Heritability and genome-wide association analyses of fasting plasma glucose in Chinese adult twins

Tracking correlations and predictors of plasma glucose in young adulthood: A comprehensive analysis from adolescence to young adulthood in TLGS study

AIMS

We investigated the tracking correlations between fasting plasma glucose (FPG) in adolescence with both FPG and 2-hour post-load glucose (2 h-PG) in adulthood, and identified the predictors of FPG and 2 h-PG in young adulthood using traditional risk factors during adolescence and adulthood.

METHODS

We included 2188 participants (1033 male) from the Tehran lipid and glucose study within the age ranges 11-18 and 19-40 years during 1999-2018. The area under the curve (AUC) was computed using the growth curve models, and predictors were identified by the linear regression model.

RESULTS

The partial correlation between AUCs of FPG in adolescence and adulthood was 0.37 (P < 0.001). The correlation between AUCs of FPG in adolescence and 2 h-PG in adulthood was 0.17 (P < 0.001). The AUC of FPG was a significant positive predictor for both FPG and 2 h-PG in young adulthood. Other predictors of adult FPG included sex, as well as BMI and the ratio of triglycerides to HDL-cholesterol during both adolescence and adulthood.

CONCLUSIONS

Tracking correlation was observed for FPG, suggesting that monitoring and managing risk factors in adolescence may have implications for future glucose metabolism in young adulthood.

Frequency of Consumption of Food Groups and Cardio-Metabolic Risk Factors: A Genetically Informative Twin Study in Sri Lanka

Low- and middle-income countries (LMICs) globally have undergone rapid urbanisation, and changes in demography and health behaviours. In Sri Lanka, cardio-vascular disease and diabetes are now leading causes of mortality. High prevalence of their risk factors, including hypertension, dysglycaemia and obesity have also been observed. Diet is a key modifiable risk factor for both cardio-vascular disease and diabetes as well as their risk factors. Although typically thought of as an environmental risk factor, dietary choice has been shown to be genetically influenced, and genes associated with this behaviour correlate with metabolic risk indicators. We used Structural Equation Model fitting to investigate the aetiology of dietary choices and cardio-metabolic phenotypes in COTASS, a population-based twin and singleton sample in Colombo, Sri Lanka. Participants completed a Food Frequency Questionnaire (N = 3934) which assessed frequency of intake of 14 food groups including meat, vegetables and dessert or sweet snacks. Anthropometric (N = 3675) and cardio-metabolic (N = 3477) phenotypes were also collected including weight, blood pressure, cholesterol, fasting plasma glucose and triglycerides. Frequency of consumption of most food items was found to be largely environmental in origin with both the shared and non-shared environmental influences indicated. Modest genetic influences were observed for some food groups (e.g. fruits and leafy greens). Cardio-metabolic phenotypes showed moderate genetic influences with some shared environmental influence for Body Mass Index, blood pressure and triglycerides. Overall, it seemed that shared environmental effects were more important for both dietary choices and cardio-metabolic phenotypes compared to populations in the Global North.

Short-Term Exposure to Nitrogen Dioxide Modifies Genetic Predisposition in Blood Lipid and Fasting Plasma Glucose: A Pedigree-Based Study

(1) Background: Previous studies suggest that exposure to nitrogen dioxide (NO2) has a negative impact on health. But few studies have explored the association between NO2 and blood lipids or fasting plasma glucose (FPG), as well as gene-air pollution interactions. This study aims to fill this knowledge gap based on a pedigree cohort in southern China. (2) Methods: Employing a pedigree-based design, 1563 individuals from 452 families participated in this study. Serum levels of triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDLC), high-density lipoprotein cholesterol (HDLC), and FPG were measured. We investigated the associations between short-term NO2 exposure and lipid profiles or FPG using linear mixed regression models. The genotype-environment interaction (GenoXE) for each trait was estimated using variance component models. (3) Results: NO2 was inversely associated with HDLC but directly associated with TG and FPG. The results showed that each 1 μg/m3 increase in NO2 on day lag0 corresponded to a 1.926% (95%CI: 1.428-2.421%) decrease in HDLC and a 1.400% (95%CI: 0.341-2.470%) increase in FPG. Moreover, we observed a significant genotype-NO2 interaction with HDLC and FPG. (4) Conclusion: This study highlighted the association between NO2 exposure and blood lipid profiles or FPG. Additionally, our investigation suggested the presence of genotype-NO2 interactions in HDLC and FPG, indicating potential loci-specific interaction effects. These findings have the potential to inform and enhance the interpretation of studies that are focused on specific gene-environment interactions.

Assessing the Link between Diabetic Metabolic Dysregulation and Breast Cancer Progression

Diabetes mellitus is a burdensome disease that affects various cellular functions through altered glucose metabolism. Several reports have linked diabetes to cancer development; however, the exact molecular mechanism of how diabetes-related traits contribute to cancer progression is not fully understood. The current study aimed to explore the molecular mechanism underlying the potential effect of hyperglycemia combined with hyperinsulinemia on the progression of breast cancer cells. To this end, gene dysregulation induced by the exposure of MCF7 breast cancer cells to hyperglycemia (HG), or a combination of hyperglycemia and hyperinsulinemia (HGI), was analyzed using a microarray gene expression assay. Hyperglycemia combined with hyperinsulinemia induced differential expression of 45 genes (greater than or equal to two-fold), which were not shared by other treatments. On the other hand, in silico analysis performed using a publicly available dataset (GEO: GSE150586) revealed differential upregulation of 15 genes in the breast tumor tissues of diabetic patients with breast cancer when compared with breast cancer patients with no diabetes. SLC26A11, ALDH1A3, MED20, PABPC4 and SCP2 were among the top upregulated genes in both microarray data and the in silico analysis. In conclusion, hyperglycemia combined with hyperinsulinemia caused a likely unique signature that contributes to acquiring more carcinogenic traits. Indeed, these findings might potentially add emphasis on how monitoring diabetes-related metabolic alteration as an adjunct to diabetes therapy is important in improving breast cancer outcomes. However, further detailed studies are required to decipher the role of the highlighted genes, in this study, in the pathogenesis of breast cancer in patients with a different glycemic index.

Identification of key DNA methylation changes on fasting plasma glucose: a genome-wide DNA methylation analysis in Chinese monozygotic twins

BACKGROUND

Elevated fasting plasma glucose (FPG) levels can increase morbidity and mortality even when it is below the diagnostic threshold of type 2 diabetes mellitus (T2DM). We conducted a genome-wide DNA methylation analysis to detect DNA methylation (DNAm) variants potentially related to FPG in Chinese monozygotic twins.

METHODS

Genome-wide DNA methylation profiling in whole blood of twins was performed using Reduced Representation Bisulfite Sequencing (RRBS), yielding 551,447 raw CpGs. Association between DNAm of single CpG and FPG was tested using a generalized estimation equation. Differentially methylated regions (DMRs) were identified using comb-P approach. ICE FALCON method was utilized to perform the causal inference. Candidate CpGs were quantified and validated using Sequenom MassARRAY platform in a community population. Weighted gene co-expression network analysis (WGCNA) was conducted using gene expression data from twins.

RESULTS

The mean age of 52 twin pairs was 52 years (SD: 7). The relationship between DNAm of 142 CpGs and FPG reached the genome-wide significance level. Thirty-two DMRs within 24 genes were identified, including TLCD1, MRPS31P5, CASZ1, and CXADRP3. The causal relationship of top CpGs mapped to TLCD1, MZF1, PTPRN2, SLC6A18, ASTN2, IQCA1, GRIN1, and PDE2A genes with FPG were further identified using ICE FALCON method. Pathways potentially related to FPG were also identified, such as phospholipid-hydroperoxide glutathione peroxidase activity and mitogen-activated protein kinase p38 binding. Three CpGs mapped to SLC6A18 gene were validated in a community population, with a hypermethylated direction in diabetic patients. The expression levels of 18 genes (including SLC6A18 and TLCD1) were positively correlated with FPG levels.

CONCLUSIONS

We detect many DNAm variants that may be associated with FPG in whole blood, particularly the loci within SLC6A18 gene. Our findings provide important reference for the epigenetic regulation of elevated FPG levels and diabetes.

Genetic and Environmental Correlation Analysis of Serum Creatinine Levels in Chinese Twins

Almost all creatinine is excreted by the kidney in individuals. Serum creatinine concentration, a widely used renal function index in clinical practice, can be affected by both genetic and environmental factors, as evidenced by current research exploring the relationship between these factors and kidney function. However, few studies have explored the heritability of serum creatinine in Asian populations. Therefore, we explored the genetic and environmental factors that affect the serum creatinine level in Asian populations. Participants in this study came from the Qingdao Twin Registry in China, and 374 pairs of twins were included, of which 139 pairs were dizygotic twins, whose ages ranged from 40 to 80 years old, and the serum creatinine level ranged from 10 to 126 μmol/L. Structural equation models were constructed using Mx software to calculate heritability, with adjusted covariates being age, sex, and body mass index. The results of heritability analysis showed that ACE was the best fit model. Serum creatinine level is influenced by genetic and environmental factors. The result of heritability was 35.44%, and the influence of shared environmental factors accounted for 52.13%. This study provided the relevant basis for future research on genetic and environmental factors affecting serum creatinine levels in Asian populations.

Genome-Wide Association Study Identifies Genetic Loci Associated With Fat Cell Number and Overlap With Genetic Risk Loci for Type 2 Diabetes

Interindividual differences in generation of new fat cells determine body fat and type 2 diabetes risk. In the GENetics of Adipocyte Lipolysis (GENiAL) cohort, which consists of participants who have undergone abdominal adipose biopsy, we performed a genome-wide association study (GWAS) of fat cell number (n = 896). Candidate genes from the genetic study were knocked down by siRNA in human adipose-derived stem cells. We report 318 single nucleotide polymorphisms (SNPs) and 17 genetic loci displaying suggestive (P < 1 × 10-5) association with fat cell number. Two loci pass threshold for GWAS significance, on chromosomes 2 (lead SNP rs149660479-G) and 7 (rs147389390-deletion). We filtered for fat cell number-associated SNPs (P < 1.00 × 10-5) using evidence of genotype-specific expression. Where this was observed we selected genes for follow-up investigation and hereby identified SPATS2L and KCTD18 as regulators of cell proliferation consistent with the genetic data. Furthermore, 30 reported type 2 diabetes-associated SNPs displayed nominal and consistent associations with fat cell number. In functional follow-up of candidate genes, RPL8, HSD17B12, and PEPD were identified as displaying effects on cell proliferation consistent with genetic association and gene expression findings. In conclusion, findings presented herein identify SPATS2L, KCTD18, RPL8, HSD17B12, and PEPD of potential importance in controlling fat cell numbers (plasticity), the size of body fat, and diabetes risk.

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

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