed. The pooled odds ratios (ORs) and corresponding 95% confidence intervals (95% CI) were evaluated by the fixed-effects model.

Results

A significant relationship between LEPR Gln223Arg gene polymorphism and T2DM in the Chinese population was found under allele (OR: 1.432, 95% CI: 1.211-1.694, P=2.67×10^-5), dominant (OR: 1.466, 95% CI: 1.215-1.769, P=6.33×10^-5), recessive (OR: 0.539, 95% CI: 0.303-0.960, P=0.036), heterozygous (OR: 0.700, 95% CI: 0.577-0.849, P=3.06×10^-4), and homozygous (OR: 0.472, 95% CI: 0.265-0.839, P=0.011) genetic models.

Conclusions

LEPR Gln223Arg gene polymorphism was associated with an increased risk of T2DM in the Chinese population. Therefore, Chinese carriers of the G allele of LEPR Gln223Arg gene polymorphism may be more susceptible to T2DM than the general population.

Leptin Receptor Gene Polymorphism and the Risk of Cardiovascular Disease: A Systemic Review and Meta-Analysis

OBJECTIVE

Few studies have assessed the association between leptin receptor (LEPR) gene polymorphism and the risk of cardiovascular disease (CVD). Of the few epidemiological studies on this topic, the results are still controversial.

METHODS

PubMed and Embase were screened for studies from their inception to 9 October 2016. The pooled odds ratio (OR) with the corresponding confidence intervals (CI) were used to measure the effect size for studies that reported the association under allelic, homozygous, and dominant models. Pre-specified characteristics were conducted in the subgroup analysis. Heterogeneity between subgroups was evaluated by meta-regression analysis.

RESULTS

Seven eligible studies involving 44,133 participants were included in our meta-analysis. Borderline significant association was observed between the LEPR gene polymorphism (rs1137101, rs1137100, rs6700896, and rs8179183) and the increased risk of CVD with considerable heterogeneity under the allelic model, and the overall pooled OR (95% CI) was 1.10 (0.99, 1.22). The LEPR gene variant rs6700896, 109G allele, and 109GG genotype were significantly associated with the increased risk of CVD. Furthermore, stratified group analysis revealed that the association was more pronounced for stroke. Race-differences might also cause the considerable heterogeneity and non-significant association.

CONCLUSIONS

This is the first systematic review and meta-analysis to investigate the association between LEPR gene variants and CVD risk. Some LEPR gene variants were significantly associated with the increased risk of CVD. However, the present study is limited in its small number of included studies, considerable heterogeneity, and observational study design. Further research is still warranted to confirm the magnitude of the association.