Association of His1085His INSR gene polymorphism with type 2 diabetes in South Indians

Current Update on Categorization of Migraine Subtypes on the Basis of Genetic Variation: a Systematic Review

Migraine is a complex neurovascular disorder that is characterized by severe behavioral, sensory, visual, and/or auditory symptoms. It has been labeled as one of the ten most disabling medical illnesses in the world by the World Health Organization (Aagaard et al Sci Transl Med 6(237):237ra65, 2014). According to a recent report by the American Migraine Foundation (Shoulson et al Ann Neurol 25(3):252-9, 1989), around 148 million people in the world currently suffer from migraine. On the basis of presence of aura, migraine is classified into two major subtypes: migraine with aura (Aagaard et al Sci Transl Med 6(237):237ra65, 2014) and migraine without aura. (Aagaard K et al Sci Transl Med 6(237):237ra65, 2014) Many complex genetic mechanisms have been proposed in the pathophysiology of migraine but specific pathways associated with the different subtypes of migraine have not yet been explored. Various approaches including candidate gene association studies (CGAS) and genome-wide association studies (Fan et al Headache: J Head Face Pain 54(4):709-715, 2014). have identified the genetic markers associated with migraine and its subtypes. Several single nucleotide polymorphisms (Kaur et al Egyp J Neurol, Psychiatry Neurosurg 55(1):1-7, 2019) within genes involved in ion homeostasis, solute transport, synaptic transmission, cortical excitability, and vascular function have been associated with the disorder. Currently, the diagnosis of migraine is majorly behavioral with no focus on the genetic markers and thereby the therapeutic intervention specific to subtypes. Therefore, there is a need to explore genetic variants significantly associated with MA and MO as susceptibility markers in the diagnosis and targets for therapeutic interventions in the specific subtypes of migraine. Although the proper characterization of pathways based on different subtypes is yet to be studied, this review aims to make a first attempt to compile the information available on various genetic variants and the molecular mechanisms involved with the development of MA and MO. An attempt has also been made to suggest novel candidate genes based on their function to be explored by future research.

Glucose-Related Traits and Risk of Migraine—A Potential Mechanism and Treatment Consideration

Migraine and glucose-related (glycaemic) traits (fasting glucose, fasting insulin, and type 2 diabetes) are common and complex comorbid disorders that cause major economic and social burdens on patients and their families. Studies on the relationship between migraine and glucose-related traits have yielded inconsistent results. The purpose of this review is to synthesise and discuss the information from the available literature on the relationship between fasting glucose, fasting insulin, and type 2 diabetes (T2D) with migraine. Publications on migraine and fasting glucose, migraine and fasting insulin, and migraine and T2D were identified from a PubMed and Google Scholar database search and reviewed for this article. Multiple publications have suggested that the comorbidity of migraine and glucose-related traits may have a similar complex pathogenic mechanism, including impaired glucose homeostasis, insulin resistance, reduced cerebrovascular reactivity, abnormal brain metabolism, shared genetic factors, neurotransmitters, and sex hormones. Furthermore, several studies have found a bi-directional link between migraine with insulin resistance and T2D. There is strong evidence for a biological association between migraine headache and glucose-related traits, and burgeoning evidence for shared genetic influences. Therefore, genetic research into these comorbid traits has the potential to identify new biomarkers and therapeutic targets and provide biological insight into their relationships. We encourage healthcare professionals to consider the co-occurrence of migraine with glucose-related traits in the evaluation and treatment of their patients.

Clinical Manifestations of Hyperandrogenism and Ovulatory Dysfunction Are Not Associated with His1058 C/T SNP (rs1799817) Polymorphism of Insulin Receptor Gene Tyrosine Kinase Domain in Kashmiri Women with PCOS

BACKGROUND

Polycystic ovary syndrome (PCOS) is the most common endocrine metabolic disorder affecting premenopausal women. Besides primary features like anovulation, hyperandrogenism, and polycystic ovaries, women with PCOS present with multiple metabolic, cardiovascular, and psychological disorders. The etiology is multifactorial and the different genetic variants are suggested to play an important role in pathogenesis. Insulin resistance is a ubiquitous finding in PCOS and SNPs in genes involved in the insulin signaling pathway are possible candidates that can explain the development of clinical manifestations of PCOS.

AIM

We aimed to investigate the association of INSR His1058 C/T (rs1799817) single nucleotide polymorphism with PCOS in Kashmiri women. The genotypic-phenotypic correlation of the tested SNP with hyperandrogenism, ovulatory dysfunction, and metabolic markers was evaluated.

RESULTS

The allele frequency (OR = 1.00, 95% CI = 0.67-1.48, χ 2 = 0.01, P=0.99) and genotype distribution (χ 2 = 3.73, P=0.15) in INSR C/T polymorphism were comparable with controls. No significant association was found with PCOS in dominant (P=0.194), recessive (P=0.442), and homo vs. het. (P=0.5) genotype models. Genotype-phenotype correlation analysis revealed that variant TT genotype had significantly higher HOMA (P=0.029) and reduced insulin sensitivity QUICKI (P=0.037) values. There was no significant variation in the prevalence of hirsutism, acne, alopecia, menstrual disturbances, acanthosis nigricans, and obesity (all P > 0.05) in different INSR C/T genotypes.

CONCLUSION

The INSR C/T SNP (rs1799817) does not increase the risk of PCOS in Kashmiri women. This SNP is unlikely to play a significant role in the development and manifestation of clinical symptoms of polycystic ovary syndrome.

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-021-01129-0.

Concentration/activity of superoxide dismutase isozymes and the pro-/antioxidative status, in context of type 2 diabetes and selected single nucleotide polymorphisms (genes: INS, SOD1, SOD2, SOD3) - Preliminary findings

The alterations in concentration/activity of superoxide dismutase isozymes in the context of type 2 diabetes or obesity are well-described. Moreover, many hereditary factors, including single-nucleotide polymorphisms (SNPs) of genes for coding insulin, insulin receptors, or insulin receptor substrates (INS, INSR, IRS1, IRS2) or superoxide dismutase isozymes (SOD1, SOD2, SOD3), have been linked with the incidence of obesity and diabetes. However, the underlying changes in the plasma concentration/activity of superoxide dismutase isozymes and their potential connection with the said hereditary factors remain unexplored. Previously, we have observed that the plasma concentration/activity of superoxide dismutase isozymes differs in the context of obesity and/or rs2234694 (SOD1) and rs4880 (SOD2) and that the concentrations of SOD1, SOD2, SOD3 are correlated with each other. Intersexual variability of SOD1 concentration was detected regardless of obesity. In this study, the variability of concentration/activity of superoxide dismutase isozymes in plasma is considered in the context of type 2 diabetes and/or SNPs: rs2234694 (SOD1), rs5746105 (SOD2), rs4880 (SOD2), rs927450 (SOD2), rs8192287 (SOD3). Genotypic variability of SNP rs3842729 (INS), previously studied in the context of insulin-dependent diabetes, is investigated in terms of selected clinical parameters associated with type 2 diabetes. This study revealed higher SOD1 concentration in diabetic men compared to women, and extremely high SOD1 concentration, higher total superoxide dismutase, and copper-zinc superoxide dismutase activity, and lower superoxide dismutase and copper-zinc superoxide dismutase activity (when adjusted for the concentration of SODs) in the diabetic group regardless of sex. Multiple logistic regression, applied to explore possible links between the studied SNPs and other factors with the odds of type 2 diabetes or obesity, revealed that the genotypic variability of rs4880 (SOD2) could affect these odds, supporting the findings of several other studies.

Could insulin receptor H1085H C > T single nucleotide polymorphism predict insulin resistance in type 2 diabetic and chronic hepatitis C virus patients in Egypt?

Background

Insulin-receptor (INSR) is an α2β2 heterotetramer disulfide-linked trans-membrane glycoprotein and a family member of tyrosine kinase receptors. It mediates the pleiotropic actions of insulin regulating glucose homeostasis. It is encoded by a single gene: INSR gene. The INSR gene comprises 22 exons. Exons 17–22 encode the tyrosine kinase domain, and mutations in this region impair the function of the insulin receptor that may cause insulin resistance and hyperinsulinemia. Single nucleotide polymorphism with C > T substitution at His 1058 position of INSR (rs 1799817) located in exon 17 was considered to be involved in insulin resistance. Insulin receptor might be counter-regulated by degradation, differential expression, or modification by phosphorylation in cells expressing HCV core protein. HCV infection eventually leads to liver steatosis and fibrosis, increased oxidative stress, and peroxidation, all of which trigger a cascade of inflammatory responses, thus contributing to the development of insulin resistance. The present retrospective case-control aimed to study INSR H1085H C > T (rs 1799817) SNP in Egyptian patients suffering from chronic HCV infection with DM. The current study was conducted on two hundred and two participants of 100 males and 102 females, divided as follows: the control group (group I) included 50 apparently healthy volunteers of comparable age, sex, and socioeconomic status as patients groups, group II included 50 type 2 DM patients without HCV infection, group III included 52 chronic HCV infected patients without DM, and group IV included 50 HCV patients with DM.

Results

HOMA-IR and QUICKI index was significantly higher in the patient groups (groups II, III, and IV) than in controls (P < 0.001, P = 0.019, and P < 0.001, respectively). It was significantly lower in patients of group III than in patients of groups II and IV with P < 0.001 for both. DM patient group without HCV infection (group II) and HCV with DM (group IV) showed a significant decrease in CC genotypes and a significant increase in TT genotypes than the controls (P < 0.001, P = 0.018, respectively). HCV patients with DM (group IV) had the highest frequency of heterozygous genotype (CT) (50%). HCV-infected patients with T2DM (group IV) also showed a significantly higher frequency of minor allele (T) (35%) than controls (20%), and a lower frequency of the wild allele (C) (65%) than controls (80%).

Conclusion

The mutant allele “T” of INSR H1085H C > T (rs 1799817) SNP might be associated with an increased risk of developing insulin resistance and T2DM.

INSULIN AND INSULIN RECEPTOR GENE POLYMORPHISMS AND SUSCEPTIBILITY TO NONALCOHOLIC FATTY LIVER DISEASE

ABSTRACT BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is an increasing global health concern defined by excessive hepatic fat content in the absence of excessive alcohol consumption. OBJECTIVE: Given the pivotal role of insulin resistance in NAFLD, we hypothesized that insulin (INS) and insulin receptor (INSR) gene polymorphisms may be associated with NAFLD risk. METHODS: A total of 312 subjects, including 153 cases with biopsy-proven NAFLD and 159 controls were enrolled in this case-control study. Four polymorphisms in INS (rs3842752, rs689) and INSR (rs1052371, rs1799817) genes were genotyped using PCR-RFLP method. RESULTS: The cases with NAFLD were older and had higher BMI, systolic blood pressure, diastolic blood pressure, as well as higher serum levels of aspartate aminotransferase, alanine aminotransferase, and gamma glutamyl transferase than the controls (P<0.001). The “TT” genotype of INSR rs1799817 compared with “CC” genotype occurred more frequently in the controls than the cases with NAFLD and the difference remained significant after adjustment for confounding factors (P=0.018; OR=0.10, 95%CI=0.02-0.76). However, no significant difference was found for INS rs3842752, INS rs689, and INSR rs1052371 gene polymorphisms between the cases with NAFLD and the controls either before or after adjustment for the confounders. CONCLUSION: These findings corroborate the hypothesis that genetic polymorphisms related to insulin resistance play a role in NAFLD susceptibility. Specifically, the INSR rs1799817 “TT” genotype had a protective effect for NAFLD. However, our results remain to be validated in other studies.

Association of AMPK Pathway-Related Gene Polymorphisms with Symptomatic Intracranial Atherosclerotic Stenosis in a Chinese Han Population

Background and Objective: Recently, AMP-activated protein kinase (AMPK) signaling was confirmed to be intimately associated with atherosclerosis. Evidence indicates that genetic susceptibility plays an important role in the etiology of symptomatic intracranial atherosclerotic stenosis (sICAS), however few genes have been pinpointed being etiologically associated. This study investigated possible links between single nucleotide polymorphisms (SNPs) of AMPK-related genes and sICAS in Han Chinese subjects. Methods: Target gene sequencing was carried out in 400 sICAS Han Chinese patients and 1007 healthy controls for 11 AMPK pathway-related genes. Chi-squared testing and multiple logistic regression in dominant, recessive, and additive models were used to evaluate the association between SNPs and risk of sICAS. Bonferroni corrections were performed with a p < (0.05/44 = 0.0011) as statistically significant. Further subgroup data analyses was conducted using chi-squared or t-tests. Results: There were 44 common variants of 11 candidate genes distributed differently between sICAS patients and healthy controls, among which the INSR rs78312382 SNP remained significant even after a Bonferroni correction. Logistic regression analysis showed that rs78312382 was significantly associated with the risk of sICAS in both dominant and additive models (p_Bonferroni = 7.874e^-5 and 0.000506, respectively), with the A allele being much more prevalent in the sICAS group (p = 0.000404). Conclusions: Variants of the INSR rs7831282 locus may play an important role in the development of sICAS among the Han Chinese with the A allele being a risk factor and a potential biomarker for this illness.

Insulin Receptor Trafficking: Consequences for Insulin Sensitivity and Diabetes

Insulin receptor (INSR) has been extensively studied in the area of cell proliferation and energy metabolism. Impaired INSR activities lead to insulin resistance, the key factor in the pathology of metabolic disorders including type 2 diabetes mellitus (T2DM). The mainstream opinion is that insulin resistance begins at a post-receptor level. The role of INSR activities and trafficking in insulin resistance pathogenesis has been largely ignored. Ligand-activated INSR is internalized and trafficked to early endosome (EE), where INSR is dephosphorylated and sorted. INSR can be subsequently conducted to lysosome for degradation or recycled back to the plasma membrane. The metabolic fate of INSR in cellular events implies the profound influence of INSR on insulin signaling pathways. Disruption of INSR-coupled activities has been identified in a wide range of insulin resistance-related diseases such as T2DM. Accumulating evidence suggests that alterations in INSR trafficking may lead to severe insulin resistance. However, there is very little understanding of how altered INSR activities undermine complex signaling pathways to the development of insulin resistance and T2DM. Here, we focus this review on summarizing previous findings on the molecular pathways of INSR trafficking in normal and diseased states. Through this review, we provide insights into the mechanistic role of INSR intracellular processes and activities in the development of insulin resistance and diabetes.

RS1799817 in INSR associates with susceptibility to polycystic ovary syndrome

Background

Insulin and its receptor (INSR) have been implicated in the etiology of the polycystic ovarian syndrome (PCOS). Here, we investigate the association between INSR rs1799817 polymorphism and PCOS in Saudi Arabian women.

Methods

Study group included 126 PCOS women and 118 normo-ovulatory matched controls. The demographic data was recorded, and the plasma levels of glucose, lipids, leptin, E2, LH, FSH, T, SHBG, and insulin were determined. The genotypic and allele frequencies of rs1799817 were evaluated in both PCOS and control group. Polymerase chain reaction (PCR) was used to amplify Exon 17 of the INSR gene, and the amplified products were analyzed by direct sequencing. A single-nucleotide polymorphism (C to T) was found at locus 10923 (His1058) of rs1799817.

Results

In the PCOS group, the mutant allele T occurs at a significantly higher frequency (0.306) compared to the control group (0.174) (p<0.001). It shows a dominant effect and elevates the relative risk of PCOS even in the heterozygotes (RR=2.82). After stratification of the participants by body mass index, the frequency of T allele was significantly higher in the lean patients with PCOS compared to the lean control. The obese PCOS also had a higher frequency than the obese control, but the difference was not statistically significant. Several parameter values were affected by the INSR genotype, particularly W/H ratio, lipid, insulin and glucose levels and insulin resistance in PCOS patients.

Conclusions

The INSR gene polymorphism rs1799817 is a susceptibility locus associated with PCOS in Saudis and associated metabolic and hormonal changes, particularly, in the lean PCOS females.

In utero Exposure to Germinated Brown Rice and Its GABA Extract Attenuates High-Fat-Diet-Induced Insulin Resistance in Rat Offspring

BACKGROUND

Numerous studies have reported on the influence of diet on insulin resistance. Our study provides insight into the effect of germinated brown rice (GBR) and γ-aminobutyric acid (GABA) on early environment-driven programming and susceptibility to insulin resistance in rat offspring.

METHODS

Male rat offspring from female Sprague-Dawley rats fed with a high-fat diet (HFD) alone, HFD + GBR, or HFD + GABA extract throughout pregnancy and lactation were weaned 4 weeks after delivery and followed up for 8 weeks. A biochemical analysis and an assessment of the hepatic expression of insulin signaling genes were performed.

RESULTS

The results showed that intrauterine exposure to HFD caused metabolic perturbations in rat offspring which gravitated towards insulin resistance even though the rat offspring did not consume an HFD. GBR and GABA attenuated the HFD-induced changes by underlying regulation of the insulin signaling genes.

CONCLUSIONS

The results suggest that intake of GBR and GABA during pregnancy and lactation can influence the programming of genes in rat offspring, thereby enhancing insulin sensitivity.

Single-Nucleotide Polymorphism on Exon 17 of Insulin Receptor Gene Influences Insulin Resistance in PCOS: A Pilot Study on North Indian Women

Polycystic ovarian syndrome (PCOS), a major cause of infertility, is also strongly associated with insulin resistance. Defects in insulin receptor signaling are considered as one of the major molecular pathogeneses for insulin resistance. To investigate the possible mechanism of this signaling defect at genetic level, single-nucleotide polymorphism (SNP) [His 1085 C/T] at the exon 17 of insulin receptor gene (INSR) was studied in this pilot study. Polymerase chain reaction was performed on leucocytic DNA of women diagnosed with PCOS, selected from the outpatient department of Safdarjung Hospital, New Delhi, using suitable primer to amplify a region on INSR. An equal number of age-matched healthy women were selected as controls. SNP analysis was performed with restriction enzyme length polymorphism technique using Pm II enzyme. Serum insulin level was measured by ELISA kit and HOMA-IR was calculated mathematically. A higher frequency of the CC genotype was observed in PCOS women than in controls. Also, HOMA-IR, a tool for estimating insulin resistance, was significantly high in PCOS women with the CC genotype. C1008T SNP at exon 17 of INSR is associated with insulin resistance in Indian women with PCOS. Presence of CC genotype (C1085T) could be developed as a marker for insulin resistance and metabolic complications in PCOS women.

Risk-associated coding synonymous SNPs in type 2 diabetes and neurodegenerative diseases: genetic silence and the underrated association with splicing regulation and epigenetics

Single nucleotide polymorphisms (SNPs) are tentatively critical with regard to disease predisposition, but coding synonymous SNPs (sSNPs) are generally considered "neutral". Nevertheless, sSNPs in serine/arginine-rich (SR) and splice-site (SS) exonic splicing enhancers (ESEs) or in exonic CpG methylation targets, could be decisive for splicing, particularly in aging-related conditions, where mis-splicing is frequently observed. We presently identified 33 genes T2D-related and 28 related to neurodegenerative diseases, by investigating the impact of the corresponding coding sSNPs on splicing and using gene ontology data and computational tools. Potentially critical (prominent) sSNPs comply with the following criteria: changing the splicing potential of prominent SR-ESEs or of significant SS-ESEs by >1.5 units (Δscore), or formation/deletion of ESEs with maximum splicing score. We also noted the formation/disruption of CpGs (tentative methylation sites of epigenetic sSNPs). All disease association studies involving sSNPs are also reported. Only 21/670 coding SNPs, mostly epigenetic, reported in 33 T2D-related genes, were found to be prominent coding synonymous. No prominent sSNPs have been recorded in three key T2D-related genes (GCGR, PPARGC1A, IGF1). Similarly, 20/366 coding synonymous were identified in ND related genes, mostly epigenetic. Meta-analysis showed that 17 of the above prominent sSNPs were previously investigated in association with various pathological conditions. Three out of four sSNPs (all epigenetic) were associated with T2D and one with NDs (branch site sSNP). Five were associated with other or related pathological conditions. None of the four sSNPs introducing new ESEs was found to be disease-associated. sSNPs introducing smaller Δscore changes (<1.5) in key proteins (INSR, IRS1, DISC1) were also correlated to pathological conditions. This data reveals that genetic variation in splicing-regulatory and particularly CpG sites might be related to disease predisposition and that in-silico analysis is useful for identifying sSNPs, which might be falsely identified as silent or synonymous.

Prediction of disease genes using tissue-specified gene-gene network

BACKGROUND

Tissue specificity is an important aspect of many genetic diseases in the context of genetic disorders as the disorder affects only few tissues. Therefore tissue specificity is important in identifying disease-gene associations. Hence this paper seeks to discuss the impact of using tissue specificity in predicting new disease-gene associations and how to use tissue specificity along with phenotype information for a particular disease.

METHODS

In order to find out the impact of using tissue specificity for predicting new disease-gene associations, this study proposes a novel method called tissue-specified genes to construct tissues-specific gene-gene networks for different tissue samples. Subsequently, these networks are used with phenotype details to predict disease genes by using Katz method. The proposed method was compared with three other tissue-specific network construction methods in order to check its effectiveness. Furthermore, to check the possibility of using tissue-specific gene-gene network instead of generic protein-protein network at all time, the results are compared with three other methods.

RESULTS

In terms of leave-one-out cross validation, calculation of the mean enrichment and ROC curves indicate that the proposed approach outperforms existing network construction methods. Furthermore tissues-specific gene-gene networks make a more positive impact on predicting disease-gene associations than generic protein-protein interaction networks.

CONCLUSIONS

In conclusion by integrating tissue-specific data it enabled prediction of known and unknown disease-gene associations for a particular disease more effectively. Hence it is better to use tissue-specific gene-gene network whenever possible. In addition the proposed method is a better way of constructing tissue-specific gene-gene networks.