Gene-gene and gene-environment interactions in the etiology of type 2 diabetes mellitus in the population of Hyderabad, India

Gene-Lifestyle Interactions in Renal Dysfunction: Polygenic Risk Modulation via Plant-Based Diets, Coffee Intake, and Bioactive Compound Interactions

Background: This study aimed to investigate genetic variants associated with the estimated glomerular filtration rate (eGFR) and their interactions with lifestyle factors and bioactive compounds in large hospital-based cohorts, assessing their impact on renal dysfunction risk. Methods: Participants were categorized into two groups based on eGFR: High-GFR (control; n = 51,084) and Low-GFR (renal dysfunction; n = 7617), using an eGFR threshold of 60 mL/min/1.73 m2. Genetic variants were identified through a genome-wide association analysis, and their interactions with lifestyle factors were assessed a using generalized multifactor dimensionality reduction (GMDR) analysis. Additionally, interactions between polygenic risk scores (PRS) and nutrient intake were examined. Results: Low eGFR was associated with higher urinary protein levels (4.67-fold) and correlated with a Western-style diet and with saturated fat, arginine, and isoleucine intakes but not sodium intake. The genetic model for low eGFR included variants linked to energy production and amino acid metabolism, such as rs1047891_CPS1, rs3770636_LRP2, rs5020545_SHROOM3, rs3812036_SLC34A1, and rs4715517_HCRTR2. A high PRS was associated with a 1.78-fold increased risk of low eGFR after adjusting for sociodemographic and lifestyle factors. The PRS from the 6-SNP model interacted with plant-based diets (PBDs) and coffee intake, where individuals with higher PBD and coffee consumption had a lower risk of renal dysfunction. Additionally, CPS1 rs1047891 interacted with vitamin D intake (p = 0.0436), where the risk allele was linked to lower eGFR with low vitamin D intake but not with high intake. Molecular docking showed that vitamin D3 had a lower binding energy to the CPS1 mutant type (-9.9 kcal/mol) than the wild type (-7.5 kcal/mol), supporting a potential gene-nutrient interaction influencing renal function. Conclusions: Middle-aged and elderly individuals with a high genetic risk for renal dysfunction may benefit from a plant-based diet, moderate coffee consumption, and sufficient vitamin D intake.

Association between genetic polymorphisms and gestational diabetes mellitus susceptibility in a Chinese population

Background

Although the association between HHEX, IGF2BP2, and FTO polymorphisms and the risk of GDM has been investigated in several studies, the findings have been inconsistent across different populations. The study aimed to investigate the association between genetic polymorphisms and GDM risk in a Chinese population.

Methods

502 control volunteers and 500 GDM patients were enrolled. IGF2BP2 rs11705701 and rs4402960, FTO rs9939609, and HHEX rs1111875 and rs5015480 were all genotyped using the SNPscan™ genotyping assay. The independent sample t-test, logistic regression, and chi-square test were used to assess the variations in genotype and allele and their relationships with the risk of GDM. The blood glucose level, gestational week of delivery, and newborn weight were compared using a one-way ANOVA.

Results

After adjusting for confounding factors, the results show that the rs1111875 heterozygous (OR=1.370; 95% CI: 1.040-1.805; P = 0.025) and overdominant (OR=1.373; 95% CI: 1.049-1.796; P = 0. 021) models are significantly associated with an increased risk of GDM, especially for the age ≥ 30 years group: heterozygote (OR=1.646; 95% CI: 1.118-2.423; P=0.012) and overdominant (OR=1.553; 95% CI: 1.064-2.266; P = 0.022) models. In the age ≥ 30 years, the rs5015480 overdominant model (OR=1.595; 95% CI: 1.034-2.459; P = 0.035) and the rs9939609 heterozygote model (OR=1.609; 95% CI: 1.016-2.550; P=0.043), allele (OR=1. 504; 95% CI: 1.006-2.248; P = 0.047), dominant model (OR=1.604; 95% CI: 1.026-2.505; P = 0.038), and overdominant model (OR=1.593; 95% CI: 1.007-2.520; P = 0.047) were associated with a significantly increased risk of GDM; Additionally, people with the TC genotype of rs1111875 had a substantially higher 1-hour blood glucose level than TT genotype (P < 0.05). The results of the meta-analysis showed that the A allele of rs11705701 was associated with an increased risk of diabetes mellitus (P < 0.05).

Conclusion

The study indicates that the TC genotype of rs1111875 is linked to a higher risk of GDM, particularly in women aged 30 years or older. Additionally, rs5015480 and rs9939609 were significantly associated with GDM in the same age group. These SNPs may therefore be more closely linked to GDM in older mothers.

High Polygenic Risk Scores Positively Associated with Gastric Cancer Risk Interact with Coffee and Polyphenol Intake and Smoking Status in Korean Adults

BACKGROUND/OBJECTIVES

This study investigated the relationship between single nucleotide polymorphisms (SNPs) and gastric cancer (GC) risk, while also examining the interaction of genetic factors with lifestyle variables including the nutrient and bioactive compound intake in Korean adults of a large hospital-based cohort.

METHODS

We conducted a genome-wide association study (GWAS) comparing GC patients (n = 312) with healthy controls without cancers (n = 47,994) to identify relevant genetic variants. Generalized multifactor dimensionality reduction (GMDR) was employed to detect SNP interactions between diets and lifestyles. We utilized polygenic risk scores (PRSs) to assess individuals' GC risk based on multiple SNP loci. Among the selected SNPs, since SEMA3C_rs1527482 was a missense mutation, bioactive compounds which decrease the binding energy were found with its wild and mutated proteins by molecular docking analysis.

RESULTS

Individuals with high PRSs exhibited a 4.12-fold increased risk of GC compared to those with low PRSs. Additional factors associated with elevated GC risk included a low white blood cell count (OR = 5.13), smoking (OR = 3.83), and low coffee consumption (OR = 6.30). The SEMA3C_rs1527482 variant showed a positive correlation with GC risk. Molecular docking analyses suggested that certain polyphenols, including theaflavate, rugosin E, vitisifuran B, and plantacyanin, reduced the binding free energy in both wild-type and mutated SEMA3C_rs1527482. However, some polyphenols exhibited differential binding energies between its wild and mutated forms, suggesting they might modulate wild and mutated proteins differently.

CONCLUSION

High PRSs and SEMA3C_rs1527482 interact with immune function, coffee intake, polyphenol consumption, and smoking status to influence GC risk. These findings could contribute to developing personalized nutrition and lifestyle interventions to reduce GC risk.

Association of a High Healthy Eating Index Diet with Long-Term Visceral Fat Loss in a Large Longitudinal Study

We aimed to investigate the association of a sustainable diet with a long-term reduction in waist circumference (WC) while identifying novel biomarkers for WC reduction (WCR). The participants were recruited initially during 2004-2013 in a large hospital-based cohort, and the follow-up measurements were conducted during 2012-2016. The 65,611 adults aged 45-75 were categorized into WC-loss (n = 22,290) and WC-gain (n = 43,321). Each study investigated demographic, anthropometric, biochemical, genetic, and dietary factors. The modified Healthy Eating Index (MHEI), dietary patterns, and glycemic index were calculated from a validated semi-quantitative food frequency questionnaire. Novel biomarkers influencing WC reduction were identified using machine learning approaches. A WCR was inversely associated with metabolic syndrome (MetS) risk and its components. Daily energy intake did not differ between those with and without WCR. However, MHEI, which represents diet quality, demonstrated a positive association with WCR. Among various dietary patterns, the Asian-style balanced diet (ABD), including more fermented soybeans and less restricted salt than the Diet Approach to Stop Hypertension, was positively associated with WCR. However, an inverse association was observed between the diet that was high in noodle and processed meat consumption and that which was high in rice consumption. However, the PRS for abdominal obesity did not significantly interrupt WCR. The receiver operating characteristic curve in the prediction model for WCR was about 0.86. The biomarkers in the models included MetS components, inflammation index, diet components, alcohol consumption, and smoking status, but not genetic factors. In conclusion, adopting a high-quality diet with a high MHEI like ABD leads to WCR, irrespective of genetic influences. These results could be applied to develop effective strategies for preventing and managing abdominal obesity.

Association of HHEX and SLC30A8 Gene Polymorphisms with Gestational Diabetes Mellitus Susceptibility: A Meta-analysis

Genetics plays a role in the development of gestational diabetes mellitus (GDM), which poses serious risks to pregnant women and their children. Several studies have demonstrated a link between GDM susceptibility and rs13266634 C/T polymorphism in SLC30A8 gene and rs1111875 C/T and rs5015480 C/T, which are located near the linkage disequilibrium block containing the IDE, HHEX, and KIF11 genes. However, the results are conflicting. Therefore, we aimed to investigate the association between susceptibility to GDM and HHEX and SLC30A8 gene polymorphisms. PubMed, Web of Science, EBSCO, CNKI, Wanfang Data, VIP, and SCOPUS were used to search for research articles. The quality of the selected literature was evaluated using the Newcastle-Ottawa scale. A meta-analysis was performed using Stata 15.1. Allelic, dominant, recessive, homozygote, and heterozygote models were used for the analysis. Nine articles with 15 studies were included. (1) Four studies about HHEX rs1111875 showed that the C allele was associated with the susceptibility to GDM; (2) three studies on HHEX rs5015480 indicated that the C allele in rs5015480 was significantly associated with GDM; (3) eight studies about SLC30A8 rs13266634 showed that the C allele was significantly associated with the susceptibility to GDM; and (4) a subgroup analysis showed that the rs5015480 polymorphism in HHEX and rs13266634 polymorphism in SLC30A8 gene were associated with GDM susceptibility in Asians. The meta-analysis provided evidence that the C allele in rs1111875 and rs5015480 in HHEX and rs13266634 in SLC30A8 can increase the risk of GDM.PROSPERO registration number CRD42022342280.

Height-Related Polygenic Variants Are Associated with Metabolic Syndrome Risk and Interact with Energy Intake and a Rice-Main Diet to Influence Height in KoGES

Adult height is inversely related to metabolic syndrome (MetS) risk, but its genetic impacts have not been revealed. The present study aimed to examine the hypothesis that adult height-related genetic variants interact with lifestyle to influence adult height and are associated with MetS risk in adults aged >40 in Korea during 2010–2014. Participants were divided into short stature (SS; control) and tall stature (TS; case) by the 85th percentile of adult height. The genetic variants linked to adult height were screened from a genome-wide association study in a city hospital-based cohort (n = 58,701) and confirmed in Ansan/Ansung plus rural cohorts (n = 13,783) among the Korean Genome and Epidemiology Study. Genetic variants that interacted with each other were identified using the generalized multifactor dimensionality reduction (GMDR) analysis. The interaction between the polygenic risk score (PRS) of the selected genetic variants and lifestyles was examined. Adult height was inversely associated with MetS, cardiovascular diseases, and liver function. The PRS, including zinc finger and BTB domain containing 38 (ZBTB38)_rs6762722, polyadenylate-binding protein-interacting protein-2B (PAIP2B)_rs13034890, carboxypeptidase Z (CPZ)_rs3756173, and latent-transforming growth factor beta-binding protein-1 (LTBP1)_rs4630744, was positively associated with height by 1.29 times and inversely with MetS by 0.894 times after adjusting for covariates. In expression quantitative trait loci, the gene expression of growth/differentiation factor-5 (GDF5)_rs224331, non-SMC condensin I complex subunit G (NCAPG)_rs2074974, ligand-dependent nuclear receptor corepressor like (LCORL)_rs7700107, and insulin-like growth factor-1 receptor (IGF1R)_rs2871865 was inversely linked to their risk allele in the tibial nerve and brain. The gene expression of PAIP2B_rs13034890 and a disintegrin and metalloproteinase with thrombospondin motifs-like-3 (ADAMTSL3)_rs13034890 was positively related to it. The PRS was inversely associated with MetS, hyperglycemia, HbA1c, and white blood cell counts. The wild type of GDF5_rs224331 (Ala276) lowered binding energy with rugosin A, D, and E (one of the hydrolyzable tannins) but not the mutated one (276Ser) in the in-silico analysis. The PRS interacted with energy intake and rice-main diet; PRS impact was higher in the high energy intake and the low rice-main diet. In conclusion, the PRS for adult height interacted with energy intake and diet patterns to modulate height and was linked to height and MetS by modulating their expression in the tibial nerve and brain.

Association of Polygenic Variants Involved in Immunity and Inflammation with Duodenal Ulcer Risk and Their Interaction with Irregular Eating Habits

Genetic and environmental factors are associated with developing and progressing duodenal ulcer (DU) risk. However, the exact nature of the disease pathophysiology and the single nucleotide polymorphism (SNP)-lifestyle interaction has yet to be determined. The purpose of the present study was to examine the SNPs linked to DU risk and their interaction with lifestyles and diets in a large hospital-based cohort of Asians. Based on an earlier diagnosis, the participants were divided into the DU (case; n = 1088) and non-DU (control, n = 56,713) groups. The SNP associated with DU risk were obtained from a genome-wide association study (GWAS), and those promoted genetic impact with SNP-SNP interactions were identified with generalized multifactor dimensionality reduction analysis. The interaction between polygenic risk score (PRS) calculated from the selected genetic variants and nutrient were examined. They were related to actin modification, immune response, and cell migration by modulating leucine-rich repeats (LRR) domain binding, Shaffer interferon regulatory factor 4 (IRF4) targets in myeloma vs. mature B lymphocyte, and Reactome runt-related transcription factor 3 (RUNX3). Among the selected SNPs, rs11230563 (R225W) showed missense mutation and low binding affinity with different food components in the autodock analysis. Glycyrrhizin, physalin B, janthitrem F, and casuarinin lowered it in only wild CD6 protein but not in mutated CD6. Plastoquinone 8, solamargine, saponin D, and matesaponin 2 decreased energy binding affinity in mutated CD6 proteins. The PRS of the 5-SNP and 6-SNP models exhibited a positive association with DU risk (OR = 3.14). The PRS of the 5-SNP PRS model interacted with irregular eating habits and smoking status. In participants with irregular eating habits or smokers, DU incidence was much higher in the participants with high PRS than in those with low PRS. In conclusion, the genetic impact of DU risk was mainly in regulating immunity, inflammation, and actin modification. Adults who are genetically susceptible to DU need to eat regularly and to be non-smokers. The results could be applied to personalize nutrition.

Genetics of type 2 diabetes mellitus in Indian and Global Population: A Review

Background

Non-communicable diseases such as cardiovascular diseases, respiratory diseases and diabetes contribute to the majority of deaths in India. Public health programmes on non-communicable diseases (NCD) prevention primarily target the behavioural risk factors of the population. Hereditary is known as a risk factor for most NCDs, specifically, type 2 diabetes mellitus (T2DM), and hence, understanding of the genetic markers of T2DM may facilitate prevention, early case detection and management.

Main body

We reviewed the studies that explored marker-trait association with type 2 diabetes mellitus globally, with emphasis on India. Globally, single nucleotide polymorphisms (SNPs) rs7903146 of Transcription Factor 7-like 2 (TCF7L2) gene was common, though there were alleles that were unique to specific populations. Within India, the state-wise data were also taken to foresee the distribution of risk/susceptible alleles. The findings from India showcased the common and unique alleles for each region.

Conclusion

Exploring the known and unknown genetic determinants might assist in risk prediction before the onset of behavioural risk factors and deploy prevention measures. Most studies were conducted in non-representative groups with inherent limitations such as smaller sample size or looking into only specific marker-trait associations. Genome-wide association studies using data from extensive prospective studies are required in highly prevalent regions worldwide. Further research is required to understand the singular effect and the interaction of genes in predicting diabetes mellitus and other comorbidities.

Association of Polygenic Variants with Type 2 Diabetes Risk and Their Interaction with Lifestyles in Asians

Over the last several decades, there has been a considerable growth in type 2 diabetes (T2DM) in Asians. A pathophysiological mechanism in Asian T2DM is closely linked to low insulin secretion, β-cell mass, and inability to compensate for insulin resistance. We hypothesized that genetic variants associated with lower β-cell mass and function and their combination with unhealthy lifestyle factors significantly raise T2DM risk among Asians. This hypothesis was explored with participants aged over 40. Participants were categorized into T2DM (case; n = 5383) and control (n = 53,318) groups. The genetic variants associated with a higher risk of T2DM were selected from a genome-wide association study in a city hospital-based cohort, and they were confirmed with a replicate study in Ansan/Ansung plus rural cohorts. The interacted genetic variants were identified with generalized multifactor dimensionality reduction analysis, and the polygenic risk score (PRS)-nutrient interactions were examined. The 8-SNP model was positively associated with T2DM risk by about 10 times, exhibiting a higher association than the 20-SNP model, including all T2DM-linked SNPs with p < 5 × 10−6. The SNPs in the models were primarily involved in pancreatic β-cell growth and survival. The PRS of the 8-SNP model interacted with three lifestyle factors: energy intake based on the estimated energy requirement (EER), Western-style diet (WSD), and smoking status. Fasting serum glucose concentrations were much higher in the participants with High-PRS in rather low EER intake and high-WSD compared to the High-EER and Low-WSD, respectively. They were shown to be higher in the participants with High-PRS in smokers than in non-smokers. In conclusion, the genetic impact of T2DM risk was mainly involved with regulating pancreatic β-cell mass and function, and the PRS interacted with lifestyles. These results highlight the interaction between genetic impacts and lifestyles in precision nutrition.

Polygenetic Variants Related to Osteoarthritis Risk and Their Interactions with Energy, Protein, Fat, and Alcohol Intake in Adults in a Large Cohort

Osteoarthritis (OA) is increasing globally, especially among elderly Asian women, and its increase may be due to the interaction between genetic factors and lifestyle. This study tested the hypothesis that polygenetic variants associated with OA risk interacted with lifestyle in adults over 40 years in the Ansan-Ansung cohort. Genetic variants were chosen through a genome-wide association study with OA participants (case; n = 580) and controls without arthritis (n = 4850). Genetic variants with interactions were selected by a generalized multifactor dimensionality reduction. The best model's polygenic risk scores (PRS) were calculated by summing the number of risk alleles in the selected genetic variants. The best five single nucleotide polymorphism (SNP) model included AIG1_rs6570550, COX10_rs62054459, DLG2_rs148643344, SOX5_rs73283615, and PLXNA4_rs1472529430, while IL12A_ rs1491318751 was added to the five-SNP model to produce a six-SNP model. Only COX10_rs62054459 in subcutaneous and visceral adipose tissue was associated with COX10 protein expression. The participants, having high-PRS from the five-SNP and six-SNP models, were at a higher OA risk than those with low-PRS by 3.88 and 4.42 times, respectively. The PRS was not associated with metabolic syndrome or with the insulin resistance index (HOMA-IR). Energy, protein, fat, alcohol, and a Western-style diet intake interacted with the PRS to influence OA risk (p = 0.005, 0.042, and 0.021, respectively). In the high energy and alcohol intake and low protein, fat, Western-style diet intake, the participants with a high-PRS had a higher incidence of OA than those with low-PRS. In conclusion, the adults with a high-PRS were at a higher OA risk. Particularly, adults with high PRS should have a lower energy intake, higher WSD containing higher protein and fat intake, and moderate alcohol intake to alleviate OA risk. These results can be applied to personalized nutrition plans to decrease OA risk.

Development and Validation of an Insulin Resistance Predicting Model Using a Machine-Learning Approach in a Population-Based Cohort in Korea

Background: Insulin resistance is a common etiology of metabolic syndrome, but receiver operating characteristic (ROC) curve analysis shows a weak association in Koreans. Using a machine learning (ML) approach, we aimed to generate the best model for predicting insulin resistance in Korean adults aged > 40 of the Ansan/Ansung cohort using a machine learning (ML) approach. Methods: The demographic, anthropometric, biochemical, genetic, nutrient, and lifestyle variables of 8842 participants were included. The polygenetic risk scores (PRS) generated by a genome-wide association study were added to represent the genetic impact of insulin resistance. They were divided randomly into the training (n = 7037) and test (n = 1769) sets. Potentially important features were selected in the highest area under the curve (AUC) of the ROC curve from 99 features using seven different ML algorithms. The AUC target was ≥0.85 for the best prediction of insulin resistance with the lowest number of features. Results: The cutoff of insulin resistance defined with HOMA-IR was 2.31 using logistic regression before conducting ML. XGBoost and logistic regression algorithms generated the highest AUC (0.86) of the prediction models using 99 features, while the random forest algorithm generated a model with 0.82 AUC. These models showed high accuracy and k-fold values (>0.85). The prediction model containing 15 features had the highest AUC of the ROC curve in XGBoost and random forest algorithms. PRS was one of 15 features. The final prediction models for insulin resistance were generated with the same nine features in the XGBoost (AUC = 0.86), random forest (AUC = 0.84), and artificial neural network (AUC = 0.86) algorithms. The model included the fasting serum glucose, ALT, total bilirubin, HDL concentrations, waist circumference, body fat, pulse, season to enroll in the study, and gender. Conclusion: The liver function, regular pulse checking, and seasonal variation in addition to metabolic syndrome components should be considered to predict insulin resistance in Koreans aged over 40 years.

Association of age-related cataract risk high polygenetic risk scores involved in galactose-related metabolism and dietary interactions

INTRODUCTION

Cataracts are associated with the accumulation of galactose and galactitol in the lens. We determined the polygenetic risk scores for the best model(PRSBM) associated with age-related cataract(ARC) risk and their interaction with diets and lifestyles in 40,262 Korean adults aged over 50 years belonged to a hospital-based city cohort.

METHODS

The genetic variants for ARC risk were selected in lactose and galactose metabolism-related genes with multivariate logistic regression using the PLINK 1.9 version. PRSBM from the selected genetic variants was estimated by generalized multifactor dimensionality reduction (GMDR) after adjusting covariates. The interactions between the PRSBM and each lifestyle factor were determined to modulate ARC risk.

RESULTS

The genetic variants for ARC risk related to lactose- and galactose metabolism were SLC2A1_rs3729548, ST3GAL3_rs3791047, LCT_rs2304371, GALNT5_rs6728956, ST6GAL1_rs2268536, GALNT17_rs17058752, CSGALNACT1_rs1994788, GALNTL4_rs10831608, B4GALT6_rs1667288, and A4GALT_ rs9623659. In GMDR, the best model included all ten genetic variants. The highest odds ratio (OR) for a single SNP in the PRSBM was 1.26. However, subjects with a high-PRSBM had a higher ARC risk by 2.1-fold than a low-PRSBM after adjusting for covariates. Carbohydrate, dairy products, kimchi, and alcohol intake interacted with PRSBM for ARC risk: the participants with high-PRSBM had a much higher ARC risk than those with low-PRSBM when consuming diets with high carbohydrate and low dairy product and kimchi intake. However, only with low alcohol intake, the participants with high-PRSBM had a higher ARC risk than those with low-PRSBM.

CONCLUSION

Adults aged >50 years having high-PRSBM may modulate dietary habits to reduce ARC risk.

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.

Interaction of Polygenetic Variants for Gestational Diabetes Mellitus Risk with Breastfeeding and Korean Balanced Diet to Influence Type 2 Diabetes Risk in Later Life in a Large Hospital-Based Cohort

The etiologies of gestational diabetes mellitus (GDM) and type 2 diabetes mellitus (T2DM) are similar. Genetic and environmental factors interact to influence the risk of both types of diabetes. We aimed to determine if the polygenetic risk scores (PRS) for GDM risk interacted with lifestyles to influence type 2 diabetes risk in women aged >40 years in a large hospital-based city cohort. The participants with GDM diagnosis without T2DM before pregnancy were considered the case group (n = 384) and those without GDM and T2DM as the control (n = 33,956) to explore GDM-related genetic variants. The participants with T2DM were the case (n = 2550), and the control (n = 33,956) was the same as GDM genetic analysis for the interaction analysis of GDM genetic risk with lifestyles to influence T2DM risk. The genetic variants for the GDM risk were selected from a genome-wide association study (GWAS), and their PRS from the best model with gene-gene interactions were generated. GDM was positively associated with age at first pregnancy, body mass index (BMI) at age 20, and education level. A previous GDM diagnosis increased the likelihood of elevated fasting serum glucose concentrations and HbA1c contents by 8.42 and 9.23 times in middle-aged and older women. However, it was not associated with the risk of any other metabolic syndrome components. Breast-feeding (≥1 year) was inversely associated with the T2DM risk in later life. In the genetic variant-genetic variant interaction, the best model with 5-SNPs included PTPRD_rs916855529, GPC6_rs9589710, CDKAL1_rs7754840, PRKAG2_rs11975504, and PTPRM_rs80164908. The PRS calculated from the 5-SNP model was positively associated with the GDM risk by 3.259 (2.17-4.89) times after adjusting GDM-related covariates. The GDM experience interacted with PRS for the T2DM risk. Only in non-GDM women PRS was positively associated with T2DM risk by 1.36-times. However, long breastfeeding did not interact with the PRS for T2DM risk. Among dietary patterns, only a Korean-style balanced diet (KBD) showed an interaction with PRS for the T2DM risk. Participants with a low-PRS had the lowest serum glucose concentrations in the high KBD intake but not low KBD intake. In conclusion, participants with a high PRS for GDM risk are positively associated with T2DM risk, and breastfeeding for ≥1 year and consuming KBD offset the PRS for GDM risk to influence T2DM risk in middle-aged and older.

Interactions between Polygenic Risk Scores, Dietary Pattern, and Menarche Age with the Obesity Risk in a Large Hospital-Based Cohort

Obese Asians are more susceptible to metabolic diseases than obese Caucasians of the same body mass index (BMI). We hypothesized that the genetic variants associated with obesity risk interact with the lifestyles of middle-aged and elderly adults, possibly allowing the development of personalized interventions based on genotype. We aimed to examine this hypothesis in a large city hospital-based cohort in Korea. The participants with cancers, thyroid diseases, chronic kidney disease, or brain-related diseases were excluded. The participants were divided into case and control according to their BMI: ≥25 kg/m2 (case; n = 17,545) and <25 kg/m2 (control; n = 36,283). The genetic variants that affected obesity risk were selected using a genome-wide association study, and the genetic variants that interacted with each other were identified by generalized multifactor dimensionality reduction analysis. The selected genetic variants were confirmed in the Ansan/Ansung cohort, and polygenetic risk scores (PRS)-nutrient interactions for obesity risk were determined. A high BMI was associated with a high-fat mass (odds ratio (OR) = 20.71) and a high skeletal muscle-mass index (OR = 3.38). A high BMI was positively related to metabolic syndrome and its components, including lipid profiles, whereas the initial menstruation age was inversely associated with a high BMI (OR = 0.78). The best model with 5-SNPs included SEC16B_rs543874, DNAJC27_rs713586, BDNF_rs6265, MC4R_rs6567160, and GIPR_rs1444988703. The high PRS with the 5-SNP model was positively associated with an obesity risk of 1.629 (1.475-1.798) after adjusting for the covariates. The 5-SNP model interacted with the initial menstruation age, fried foods, and plant-based diet for BMI risk. The participants with a high PRS also had a higher obesity risk when combined with early menarche, low plant-based diet, and a high fried-food intake than in participants with late menarche, high plant-based diet, and low fried-food intake. In conclusion, people with a high PRS and earlier menarche age are recommended to consume fewer fried foods and a more plant-based diet to decrease obesity risk. This result can be applied to personalized nutrition for preventing obesity.

Association of Polygenetic Risk Scores Related to Immunity and Inflammation with Hyperthyroidism Risk and Interactions between the Polygenetic Scores and Dietary Factors in a Large Cohort

Graves's disease and thyroiditis induce hyperthyroidism, the causes of which remain unclear, although they are involved with genetic and environmental factors. We aimed to evaluate polygenetic variants for hyperthyroidism risk and their interaction with metabolic parameters and nutritional intakes in an urban hospital-based cohort. A genome-wide association study (GWAS) of participants with (cases; n = 842) and without (controls, n = 38,799) hyperthyroidism was used to identify and select genetic variants. In clinical and lifestyle interaction with PRS, 312 participants cured of hyperthyroidism were excluded. Single nucleotide polymorphisms (SNPs) associated with gene-gene interactions were selected by hyperthyroidism generalized multifactor dimensionality reduction. Polygenic risk scores (PRSs) were generated by summing the numbers of selected SNP risk alleles. The best gene-gene interaction model included tumor-necrosis factor (TNF)_rs1800610, mucin 22 (MUC22)_rs1304322089, tribbles pseudokinase 2 (TRIB2)_rs1881145, cytotoxic T-lymphocyte-associated antigen 4 (CTLA4)_rs231775, lipoma-preferred partner (LPP)_rs6780858, and human leukocyte antigen (HLA)-J_ rs767861647. The PRS of the best model was positively associated with hyperthyroidism risk by 1.939-fold (1.317-2.854) after adjusting for covariates. PRSs interacted with age, metabolic syndrome, and dietary inflammatory index (DII), while hyperthyroidism risk interacted with energy, calcium, seaweed, milk, and coffee intake (P < 0.05). The PRS impact on hyperthyroidism risk was observed in younger (<55 years) participants and adults without metabolic syndrome. PRSs were positively associated with hyperthyroidism risk in participants with low dietary intakes of energy (OR = 2.74), calcium (OR = 2.84), seaweed (OR = 3.43), milk (OR = 2.91), coffee (OR = 2.44), and DII (OR = 3.45). In conclusion, adults with high PRS involved in inflammation and immunity had a high hyperthyroidism risk exacerbated under low intakes of energy, calcium, seaweed, milk, or coffee. These results can be applied to personalized nutrition in a clinical setting.

Association between polygenetic risk scores related to sarcopenia risk and their interactions with regular exercise in a large cohort of Korean adults

BACKGROUND & AIMS

Sarcopenia elevates metabolic disorders in the elderly, and genetic and environmental factors influence the risk of sarcopenia. The purpose of the study was to examine the hypothesis that polygenetic variants for sarcopenic risk had interactions with metabolic disorders and lifestyles associated with sarcopenia risk in adults >50 years in a large urban hospital cohort.

METHODS

Sarcopenia was defined as an appendicular skeletal muscle mass/body weight (SMI) < 29.0% for men and <22.8% for women estimated from participants aged 18-39 years in the KNHANES 2009-2010. Genetic variants were selected using a genome-wide association study for sarcopenia (sarcopenia, n = 1368; control, n = 15,472). The best model showing the gene-gene interactions was selected using a generalized multifactor dimensionality reduction. The polygenic risk scores (PRS) were generated by summing the selected SNP risk alleles in the best model.

RESULTS

SMI was much higher in the control subjects than the sarcopenia subjects in both genders, and the fat mass index was opposite the SMI. The five-single nucleotide polymorphisms (SNPs) model included FADS2_rs97384, MYO10_rs31574 KCNQ5_rs6453647, DOCK5_rs11135857, and LRP1B_ rs74659977. Sarcopenia risk was positively associated with the PRS of the five-SNP model (ORs = 1.977, 95% CI = 1.634-2.393). The PRS interacted with age (P < 0.0001), metabolic syndrome (P = 0.01), grip strength (P = 0.007), and serum total cholesterol concentrations (P = 0.005) for the sarcopenia risk. There were no interactions of PRS with the lifestyle components except for exercise.

CONCLUSION

The genetic impact may be offset in the elderly, having metabolic syndrome, high serum total cholesterol concentrations, and high grip strength, but only exercise in the lifestyle factors can overcome the genetic effect. Middle-aged and elderly participants with a genetic risk for sarcopenia may require regular exercise to maintain high grip strength and prevent metabolic syndrome.

Association between Polygenetic Risk Scores of Low Immunity and Interactions between These Scores and Moderate Fat Intake in a Large Cohort

White blood cell (WBC) counts represent overall immunity. However, a few studies have been conducted to explore the genetic impacts of immunity and their interaction with lifestyles. We aimed to identify genetic variants associated with a low-WBC risk and document interactions between polygenetic risk scores (PRS), lifestyle factors, and nutrient intakes that influence low-WBC risk in a large hospital-based cohort. Single nucleotide polymorphisms (SNPs) were selected by genome-wide association study of participants with a low-WBC count (<4 × 109/L, n = 4176; low-WBC group) or with a normal WBC count (≥4 × 109/L, n = 36,551; control group). The best model for gene-gene interactions was selected by generalized multifactor dimensionality reduction. PRS was generated by summing selected SNP risk alleles of the best genetic model. Adjusted odds ratio (ORs) of the low-WBC group were 1.467 (1.219-1.765) for cancer incidence risk and 0.458 (0.385-0.545) for metabolic syndrome risk. Vitamin D intake, plant-based diet, and regular exercise were positively related to the low-WBC group, but smoking and alcohol intake showed an inverse association. The 7 SNPs included in the best genetic model were PSMD3_rs9898547, LCT_rs80157389, HLA-DRB1_rs532162239 and rs3097649, HLA-C rs2308575, CDKN1A_rs3176337 and THRA_rs7502539. PRS with 7 SNP model were positively associated with the low-WBC risk by 2.123-fold (1.741 to 2.589). PRS interacted with fat intake and regular exercise but not with other nutrient intakes or lifestyles. The proportion with the low WBC in the participants with high-PRS was lower among those with moderate-fat intake and regular exercise than those with low-fat intake and no exercise. In conclusion, adults with high-PRS had a higher risk of a low WBC count, and they needed to be advised to have moderate fat intake (20-25 energy percent) and regular exercise.

Association of Polygenetic Risk Scores Related to Cell Differentiation and Inflammation with Thyroid Cancer Risk and Genetic Interaction with Dietary Intake

The incidence of thyroid cancer continues to increase steadily, and this increasing incidence cannot be attributed solely to the overdiagnosis of microcarcinoma or technical advancements in detection methods and may also depend on environmental and genetic factors. However, the impacts and interactions of genetic and environmental factors remain controversial, and they may differ in Eastern and Western countries. The study's purpose was to identify single nucleotide polymorphisms of genes related to cell differentiation and inflammation to influence thyroid cancer incidence and determine interactions with lifestyles in a large city hospital-based cohort. Genetic variants were selected by genome-wide association study with thyroid cancer participants (case; n = 495) and controls without cancers (n = 56,439). SNPs having gene-gene interactions were selected by generalized multifactor dimensionality reduction. Polygenic risk scores (PRSs) were generated by summing the number of selected SNP risk alleles. PRSs of the best model included 6 SNPs, that is, DIRC3_rs6759952, GAP43_rs13059137, NRG1_rs7834206, PROM1_rs72616195, LRP1B_rs1369535, and LOC100507065_rs11175834. Participants with a high-PRS had a higher thyroid cancer risk by 3.9-fold than those with a low-PRS. The following variables were related to an increased thyroid cancer risk; female (OR = 4.21), high white blood cell count (OR = 4.03), and high energy (OR = 7.00), low alcohol (OR = 4.11), and high seaweed (OR = 4.02) intakes. These variables also interacted with PRS to influence thyroid cancer risk. Meat/noodle diet patterns interacted with PRSs to increase thyroid cancer risk (p = 0.0023). In conclusion, women with a high-PRS associated with cell differentiation and inflammation were at an elevated thyroid cancer risk. Daily energy, seaweeds, and alcohol intake interacted with PRS for thyroid cancer risk. These results could be applied to personalized nutrition plans to reduce the risk of thyroid cancer.

A Novel Mapping Strategy Utilizing Mouse Chromosome Substitution Strains Identifies Multiple Epistatic Interactions That Regulate Complex Traits

The genetic contribution of additive vs. non-additive (epistatic) effects in the regulation of complex traits is unclear. While genome-wide association studies typically ignore gene-gene interactions, in part because of the lack of statistical power for detecting them, mouse chromosome substitution strains (CSSs) represent an alternate approach for detecting epistasis given their limited allelic variation. Therefore, we utilized CSSs to identify and map both additive and epistatic loci that regulate a range of hematologic- and metabolism-related traits, as well as hepatic gene expression. Quantitative trait loci (QTL) were identified using a CSS-based backcross strategy involving the segregation of variants on the A/J-derived substituted chromosomes 4 and 6 on an otherwise C57BL/6J genetic background. In the liver transcriptomes of offspring from this cross, we identified and mapped additive QTL regulating the hepatic expression of 768 genes, and epistatic QTL pairs for 519 genes. Similarly, we identified additive QTL for fat pad weight, platelets, and the percentage of granulocytes in blood, as well as epistatic QTL pairs controlling the percentage of lymphocytes in blood and red cell distribution width. The variance attributed to the epistatic QTL pairs was approximately equal to that of the additive QTL; however, the SNPs in the epistatic QTL pairs that accounted for the largest variances were undetected in our single locus association analyses. These findings highlight the need to account for epistasis in association studies, and more broadly demonstrate the importance of identifying genetic interactions to understand the complete genetic architecture of complex traits.

Polygenetic-Risk Scores Related to Crystallin Metabolism Are Associated with Age-Related Cataract Formation and Interact with Hyperglycemia, Hypertension, Western-Style Diet, and Na Intake

Age-related cataract (ARC) development is associated with loss of crystalline lens transparency related to interactions between genetic and environmental factors. We hypothesized that polygenetic risk scores (PRS) of the selected genetic variants among the ARC-related genes might reveal significant genetic impacts on ARC risk, and the PRS might have gene-gene and gene-lifestyle interactions. We examined the hypothesis in 1972 and 39,095 subjects aged ≥50 years with and without ARC, respectively, in a large-scale hospital-based cohort study conducted from 2004 to 2013. Single nucleotide polymorphisms (SNPs) of the genes related to ARC risk were identified, and polygenetic risk scores (PRS) were generated based on the results of a generalized multifactor dimensionality reduction analysis. Lifestyle interactions with PRS were evaluated. The PRS derived from the best model included the following six SNPs related to crystallin metabolism: ULK4_rs1417380362, CRYAB_rs2070894, ACCN1_rs55785344, SSTR2_rs879419608, PTN_rs322348, and ICA1_rs200053781. The risk of ARC in the high-PRS group was 2.47-fold higher than in the low-PRS group after adjusting for confounders. Age, blood pressure, and glycemia interacted with PRS to influence the risk of ARC: the incidence of ARC was much higher in the elderly (≥65 years) and individuals with hypertension or hyperglycemia. The impact of PRS on ARC risk was greatest in middle-aged individuals with hypertension or hyperglycemia. Na, coffee, and a Western-style diet intake also interacted with PRS to influence ARC risk. ARC risk was higher in the high-PRS group than in the low-PRS group, and high Na intake, Western-style diet, and low coffee intake elevated its risk. In conclusion, ARC risk had a positive association with PRS related to crystallin metabolism. The genetic impact was greatest among those with high Na intake or hypertension. These results can be applied to precision nutrition interventions to prevent ARC.

Polygenetic-Risk Scores for A Glaucoma Risk Interact with Blood Pressure, Glucose Control, and Carbohydrate Intake

Glaucoma, a leading cause of blindness, has multifactorial causes, including environmental and genetic factors. We evaluated genetic risk factors of glaucoma with gene-gene interaction and explored modifications of genetic risk with gene-lifestyles interaction in adults >40 years. The present study included 377 subjects with glaucoma and 47,820 subjects without glaucoma in a large-scale hospital-based cohort study from 2004 to 2013. The presence of glaucoma was evaluated by a diagnostic questionnaire evaluated by a doctor. The genome-wide association study was performed to identify genetic variants associated with glaucoma risk. Food intake was assessed using a semiquantitative food frequency questionnaire. We performed generalized multifactor dimensionality reduction analysis to construct polygenetic-risk score (PRS) and explored gene × nutrient interaction. PRS of the best model included LIM-domain binding protein-2 (LDB2) rs3763969, cyclin-dependent kinase inhibitor 2B (CDKN2B) rs523096, ABO rs2073823, phosphodiesterase-3A (PDE3A) rs12314390, and cadherin 13 (CDH13) rs12449180. Glaucoma risk in the high-PRS group was 3.02 times that in the low-PRS group after adjusting for confounding variables. For those with low serum glucose levels (<126 mg/dL), but not for those with high serum glucose levels, glaucoma risk in the high-PRS group was 3.16 times that in the low-PRS group. In those with high carbohydrate intakes (≥70%), but not in those with low carbohydrate intakes, glaucoma risk was 3.74 times higher in the high-PRS group than in the low-PRS group. The glaucoma risk was 3.87 times higher in the high-PRS group than in the low-PRS group only in a low balanced diet intake. In conclusion, glaucoma risk increased by three-fold in adults with a high PRS, and it can be reduced by good control of serum glucose concentrations and blood pressure (BP) with a balanced diet intake. These results can be applied to precision nutrition to reduce glaucoma risk.

Detection of epistasis between ACTN3 and SNAP-25 with an insight towards gymnastic aptitude identification

In this study, we performed an analysis of the impact of performance enhancing polymorphisms (PEPs) on gymnastic aptitude while considering epistatic effects. Seven PEPs (rs1815739, rs8192678, rs4253778, rs6265, rs5443, rs1076560, rs362584) were considered in a case (gymnasts)-control (sedentary individuals) setting. The study sample comprised of two athletes' sets: 27 elite (aged 24.8 ± 2.1 years) and 46 sub-elite (aged 19.7 ± 2.4 years) sportsmen as well as a control group of 245 sedentary individuals (aged 22.5 ± 2.1 years). The DNA was derived from saliva and PEP alleles were determined by PCR, RT-PCR. Following Multifactor Dimensionality Reduction, logistic regression models were built. The synergistic effect for rs1815739 x rs362584 reached 5.43%. The rs1815739 x rs362584 epistatic regression model exhibited a good fit to the data (Chi-squared = 33.758, p ≈ 0) achieving a significant improvement in sportsmen identification over naïve guessing. The area under the receiver operating characteristic curve was 0.715 (Z-score = 38.917, p ≈ 0). In contrast, the additive ACTN3 -SNAP-25 logistic regression model has been verified as non-significant. We demonstrate that a gene involved in the differentiation of muscle architecture-ACTN3 and a gene, which plays an important role in the nervous system-SNAP-25 interact. From the perspective originally established by the Berlin Academy of Science in 1751, the matter of communication between the brain and muscles via nerves adopts molecular manifestations. Further in-vitro investigations are required to explain the molecular details of the rs1815739 -rs362584 interaction.

Gene-gene and gene-lifestyle interactions of AKAP11, KCNMA1, PUM1, SPTBN1, and EPDR1 on osteoporosis risk in middle-aged adults

OBJECTIVES

Osteoporosis is associated with genetic and environmental factors. The aim of this article was to determine how the polygenic risk scores (PRS) of genetic variants that affect osteoporosis and its related signaling interact with the lifestyle of middle-aged adults.

METHODS

The study examined 8845 participants from Ansan/Ansung cohorts. Osteoporosis was defined as a T-score of bone mineral density ≤-2.5 in either the wrist or tibia; 1136 participants had osteoporosis. Genome-wide association studies of individuals 40 to 65 y of age were conducted and the best gene-gene interactions from the genetic variants related to osteoporosis were selected and explored using the generalized multifactor dimensionality reduction method. PRS for the best model (PRSBM) was calculated by weighted PRS that was divided into low, medium, and high groups.

RESULTS

The model that contributed the most influence on osteoporosis risk with gene-gene interactions included AKAP11_rs238340, KCNMA1_ rs628948, PUM1_rs7529390, SPTBN1_ rs6752877, and EPDR1_rs2722298. The risk for osteoporosis in the tibia was elevated by 1.71-fold in the high PRSBM group compared with the low PRSBM group. Energy and nutrient intake did not have any interaction with PRSBM and thus did not influence risk for osteoporosis. However, interestingly, only coffee and caffeine intake did interact with PRSBM and affected risk for osteoporosis. In patients with low coffee (<3 cup/wk) and caffeine(<60 mg/d) consumption, osteoporosis risk was higher in the high PRSBM group than the low PRSBM group by 2.27- and 2.29-fold, respectively. In the low coffee intake group, bone mineral density in the high PRSBM group was significantly higher than in the low PRSBM arm.

CONCLUSIONS

Carriers with high PRSBM increased susceptibility to osteoporosis, especially in low coffee and caffeine intake. The results can be applied to personalized nutrition for lowering the risk for osteoporosis.

Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose

Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p<1x10-7 (adjusted for multiple hypothesis-testing with the IBC array). Two SNPs had significant joint effects in the overall model and significant main effects only in one smoking stratum: rs140637 (FBN1) in AA individuals had a significant main effect only among smokers, and rs1444261 (closest gene C2orf63) in EA individuals had a significant main effect only among nonsmokers. Three additional SNPs were identified as having potential interaction by exhibiting a significant main effects only in smokers: rs1801232 (CUBN) in AA individuals, rs12243326 (TCF7L2) in EA individuals, and rs4132670 (TCF7L2) in EA individuals. No SNP met significance for potential interaction with smoking on baseline FG. The identification of these loci provides evidence for genetic interactions with smoking exposure that may explain some of the heterogeneity in the association between smoking and T2D.

Subcutaneous fat mass is associated with genetic risk scores related to proinflammatory cytokine signaling and interact with physical activity in middle-aged obese adults

Background and aims

Subcutaneous fat mass is negatively correlated with atherogenic risk factors, but its putative benefits remain controversial. We hypothesized that genetic variants that influence subcutaneous fat mass would modulate lipid and glucose metabolism and have interactions with lifestyles in Korean middle-aged adults with high visceral fat.

Materials and methods

Subcutaneous fat mass was categorized by dividing the average of subscapular skin-fold thickness by BMI and its cutoff point was 1.2. Waist circumferences were used for representing visceral fat mass with Asian cutoff points. GWAS of subjects aged 40–65 years with high visceral fat (n = 3303) were conducted and the best gene-gene interactions from the genetic variants related to subcutaneous fat were selected and explored using the generalized multifactor dimensionality reduction. Genetic risk scores (GRS) were calculated by weighted GRS that was divided into low, medium and high groups.

Results

Subjects with high subcutaneous fat did not have dyslipidemia compared with those with low subcutaneous fat, although both subject groups had similar amounts of total fat. The best model to influence subcutaneous fat included IL17A_rs4711998, ADCY2_rs326149, ESRRG_rs4846514, CYFIP2_rs733730, TCF7L2_rs7917983, ZNF766_rs41497444 and TGFBR3_rs7526590. The odds ratio (OR) for increasing subcutaneous fat was higher by 2.232 folds in the high-GRS group, after adjusting for covariates. However, total and LDL cholesterol, triglyceride and C-reactive protein concentrations in the circulation were not associated with GRS. Subjects with high-GRS had higher serum HDL cholesterol levels than those with low-GRS. Physical activity and GRS had an interaction with subcutaneous fat. In subjects with low physical activity, the odds ratio for high subcutaneous fat increased by 2.232, but subcutaneous fat deposition was not affected in the high-GRS group with high physical activity.

Conclusion

Obese adults with high-GRS had more subcutaneous fat, but they did not show more dyslipidemia and inflammation compared to low-GRS. High physical activity prevented subcutaneous fat deposition in subjects with high GRS for subcutaneous fat.

Overview of genomics and post-genomics research on type 2 diabetes mellitus: Future perspectives and a framework for further studies

In this review, we briefly outlined salient features of pathophysiology and results of the genetic association studies hitherto conducted on type 2 diabetes. Primarily focusing on the current status of genomic research, we briefly discussed the limited progress made during the post-genomic era and tried to identify the limitations of the post-genomic research strategies. We suggested reanalysis of the existing genomic data through advanced statistical and computational methods and recommended integrated genomics-metabolomics approaches for future studies to facilitate understanding of the gene-environment interactions in the manifestation of the disease. We also propose a framework for research that may be apt for determining the effects of urbanization and changing lifestyles in the manifestation of complex genetic disorders like type 2 diabetes in the Indian populations and offset the confounding effects of both genetic and environmental factors in the natural way.

High genetic risk scores of SLIT3, PLEKHA5 and PPP2R2C variants increased insulin resistance and interacted with coffee and caffeine consumption in middle-aged adults

BACKGROUNDS AND AIMS

Insulin resistance is a common feature of metabolic syndrome that may be influenced by genetic risk factors. We hypothesized that genetic risk scores (GRS) of SNPs that influence insulin resistance and signaling interact with lifestyles to modulate insulin resistance in Korean adults.

METHODS AND RESULTS

Genome-wide association studies (GWAS) of subjects aged 40-65 years who participated in the Ansung/Ansan cohorts (8842 adults) in Korea revealed 52 genetic variants that influence insulin resistance. The best gene-gene interaction model was explored using the generalized multifactor dimensionality reduction (GMDR) method. GRS from the best model were calculated and the GRS were divided into low, medium and high groups. The best model for representing insulin resistance included SLIT3_rs2974430, PLEKHA5_rs1077044, and PPP2R2C_rs16838853. The odds ratios for insulin resistance were increased by 150% in the High-GRS group compared to the Low-GRS group. However, ORs for insulin secretion capacity, measured by HOMA-B, were not associated with GRS. Coffee and caffeine intake and GRS had an interaction with insulin resistance: In subjects with high coffee (≥10 cups/week) or caffeine intake (≥220 mg caffeine/day), insulin resistance was significantly elevated in the High-GRS group, but not in the Low-GRS. However, alcohol intake, smoking and physical activity did not have an interaction with GRS. Insulin secretion capacity was not significantly influenced by GRS when evaluating the adjusted odds ratios.

CONCLUSIONS

Subjects with High-GRS may be susceptible to increased insulin resistance by 50% and its risk may be exacerbated by consuming more than 10 cups coffee/week or 220 mg caffeine/day.

Interactions among the variants of insulin-related genes and nutrients increase the risk of type 2 diabetes

Asians easily develops type 2 diabetes (T2DM) since they have insufficient glucose-stimulated insulin secretion (GSIS) in insulin resistant states. Since this may be associated with genetic background, the hypothesis of this study was that inter-genetic and gene-nutrient interactions may explain the low insulin secretory capacity of Asians. Accordingly, we identified the best gene-gene and gene-nutrient interactions using generalized multifactor dimensionality reduction (GMDR) in a large Korean cohort (n=8,842). Initially, we used 105 genetic variants associated with GSIS to identify the best gene-gene interaction model using the GMDR method. The best model included six SNPs, FNBP1L-rs4847428, FNBP1L-rs23766, GLIS3-rs2027393, GLIS3-rs3892354, GLIS3-rs486163 and DLC1-rs17093957. For each individual, we obtained the genetic risk scores based on the best model (GRSBM) to predict the GSIS levels. The GRSBM were divided into low, medium and high groups, and the association between T2DM and the GRSBM was measured using logistic regression. We analyzed the interaction between the GRSBM and the nutrition intakes. The adjusted odds ratios for T2DM risk increased by 1.701 fold in the high-score group compared to the low-score group. HOMA-B, an index of insulin secretion capacity, but not insulin resistance index was much lower in the high-score group than the low-score group. The association between the GRSBM and T2DM risk was greater in subjects with high energy intakes and low Ca intake, than those with low energy intake and high Ca intake. The high-score group was susceptible to T2DM incidence due to lower GSIS than the low-score group especially in subjects with high energy intake. In conclusion, the hypothesis of the study was accepted. These findings suggested that individuals with high GRSBM of the 6 genes in the model should avoid diets in high energy and low in calcium (<500 mg/day) to protect against T2DM.

Association of type 2 diabetes mellitus genes in polycystic ovary syndrome aetiology among women from southern India

BACKGROUND & OBJECTIVES

Polycystic ovary syndrome (PCOS) is the most common reproductive endocrine disorder of premenopausal women. Given the phenotypic overlap between PCOS and type 2 diabetes mellitus (T2DM), this study was carried out to investigate whether genes implicated in T2DM were also involved in the susceptibility to PCOS among women from southern India.

METHODS

A total of 248 women with PCOS and 210 healthy women as controls were genotyped for a panel of 15 single nucleotide polymorphisms (SNPs) from the nine T2DM genes, such as TCF7L2, IGF2BP2, SLC30A8, HHEX, CDKAL1, CDKN2A, IRS1, CAPN10 and PPARG, on Sequenom MassARRAY platform.

RESULTS

None of the 15 SNPs were found to be significantly associated with PCOS after Bonferroni correction for multiple testing, either in the univariate or multivariate context. The cumulative effect of risk alleles observed with reference to T2DM was also not seen with reference to PCOS.

INTERPRETATION & CONCLUSIONS

The nine T2DM genes considered in this exploratory study might not be the primary susceptibility factors for PCOS among Indian women. Our results supplement the lack of evidence of the association of T2DM genes with PCOS among the Chinese and Caucasians hinting at the possible universality of this pattern. Specifically designed comprehensive studies that include women with T2DM and PCOS are required to explore the precise role of the diabetes genes.

Interaction between β-hexachlorocyclohexane and ADIPOQ genotypes contributes to the risk of type 2 diabetes mellitus in East Chinese adults

Growing evidence links environmental exposure to hexachlorocyclohexanes (HCHs) to the risk of type 2 diabetes mellitus (T2DM), and ADIPOQ that encodes adiponectin is considered as an important gene for T2DM. However, the role of ADIPOQ-HCH interaction on T2DM risk remains unclear. Thus, a paired case-control study was conducted in an East Chinese community. A total of 1446 subjects, including 723 cases and 723 controls matched on age, gender and residence, were enrolled, and 4 types of HCH isomers were measured in serum samples using GC-MS/MS. Additionally, 4 candidate ADIPOQ SNPs (rs182052, rs266729, rs6810075, and rs16861194) were genotyped by TaqMan assay, and plasma adiponectin was measured using ELISA. No associations between 4 SNPs and T2DM risk were found, but T2DM risk significantly increased with serum levels of β-HCH (P < 0.001). Furthermore, the synergistic interaction between β-HCH and rs182052 significantly increased T2DM risk (OR _{I-additive model} = 2.20, OR _{I-recessive model} = 2.13). Additionally, individuals carrying only rs182052 (A allele) with high levels of β-HCH had significant reduction in adiponectin levels (P = 0.016). These results indicate that the interaction between rs182052 and β-HCH might increase the risk of T2DM by jointly decreasing the adiponectin level and potentially trigger T2DM development.

Distinct Patterns of Association of Variants at 11q23.3 Chromosomal Region with Coronary Artery Disease and Dyslipidemia in the Population of Andhra Pradesh, India

In our attempt to comprehensively understand the nature of association of variants at 11q23.3 apolipoprotein gene cluster region, we genotyped a prioritized set of 96 informative SNPs using Fluidigm customized SNP genotyping platform in a sample of 508 coronary artery disease (CAD) cases and 516 controls. We found 12 SNPs as significantly associated with CAD at P <0.05, albeit only four (rs2849165, rs17440396, rs6589566 and rs633389) of these remained significant after Benjamin Hochberg correction. Of the four, while rs6589566 confers risk to CAD, the other three SNPs reduce risk for the disease. Interaction of variants that belong to regulatory genes BUD13 and ZPR1 with APOA5-APOA4 intergenic variants is also observed to significantly increase the risk towards CAD. Further, ROC analysis of the risk scores of the 12 significant SNPs suggests that our study has substantial power to confer these genetic variants as predictors of risk for CAD, as illustrated by AUC (0.763; 95% CI: 0.729-0.798, p = <0.0001). On the other hand, the protective SNPs of CAD are associated with elevated Low Density Lipoprotein Cholesterol and Total Cholesterol levels, hence with dyslipidemia, in our sample of controls, which may suggest distinct effects of the variants at 11q23.3 chromosomal region towards CAD and dyslipidemia. It may be necessary to replicate these findings in the independent and ethnically heterogeneous Indian samples in order to establish this as an Indian pattern. However, only functional analysis of the significant variants identified in our study can provide more precise understanding of the mechanisms involved in the contrasting nature of their effects in manifesting dyslipidemia and CAD.

Lack of Association between SLC30A8 Variants and Type 2 Diabetes in Mexican American Families

SLC30A8 encodes zinc transporter 8 which is involved in packaging and release of insulin. Evidence for the association of SLC30A8 variants with type 2 diabetes (T2D) is inconclusive. We interrogated single nucleotide polymorphisms (SNPs) around SLC30A8 for association with T2D in high-risk, pedigreed individuals from extended Mexican American families. This study of 118 SNPs within 50 kb of the SLC30A8 locus tested the association with eight T2D-related traits at four levels: (i) each SNP using measured genotype approach (MGA); (ii) interaction of SNPs with age and sex; (iii) combinations of SNPs using Bayesian Quantitative Trait Nucleotide (BQTN) analyses; and (iv) entire gene locus using the gene burden test. Only one SNP (rs7817754) was significantly associated with incident T2D but a summary statistic based on all T2D-related traits identified 11 novel SNPs. Three SNPs and one SNP were weakly but interactively associated with age and sex, respectively. BQTN analyses could not demonstrate any informative combination of SNPs over MGA. Lastly, gene burden test results showed that at best the SLC30A8 locus could account for only 1-2% of the variability in T2D-related traits. Our results indicate a lack of association of the SLC30A8 SNPs with T2D in Mexican American families.

Erchen Decoction Prevents High-Fat Diet Induced Metabolic Disorders in C57BL/6 Mice

Erchen decoction (ECD) is a traditional Chinese medicine prescription, which is used in the treatment of obesity, hyperlipidemia, fatty liver, diabetes, hypertension, and other diseases caused by retention of phlegm dampness. In this study we investigated the potential mechanism of ECD, using metabolism-disabled mice induced by high-fat diet. Body weight and abdominal circumference were detected. OGTT was measured by means of collecting blood samples from the tail vein. Blood lipid levels and insulin were measured using biochemical assay kit. Real-time PCR was used to measure the CDKAL1 gene expression and western blot was used to measure the protein expression. Through the research, it was found that ECD showed markedly lower body weight and abdominal circumference than those in the HFD group. Consistently, we observed that ECD significantly improved glucose tolerance, promoted the secretion of insulin and decreased the level of TG, TC level. Meanwhile, we observed significantly increased CDKAL1 mRNA and protein level in the ECD group. Therefore, we speculate that the potential molecular mechanism of ECD is to promote the CDKAL1 expression, ameliorate islet cell function, and raise insulin levels to regulate the metabolic disorder.