A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance

Ppp1r3b is a metabolic switch that shifts hepatic energy storage from lipid to glycogen

The PPP1R3B gene, encoding PPP1R3B protein, is critical for liver glycogen synthesis and maintaining blood glucose levels. Genetic variants affecting PPP1R3B expression are associated with several metabolic traits and liver disease, but the precise mechanisms are not fully understood. We studied the effects of both Ppp1r3b overexpression and deletion in mice and cell models and found that both changes in Ppp1r3b expression result in dysregulated metabolism and liver damage, with overexpression increasing liver glycogen stores, while deletion resulted in higher liver lipid accumulation. These patterns were confirmed in humans where variants increasing PPP1R3B expression had lower liver fat and decreased plasma lipids, whereas putative loss-of-function variants were associated with increased liver fat and elevated plasma lipids. These findings support that PPP1R3B is a crucial regulator of hepatic metabolism beyond glycogen synthesis and that genetic variants affecting PPP1R3B expression levels influence if hepatic energy is stored as glycogen or triglycerides.

Contrastive sequence signatures between the both sides of a recombination spot reveal an adaptation at PPARD locus from standing variation for pleiotropy since out-of-Africa dispersal

BACKGROUND

Drug metabolism and transporter genes are a specialized class of genes involved in absorption, distribution, metabolism and excretion. They easily present distinct genetic population differentiation and are vulnerable to natural selection.

RESULTS

We initiated a study using a special panel of informative genetic markers in such genes and dissected the genetic structure in representative Chinese and worldwide populations. A distinctive sub-population stratification was discovered in extensive Eurasians and resulted from divergence at the PPARD locus. The contrastive sequence signatures between the both sides of a recombination spot prove a selective sweep on this locus for genetic hitchhiking effect. A genealogy-based framework demonstrates the positive selection acting from standing variation exerted a moderate pressure in Eurasians, and drove the adaptive allele up to a high frequency. The timing and tempo estimations for the genetic adaptation indicate its onset coincided with the early out-of-Africa migration of modern humans and it lasted over a prolonged evolutionary history. A phenome-wide association analysis reveals an extended cis-regulation on the local gene expression and the pleiotropy implicated in a variety of complex traits. The colocalization analyses between the genetic associations from cis-acting gene expression and complex traits signify the most likely selective pressure from physical capacity, energy metabolism, and immune-related involvement, and provide prioritization for the effective genes and casual variants.

CONCLUSIONS

This work has laid a foundation for following efforts to make full sense of the biological mechanisms underlying the genetic adaptation.

Mendelian randomization study on the causal relationships among fasting blood glucose, plasma proteins, and squamous cell lung cancer

BACKGROUND

Squamous cell lung cancer (SQCLC) represents the second most common subtype of lung cancer (LC) with characteristics of treatment resistance. Plasma proteins often influence levels of fasting blood glucose (FBG), consequently impacting LC. However, the precise role of FBG in this association remains unclear.

OBJECTIVE

To investigate the causal relationships of FBG with LC and its subtypes, plasma proteins, and SQCLC, as well as the mediating role of FBG.

METHODS

Mendelian randomization (MR) analysis was employed to assess the causal associations of FBG with LC and its subtypes, plasma proteins and SQCLC, and plasma proteins and FBG, using the two-step MR approach with the primary method being Inverse Variance Weighted (IVW). Protein-Protein Interaction (PPI) network was utilized to identify hub genes of plasma proteins causally linked to SQCLC.

RESULTS

FBG was a risk factor for SQCLC (OR: 1.376, 95% CI 1.017-1.862, P = 0.038) but had no significant causal associations with LC and other subtypes (P > 0.05). Furthermore, 54 plasma proteins had significant causal associations with SQCLC (P < 0.05). EEF2 K (OR: 1.111, 95% CI 1.015-1.216, P = 0.023) and SSR1 (OR: 0.546, 95% CI 0.487-0.613, P < 0.001) were identified as a risk and protective factor for FBG, respectively. Mediation analysis indicated a significant negative mediating effect of FBG in the causal relationship between SSR1 and SQCLC (B = - 0.193, 95% CI - 0.312-0.074, P = 0.001), with a mediation proportion of 44.4%.

CONCLUSION

Our study revealed FBG as a risk factor for SQCLC and demonstrated the mediating role of FBG in the causal association between SSR1 and SQCLC.

Association of MTNR1B Gene Polymorphisms with Body Mass Index in Hashimoto's Thyroiditis

Hashimoto's thyroiditis (HT) is an autoimmune disorder of the thyroid gland characterized by chronic inflammation, which in most cases results in hypothyroidism. The melatonin receptor MTNR1B is sporadically expressed in the thyroid gland. It modulates immune responses, and alterations in the melatonin-MTNR1B receptor signaling pathway may play a role in developing autoimmune diseases. Obesity worsens the severity and progression of some autoimmune diseases and reduces treatment efficacy. This study aimed to investigate the association of MTNR1B gene polymorphisms (rs10830963, rs1387153, and rs4753426) with HT with regards to the body mass index (BMI). Patients with HT were categorized into normal weight BMI ≤ 25 kg/m2 and overweight/obese BMI > 25 kg/m2 groups. This study included 115 patients with a clinical-, ultrasound-, and laboratory-confirmed diagnosis of HT (64 normal-weight patients and 51 overweight/obese patients) with a mean age of 43 ± 12 years. The results showed that specific MTNR1B polymorphisms are associated with obesity in HT patients. BMI was found to be associated with the rs10830963 polymorphism, and the G allele and GG genotype of the rs10830963 polymorphism were more common in overweight/obese HT patients. Furthermore, the results suggest that genetic factors associated with BMI play a role in developing HT and open new possibilities for personalized treatment approaches.

Associations of Lipid-Lowering Drugs With Blood Pressure and Fasting Glucose: A Mendelian Randomization Study

BACKGROUND

Observational studies have linked LDL-C (low-density lipoprotein-cholesterol)-lowering drugs with lower blood pressure (BP) and higher fasting glucose, but the causality remains unclear. We conducted a drug target Mendelian randomization study to assess the causal associations of genetically proxied inhibition of HMGCR (3-hydroxy-3-methylglutaryl coenzyme A reductase), PCSK9 (proprotein convertase subtilisin/kexin type 9), and NPC1L1 (Niemann-Pick C1-Like 1) with BP and fasting glucose.

METHODS

Single-nucleotide polymorphisms in HMGCR, NPC1L1, and PCSK9 associated with LDL-C in a genome-wide association study meta-analysis from the Global Lipid Genetics Consortium (173 082 European individuals) were used to proxy LDL-C-lowering drug targets. BP and fasting glucose data were obtained from genome-wide association studies conducted by the International Consortium of Blood Pressure (757 601 European participants) and the Glucose and Insulin-related Traits Consortium (58 074 European participants). We used the inverse-variance weighted method and a series of sensitivity analyses for assessment.

RESULTS

Genetically proxied inhibition of HMGCR was negatively associated with systolic BP (β, -0.81 [95% CI, -1.26 to -0.37 mm Hg]; P=3.72×10-4) and diastolic BP (β, -1.58 [95% CI, -2.24 to -0.91 mm Hg]; P=3.23×10-6). Conversely, we observed a positive association between genetically proxied inhibition of HMGCR and high fasting glucose (β, 0.13 [95% CI, 0.08-0.17 mmol/L]; P=4.25×10-8). However, there was no association of PCSK9 and NPC1L1 inhibition with BP or fasting glucose.

CONCLUSIONS

Genetically proxied inhibition of HMGCR was significantly associated with low BP and high fasting glucose, while there was no effect of PCSK9 and NPC1L1 inhibition on BP or fasting glucose.

Assessing the effect of modifiable risk factors on hepatocellular carcinoma: evidence from a bidirectional Mendelian randomization analysis

BACKGROUND

The pathogenesis of hepatocellular carcinoma (HCC) involves a variety of environmental risk factors, some of which have yet to be fully clarified. Using the Mendelian randomization (MR) approach, this study comprehensively investigates the causal effect of genetically predicted modifiable risk factors on HCC.

METHODS

Genetic variants related to the 50 risk factors that had been identified in previous research were derived from genome-wide association studies. Summary statistics for the discovery cohort and validation cohort of HCC were sourced from the FinnGen consortium and the UK Biobank, respectively. Bidirectional MR analysis and sensitivity analysis were performed to establish causative risk factors for HCC.

RESULTS

Through the inverse variance weighted method, the results of the discovery cohort indicated that waist circumference, nonalcoholic fatty liver disease (NAFLD), alanine aminotransferase (ALT) levels, and aspartate aminotransferase (AST) levels were significantly linked to HCC occurrence risk. Furthermore, body fat percentage, glycated hemoglobin (HbA1c), obesity class 1-3, waist-to-hip ratio, iron, ferritin, transferrin saturation, and urate had suggestive associations with HCC. The validation cohort further confirmed that NAFLD and ALT levels were strongly related to HCC. Reverse MR indicated that genetic susceptibility to HCC was connected to NAFLD and transferrin saturation. Sensitivity analyses showed that most of the findings were robust.

CONCLUSION

This MR study delivers evidence of the complex causal relationship between modifiable risk factors and HCC. These findings offer new insights into potential prevention and treatment strategies for HCC.

Shared genetic architecture of type 2 diabetes with muscle mass and function and frailty reveals comorbidity etiology and pleiotropic druggable targets

BACKGROUND

Delineating the shared genetic architecture of type 2 diabetes with muscle mass and function and frailty is essential for unraveling the common etiology and developing holistic therapeutic strategies for these co-existing conditions.

METHODS

In this genome-wide pleiotropic association study, we performed multi-level pairwise trait pleiotropic analyses using genome-wide association study summary statistics from up to 461,026 European ancestry individuals to dissect the shared genetic factors and causal relationships of type 2 diabetes and seven glycemic traits with four muscle mass- and function-related phenotypes and the frailty index.

RESULTS

We first identified 27 pairs with significant genetic correlations through the linkage disequilibrium score regression and high-definition likelihood analysis. Then we determined 79 pleiotropic loci and 109 pleiotropic genes across linkage pairs via the pleiotropic analysis under the composite null hypothesis (PLACO), the colocalization, and the Multi-marker Analysis of GenoMic Annotation (MAGMA) analyses. We subsequently performed transcriptome-wide association study (TWAS) analyses using joint-tissue imputation, refined by gene-based integrative fine-mapping through a conditional TWAS approach, and identified 44 unique causal shared genes across 13 tissues in linkage pairs, including eight druggable genes (ABO, AOC1, FTO, GCKR, MTOR, POLK, PPARG, and APEH), with MTOR and PPARG categorized as clinically actionable. Two-sample Mendelian randomization analysis supported bidirectional causality between diabetes and frailty index and unidirectional causal effects of muscle phenotypes on glycemic profiles.

CONCLUSIONS

Our findings highlight the common genetic underpinnings between type 2 diabetes and muscle loss and frailty and inform drug targets with pleiotropic effects on both of these aging-related challenges.

Decoding Health: Exploring Essential Biomarkers Linked to Metabolic Dysfunction-Associated Steatohepatitis and Type 2 Diabetes Mellitus

The investigation of biomarkers for metabolic diseases such as type 2 diabetes mellitus (T2DM) and metabolic dysfunction-associated steatohepatitis (MASH) reveals their potential for advancing disease treatment and addressing their notable overlap. The connection between MASH, obesity, and T2DM highlights the need for an integrative management approach addressing mechanisms like insulin resistance and chronic inflammation. Obesity contributes significantly to the development of MASH through lipid dysregulation, insulin resistance, and chronic inflammation. Selective biomarker targeting offers a valuable strategy for detecting these comorbidities. Biomarkers such as CRP, IL-6, and TNF-α serve as indicators of inflammation, while HOMA-IR, fasting insulin, and HbA1c are essential for evaluating insulin resistance. Additionally, triglycerides, LDL, and HDL are crucial for comprehending lipid dysregulation. Despite the growing importance of digital biomarkers, challenges in research methodologies and sample variability persist, necessitating further studies to validate diagnostic tools and improve health interventions. Future opportunities include developing non-invasive biomarker panels, using multiomics, and using machine learning to enhance prognoses for diagnostic accuracy and therapeutic outcomes.

Causality between diabetes and membranous nephropathy: Mendelian randomization

BACKGROUND

Membranous nephropathy (MN) has not yet been fully elucidated regarding its relationship with Type I and II Diabetes. This study aims to evaluate the causal effect of multiple types of diabetes and MN by summarizing the evidence from the Mendelian randomization (MR) study.

METHODS

The statistical data for MN was obtained from a GWAS study encompassing 7979 individuals. Regarding diabetes, fasting glucose, fasting insulin, and HbA1C data, we accessed the UK-Biobank, within family GWAS consortium, MAGIC, FinnGen database, MRC-IEU, and Neale Lab, which provided sample sizes ranging from 17,724 to 298,957. As a primary method in this MR analysis, we employed the Inverse Variance Weighted (IVW), Weighted Median, Weighted mode, MR-Egger, Mendelian randomization pleiotropy residual sum, and outlier (MR-PRESSO) and Leave-one-out sensitivity test. Reverse MR analysis was utilized to investigate whether MN affects Diabetes. Meta-analysis was applied to combine study-specific estimates.

RESULTS

It has been determined that type 2 diabetes, gestational diabetes, type 1 diabetes with or without complications, maternal diabetes, and insulin use pose a risk to MN. Based on the genetic prediction, fasting insulin, fasting blood glucose, and HbA1c levels were not associated with the risk of MN. No heterogeneity, horizontal pleiotropy, or reverse causal relationships were found. The meta-analysis results further validated the accuracy.

CONCLUSIONS

The MR analysis revealed the association between MN and various subtypes of diabetes. This study has provided a deeper understanding of the pathogenic mechanisms connecting MN and diabetes.

Glo1 reduction in mice results in age- and sex-dependent metabolic dysfunction

Objectives

Advanced glycation end products (AGEs) have been implicated as an important mediator of metabolic disorders including obesity, insulin resistance, and coronary artery disease. Glyoxalase 1 (Glo1) is a critical enzyme in the clearance of toxic dicarbonyl such as methylglyoxal, precursors of AGEs. The role of AGE-independent mechanisms that underly Glo1-induced metabolic disorders have yet to be elucidated.

Methods

We performed a longitudinal study of female and male Glo1 heterozygous knockdown (Glo1 +/- ) mice with ~50% gene expression and screened metabolic phenotypes such as body weight, adiposity, glycemic control and plasma lipids. We also evaluated atherosclerotic burden, AGE levels, and gene expression profiles across cardiometabolic tissues (liver, adipose, muscle, kidney and aorta) to identify pathway perturbations and potential regulatory genes of Glo1 actions.

Results

Partial loss of Glo1 resulted in obesity, hyperglycemia, dyslipidemia, and alterations in lipid metabolism in metabolic tissues in an age- and sex-dependent manner. Glo1 +/- females displayed altered glycemic control and increased plasma triglycerides, which aligned with significant perturbations in genes involved in adipogenesis, PPARg, insulin signaling, and fatty acid metabolism pathways in liver and adipose tissues. Conversely, Glo1 +/- males developed increased skeletal muscle mass and visceral adipose depots along with changes in lipid metabolism pathways. For both cohorts, most phenotypes manifested after 14 weeks of age. Evaluation of methylglyoxal-derived AGEs demonstrated changes in only male skeletal muscle but not in female tissues, which cannot explain the broad metabolic changes observed in Glo1 +/- mice. Transcriptional profiles suggest that altered glucose and lipid metabolism may be partially explained by alternative detoxification of methylglyoxal to metabolites such as pyruvate. Moreover, transcription factor (TF) analysis of the tissue-specific gene expression data identified TFs involved in cardiometabolic diseases such as Hnf4a (all tissues) and Arntl (aorta, liver, and kidney) which are female-biased regulators and whose targets are altered in response to Glo1 +/- .

Conclusions

Our results indicate that Glo1 reduction perturbs metabolic health and metabolic pathways in a sex- and age-dependent manner without significant changes in AGEs across metabolic tissues. Rather, tissue-specific gene expression analysis suggests that key transcription factors such as Hfn4a and Arntl as well as metabolite changes from alternative methylglyoxal detoxification such as pyruvate, likely contribute to metabolic dysregulation in Glo1 +/- mice.

Genetically predicted brain cortical structure mediates the causality between insulin resistance and cognitive impairment

Background

Insulin resistance is tightly related to cognition; however, the causal association between them remains a matter of debate. Our investigation aims to establish the causal relationship and direction between insulin resistance and cognition, while also quantifying the mediating role of brain cortical structure in this association.

Methods

The publicly available data sources for insulin resistance (fasting insulin, homeostasis model assessment beta-cell function and homeostasis model assessment insulin resistance, proinsulin), brain cortical structure, and cognitive phenotypes (visual memory, reaction time) were obtained from the MAGIC, ENIGMA, and UK Biobank datasets, respectively. We first conducted a bidirectional two-sample Mendelian randomization (MR) analysis to examine the susceptibility of insulin resistance on cognitive phenotypes. Additionally, we applied a two-step MR to assess the mediating role of cortical surficial area and thickness in the pathway from insulin resistance to cognitive impairment. The primary Inverse-variance weighted, accompanied by robust sensitivity analysis, was implemented to explore and verify our findings. The reverse MR analysis was also performed to evaluate the causal effect of cognition on insulin resistance and brain cortical structure.

Results

This study identified genetically determined elevated level of proinsulin increased reaction time (beta=0.03, 95% confidence interval [95%CI]=0.01 to 0.05, p=0.005), while decreasing the surface area of rostral middle frontal (beta=-49.28, 95%CI=-86.30 to -12.27, p=0.009). The surface area of the rostral middle frontal mediated 20.97% (95%CI=1.44% to 40.49%) of the total effect of proinsulin on reaction time. No evidence of heterogeneity, pleiotropy, or reverse causality was observed.

Conclusions

Briefly, our study noticed that elevated level of insulin resistance adversely affected cognition, with a partial mediation effect through alterations in brain cortical structure.

Genetics of glucose homeostasis in pregnancy and postpartum

AIMS/HYPOTHESIS

Pregnancy is accompanied by maternal metabolic adaptations to ensure fetal growth and development, including insulin resistance, which occurs primarily during the second and third trimesters of pregnancy, and a decrease in fasting blood sugar levels over the course of pregnancy. Glucose-related traits are regulated by genetic and environmental factors and modulated by physiological variations throughout the life course. We addressed the hypothesis that there are both overlaps and differences between genetic variants associated with glycaemia-related traits during and outside of pregnancy.

METHODS

Genome-wide SNP data were used to identify genetic variations associated with glycaemia-related traits measured during an OGTT performed at ~28 weeks' gestation in 8067 participants in the Hyperglycaemia and Adverse Pregnancy Outcome (HAPO) Study. Associations outside of pregnancy were determined in 3977 individuals who also participated in the HAPO Follow-Up Study at 11-14 years postpartum. A Bayesian classification algorithm was used to determine whether SNPs associated with fasting and 2 h glucose and fasting C-peptide during pregnancy had a pregnancy-predominant effect vs a similar effect during pregnancy and postpartum.

RESULTS

SNPs in six loci (GCKR, G6PC2, GCK, PPP1R3B, PCSK1 and MTNR1B) were significantly associated with fasting glucose during pregnancy, while SNPs in CDKAL1 and MTNR1B were associated with 1 h glucose and SNPs in MTNR1B and HKDC1 were associated with 2 h glucose. Variants in CDKAL1 and MTNR1B were associated with insulin secretion during pregnancy. Variants in multiple loci were associated with fasting C-peptide during pregnancy, including GCKR, IQSEC1, PPP1R3B, IGF1 and BACE2. GCKR and BACE2 were associated with 1 h C-peptide and GCKR, IQSEC1 and BACE2 with insulin sensitivity during pregnancy. The associations of MTNR1B with 2 h glucose, BACE2 with fasting and 1 h C-peptide and insulin sensitivity, and IQSEC1 with fasting C-peptide and insulin sensitivity that we identified during pregnancy have not been previously reported in non-pregnancy cohorts. The Bayesian classification algorithm demonstrated that the magnitude of effect of the lead SNP was greater during pregnancy compared with 11-14 years postpartum in PCSK1 and PPP1R3B with fasting glucose, in three loci, including MTNR1B, with 2 h glucose, and in six loci, including IGF1, with fasting C-peptide.

CONCLUSIONS/INTERPRETATION

Our findings support the hypothesis that there are both overlaps and differences between the genetic architecture of glycaemia-related traits during and outside of pregnancy. Genetic variants at several loci, including PCSK1, PPP1R3B, MTNR1B and IGF1, appear to influence glycaemic regulation in a unique fashion during pregnancy. Future studies in larger cohorts will be needed to replicate the present findings, fully characterise the genetics of maternal glycaemia during pregnancy and determine similarities to and differences from the non-gravid state.

Impact of gut microbiota on metabolic syndrome and its comprising traits: a two-sample mendelian randomization study

BACKGROUND

The prevalence of metabolic syndrome is on the rise globally. Understanding the etiology and discovering potential treatment target have become a priority. Observational data have linked gut microbiota with metabolic syndrome and its comprising traits. However, whether these relations underlie causal effects remains unclear.

METHODS

Using Inver Variance Weighted (IVW) as primary analysis method, we performed two-sample Mendelian Randomization (MR) analyses to explore the causal relationship between gut microbiota and metabolic syndrome with its comprising traits. Methods including MR-Egger regression, MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO), Weighted Mode, and Weighted Median were chosen for additional MR analysis to test the robustness of MR results. Cochran's IVW Q test and leave-one-out IVW analysis tested the heterogeneity among instrumental variables (IVs). Steiger filtering was utilized to exclude all IVs with reverse causality. Genome-wide association study (GWAS) data used in this study were all from the largest respective GWAS studies available.

RESULTS

Out of 1172 tests, a total of 16 associations with evidence of causality were identified after sensitivity analyses, but only 3 remained after multiple testing correction. Class Melainabacteria (β = 0.02, adjusted P = 0.01) with affiliated order Gastranaerophilales (β = 0.02, adjusted P = 1.20*10- 3) and genus Eubacterium hallii (β = 0.03, adjusted P = 0.03) showed a positive effect on abdominal obesity. All effect sizes were small (abs(β) < 0.1). All causal relationships identified were unidirectional.

CONCLUSIONS

Given the study's limitations, we found little evidence supporting a large causal effect, i.e. absolute effect size > 0.1, of gut microbial taxa abundance on metabolic syndrome and its comprising traits. This study also suggests that previously reported associations between gut microbiota and metabolic syndrome with its comprising traits may not necessarily lead to causal relations.

CLINICAL TRIAL NUMBER

Not applicable.

A noncoding variant confers pancreatic differentiation defect and contributes to diabetes susceptibility by recruiting RXRA

Human genetics analysis has identified many noncoding SNPs associated with diabetic traits, but whether and how these variants contribute to diabetes is largely unknown. Here, we focus on a noncoding variant, rs6048205, and report that the risk-G variant impairs the generation of PDX1+/NKX6-1+ pancreatic progenitor cells and further results in the abnormal decrease of functional β cells during pancreatic differentiation. Mechanistically, this risk-G variant greatly enhances RXRA binding and over-activates FOXA2 transcription, specifically in the pancreatic progenitor stage, which in turn represses NKX6-1 expression. Consistently, inducible FOXA2 overexpression could phenocopy the differentiation defect. More importantly, mice carrying risk-G exhibit abnormal pancreatic islet architecture and are more sensitive to streptozotocin or a high-fat diet to develop into diabetes eventually. This study not only identifies a causal noncoding variant in diabetes susceptibility but also dissects the underlying gain-of-function mechanism by recruiting stage-specific factors.

Gene-environment interactions in human health

Gene-environment interactions (G × E), the interplay of genetic variation with environmental factors, have a pivotal impact on human complex traits and diseases. Statistically, G × E can be assessed by determining the deviation from expectation of predictive models based solely on the phenotypic effects of genetics or environmental exposures. Despite the unprecedented, widespread and diverse use of G × E analytical frameworks, heterogeneity in their application and reporting hinders their applicability in public health. In this Review, we discuss study design considerations as well as G × E analytical frameworks to assess polygenic liability dependent on the environment, to identify specific genetic variants exhibiting G × E, and to characterize environmental context for these dynamics. We conclude with recommendations to address the most common challenges and pitfalls in the conceptualization, methodology and reporting of G × E studies, as well as future directions.

Education and metabolic syndrome: a Mendelian randomization study

Aims

The metabolic syndrome (MetS), a collection of conditions that heighten the risk of disease development and impose economic burdens on patients. However, the causal relationship between education and MetS was uncertain. In this study, the Mendelian randomization (MR) method was employed to elucidate the potential causal link between education and the MetS and its components.

Method

Single nucleotide polymorphisms (SNPs) associated with education, MetS, and its components were sourced from a public database, with the inverse variance-weighted (IVW) method utilized for analysis.

Results

Education demonstrated a significant negative correlation with the risk of MetS (OR = 0.55, 95% CI = 0.48-0.63, p = 2.18E-51), waist circumference(OR = 0.80, 95% CI = 0.76-0.83, p = 4.98E-33), hypertension (OR = 0.96, 95% CI = 0.95-0.97; p = 4.54E-10), Fasting blood glucose (OR = 0.94, 95% CI = 0.91-0.97, p = 7.58E-6) and triglycerides (OR = 0.83, 95% CI = 0.79-0.87, p = 7.87E-18) while showing a positive association with high-density lipoprotein cholesterol (OR = 1.22, 95% CI = 1.18-1.25, p = 1.45E-31).

Conclusion

The findings of this study suggest that education can decrease the incidence of MetS.

Association between gastroesophageal reflux disease and metabolic syndrome: a bidirectional two-sample Mendelian randomization analysis

Introduction

The development of gastroesophageal reflux disease (GERD) may be influenced by metabolic syndrome (MetS) and its components, but the causal relationships remain unclear. This study employs Mendelian randomization (MR) to investigate the potential causal effects of MetS and its components on GERD risk.

Methods

Genome-wide association study (GWAS) summary data were utilized to assess the causal effects of MetS and its components on GERD risk using univariable (UVMR) and multivariable MR (MVMR) analyses. The inverse-variance weighted (IVW) method served as the primary analytical approach.

Results

UVMR analysis revealed significant associations between GERD risk and genetically predicted MetS and its components. Notably, MVMR analysis identified hypertension (OR (95% CI): 5.087 (3.109–8.324); p = 9.51E–11) and body mass index (BMI) [OR (95% CI): 2.103 (1.752–2.525); p = 1.60E–15) as key factors associated with GERD development.

Conclusions

This study provides evidence of a genetically determined causal relationship between MetS, including its components, and the risk of developing GERD. These findings suggest potential targets for early intervention to reduce GERD risk.

Genetic Underpinnings of Fasting and Oral Glucose-stimulated Based Insulin Sensitivity Indices

CONTEXT

Insulin sensitivity (IS) is an important factor in type 2 diabetes (T2D) and can be estimated by many different indices.

OBJECTIVE

We aimed to compare the genetic components underlying IS indices obtained from fasting and oral glucose-stimulated plasma glucose and serum insulin levels.

METHODS

We computed 21 IS indices, classified as fasting, OGTT0,120, and OGTT0,30,120 indices, using fasting and oral glucose tolerance test (OGTT) data in 2 cohorts. We used data from a family cohort (n = 313) to estimate the heritability and the genetic and phenotypic correlations of IS indices. The population cohort, Inter99 (n = 5343), was used to test for associations between IS indices and 426 genetic variants known to be associated with T2D.

RESULTS

Heritability estimates of IS indices ranged between 19% and 38%. Fasting and OGTT0,30,120 indices had high genetic (ρG) and phenotypic (ρP) pairwise correlations (ρG and ρP: 0.88 to 1) The OGTT0,120 indices displayed a wide range of pairwise correlations (ρG: 0.17-1.00 and ρP: 0.13-0.97). We identified statistically significant associations between IS indices and established T2D-associated variants. The PPARG rs11709077 variant was associated only with fasting indices and PIK3R rs4976033 only with OGTT0,30,120 indices. The variants in FAM63A/MINDY1, GCK, C2CD4A/B, and FTO loci were associated only with OGTT0,120 indices.

CONCLUSION

Even though the IS indices mostly share a common genetic background, notable differences emerged between OGTT0,120 indices. The fasting and OGTT-based indices have distinct associations with T2D risk variants. This work provides a basis for future large-scale genetic investigations into the differences between IS indices.

Novel insights into the genetic architecture of pregnancy glycemic traits from 14,744 Chinese maternities

Glycemic traits are critical indicators of maternal and fetal health during pregnancy. We performed genetic analysis for five glycemic traits in 14,744 Chinese pregnant women. Our genome-wide association study identified 25 locus-trait associations, including established links between gestational diabetes mellitus (GDM) and the genes CDKAL1 and MTNR1B. Notably, we discovered a novel association between fasting glucose during pregnancy and the ESR1 gene (estrogen receptor), which was validated by an independent study in pregnant women. The ESR1-GDM link was recently reported by the FinnGen project. Our work enhances the findings in East Asian populations and highlights the need for independent studies. Further analyses, including genetic correlation, Mendelian randomization, and transcriptome-wide association studies, provided genetic insights into the relationship between pregnancy glycemic traits and hypertension. Overall, our findings advance the understanding of genetic architecture of pregnancy glycemic traits, especially in East Asian populations.

The association between patterns of exposure to adverse life events and the risk of chronic kidney disease: a prospective cohort study of 140,997 individuals

Exposure to adverse life events is linked to somatic disorders. The study aims to evaluate the association between adverse events at varying life stages and the risk of chronic kidney disease (CKD), a condition affecting about 10% population worldwide. This prospective cohort study included 140,997 participants from the UK Biobank. Using survey items related to childhood maltreatment, adulthood adversity and catastrophic trauma, we performed latent class analysis to summarize five distinct patterns of exposure to adverse life events, namely "low-level exposure", "childhood exposure", "adulthood exposure", "sexual abuse" and "child-to-adulthood exposure". We used Cox proportional hazard regression to evaluate the association of patterns of exposure to adverse life events with CKD, regression-based mediation analysis to decompose the total effect, and gene-environment-wide interaction study (GEWIS) to identify interactions between genetic loci and adverse life events. During a median follow-up of 5.98 years, 2734 cases of incident CKD were identified. Compared with the "low-level exposure" pattern, "child-to-adulthood exposure" was associated with increased risk of CKD (hazard ratio 1.37, 95% CI 1.14 to 1.65). BMI, smoking and hypertension mediated 11.45%, 9.79%, and 4.50% of this total effect, respectively. Other patterns did not show significant results. GEWIS and subsequent analyses indicated that the magnitude of the association between adverse life events and CKD differed according to genetic polymorphisms, and identified potential underlying pathways (e.g., interleukin 1 receptor activity). These findings underscore the importance of incorporating an individual's psychological encounters and genetic profiles into the precision prevention of CKD.

Genome-wide discovery and integrative genomic characterization of insulin resistance loci using serum triglycerides to HDL-cholesterol ratio as a proxy

Insulin resistance causes multiple epidemic metabolic diseases, including type 2 diabetes, cardiovascular disease, and fatty liver, but is not routinely measured in epidemiological studies. To discover novel insulin resistance genes in the general population, we conducted genome-wide association studies in 382,129 individuals for triglyceride to HDL-cholesterol ratio (TG/HDL), a surrogate marker of insulin resistance calculable from commonly measured serum lipid profiles. We identified 251 independent loci, of which 62 were more strongly associated with TG/HDL compared to TG or HDL alone, suggesting them as insulin resistance loci. Candidate causal genes at these loci were prioritized by fine mapping with directions-of-effect and tissue specificity annotated through analysis of protein coding and expression quantitative trait variation. Directions-of-effect were corroborated in an independent cohort of individuals with directly measured insulin resistance. We highlight two phospholipase encoding genes, PLA2G12A and PLA2G6, which liberate arachidonic acid and improve insulin sensitivity, and VGLL3, a transcriptional co-factor that increases insulin resistance partially through enhanced adiposity. Finally, we implicate the anti-apoptotic gene TNFAIP8 as a sex-dimorphic insulin resistance factor, which acts by increasing visceral adiposity, specifically in females. In summary, our study identifies several candidate modulators of insulin resistance that have the potential to serve as biomarkers and pharmacological targets.

The impact of sex hormones on metabolic syndrome: univariable and multivariable Mendelian randomization studies

BACKGROUND

Observational studies have found associations between sex hormones and metabolic syndrome(Mets), but the causal relationships remains unclear. This study utilizes univariable and multivariable Mendelian randomization (MR) to elucidate the associations between sex hormones (including sex hormone-binding globulin(SHBG), estradiol(E2), testosterone(T)) and Mets and its subtypes (including waist circumference(WC), fasting blood glucose(FBG), high blood pressure(HBP), high-density lipoprotein(HDL-C), triglycerides(TG)).

METHODS

We utilized summary data from large-scale genome-wide association studies. Univariable Mendelian randomization (UMVMR) analysis was primarily conducted using the inverse variance weighted method (IVW), with secondary analyses employing the weighted median, MR-Egger regression, simple mode method, and weighted mode method. Subsequently, multivariable Mendelian randomization (MVMR) was employed to assess the causal relationships between SHBG, T, E2, and MetS and its components: WC, FPG, HBP, HDL-C, and TG. Sensitivity analyses were conducted to assess result reliability.

RESULTS

Genetically predicted SHBG was significantly negatively associated with MetS (UMVMR: β=-0.72; 95% CI = 0.41 to 0.57; P = 1.28e-17; MVMR: β=-0.60; 95% CI=-0.83 to -0.38; P < 0.001). Positive causal relationships were observed between SHBG and WC(MVMR: β = 0.10; 95% CI = 0.03 to 0.17; P = 0.01) and HDL-C (MVMR: β = 0.41; 95% CI = 0.21 to 0.60; P < 0.001), while negative causal relationships were found between SHBG and HBP (MVMR: β=-0.02; 95% CI=-0.04 to -0.00; P = 0.02), TG (MVMR: β=-0.48; 95% CI=-0.70 to -0.26; P < 0.001). Genetically predicted E2 exhibited a negative association with TG (MVMR: β=-1.49; 95% CI=-2.48 to -0.50; P = 0.003). Genetically predicted T was negatively associated with TG (MVMR: β=-0.36; 95% CI=-0.71 to -0.00; P = 0.049) and WC (MVMR: β=-0.13; 95% CI=-0.24 to -0.02; P = 0.02), with inconsistent sensitivity analyses. Additionally, No other causal associations were found.

CONCLUSION

Our study indicates that SHBG is a protective factor for MetS, potentially delaying its onset and progression through improvements in HBP and TG. Furthermore, T and E2 may improve TG levels, with T also reducing WC levels. Importantly, our study provides new insights for the prevention and treatment of MetS.

Managing insulin resistance: the forgotten pathophysiological component of type 2 diabetes

Glucagon-like peptide-1 (GLP-1) receptor agonists have gained widespread use in the treatment of individuals with type 2 diabetes because of their potent weight loss promoting effect, ability to augment β-cell function, and cardiovascular protective effects. However, despite causing impressive weight loss, GLP-1 receptor agonists do not normalise insulin sensitivity in people with type 2 diabetes and obesity, and the long-term effects of this class of antidiabetic medication on muscle mass, frailty, and bone density have been poorly studied. Although GLP-1 receptor agonists improve insulin sensitivity secondary to weight loss, the only true direct insulin-sensitising drugs are thiazolidinediones. Because of side-effects associated with type 2 diabetes therapy, these drugs have not gained widespread use. In lieu of the important role of insulin resistance in the cause of type 2 diabetes and in the pathogenesis of atherosclerotic cardiovascular disease in type 2 diabetes, development of potent insulin-sensitising drugs that can be used in combination with GLP-1 receptor agonists remains a large unmet need in the management of individuals with type 2 diabetes.

Causal link between metabolic related factors and osteoarthritis: a Mendelian randomization investigation

Introduction

Metabolic syndrome (MetS) is significantly associated with osteoarthritis (OA), especially in MetS patients with blood glucose abnormalities, such as elevated fasting blood glucose (FG), which may increase OA risk. Dietary modifications, especially the intake of polyunsaturated fatty acids (PUFAs), are regarded as a potential means of preventing MetS and its complications. However, regarding the effects of FG, Omega-3s, and Omega-6s on OA, the research conclusions are conflicting, which is attributed to the complexity of the pathogenesis of OA. Therefore, it is imperative to thoroughly evaluate multiple factors to fully understand their role in OA, which needs further exploration and clarification.

Methods

Two-sample univariable Mendelian randomization (UVMR) and multivariable Mendelian randomization (MVMR) were employed to examine the causal effect of metabolic related factors on hip OA (HOA) or knee OA (KOA). The exposure and outcome datasets were obtained from Open GWAS IEU. All cases were independent European ancestry data. Three MR methods were performed to estimate the causal effect: inverse-variance weighting (IVW), weighted median method (WMM), and MR-Egger regression. Additionally, the intercept analysis in MR-Egger regression is used to estimate pleiotropy, and the IVW method and MR-Egger regression are used to test the heterogeneity.

Results

The UVMR analysis revealed a causal relationship between FG and HOA. By MVMR analysis, the study discovered a significant link between FG (OR = 0.79, 95%CI: 0.64∼0.99, p = 0.036) and KOA after accounting for body mass index (BMI), age, and sex hormone-binding globulin (SHBG). However, no causal effects of FG on HOA were seen. Omega-3s and Omega-6s did not have a causal influence on HOA or KOA. No significant evidence of pleiotropy was identified.

Discussion

The MR investigation showed a protective effect of FG on KOA development but no causal relationship between FG and HOA. No causal effect of Omega-3s and Omega-6s on HOA and KOA was observed. Shared genetic overlaps might also exist between BMI and age, SHBG and PUFAs for OA development. This finding offers a novel insight into the treatment and prevention of KOA from glucose metabolism perspective. The FG cutoff value should be explored in the future, and consideration should be given to demonstrating the study in populations other than Europeans.

Shared genetic architecture between periodontal disease and type 2 diabetes: a large scale genome-wide cross-trait analysis

PURPOSE

To investigate the relationship between abnormal glucose metabolism, type 2 diabetes (T2D), and periodontal disease (PER) independent of Body Mass Index (BMI), we employed a genome-wide cross-trait approach to clarify the association.

METHODS

Our study utilized the most extensive genome-wide association studies conducted for populations of European ancestry, including PER, T2D, fasting glucose, fasting insulin, 2-hour glucose after an oral glucose challenge, HOMA-β, HOMA-IR (unadjusted or adjusted for BMI) and HbA1c.

RESULTS

With this approach, we were able to identify pleiotropic loci, establish expression-trait associations, and quantify global and local genetic correlations. There was a significant positive global genetic correlation between T2D (rg = 0.261, p = 2.65 × 10-13), HbA1c (rg = 0.182, p = 4.14 × 10-6) and PER, as well as for T2D independent of BMI (rg = 0.158, p = 2.34 × 10-6). A significant local genetic correlation was also observed between PER and glycemic traits or T2D. We also identified 62 independent pleiotropic loci that impact both PER and glycemic traits, including T2D. Nine significant pathways were identified between the shared genes between T2D, glycemic traits and PER. Genetically liability of HOMA-βadjBMI was causally associated with the risk of PER.

CONCLUSION

Our research has revealed a genetic link between T2D, glycemic traits, and PER that is influenced by biological pleiotropy. Notably, some of these links are not related to BMI. Our research highlights an underlying link between patients with T2D and PER, regardless of their BMI.

The role of hypertension in the relationship between leisure screen time, physical activity and migraine: a 2-sample Mendelian randomization study

BACKGROUND

The relationship between lifestyle and migraine is complex, as it remains uncertain which specific lifestyle factors play the most prominent role in the development of migraine, or which modifiable metabolic traits serve as mediators in establishing causality.

METHODS

Independent genetic variants strongly associated with 20 lifestyle factors were selected as instrumental variables from corresponding genome-wide association studies (GWASs). Summary-level data for migraine were obtained from the FinnGen consortium (18,477 cases and 287,837 controls) as a discovery set and the GWAS meta-analysis data (26,052 cases and 487,214 controls) as a replication set. Estimates derived from the two datasets were combined using fixed-effects meta-analysis. Two-step univariable MR (UVMR) and multivariable Mendelian randomization (MVMR) analyses were conducted to evaluate 19 potential mediators of association and determine the proportions of these mediators.

RESULTS

The combined effect of inverse variance weighted revealed that a one standard deviation (SD) increase in genetically predicted Leisure screen time (LST) was associated with a 27.7% increase (95% CI: 1.14-1.44) in migraine risk, while Moderate or/and vigorous physical activity (MVPA) was associated with a 26.9% decrease (95% CI: 0.61-0.87) in migraine risk. The results of the mediation analysis indicated that out of the 19 modifiable metabolic risk factors examined, hypertension explains 24.81% of the relationship between LST and the risk of experiencing migraine. Furthermore, hypertension and diastolic blood pressure (DBP) partially weaken the association between MVPA and migraines, mediating 4.86% and 4.66% respectively.

CONCLUSION

Our research findings indicated that both LST and MVPA in lifestyle have independent causal effects on migraine. Additionally, we have identified that hypertension and DBP play a mediating role in the causal pathway between these two factors and migraine.

The circadian syndrome is a better predictor for psoriasis than the metabolic syndrome via an explainable machine learning method - the NHANES survey during 2005-2006 and 2009-2014

Objective

To explore the association between circadian syndrome (CircS) and Metabolic Syndrome (MetS) with psoriasis. Compare the performance of MetS and CircS in predicting psoriasis.

Methods

An observational study used data from the NHANES surveys conducted in 2005-2006 and 2009-2014. We constructed three multiple logistic regression models to investigate the relationship between MetS, CircS, and their components with psoriasis. The performance of MetS and CircS in predicting psoriasis was compared using five machine-learning algorithms, and the best-performing model was explained via SHAP. Then, bidirectional Mendelian randomization analyses with the inverse variance weighted (IVW) as the primary method were employed to determine the causal effects of each component.

Result

A total of 9,531 participants were eligible for the study. Both the MetS (OR = 1.53, 95%CI: 1.07-2.17, P = 0.02) and CircS (OR = 1.40, 95%CI: 1.02-1.91, P = 0.039) positively correlated with psoriasis. Each CircS algorithmic model performs better than MetS, with Categorical Features+Gradient Boosting for CircS (the area under the precision-recall curve = 0.969) having the best prediction effect on psoriasis. Among the components of CircS, elevated blood pressure, depression symptoms, elevated waist circumference (WC), and short sleep contributed more to predicting psoriasis. Under the IVW methods, there were significant causal relationships between WC (OR = 1.52, 95%CI: 1.34-1.73, P = 1.35e-10), hypertension (OR = 1.68, 95%CI: 1.19-2.37, P = 0.003), depression symptoms (OR = 1.39, 95%CI: 1.17-1.65, P = 1.51e-4), and short sleep (OR = 2.03, 95%CI: 1.21-3.39, p = 0.007) with psoriasis risk.

Conclusion

CircS demonstrated superior predictive ability for prevalent psoriasis compared to MetS, with elevated blood pressure, depression symptoms, and elevated WC contributing more to the prediction.

Genome-wide association study and polygenic score assessment of insulin resistance

Insulin resistance (IR) and beta cell dysfunction are the major drivers of type 2 diabetes (T2D). Genome-Wide Association Studies (GWAS) on IR have been predominantly conducted in European populations, while Middle Eastern populations remain largely underrepresented. We conducted a GWAS on the indices of IR (HOMA2-IR) and beta cell function (HOMA2-%B) in 6,217 non-diabetic individuals from the Qatar Biobank (QBB; Discovery cohort; n = 2170, Replication cohort; n = 4047) with and without body mass index (BMI) adjustment. We also developed polygenic scores (PGS) for HOMA2-IR and compared their performance with a previously derived PGS for HOMA-IR (PGS003470). We replicated 11 loci that have been previously associated with HOMA-IR and 24 loci that have been associated with HOMA-%B, at nominal statistical significance. We also identified a novel locus associated with beta cell function near VEGFC gene, tagged by rs61552983 (P = 4.38 × 10-8). Moreover, our best performing PGS (Q-PGS4; Adj R2 = 0.233 ± 0.014; P = 1.55 x 10-3) performed better than PGS003470 (Adj R2 = 0.194 ± 0.014; P = 5.45 x 10-2) in predicting HOMA2-IR in our dataset. This is the first GWAS on HOMA2 and the first GWAS conducted in the Middle East focusing on IR and beta cell function. Herein, we report a novel locus in VEGFC that is implicated in beta cell dysfunction. Inclusion of under-represented populations in GWAS has potentials to provide important insights into the genetic architecture of IR and beta cell function.

A mendelian randomization study revealing that metabolic syndrome is causally related to renal failure

Background

The onset and progression of chronic kidney disease (CKD) has been linked to metabolic syndrome (MetS), with the results of recent observational studies supporting a potential link between renal failure and MetS. The causal nature of this relationship, however, remains uncertain. This study thus leveraged a Mendelian Randomization (MR) approach to probe the causal link of MetS with renal failure.

Methods

A genetic database was initially used to identify SNPs associated with MetS and components thereof, after which causality was evaluated through the inverse variance weighted (IVW), MR-Egger regression, and weighted media techniques. Results were subsequently validated through sensitivity analyses.

Results

IVW (OR = 1.48, 95% CI = 1.21-1.82, P =1.60E-04) and weighted median (OR = 1.58, 95% CI =1.15-2.17, P = 4.64E-03) analyses revealed that MetS was linked to an elevated risk of renal failure. When evaluating the specific components of MetS, waist circumference was found to be causally related to renal failure using the IVW (OR= 1.58, 95% CI = 1.39-1.81, P = 1.74e-11), MR-Egger (OR= 1.54, 95% CI = 1.03-2.29, P = 0.036), and weighted median (OR= 1.82, 95% CI = 1.48-2.24, P = 1.17e-8). The IVW method also revealed a causal association of hypertension with renal failure (OR= 1.95, 95% CI = 1.34-2.86, P = 5.42e-04), while renal failure was not causally related to fasting blood glucose, triglyceride levels, or HDL-C levels.

Conclusion

These data offer further support for the existence of a causal association of MetS with kidney failure. It is thus vital that MetS be effectively managed in patients with CKD in clinical settings, particularly for patients with hypertension or a high waist circumference who are obese. Adequate interventions in these patient populations have the potential to prevent or delay the development of renal failure.

A new test for trait mean and variance detects unreported loci for blood-pressure variation

Variability in quantitative traits has clinical, ecological, and evolutionary significance. Most genetic variants identified for complex quantitative traits have only a detectable effect on the mean of trait. We have developed the mean-variance test (MVtest) to simultaneously model the mean and log-variance of a quantitative trait as functions of genotypes and covariates by using estimating equations. The advantages of MVtest include the facts that it can detect effect modification, that multiple testing can follow conventional thresholds, that it is robust to non-normal outcomes, and that association statistics can be meta-analyzed. In simulations, we show control of type I error of MVtest over several alternatives. We identified 51 and 37 previously unreported associations for effects on blood-pressure variance and mean, respectively, in the UK Biobank. Transcriptome-wide association studies revealed 633 significant unique gene associations with blood-pressure mean variance. MVtest is broadly applicable to studies of complex quantitative traits and provides an important opportunity to detect novel loci.

Association between a polygenic lipodystrophy genetic risk score and diabetes risk in the high prevalence Maltese population

BACKGROUND

Type 2 diabetes (T2DM) is genetically heterogenous, driven by beta cell dysfunction and insulin resistance. Insulin resistance drives the development of cardiometabolic complications and is typically associated with obesity. A group of common variants at eleven loci are associated with insulin resistance and risk of both type 2 diabetes and coronary artery disease. These variants describe a polygenic correlate of lipodystrophy, with a high metabolic disease risk despite a low BMI.

OBJECTIVES

In this cross-sectional study, we sought to investigate the association of a polygenic risk score composed of eleven lipodystrophy variants with anthropometric, glycaemic and metabolic traits in an island population characterised by a high prevalence of both obesity and type 2 diabetes.

METHODS

814 unrelated adults (n = 477 controls and n = 337 T2DM cases) of Maltese-Caucasian ethnicity were genotyped and associations with phenotypes explored.

RESULTS

A higher polygenic lipodystrophy risk score was correlated with lower adiposity indices (lower waist circumference and body mass index measurements) and higher HOMA-IR, atherogenic dyslipidaemia and visceral fat dysfunction as assessed by the visceral adiposity index in the DM group. In crude and covariate-adjusted models, individuals in the top quartile of polygenic risk had a higher T2DM risk relative to individuals in the first quartile of the risk score distribution.

CONCLUSION

This study consolidates the association between polygenic lipodystrophy risk alleles, metabolic syndrome parameters and T2DM risk particularly in normal-weight individuals. Our findings demonstrate that polygenic lipodystrophy risk alleles drive insulin resistance and diabetes risk independent of an increased BMI.

Zebrafish cobll1a regulates lipid homeostasis via the RA signaling pathway

Background

The COBLL1 gene has been implicated in human central obesity, fasting insulin levels, type 2 diabetes, and blood lipid profiles. However, its molecular mechanisms remain largely unexplored.

Methods

In this study, we established cobll1a mutant lines using the CRISPR/Cas9-mediated gene knockout technique. To further dissect the molecular underpinnings of cobll1a during early development, transcriptome sequencing and bioinformatics analysis was employed.

Results

Our study showed that compared to the control, cobll1a -/- zebrafish embryos exhibited impaired development of digestive organs, including the liver, intestine, and pancreas, at 4 days post-fertilization (dpf). Transcriptome sequencing and bioinformatics analysis results showed that in cobll1a knockout group, the expression level of genes in the Retinoic Acid (RA) signaling pathway was affected, and the expression level of lipid metabolism-related genes (fasn, scd, elovl2, elovl6, dgat1a, srebf1 and srebf2) were significantly changed (p < 0.01), leading to increased lipid synthesis and decreased lipid catabolism. The expression level of apolipoprotein genes (apoa1a, apoa1b, apoa2, apoa4a, apoa4b, and apoea) genes were downregulated.

Conclusion

Our study suggest that the loss of cobll1a resulted in disrupted RA metabolism, reduced lipoprotein expression, and abnormal lipid transport, therefore contributing to lipid accumulation and deleterious effects on early liver development.

A Simplified Screening Model to Predict the Risk of Gestational Diabetes Mellitus in Caucasian and Latin American Pregnant Women

The pathophysiology of gestational diabetes mellitus (GDM) comprises clinical and genetic factors. In fact, GDM is associated with several single nucleotide polymorphisms (SNPs). This study aimed to build a prediction model of GDM combining clinical and genetic risk factors. A total of 1588 pregnant women from the San Carlos Cohort participated in the present study, including 1069 (67.3%) Caucasian (CAU) and 519 (32.7%) Latin American (LAT) individuals, and 255 (16.1%) had GDM. The incidence of GDM was similar in both groups (16.1% CAU and 16.0% LAT). Genotyping was performed via IPLEX Mass ARRAY PCR, selecting 110 SNPs based on literature references. SNPs showing the strongest likelihood of developing GDM were rs10830963, rs7651090, and rs1371614 in CAU and rs1387153 and rs9368222 in LAT. Clinical variables, including age, pre-pregnancy body mass index, and fasting plasma glucose (FPG) at 12 gestational weeks, predicted the risk of GDM (AUC 0.648, 95% CI 0.601-0.695 in CAU; AUC 0.688, 95% CI 0.628-9.748 in LAT), and adding SNPs modestly improved prediction (AUC 0.722, 95%CI 0.680-0.764 in CAU; AUC 0.769, 95% CI 0.711-0.826 in LAT). In conclusion, adding genetic variants enhanced the prediction model of GDM risk in CAU and LAT pregnant women.

Association between fatty liver index and controlled attenuation parameters as markers of metabolic dysfunction-associated fatty liver disease and bone mineral density: observational and two-sample Mendelian randomization studies

Previously observational studies did not draw a clear conclusion on the association between fatty liver diseases and bone mineral density (BMD). Our large-scale studies revealed that MAFLD and hepatic steatosis had no causal effect on BMD, while some metabolic factors were correlated with BMD. The findings have important implications for the relationship between fatty liver diseases and BMD, and may help direct the clinical management of MAFLD patients who experience osteoporosis and osteopenia.

PURPOSE

Liver and bone are active endocrine organs with several metabolic functions. However, the link between metabolic dysfunction-associated fatty liver disease (MAFLD) and bone mineral density (BMD) is contradictory.

METHODS

Using the UK Biobank and National Health and Nutrition Examination Survey (NHANES) dataset, we investigated the association between MAFLD, steatosis, and BMD in the observational analysis. We performed genome-wide association analysis to identify single-nucleotide polymorphisms associated with MAFLD. Large-scale two-sample Mendelian randomization (TSMR) analyses examined the potential causal relationship between MAFLD, hepatic steatosis, or major comorbid metabolic factors, and BMD.

RESULTS

After adjusting for demographic factors and body mass index, logistic regression analysis demonstrated a significant association between MAFLD and reduced heel BMD. However, this association disappeared after adjusting for additional metabolic factors. MAFLD was not associated with total body, femur neck, and lumbar BMD in the NHANES dataset. Magnetic resonance imaging-measured steatosis did not show significant associations with reduced total body, femur neck, and lumbar BMD in multivariate analysis. TSMR analyses indicated that MAFLD and hepatic steatosis were not associated with BMD. Among all MAFLD-related comorbid factors, overweight and type 2 diabetes showed a causal relationship with increased BMD, while waist circumference and hyperlipidemia had the opposite effect.

CONCLUSION

No causal effect of MAFLD and hepatic steatosis on BMD was observed in this study, while some metabolic factors were correlated with BMD. This has important implications for understanding the relationship between fatty liver disease and BMD, which may help direct the clinical management of MAFLD patients with osteoporosis.

Pancreatic Crosstalk in the Disease Setting: Understanding the Impact of Exocrine Disease on Endocrine Function

The exocrine and endocrine are functionally distinct compartments of the pancreas that have traditionally been studied as separate entities. However, studies of embryonic development, adult physiology, and disease pathogenesis suggest there may be critical communication between exocrine and endocrine cells. In fact, the incidence of the endocrine disease diabetes secondary to exocrine disease/dysfunction ranges from 25% to 80%, depending on the type and severity of the exocrine pathology. Therefore, it is necessary to investigate how exocrine-endocrine "crosstalk" may impact pancreatic function. In this article, we discuss common exocrine diseases, including cystic fibrosis, acute, hereditary, and chronic pancreatitis, and the impact of these exocrine diseases on endocrine function. Additionally, we review how obesity and fatty pancreas influence exocrine function and the impact on cellular communication between the exocrine and endocrine compartments. Interestingly, in all pathologies, there is evidence that signals from the exocrine disease contribute to endocrine dysfunction and the progression to diabetes. Continued research efforts to identify the mechanisms that underlie the crosstalk between various cell types in the pancreas are critical to understanding normal pancreatic physiology as well as disease states. © 2024 American Physiological Society. Compr Physiol 14:5371-5387, 2024.

Exploring the bidirectional relationship between metabolic syndrome and thyroid autoimmunity: a Mendelian randomization study

Background

Observational studies have reported a possible association between metabolic syndrome (MetS) and thyroid autoimmunity. Nevertheless, the relationship between thyroid autoimmunity and MetS remains unclear. The objective of this research was to assess the causal impact of MetS on thyroid autoimmunity through the utilization of Mendelian randomization (MR) methodology.

Methods

We performed bidirectional MR to elucidate the causal relationship between MetS and their components and thyroid autoimmunity (positivity of TPOAb). Single nucleotide polymorphisms (SNPs) of MetS and its components were obtained from the publicly available genetic variation summary database. The Thyroidomics Consortium conducted a genome-wide association analysis, which provided summary-level data pertaining to thyroid autoimmunity. The study included several statistical methods, including the inverse variance weighting method (IVW), weighted median, simple mode, weight mode, and MR-Egger methods, to assess the causal link. In addition, to ensure the stability of the results, a sensitivity analysis was conducted.

Results

IVW showed that MetS reduced the risk of developing thyroid autoimmunity (OR = 0.717, 95% CI = 0.584 - 0.88, P = 1.48E-03). The investigation into the causative association between components of MetS and thyroid autoimmune revealed a statistically significant link between triglycerides levels and the presence of thyroid autoimmunity (IVW analysis, OR = 0.603, 95%CI = 0.45 -0.807, P = 6.82E-04). The reverse analysis did not reveal any causal relationship between thyroid autoimmunity and MetS, including its five components.

Conclusions

We have presented new genetic evidence demonstrating that MetS and its triglyceride components may serve as potential protective factors against thyroid autoimmunity.

Mendelian randomization study on insulin resistance and risk of hypertension and cardiovascular disease

Observational studies have suggested that insulin resistance (IR) is associated with hypertension and various cardiovascular diseases. However, the presence of a causal relationship between IR and cardiovascular disease remains unclear. Here, we applied Mendelian randomization (MR) approaches to address the causal association between genetically determined IR and the risk of cardiovascular diseases. Our primary genetic instruments comprised 53 SNPs associated with IR phenotype from a GWAS of up to 188,577 participants. Genetic association estimates for hypertension and venous thromboembolism (VTE) were extracted from UK Biobank, estimates for atrial fibrillation (AF) were extracted from the hitherto largest GWAS meta-analysis on AF, estimates for heart failure were extracted from HERMES Consortium, estimates for peripheral artery disease (PAD) and aortic aneurysm were extracted from the FinnGen Study. The main analyses were performed using the random-effects inverse-variance weighted approach, and complemented by sensitivity analyses and multivariable MR analyses. Corresponding to 55% higher fasting insulin adjusted for body mass index, 0.46 mmol/L lower high-density lipoprotein cholesterol and 0.89 mmol/L higher triglyceride, one standard deviation change in genetically predicted IR was associated with increased risk of hypertension (odds ratio (OR) 1.06, 95% CI 1.04-1.08; P = 1.91 × 10-11) and PAD (OR 1.90, 95% CI 1.43-2.54; P = 1.19 × 10-5). Suggestive evidence was obtained for an association between IR and heart failure (OR per SD change in IR: 1.19, 95% CI 1.01-1.41, P = 0.041). There was no MR evidence for an association between genetically predicted IR and atrial fibrillation, VTE, and aortic aneurysm. Results were widely consistent across all sensitivity analyses. In multivariable MR, the association between IR and PAD was attenuated after adjustment for lipids (P = 0.347) or BMI (P = 0.163). Our findings support that genetically determined IR increases the risk of hypertension and PAD.

Mitigating type 1 error inflation and power loss in GxE PRS: Genotype-environment interaction in polygenic risk score models

The use of polygenic risk score (PRS) models has transformed the field of genetics by enabling the prediction of complex traits and diseases based on an individual's genetic profile. However, the impact of genotype-environment interaction (GxE) on the performance and applicability of PRS models remains a crucial aspect to be explored. Currently, existing genotype-environment interaction polygenic risk score (GxE PRS) models are often inappropriately used, which can result in inflated type 1 error rates and compromised results. In this study, we propose novel GxE PRS models that jointly incorporate additive and interaction genetic effects although also including an additional quadratic term for nongenetic covariates, enhancing their robustness against model misspecification. Through extensive simulations, we demonstrate that our proposed models outperform existing models in terms of controlling type 1 error rates and enhancing statistical power. Furthermore, we apply the proposed models to real data, and report significant GxE effects. Specifically, we highlight the impact of our models on both quantitative and binary traits. For quantitative traits, we uncover the GxE modulation of genetic effects on body mass index by alcohol intake frequency. In the case of binary traits, we identify the GxE modulation of genetic effects on hypertension by waist-to-hip ratio. These findings underscore the importance of employing a robust model that effectively controls type 1 error rates, thus preventing the occurrence of spurious GxE signals. To facilitate the implementation of our approach, we have developed an innovative R software package called GxEprs, specifically designed to detect and estimate GxE effects. Overall, our study highlights the importance of accurate GxE modeling and its implications for genetic risk prediction, although providing a practical tool to support further research in this area.

Causal links between sedentary behavior, physical activity, and psychiatric disorders: a Mendelian randomization study

BACKGROUND

Studies suggest a correlation between excessive sedentary behavior, insufficient physical activity, and an elevated likelihood of experiencing psychiatric disorder. Nonetheless, the precise influence of sedentary behavior and physical activity on psychiatric disorder remains uncertain. Hence, the objective of this research was to investigate the possible causal relationship between sedentary behavior, physical activity, and the susceptibility to psychiatric disorder (depression, schizophrenia and bipolar disorder), utilizing a two-sample Mendelian randomization (MR) approach.

METHODS

Potential genetic instruments related to sedentary leisure behaviors were identified from the UK Biobank database, specifically a summary-level genome-wide association study (GWAS) involving 422,218 individuals of European descent. The UK Biobank database also provided the GWAS data for physical activity. Primary analysis was performed using inverse variance weighting (IVW) to assess the causal relationship between sedentary behavior, physical activity, and the risk of psychiatric disorder (depression, schizophrenia and bipolar disorder). Sensitivity analysis was conducted using Cochran's Q test, the MR-Egger intercept test, the MR-pleiotropy RESidual sum and outlier test, leave-one-out analysis, and funnel plot analysis.

RESULTS

According to the IVW analysis, there was a significant association between genetically predicted leisure television watching and an increased risk of depression (odds ratio [OR] = 1.027, 95% confidence interval [CI]: 1.001-1.053; P = 0.04). The IVW analysis also indicated that there was a decreased risk of depression associated with fraction accelerations of > 425 milligravities, as measured by accelerometers (OR = 0.951, 95%CI: 0.914-0.989; P = 0.013). The other MR methods obtained consistent but non-significant results in the same direction. However, there was no evidence of a causal association between genetic liability for moderate-to-vigorous physical activity, accelerometer-assessed physical activity, computer use, or driving and the risk of depression. Furthermore, IVW analysis has also found that driving has a slight effect in reducing the risk of schizophrenia (OR = 0.092, 95%CI: 0.010-0.827; P = 0.033), while leisure television viewing has a significant protective effect against the onset of bipolar disorder (OR = 0.719, 95%CI: 0.567-0.912; P = 0.006).

CONCLUSION

The study provides compelling evidence of a link between depression, bipolar disorder, and excessive TV watching. Furthermore, it suggests that higher accelerometer-assessed fraction accelerations of > 425 milligravities can serve as a genetic protective factor against depression. To mitigate the risk of developing depression, it is advisable to reduce sedentary activities, particularly television watching, and prioritize engaging in vigorous physical exercise.

Separating the effects of life course adiposity on diabetic nephropathy: a comprehensive multivariable Mendelian randomization study

Aims

Previous Mendelian randomization (MR) of obesity and diabetic nephropathy (DN) risk used small sample sizes or focused on a single adiposity metric. We explored the independent causal connection between obesity-related factors and DN risk using the most extensive GWAS summary data available, considering the distribution of adiposity across childhood and adulthood.

Methods

To evaluate the overall effect of each obesity-related exposure on DN (Ncase = 3,676, Ncontrol = 283,456), a two-sample univariate MR (UVMR) analysis was performed. The independent causal influence of each obesity-related feature on DN was estimated using multivariable MR (MVMR) when accounting for confounding variables. It was also used to examine the independent effects of adult and pediatric obesity, adjusting for their interrelationships. We used data from genome-wide association studies, including overall general (body mass index, BMI) and abdominal obesity (waist-to-hip ratio with and without adjustment for BMI, i.e., WHR and WHRadjBMI), along with childhood obesity (childhood BMI).

Results

UVMR revealed a significant association between adult BMI (OR=1.24, 95%CI=1.03-1.49, P=2.06×10-2) and pediatric BMI (OR=1.97, 95%CI=1.59-2.45, P=8.55×10-10) with DN risk. At the same time, adult WHR showed a marginally significant increase in DN (OR =1.27, 95%CI = 1.01-1.60, P=3.80×10-2). However, the outcomes were adverse when the influence of BMI was taken out of the WHR (WHRadjBMI). After adjusting for childhood BMI, the causal effects of adult BMI and adult abdominal obesity (WHR) on DN were significantly attenuated and became nonsignificant in MVMR models. In contrast, childhood BMI had a constant and robust independent effect on DN risk(adjusted for adult BMI: IVW, OR=1.90, 95% CI=1.60-2.25, P=2.03×10-13; LASSO, OR=1.91, 95% CI=1.65-2.21, P=3.80×10-18; adjusted for adult WHR: IVW, OR=1.80, 95% CI=1.40-2.31, P=4.20×10-6; LASSO, OR=1.90, 95% CI=1.56-2.32, P=2.76×10-10).

Interpretation

Our comprehensive analysis illustrated the hazard effect of obesity-related exposures for DN. In addition, we showed that childhood obesity plays a separate function in influencing the risk of DN and that the adverse effects of adult obesity (adult BMI and adult WHR) can be substantially attributed to it. Thus, several obesity-related traits deserve more attention and may become a new target for the prevention and treatment of DN and warrant further clinical investigation, especially in childhood obesity.

Comprehensive genetic study of the insulin resistance marker TG:HDL-C in the UK Biobank

Insulin resistance (IR) is a well-established risk factor for metabolic disease. The ratio of triglycerides to high-density lipoprotein cholesterol (TG:HDL-C) is a surrogate marker of IR. We conducted a genome-wide association study of the TG:HDL-C ratio in 402,398 Europeans within the UK Biobank. We identified 369 independent SNPs, of which 114 had a false discovery rate-adjusted P value < 0.05 in other genome-wide studies of IR making them high-confidence IR-associated loci. Seventy-two of these 114 loci have not been previously associated with IR. These 114 loci cluster into five groups upon phenome-wide analysis and are enriched for candidate genes important in insulin signaling, adipocyte physiology and protein metabolism. We created a polygenic-risk score from the high-confidence IR-associated loci using 51,550 European individuals in the Michigan Genomics Initiative. We identified associations with diabetes, hyperglyceridemia, hypertension, nonalcoholic fatty liver disease and ischemic heart disease. Collectively, this study provides insight into the genes, pathways, tissues and subtypes critical in IR.

Associations of diabetes, circulating protein biomarkers, and risk of pancreatic cancer

BACKGROUND

Type 2 diabetes (T2D) is associated with higher risk of pancreatic cancer (PC), but the underlying mechanisms are not fully understood.

METHODS

We conducted a case-subcohort study involving 610 PC cases and 623 subcohort participants with 92 protein biomarkers measured in baseline plasma samples. Genetically-instrumented T2D was derived using 86 single-nucleotide polymorphisms (SNPs), including insulin resistance (IR) SNPs.

RESULTS

In observational analyses of 623 subcohort participants (mean age, 52 years; 61% women), T2D was positively associated with 13 proteins (SD difference: IL6: 0.52 [0.23-0.81]; IL10: 0.41 [0.12-0.70]), of which 8 were nominally associated with incident PC. The 8 proteins potentially mediated 36.9% (18.7-75.0%) of the association between T2D and PC. In MR, no associations were observed for genetically-determined T2D with proteins, but there were positive associations of genetically-determined IR with IL6 and IL10 (SD difference: 1.23 [0.05-2.41] and 1.28 [0.31-2.24]). In two-sample MR, fasting insulin was associated with both IL6 and PC, but no association was observed between IL6 and PC.

CONCLUSIONS

Proteomics were likely to explain the association between T2D and PC, but were not causal mediators. Elevated fasting insulin driven by insulin resistance might explain the associations of T2D, proteomics, and PC.

mTORC1 controls murine postprandial hepatic glycogen synthesis via Ppp1r3b

In response to a meal, insulin drives hepatic glycogen synthesis to help regulate systemic glucose homeostasis. The mechanistic target of rapamycin complex 1 (mTORC1) is a well-established insulin target and contributes to the postprandial control of liver lipid metabolism, autophagy, and protein synthesis. However, its role in hepatic glucose metabolism is less understood. Here, we used metabolomics, isotope tracing, and mouse genetics to define a role for liver mTORC1 signaling in the control of postprandial glycolytic intermediates and glycogen deposition. We show that mTORC1 is required for glycogen synthase activity and glycogenesis. Mechanistically, hepatic mTORC1 activity promotes the feeding-dependent induction of Ppp1r3b, a gene encoding a phosphatase important for glycogen synthase activity whose polymorphisms are linked to human diabetes. Reexpression of Ppp1r3b in livers lacking mTORC1 signaling enhances glycogen synthase activity and restores postprandial glycogen content. mTORC1-dependent transcriptional control of Ppp1r3b is facilitated by FOXO1, a well characterized transcriptional regulator involved in the hepatic response to nutrient intake. Collectively, we identify a role for mTORC1 signaling in the transcriptional regulation of Ppp1r3b and the subsequent induction of postprandial hepatic glycogen synthesis.

Evaluating polygenic risk scores for predicting cardiometabolic traits and disease risks in the Taiwan Biobank

Type 2 diabetes (T2D) and hypertension are common comorbidities and, along with hyperlipidemia, serve as risk factors for cardiovascular diseases. This study aimed to evaluate the predictive value of polygenic risk scores (PRSs) on cardiometabolic traits related to T2D, hypertension, and hyperlipidemia and the incidence of these three diseases in Taiwan Biobank samples. Using publicly available, large-scale genome-wide association studies summary statistics, we constructed cross-ethnic PRSs for T2D, hypertension, body mass index, and nine quantitative traits typically used to define the three diseases. A composite PRS (cPRS) for each of the nine traits was constructed by aggregating the significant PRSs of its genetically correlated traits. The associations of each of the nine traits at baseline as well as the change of trait values during a 3- to 6-year follow-up period with its cPRS were evaluated. The predictive performances of cPRSs in predicting future incidences of T2D, hypertension, and hyperlipidemia were assessed. The cPRSs had significant associations with baseline and changes of trait values in 3-6 years and explained a higher proportion of variance for all traits than individual PRSs. Furthermore, models incorporating disease-related cPRSs, along with clinical features and relevant trait measurements achieved area under the curve values of 87.8%, 83.7%, and 75.9% for predicting future T2D, hypertension, and hyperlipidemia in 3-6 years, respectively.

FORGEdb: a tool for identifying candidate functional variants and uncovering target genes and mechanisms for complex diseases

The majority of disease-associated variants identified through genome-wide association studies are located outside of protein-coding regions. Prioritizing candidate regulatory variants and gene targets to identify potential biological mechanisms for further functional experiments can be challenging. To address this challenge, we developed FORGEdb ( https://forgedb.cancer.gov/ ; https://forge2.altiusinstitute.org/files/forgedb.html ; and https://doi.org/10.5281/zenodo.10067458 ), a standalone and web-based tool that integrates multiple datasets, delivering information on associated regulatory elements, transcription factor binding sites, and target genes for over 37 million variants. FORGEdb scores provide researchers with a quantitative assessment of the relative importance of each variant for targeted functional experiments.

Multi-tissue transcriptome-wide association study reveals susceptibility genes and drug targets for insulin resistance-relevant phenotypes

AIM

Genome-wide association studies (GWAS) have identified multiple susceptibility loci associated with insulin resistance (IR)-relevant phenotypes. However, the genes responsible for these associations remain largely unknown. We aim to identify susceptibility genes for IR-relevant phenotypes via a transcriptome-wide association study.

MATERIALS AND METHODS

We conducted a large-scale multi-tissue transcriptome-wide association study for IR (Insulin Sensitivity Index, homeostasis model assessment-IR, fasting insulin) and lipid-relevant traits (high-density lipoprotein cholesterol, triglycerides, low-density lipoprotein cholesterol and total cholesterol) using the largest GWAS summary statistics and precomputed gene expression weights of 49 human tissues. Conditional and joint analyses were implemented to identify significantly independent genes. Furthermore, we estimated the causal effects of independent genes by Mendelian randomization causal inference analysis.

RESULTS

We identified 1190 susceptibility genes causally associated with IR-relevant phenotypes, including 58 genes that were not implicated in the original GWAS. Among them, 11 genes were further supported in differential expression analyses or a gene knockout mice database, such as KRIT1 showed both significantly differential expression and IR-related phenotypic effects in knockout mice. Meanwhile, seven proteins encoded by susceptibility genes were targeted by clinically approved drugs, and three of these genes (H6PD, CACNB2 and DRD2) have been served as drug targets for IR-related diseases/traits. Moreover, drug repurposing analysis identified four compounds with profiles opposing the expression of genes associated with IR risk.

CONCLUSIONS

Our study provided new insights into IR aetiology and avenues for therapeutic development.

Genetic effect of metformin use on risk of cancers: evidence from Mendelian randomization analysis

BACKGROUND

Increasing number of studies reported the positive effect of metformin on the prevention and treatment of cancers. However, the genetic causal effect of metformin utilization on the risk of common cancers was not completely demonstrated.

METHODS

Two-sample Mendelian Randomization (two-sample MR) analysis was conducted to uncover the genetically predicted causal association between metformin use and 26 kinds of cancers. Besides, two-step Mendelian Randomization (two-step MR) assessment was applied to clarify the mediators which mediated the causal effect of metformin on certain cancer. We utilized five robust analytical methods, in which the inverse variance weighting (IVW) method served as the major one. Sensitivity, pleiotropy, and heterogeneity were assessed. The genetic statistics of exposure, outcomes, and mediators were downloaded from publicly available datasets, including the Open Genome-Wide Association Study (GWAS), FinnGen consortium (FinnGen), and UK Biobank (UKB).

RESULTS

Among 26 kinds of common cancers, HER-positive breast cancer was presented with a significant causal relationship with metformin use [Beta: - 4.0982; OR: 0.0166 (95% CI: 0.0008, 0.3376); P value: 0.0077], which indicated metformin could prevent people from HER-positive breast cancer. Other cancers only showed modest associations with metformin use. Potential mediators were included in two-step MR, among which total testosterone levels (mediating effect: 24.52%) displayed significant mediating roles. Leave-one-out, MR-Egger, and MR-PRESSO analyses produced consistent outcomes.

CONCLUSION

Metformin use exhibited a genetically protective effect on HER-positive breast cancer, which was partially mediated by total testosterone levels.

Interaction between the GCKR rs1260326 variant and serum HDL cholesterol contributes to HOMA-β and ISIMatusda in the middle-aged T2D individuals

This study aims to investigate the correlations between islet function/ insulin resistance and serum lipid levels, as well as to assess whether the strength of such correlations is affected by the GCKR rs1260326 variant in healthy and T2D individuals. We performed an oral glucose tolerance test (OGTT) on 4889 middle-aged adults, including 3135 healthy and 1754 T2D individuals from the REACTION population study in the Nanjing region. We also measured their serum lipid levels and genotyped for rs1260326. We found that serum high-density lipoprotein (HDL) cholesterol and triglyceride (TG) levels were independently correlated with indexes of islet function (HOMA-β and IGI [insulinogenic index]) and insulin resistance (HOMO-IR and ISIMatsuda) in both healthy and T2D individuals. The correlations were significantly decreased in T2D individuals, with significant heterogeneities compared to healthy controls (I2 > 75%, Phet < 0.05). Although no correlation was observed between serum total cholesterol (TC) level and islet function/ insulin resistance in healthy controls, significant correlations were found in T2D individuals, with significant heterogeneity to healthy controls in the correlation with ISIMatsuda(I2 = 85.3%, Phet = 0.009). Furthermore, we found significant interactions of the GCKR rs1260326 variant for the correlations between serum HDL cholesterol and HOMA-β/ISIMatsuda in T2D subjects (P = 0.015 and 0.038, respectively). These findings illustrate that distinct correlations between serum lipid levels and islet function/ insulin resistance occurred in T2D subjects compared to healthy individuals. Common gene variants, such as rs1260326, might interact substantially when studied in specific populations, especially T2D disease status.

Re-analysis and meta-analysis of summary statistics from gene-environment interaction studies

MOTIVATION

statistics from genome-wide association studies enable many valuable downstream analyses that are more efficient than individual-level data analysis while also reducing privacy concerns. As growing sample sizes enable better-powered analysis of gene-environment interactions, there is a need for gene-environment interaction-specific methods that manipulate and use summary statistics.

RESULTS

We introduce two tools to facilitate such analysis, with a focus on statistical models containing multiple gene-exposure and/or gene-covariate interaction terms. REGEM (RE-analysis of GEM summary statistics) uses summary statistics from a single, multi-exposure genome-wide interaction study to derive analogous sets of summary statistics with arbitrary sets of exposures and interaction covariate adjustments. METAGEM (META-analysis of GEM summary statistics) extends current fixed-effects meta-analysis models to incorporate multiple exposures from multiple studies. We demonstrate the value and efficiency of these tools by exploring alternative methods of accounting for ancestry-related population stratification in genome-wide interaction study in the UK Biobank as well as by conducting a multi-exposure genome-wide interaction study meta-analysis in cohorts from the diabetes-focused ProDiGY consortium. These programs help to maximize the value of summary statistics from diverse and complex gene-environment interaction studies.

AVAILABILITY AND IMPLEMENTATION

REGEM and METAGEM are open-source projects freely available at https://github.com/large-scale-gxe-methods/REGEM and https://github.com/large-scale-gxe-methods/METAGEM.

Candidate genes related to acute cerebral circulatory disorders in Preeclampsia in the Kazakh Population

BACKGROUND

The purpose of this study is to conduct a comparative analysis of the population frequencies of alleles and genotypes of polymorphic variants of coagulation and fibrinolysis genes SERPINE1 rs1799889, ITGA2 rs1126643, THBD rs1042580, FII rs1799963, FV rs6025, FVII rs6046, angiogenesis and endothelial dysfunction PGF rs12411, FLT1 rs4769612, KDR rs2071559, ACE rs4340, GWAS associated with the development of acute cerebral circulatory disorders in preeclampsia, in an ethnically homogeneous population of Kazakhs with previously studied populations of the world.

METHODS

The genomic database was analysed based on the results of genotyping of 1800 conditionally healthy individuals of Kazakh nationality ∼2.5 million SNPs using OmniChip 2.5 M Illumina chips at the DECODE Iceland Genomic Center as part of the joint implementation of the project "Genetic Studies of Preeclampsia in Populations of Central Asia and Europe" (InterPregGen) within the 7th Framework Programme of the European Commission under Grant Agreement No. 282540.

RESULT

The study discovered a significantly higher population frequency of carrying the unfavorable rs1126643 allele of the ITGA2 gene polymorphism when compared with European populations. The population frequencies of carrying minor alleles of the SERPINE1 (rs179988) and KDR (rs2071559) genes in the Kazakh population were significantly lower when compared with the previously studied populations of Europe and Asia. An intermediate frequency of unfavorable minor alleles between European and Asian populations was found in Kazakhs for gene polymorphisms: FV rs6025, PGF rs12411, and ACE rs4340. The genomic analysis determined the choice of polymorphisms for their further replicative genotyping in patients with ACCD in PE in the Kazakh population.

CONCLUSION

The obtained results will serve as a basis for the development of effective methods of early diagnosis and treatment of PE in pregnant women, carriers of unfavorable genotypes.