Increased Risk Of Type 2 Diabetes Mellitus Research Articles

Association of combined -344T/C and K173R polymorphisms in aldosterone synthase gene with type 2 diabetes mellitus in the Moroccan population.

Background: Aldosterone synthase (CYP11B2) is crucial for aldosterone production, and variations in its gene may influence type 2 diabetes mellitus (T2DM) development. This study explores the link between two single nucleotide polymorphisms (SNPs) in the CYP11B2 gene - -344T/C and K173R and T2DM in the Moroccan population . Methods: The research involved 86 individuals with T2DM and 75 control subjects. Genotyping for the -344T/C and K173R SNPs was performed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis . Result: Results indicated significant differences in the genotype and allelic distribution of the CYP11B2 K173R polymorphism between T2DM patients and control subjects, with P-values of 0.02 and 0.04, respectively. The -344T/C polymorphism showed no significant genomic level differences, but its allelic variations were statistically significant (P=0.01), indicating a notable association between the C allele and T2DM. Furthermore, the K173R polymorphism was found to significantly increase T2DM risk, with a 2.34-fold higher risk in individuals carrying the KR genotype. The study also examined the combined effect of these SNPs. The dominant model analysis (TT vs. TC+CC and KK vs. KR+RR) showed significant differences between T2DM patients and controls for both SNPs. Additionally, a haplotype-based analysis revealed that the C-R haplotype was associated with an increased risk of T2DM. Conclusion: Our study suggests a significant association between the CYP11B2-K173R polymorphism and T2DM in the Moroccan population. Conversely, while the CYP11B2 -344T/C polymorphism exhibits a significant difference in allelic distribution, no significant difference is observed at the genomic level.

Trajectories of social isolation and loneliness and the risk of incident type 2 diabetes mellitus across genetic risk score

AimThis study aimed to investigate the association of social isolation, loneliness, and their trajectory with the risk of developing type 2 diabetes mellitus (T2DM) across genetic risk. MethodsWe included 439,337 participants (mean age 56.3 ± 8.1 years) enrolled in the UK Biobank study who were followed up until May 31, 2021. Social isolation and loneliness were self-reported and were further categorized into never, transient, incident, and persistent patterns. ResultsDuring a median follow-up of 12.7 years, 15,258 incident T2DM cases were documented. Social isolation (versus no social isolation: hazard ratio (HR) 95 % confidence interval (CI) 1.04 [1.00;1.09]) and loneliness (versus no loneliness: 1.26 [1.19;1.34]) were associated with an increased T2DM risk, independent of the genetic risk for T2DM. The interactions existed between social isolation and loneliness (Pinteraction < 0.05); the increased T2DM risk associated with social isolation was only significant among participants without loneliness. In the longitudinal analysis, only persistent social isolation (versus never social isolation: 1.22 [1.02;1.45]) was associated with an increased T2DM risk, whereas incident loneliness (versus never loneliness: 1.95 [1.40;2.71]) and persistent loneliness (2.00 [1.31;3.04]) were associated with higher T2DM risks. ConclusionSocial isolation and loneliness, especially their persistent pattern, were independently associated with an increased incident T2DM risk, irrespective of an individual's genetic risk. Loneliness modified the association between social isolation and incident T2DM.

The risk of type 2 diabetes mellitus in multiple sclerosis and neuromyelitis optica spectrum disorder: A nationwide cohort study

Background and objectivesAn association has been suggested between premorbid type 2 diabetes mellitus (T2DM) and the risk of multiple sclerosis (MS). However, little is known about the risk of developing T2DM in MS and neuromyelitis optica spectrum disorder (NMOSD). This study aimed to determine the T2DM risk in patients with MS and NMSOD. MethodsThe Korean National Health Insurance Service database was analyzed, and 1,801 and 1,721 adults with MS and NMOSD, respectively, who were free of T2DM between January 2010 and December 2017, were included. Matched controls were selected based on age, sex, and the presence of hypertension and dyslipidemia. ResultsThe risk of developing T2DM was 1.54 times higher in NMOSD than in the controls (adjusted hazard ratio [aHR], 95 % confidence interval [CI] = 1.20–1.96). However, increased T2DM risk was not observed in MS (aHR = 1.13, 95 % CI = 0.91–1.42). The T2DM risk in patients with NMOSD was higher in those who received steroid treatment (aHR = 1.77, 95 % CI = 1.36–2.30) but not in those who did not (aHR = 0.59, 95 % CI = 0.24–1.43, p for interaction = 0.02). DiscussionT2DM risk was increased in NMOSD but not in MS. Administering steroid treatment to patients with NMOSD may increase their T2DM risk.

Abstract 13186: Factors Associated With Dysglycemia and Type 2 Diabetes Mellitus Onset in Familial Hypercholesterolemia

Introduction: Familial hypercholesterolemia (FH) is an autosomal dominant monogenic disorder characterized by high blood LDL-C and cardiovascular disease (CVD). Type 2 diabetes mellitus (T2DM) is an independent cause of CVD and there is evidence that FH is associated with a lower frequency of its development. On the other hand, lipid lowering therapy (LLT) may increase T2DM risk. Goals: Evaluate the risk of dysglycemia and T2DM development in a cohort of molecularly proven FH individuals. Methods: This is a prospective analysis of a population enrolled on a genetic cascade screening program evaluated from March 2011 to January 2022. FH diagnosis was confirmed by molecular testing of variants in LDLR, APOB and PCSK9. Dysglycemia and T2DM diagnoses were done according to the ADA Criteria or use of any antidiabetic drugs. Results: 790 FH patients were included (age 45.5±15.0 years, 56.8% female, baseline LDL-C 198±74 mg/dL), 96.6% had LDLR variants. The prevalence of T2DM was 13.3% and 67.4% were taking LLT at baseline . There were 206 (26%) new cases of T2DM or dysglycemia after a median 51-month follow-up . In multivariate Cox regression analysis age (HR:1.026, CI95%: 1.014-1.038, p=0.000) , body mass index (HR: 1.062, CI95%: 1.035-1.090, p=0.000) and current smoking (HR: 2.005, HR: 1.337-3.008, p=0.001) were independently associated with T2DM and dysglycemia, while metformin use was associated with a lower risk (HR: 0.147, CI95%: 0.076-0.284, p=0.000). History of previous CVD, use of lipid lowering therapy at baseline, high intensity LLT , or type of molecular defect were not associated with higher T2DM/dysglycemia risk. Conclusions: In this cohort of molecularly proven FH subjects, T2DM affected more than 1 in 10 people at baseline. Previous CVD and classical risk factors but neither molecular defects nor lipid lowering therapy were associated with T2DM/dysglycemia onset.

Social isolation, loneliness, and incident type 2 diabetes mellitus: results from two large prospective cohorts in Europe and East Asia and Mendelian randomization

Social isolation and loneliness pose significant public health challenges globally. The objective of this study is to investigate the association between social isolation, loneliness, and the risk of type 2 diabetes mellitus (T2DM). 423,503 UK adults from the UK Biobank (UKB) and 13,800 Chinese adults from the China Health and Retirement Longitudinal Study (CHARLS) were analyzed. The exposures of interest were social isolation and loneliness. Social isolation was evaluated based on the number of household members, frequency of social activities, contact with others, and marriage status (CHARLS only). Loneliness was evaluated by the subjective feeling of loneliness and the willingness to confide in others (UKB only). The primary endpoint was incident T2DM. The two-sample Mendelian randomization (MR) analysis was based on the genome-wide association studies of UKB (n=463,010) and the European Bioinformatics Institute (n=655,666). The UKB cohort study documented 15,072 T2DM cases during a mean follow-up of 13.5 years, and the CHARLS cohort study recorded 1,249 T2DM cases during a mean follow-up of 5.8 years. Social isolation and loneliness showed significant associations with an elevated risk of T2DM in both UKB (social isolation [most vs least]: HR 1.17, 95% CI 1.11-1.23; loneliness [yes vs no]: HR 1.21, 95% CI 1.13-1.30) and CHARLS cohorts (social isolation [yes vs no]: HR 1.22, 95% CI 1.06-1.40; loneliness [yes vs no]: HR 1.21, 95% CI 1.07-1.36). These associations remained significant after accounting for baseline glucose status and genetic susceptibility to T2DM. Two-sample MR analyses determined that feeling lonely (OR 1.04, 95% CI 1.02-1.06) and engaging in fewer leisure/social activities (OR 1.03, 95% CI 1.02-1.05) were associated with increased T2DM risk, whereas more contact with friends or family (OR 0.99, 95% CI 0.98-0.99) was associated with reduced T2DM risk. Social isolation and loneliness are each associated with an elevated risk of T2DM, with MR analyses suggesting potential causal links. These associations remain significant after considering genetic susceptibility to T2DM. The findings highlight the importance of promoting initiatives to address social isolation and loneliness as part of T2DM prevention strategies. CAMS Innovation Fund for Medical Sciences (No. 2021-I2M-1-008) and National Natural Science Foundation of China (No. 72103187).

Association of sleep quality, its change and sleep duration with the risk of type 2 diabetes mellitus: Findings from the English longitudinal study of ageing.

This study aimed to evaluate the association of sleep quality and its long-term change with the risk of type 2 diabetes mellitus (T2DM) and to assess the relationship between sleep duration and the risk of T2DM according to categories of sleep quality. 5728 participants free of T2DM at wave 4 from the English Longitudinal Study of Ageing were included and received a follow-up with a median time of 8years. We created a sleep quality score to evaluate sleep quality, which was based on three Jenkins Sleep Problems Scale questions (the frequency of feeling hard to fall asleep, waking up at night, and feeling tired in the morning) and one question for rating overall sleep quality. Participants were allocated into three groups according to their baseline sleep quality scores (groups of good [4-8], intermediate [8-12], and poor quality [12-16]). Sleep duration was assessed by a self-reporting sleep hours from each participant. 411 (7.2%) T2DM cases were documented during the follow-up. Compared with the good quality group, subjects with poor sleep quality showed a significantly higher risk of T2DM (hazard ratio (HR) 1.45, confidence interval (CI) 1.09, 1.92). In participants with good baseline sleep quality, those who experienced worsened sleep quality showed a significantly increased T2DM risk (HR 1.77, 95% CI 1.26, 2.49). Type 2 diabetes mellitus risk was not changed regardless of sleep duration in subjects with good quality. Short sleep duration (≤4h) was associated with an elevated T2DM risk in participants with intermediate sleep quality, and both short (≤4h) and prolonged sleep time (≥9h) were associated with an increased T2DM risk in the poor sleep quality group. Poor sleep quality is correlated with an increase in T2DM risk, and regulating sleep quality to a good range could potentially be an effective approach for preventing T2DM.

Evaluating the distinct pleiotropic effects of omega-3 fatty acids on type 2 diabetes mellitus: a mendelian randomization study

BackgroundObservational studies and conventional Mendelian randomization (MR) studies showed inconclusive evidence to support the association between omega-3 fatty acids and type 2 diabetes. We aim to evaluate the causal effect of omega-3 fatty acids on type 2 diabetes mellitus (T2DM), and the distinct intermediate phenotypes linking the two.MethodsTwo-sample MR was performed using genetic instruments derived from a recent genome-wide association study (GWAS) of omega-3 fatty acids (N = 114,999) from UK Biobank and outcome data obtained from a large-scale T2DM GWAS (62,892 cases and 596,424 controls) in European ancestry. MR-Clust was applied to determine clustered genetic instruments of omega-3 fatty acids that influences T2DM. Two-step MR analysis was used to identify potential intermediate phenotypes (e.g. glycemic traits) that linking omega-3 fatty acids with T2DM.ResultsUnivariate MR showed heterogenous effect of omega-3 fatty acids on T2DM. At least two pleiotropic effects between omega-3 fatty acids and T2DM were identified using MR-Clust. For cluster 1 with seven instruments, increasing omega-3 fatty acids reduced T2DM risk (OR: 0.52, 95%CI 0.45–0.59), and decreased HOMA-IR (β = − 0.13, SE = 0.05, P = 0.02). On the contrary, MR analysis using 10 instruments in cluster 2 showed that increasing omega-3 fatty acids increased T2DM risk (OR:1.10; 95%CI 1.06–1.15), and decreased HOMA-B (β = − 0.04, SE = 0.01, P = 4.52 × 10–5). Two-step MR indicated that increasing omega-3 fatty acid levels decreased T2DM risk via decreasing HOMA-IR in cluster 1, while increased T2DM risk via decreasing HOMA-B in cluster 2.ConclusionsThis study provides evidence to support two distinct pleiotropic effects of omega-3 fatty acids on T2DM risk influenced by different gene clusters, which could be partially explained by distinct effects of omega-3 fatty acids on insulin resistance and beta cell dysfunction. The pleiotropic feature of omega-3 fatty acids variants and its complex relationships with T2DM need to be carefully considered in future genetic and clinical studies.

Genetic Risk Scores for the Determination of Type 2 Diabetes Mellitus (T2DM) in North India

Globally, type 2 diabetes mellitus (T2DM) is one of the fastest-growing noncommunicable multifactorial and polygenic diseases, which leads to many health complications and significant morbidity and mortality. South Asians have a high genetic predisposition to T2DM, with India being home to one in six diabetics. This study investigates the association of selected genetic polymorphisms with T2DM risk and develops a polygenic risk score (PRS). A case-control study recruited fully consented participants from a population of Jat Sikhs in north India. DNA samples were genotyped for a range of polymorphisms and odds ratios were calculated under several genetic association models. Receiver operating characteristic (ROC) curves were produced for combinations of the PRS and clinical parameters. The GSTT1(rs17856199), GSTM1(rs366631), GSTP1(rs1695), KCNQ1(rs2237892), ACE(rs4646994), and TCF7L2(rs12255372; rs7903146; rs7901695) polymorphisms were associated with increased T2DM risk (p ≤ 0.05). No association was observed with IGF2BP2(rs4402960) or PPARG2(rs1801282). The weighted PRS was found to be significantly higher in patients (mean = 15.4, SD = 3.24) than controls (mean = 11.9, SD = 3.06), and t(454) = -12.2 (p < 0.001). The ROC curve analysis found the weighted PRS in combination with clinical variables to be the most effective predictor of T2DM (area under the curve = 0.844, 95%CI = 0.0.808-0.879). Several polymorphisms were associated with T2DM risk. PRS based on even a limited number of loci improves the prediction of the disease. This may provide a useful method for determining T2DM susceptibility for clinical and public health applications.

Elevated remnant cholesterol increase 6-year type 2 diabetes mellitus onset risk

AimTo investigate the association of remnant cholesterol (RC) with future type 2 diabetes mellitus (T2DM) risk, and to assess the underlying impact of some recognized risk factors on it. MethodsA total of 11468 nondiabetic adults in rural China were recruited in 2007–2008 and followed up in 2013–2014. Logistic regression was used to assess the risk of incident T2DM by quartiles of baseline RC, estimating odds ratios (ORs) and 95% confidence intervals (CIs). Association of the combinations of RC and low-density lipoprotein cholesterol (LDL-C) with T2DM risk were further evaluated. ResultsMultivariable adjusted OR (95% CI) for incident T2DM associated with quartile 4 versus quartile 1 of RC was 2.72 (2.05–3.62). Per 1-standard deviation (SD) increases in RC levels was associated with a 34% higher T2DM risk. However, gender modified the specific association (Pinteraction < 0.05), with the association stronger among females. When combining the low LDL-C and low RC groups as reference, individuals with RC levels ≥ 0.56 mmol/L had more than a 2-fold T2DM risk, regardless of LDL-C level. ConclusionsElevated RC levels increase T2DM risk in rural Chinese populations. In those who cannot control their risk by lowering LDL-C levels, the goal of lipid-lowering therapy can be shifted to RC.

Platelet–Lymphocyte Ratio, Neutrophil–Lymphocyte Ratio and Their Dynamic Changes with Type 2 Diabetes Mellitus: A Cohort Study in China

ABSTRACT Background This study aimed at investigating the relationships between Platelet-Lymphocyte ratio (PLR) and Neutrophil–Lymphocyte ratio (NLR) and their dynamic changes (∆PLR, ∆NLR) with type 2 diabetes mellitus (T2DM) in a Chinese cohort study. Methods This study recruited 41,439 individuals who were diagnosed without T2DM at first health examination and completed at least one follow-up. The relationships between NLR, PLR, ∆PLR, ∆NLR and T2DM risk were analyzed using the Cox regression model with corresponding Hazard Ratios (HRs) and 95% Confidence Intervals (CIs). Results PLR exhibited significant correlation with T2DM risk in a linear reverse dose–response pattern, the corresponding HRs and 95% CIs were 0.81 (0.72, 0.90), 0.71 (0.63, 0.80) and 0.56 (0.49, 0.64) respectively (P trend < 0.001) for Q2, Q3 and Q4 vs Q1 after adjusting for age, gender, BMI, TG, TC, HDL-C, FPG, ALT, AST, heart rate, smoking, family history of diabetes, and alcohol consumption at baseline in Model 3. The significance remained in subgroups of women, <45 years, ≥45 years, BMI ≥ 24, with fatty liver disease, without fatty liver disease and normotension. Comparing with the largest decrease group of NLR (∆NLR < −0.32), the risk of T2DM increased for −0.003 ≤ ∆NLR < 0.31 (HR 1.17, 95% CI 1.01–1.36) and ∆NLR ≥ 0.31 (HR 1.23, 95% CI 1.06–1.43). Conclusions Higher PLR could reduce the risk of T2DM. Larger increase of NLR could increase T2DM risk.

Selective serotonin reuptake inhibitors and the risk of type 2 diabetes mellitus in youths

BackgroundSelective serotonin reuptake inhibitors (SSRIs) have been associated with type 2 diabetes mellitus (T2DM) in youths, possibly via 5-HT2C, H1 receptors and serotonin transporter (SERT). SSRIs have similar affinity for SERT but variable affinity for 5-HT2C and H1. This study assessed whether SSRIs with strong affinity for 5-HT2C and H1 (relative to SERT) were associated with T2DM risk compared with weak-affinity SSRIs. MethodsUsing the UK Clinical Practice Research Datalink, we assembled a cohort of patients aged 5–24, newly prescribed a strong-affinity SSRI (citalopram, escitalopram, fluoxetine) or weak affinity (paroxetine, sertraline, fluvoxamine) between 1990 and 2019. We controlled for confounding using standardized mortality ratio weighting, estimated from calendar time-specific propensity scores. We used weighted Cox proportional hazards models to estimate hazard ratios (HRs) of incident T2DM with 95 % confidence intervals (CIs). ResultsThe cohort included 347,368 new users of strong-affinity SSRIs and 131,359 of weak-affinity SSRIs. Strong-affinity SSRIs were not associated with an increased T2DM risk compared with weak-affinity SSRIs (incidence rate 2.8 vs 2.7 per 1000 person-years; HR 1.03, 95 % CI 0.85–1.25). T2DM risk did not vary with duration of use, age or sex. However, the HR was numerically higher in youths with normal or low weight (HR 1.30, 95 % CI 0.85–1.98) and with prior antipsychotic use (HR 1.62, 95 % CI 0.83–3.18). LimitationsMedian duration of SSRI use, in line with real-world SSRI prescribing, was relatively short. ConclusionT2DM risk did not differ between strong- and weak-affinity SSRIs, providing reassurance for clinicians when choosing between SSRIs in youths.

The Risk of T2DM in College Women: The Predictive Power of Financial versus Residential Status in a Cross-Sectional Pilot Study in Turkey.

Aim: This study aimed to investigate the relationships between dietary habits, income levels and type 2 diabetes mellitus (T2DM) risk in Turkish female university students who are living with their family or in the dormitory. Materials and Methods: This work was a cross-sectional pilot study conducted during December 2016–January 2017 in Istanbul Yeni Yuzyıl University. A survey was administered to 100 female students, 60 living with their family and 40 in dormitories. Income level was determined based on TURKSTAT 2015 percentiles. T2DM risk was determined using the Finnish Diabetes Association Type 2 Diabetes Risk Assessment Form (FINDRISC). Food frequency questionnaire and 24 h dietary recall results were analyzed by the diet analysis software Beslenme Bilgi Sistemi (BeBiS), specially developed for Turkey. Results: Results indicated inadequacies and imbalanced nutrition among female college students overall. Notably, there was a statistically significant higher diet quality for the students living with their families compared to those living in dormitories. Income level was consistently positively associated with better nutritional outcomes, while negatively associated with T2DM risk, but interestingly, only in the case of students living in the dormitory and not for those living with family. Conclusions: Our findings indicated that financial status, rather than living in the dormitory versus with family, is positively associated with increased T2DM risk as assessed via FINDRISC among Turkish female college students. This study’s results indicate a potential need for educational programs and nutritional support for students, particularly those living away from family.

A causal relationship between alcohol intake and type 2 diabetes mellitus: A two-sample Mendelian randomization study

Background and aimsWe investigated whether alcohol intake has a causal relationship with type 2 diabetes mellitus (T2DM) risk in adults of the Korean Genomic Epidemiology Study using two-sample Mendelian randomization (MR) analysis. Methods and resultsDaily alcohol intake was calculated based on the type, average amount, and frequency of alcohol consumption for six months before the interview. The participants were divided into low- and high-alcohol intake of 20 g/day. After adjusting for the covariates related to T2DM, the independent genetic variants (instrumental variables) related to alcohol intake were explored by GWAS analysis in a city hospital-based cohort (n = 58,701). SNPs with a significant level of p-value <5 × 10−8 and linkage disequilibrium of r2 < 0.001 were retrieved. MR methods were used to analyze the causality between alcohol intake and the T2DM risk, and the heterogeneity and leave-one-out sensitivity analyses were conducted in Ansan/Ansung plus rural cohorts (n = 13,598). High alcohol intake increased T2DM risk when the inverse-variance weighted (P = 0.012) and weighted median (P = 0.034) methods were used, but not when the MR-Egger method was used. No significant heterogeneity and horizontal pleiotropy between alcohol intake and T2DM were detected. A single genetic variant did not affect the causal association in a leave-one-out sensitivity analysis. ConclusionThis study supports that heavy alcohol intake appears to be causally associated with T2DM risk.

The Polymorphism Study of LEP and LEPR Genes in Association of its Serum Level in Iraqi Patients with Type 2 Diabetic

Background: Diabetes is a major cause of mortality worldwide. There are several types of diabetes, with type 2 diabetes mellitus (T2DM) being the most common. Many factors, including environmental and genetic factors, are involved in the etiology of the disease. Numerous studies have reported the role of genetic polymorphisms in the initiation and development of T2DM. Aim of study to investigate the prevalence of single nucleotide polymorphisms in LEP gene (LEP 3′UTR A/C, −2548 G/A) and LEPR (K109R and Q223R) and their association with Leptin level and obesity Methods: Here we recruited 150 patients with T2DM and 150 normal individuals. Genotyping was performed using polymerase chain reaction‐restriction fragment length polymorphism, BMI was calculated, and Leptin level was measured by ELISA. The polymorphism study was performed At Leptin -2548G/A and Leptin receptor LEPR Q223R. Statistical analyses were performed by spss19.0. Results: Our data showed that there was a significant difference between BMI, HbA1c, Cholesterol, TG, HDL, LDL and Leptin level in T2DM and normal group, however there was no significant difference in gender of all individuals in two groups of T2DM and normal groups. The G-allele frequency was found to be significantly different between T2DM and control groups. In addition, the genotypic and allele frequencies of Leptin receptor LEPR Q223 Polymorphism in the study individuals have been presenteted. The Q-allele frequency was found to have no significant difference between T2DM and control groups. Our data clearly indicated that HbA1c significantly related with BMI. Similarly cholesterol level significantly related to BMI and HbA1c. There was a similar pattern between other parameters. However there were no significant relationship between HDL and other lipid profile. Moreover, the concentration of Leptin was 5.74± 1.27, 5.67± 1.24 And 4.09 ± 1.44 For genotypes of QQ, QR and RR, respectively. However there was no significant difference in normal group. Conclusion: We found a significant association between the LEPR gene polymorphism and increased T2DM risk in the Iraqi population. Iraqi carriers of the G allele of LEPR gene polymorphism may be more susceptible to T2DM. Keywords: Leptin, Leptin Receptor, Polymorphism, Type 2 Diabetes

Single Nucleotide Polymorphisms at +45 T&gt;G and at +276 G&gt;T of the Adiponectin Gene and Plasma Adiponectin Level in Myanmar Type 2 Diabetic Patients

Introduction: Type 2 Diabetes Mellitus (T2DM) is one of the most common metabolic diseases and poses a substantial burden on health care systems globally. There is compelling data that genetic susceptibility to T2DM is polygenic. Genome-wide association studies have identified almost 50 loci associated with T2DM risk. Adiponectin gene polymorphism may be a causal role in the pathogenesis of insulin resistance and T2DM.&#x0D; Aims: The aim of the study was to investigate the association between single nucleotide polymorphisms (SNP) at rs 2241766 (SNP+45 T&gt;G) and at rs 1501299 (SNP+276 G&gt;T) of adiponectin gene and plasma adiponectin level in Myanmar Type 2 Diabetic patients.&#x0D; Study Design: It was a cross-sectional analytical study.&#x0D; Methodology: 100 Type 2 Diabetic patients and 104 non-diabetic subjects were included. Genotype frequencies were determined by PCR-RFLP method and plasma adiponectin level was measured by ELISA method.&#x0D; Results: Carrier groups (TG and GG genotypes of SNP+45) were more likely to develop T2DM risk than non-carrier groups (TT) [OR =1.8 (95% CI = 0.89-3.63, p = 0.09) and OR = 3.51 (95% CI = 1.07-11.54, p =0.04)] respectively. Carrier groups (GT and TT genotypes of SNP+276) were more likely to develop T2DM risk than non-carrier groups (GG) [OR =1.98 (95% CI =1.10-3.55, p = 0.02) and OR = 4.07 (95% CI =1.34-12.3, p = 0.01)] respectively. Therefore, G allele of SNP+45 was found to statistically increase T2DM risk than T allele and T allele of SNP+276 was found to statistically increase T2DM risk than G allele. Mean plasma adiponectin level (27.41±16.7µg/ml) of T2DM patients was significantly lower than that of non-diabetic subjects (37.19±26.77 µg/ml), (p =0.002). Mean plasma adiponectin levels of carrier groups (TG and GG of SNP+45) were significantly lower than that of non-carrier groups (TT). Mean plasma adiponectin levels of carrier groups (GT and TT of SNP+276) were significantly lower than that of non-carrier groups (GG).&#x0D; Conclusion: SNP+45 T&gt;G and +276 G&gt;T of adiponectin gene are significantly associated with low plasma adiponectin level and type 2 diabetes mellitus in this study groups of Myanmar population.

Association of age at menopause with type 2 diabetes mellitus in postmenopausal women in the United States: National Health and Nutrition Examination Survey 2011-2018.

The present study aimed to examine the impact of age at menopause on the type 2 diabetes mellitus (T2DM) risk in postmenopausal women. We included 4,968 postmenopausal women from the National Health and Nutrition Examination Survey 2011-2018. Age at menopause was measured by single year and categorically (< 40 years, 40-44 years, 45-54 years, 55 years and above). The outcome variable T2DM was measured with self-report and fasting blood glucose level. We performed logistic regression to estimate the odds ratio (OR) (95% confidence interval [CI]). Linear regression was used to examine the correlation between age at menopause and age at T2DM. Of the 4,968 postmenopausal women, 796 (16.0%) had T2DM after menopause. The mean age at menopause was 44.2 years. The mean age at T2DM was 57.2 years. Adjusting for potential confounders, the ORs for the association between age at menopause of < 40 years, 40-44 years and ≥ 55 years and T2DM were 1.97 (95% CI: 1.47-2.63), 1.27 (95% CI: 0.90-1.79) and 0.98 (95% CI: 0.66-1.45), respectively, compared to women having menopause at age 45 to 54 years. Each increase by 1 year in age at menopause was associated with a 3% reduction in the prevalence of T2DM (95% CI: 2-5). Age at menopause was significantly correlated with age at T2DM. Each 1-year increase in age at menopause might lead to a decrease of 0.39 years in age at T2DM. Premature menopause was associated with increased T2DM risk in women. The earlier menopause occurs, the younger is the age at which T2DM may occur.

The Effect of SOCS2 Polymorphisms on Type 2 Diabetes Mellitus Susceptibility and Diabetic Complications in the Chinese Han Population.

BackgroundSOCS2 is downregulated in diabetes, which might be related to diabetes. We explored the effect of SOCS2 polymorphisms on the development of type 2 diabetes mellitus (T2DM) and diabetic complications.MethodsThe subjects consisted of 500 patients with T2DM and 501 healthy controls. Five variants in SOCS2 were genotyped by Agena MassARRAY system. RT-qPCR profiling was performed to detect the expression of SOCS2 mRNA. Logistic regression analysis was utilized to calculate odds ratio (OR) and 95% confidence intervals (95% CIs).ResultsRs3825199 (OR = 1.44, p = 0.007), rs11107116 (OR = 1.39, p = 0.014) and rs10492321 (OR = 1.48, p = 0.004) had an increased T2DM risk of T2DM. Moreover, the contribution of SOCS2 polymorphisms to T2DM risk was associated with age, gender, smoking, drinking, and BMI. SOCS2 variants also had a reduced risk for T2DM patients with diabetic nephropathy, diabetic retinopathy and coronary heart disease. SOCS2 rs10492321 was the best single locus model. SOCS2 mRNA was downregulated in patients with T2DM compared to healthy controls (p = 0.029).ConclusionThis study firstly reported that rs3825199, rs11107116 and rs10492321 in SOCS2 conferred to an increased risk for the occurrence of T2DM in the Chinese Han population. Moreover, SOCS2 mRNA was downregulated in patients with T2DM, suggesting that SOCS2 might have an important role in the occurrence of T2DM.

Association Between Insulin-like Growth Factor-1 rs35767 Polymorphism and Type 2 Diabetes Mellitus Susceptibility: A Meta-Analysis.

Background: Insulin-like growth factor-1 (IGF-1) has been demonstrated to increase fatty acid β oxidation during fasting, and play an important role in regulating lipid metabolism and type 2 diabetes mellitus (T2DM). The rs35767 (T > C) polymorphism, a functional SNP was found in IGF-1 promoter, which may directly affect IGF-1 expression. However, the inconsistent findings showed on the IGF-1 rs35767 polymorphism and T2DM risk. Methods: We performed a comprehensive meta-analysis to estimate the association between the IGF-1 rs35767 and T2DM risk among four genetic models (the allele, additive, recessive and dominant models). Results: A total 49,587 T2DM cases and 97,906 NDM controls were included in the allele model, a total 2256 T2DM cases and 2228 NDM controls were included in the other three genetic models (the additive; recessive and dominant models). In overall analysis, the IGF-1 rs35767 was shown to be significantly associated with increased T2DM risk for the allele model (T vs. C: OR = 1.251, 95% CI: 1.082–1.447, p = 0.002), additive model (homozygote comparisons: TT vs. CC: OR = 2.433, 95% CI: 1.095–5.405, p = 0.029; heterozygote comparisons: TC vs. CC: OR = 1.623, 95% CI: 1.055–2.495, p = 0.027) and dominant model (TT + CT vs. CC: OR = 1.934, 95% CI: 1.148–3.257, p = 0.013) with random effects model. After omitting Gouda’s study could reduce the heterogeneity, especially in the recessive model (TT vs. CC + CT: I2 = 38.7%, p = 0.163), the fixed effects model for recessive effect of the T allele (TT vs. CC + CT) produce results that were of borderline statistical significance (OR = 1.206, 95% CI: 1.004–1.448, p = 0.045). And increasing the risk of T2DM in Uyghur population of subgroup for the allele model. Conclusion: The initial analyses that included all studies showed statistically significant associations between the rs35767 SNP and type 2 diabetes, but after removing the Gouda et al. study produced results that were mostly not statistically significant. Therefore, there is not enough evidence from the results of the meta-analysis to indicate that the rs35767 SNP has a statistically significant association with type 2 diabetes.

Overweight and risk of type 2 diabetes: A prospective Chinese twin study

Objectives: This study aimed to estimate the association between overweight and type 2 diabetes mellitus (T2DM) in twins, and further to explore whether genetic and early-life environmental factors account for this association. Methods: This study included 31,197 twin individuals from the Chinese National Twin Registry (CNTR). Generalized estimating equation (GEE) models were applied for unmatched case-control analysis. Conditional logistic regressions were used in co-twin matched case-control analysis. Logistic regressions were fitted to examine the differences in odds ratios (ORs) from the GEE models and conditional logistic regressions. Bivariate genetic model was used to explore the genetic and environmental correlation between body mass index (BMI) and T2DM. Results: In the GEE model, overweight was associated with a higher T2DM risk (OR=2.71, 95% confidence interval (CI): 1.96∼3.73), compared with participants with normal BMI. In the multi-adjusted conditional logistic regression, the association was still significant (OR=2.60, 95% CI: 1.15∼5.87). The ORs from the unmatched and matched analyses were different (P = 0.042). Particularly, overweight could increase T2DM risk in monozygotic (MZ) twins, and the difference in ORs between the unmatched and matched designs was significant (P = 0.014). After controlling for age and sex, the positive BMI-T2DM association was partly due to a significant genetic correlation (rA= 0.31, 95% CI: 0.20∼0.41). Conclusions: Our findings suggest that genetics and early-life environments might account for the observed overweight-T2DM association. Genetic correlation between BMI and T2DM further provides evidence for the influence of overlap genes on their association.

Integrated analysis of probability of type 2 diabetes mellitus with polymorphisms and methylation of KCNQ1 gene: A nested case-control study.

To estimate the associations between single-nucleotide polymorphisms (SNPs) and methylation of KCNQ1 gene and type 2 diabetes mellitus (T2DM) risk and the interactions among SNPs, methylation, and environmental factors on T2DM risk. We genotyped five SNPs and tested methylation at 39 CpG loci of KCNQ1 in 290 T2DM cases and 290 matched controls nested in the Rural Chinese Cohort Study. Conditional logistic regression model was used to estimate the associations between SNPs and KCNQ1 methylation and T2DM risk. Multifactor dimensionality reduction (MDR) analysis was used to estimate the effect of the interactions SNPs-SNPs, SNPs-methylation, methylation-methylation and SNPs, and methylation-environment on T2DM risk. Probability of T2DM was decreased with rs2283228 of KCNQ1 (CA vs AA, odds ratio [OR]=0.65, 95% confidence interval [CI] 0.42-0.99). T2DM probability was significantly increased with rs2237895 combined with hypertriglyceridemia (OReg =2.76, 95% CI 1.35-5.62), with hypertension (OReg =2.23, 95% CI 1.25-3.98), and with body mass index (BMI; OReg =1.93, 95% CI 1.12-3.34). T2DM probability was associated with methylation of CG11 and CG41 (OR=1.89, 95% CI 1.23-2.89, P=.003). It was significantly associated with the interaction between BMI, hypertriglyceridemia, and CG5 methylation (P=.028 and .028), and the combined effects of CG11 with hypertriglyceridemia and hypertension. On MDR analysis, no significant interaction was observed. T2DM probability was reduced 35% with rs2283228 polymorphism. It was associated with rs2237895 combined with hypertension, with BMI and with hypertriglyceridemia. The methylation at two CpG loci of KCNQ1 significantly increased T2DM risk by 89%.