The Metabolic Syndrome in Men study: a resource for studies of metabolic and cardiovascular diseases

Novel Metabolites Associated with Decreased GFR in Finnish Men: A 12-Year Follow-Up of the METSIM Cohort

Identification of the individuals having impaired kidney function is essential in preventing the complications of this disease. We measured 1009 metabolites at the baseline study in 10,159 Finnish men of the METSIM cohort and associated the metabolites with an estimated glomerular filtration rate (eGFR). A total of 7090 men participated in the 12-year follow-up study. Non-targeted metabolomics profiling was performed at Metabolon, Inc. (Morrisville, NC, USA) on EDTA plasma samples obtained after overnight fasting. We applied liquid chromatography mass spectrometry (LC-MS/MS) to identify the metabolites (the Metabolon DiscoveryHD4 platform). We performed association analyses between the eGFR and metabolites using linear regression adjusted for confounding factors. We found 108 metabolites significantly associated with a decrease in eGFR, and 28 of them were novel, including 12 amino acids, 8 xenobiotics, 5 lipids, 1 nucleotide, 1 peptide, and 1 partially characterized molecule. The most significant associations were with five amino acids, N-acetylmethionine, N-acetylvaline, gamma-carboxyglutamate, 3-methylglutaryl-carnitine, and pro-line. We identified 28 novel metabolites associated with decreased eGFR in the 12-year follow-up study of the METSIM cohort. These findings provide novel insights into the role of metabolites and metabolic pathways involved in the decline of kidney function.

A novel multivariable Mendelian randomization framework to disentangle highly correlated exposures with application to metabolomics

Mendelian randomization (MR) utilizes genome-wide association study (GWAS) summary data to infer causal relationships between exposures and outcomes, offering a valuable tool for identifying disease risk factors. Multivariable MR (MVMR) estimates the direct effects of multiple exposures on an outcome. This study tackles the issue of highly correlated exposures commonly observed in metabolomic data, a situation where existing MVMR methods often face reduced statistical power due to multicollinearity. We propose a robust extension of the MVMR framework that leverages constrained maximum likelihood (cML) and employs a Bayesian approach for identifying independent clusters of exposure signals. Applying our method to the UK Biobank metabolomic data for the largest Alzheimer disease (AD) cohort through a two-sample MR approach, we identified two independent signal clusters for AD: glutamine and lipids, with posterior inclusion probabilities (PIPs) of 95.0% and 81.5%, respectively. Our findings corroborate the hypothesized roles of glutamate and lipids in AD, providing quantitative support for their potential involvement.

Gut microbe-derived metabolites and the risk of cardiovascular disease in the METSIM cohort

Background

An association between gut microbes and cardiovascular disease (CVD) has been established, but the underlying mechanisms remain largely unknown.

Methods

We conducted a secondary analysis of the cross-sectional data obtained from the Metabolic Syndrome in Men (METSIM) population-based cohort of 10,194 Finnish men (age = 57.65 ± 7.12 years). We tested the levels of circulating gut microbe-derived metabolites as predictors of CVD, ischemic cerebrovascular accident (CVA), and myocardial infarction (MI). The Kaplan-Meier method was used to estimate the time from the participants' first outpatient clinic visit to the occurrence of adverse outcomes. The associations between metabolite levels and the outcomes were assessed using Cox proportional hazard models.

Results

During a median follow-up period of 200 months, 979 participants experienced CVD, 397 experienced CVA, and 548 experienced MI. After adjusting for traditional risk factors and correcting for multiple comparisons, higher plasma levels of succinate [quartile 4 vs. quartile 1; adjusted hazard ratio, aHR = 1.30, (confidence interval (CI), 1.10-1.53) p = 0.0003, adjusted p = 0.01] were significantly associated with the risk of CVD. High plasma levels of ursodeoxycholic acid (UDCA) (quartile 3 vs. quartile 1); [aHR = 1.68, (CI, 1.26-2.2); p = 0.0003, adj. p = 0.01] were associated with a higher risk of CVA. Furthermore, as a continuous variable, succinate was associated with a 10% decrease in the risk of CVD [aHR = 0.9; (CI, 0.84-0.97); p = 0.008] and a 15% decrease in the risk of MI [aHR = 0.85, (CI, 0.77-0.93); p = 0.0007].

Conclusion

Gut microbe-derived metabolites, succinate, and ursodeoxycholic acid were associated with CVD, MI, and CVA, respectively. Regulating the gut microbes may represent a potential therapeutic target for modulating CVD and CVA.

Single nucleus RNA-sequencing integrated into risk variant colocalization discovers 17 cell-type-specific abdominal obesity genes for metabolic dysfunction-associated steatotic liver disease

BACKGROUND

Abdominal obesity increases the risk for non-alcoholic fatty liver disease (NAFLD), now known as metabolic dysfunction-associated steatotic liver disease (MASLD).

METHODS

To elucidate the directional cell-type level biological mechanisms underlying the association between abdominal obesity and MASLD, we integrated adipose and liver single nucleus RNA-sequencing and bulk cis-expression quantitative trait locus (eQTL) data with the UK Biobank genome-wide association study (GWAS) data using colocalization. Then we used colocalized cis-eQTL variants as instrumental variables in Mendelian randomization (MR) analyses, followed by functional validation experiments on the target genes of the cis-eQTL variants.

FINDINGS

We identified 17 colocalized abdominal obesity GWAS variants, regulating 17 adipose cell-type marker genes. Incorporating these 17 variants into MR discovers a putative tissue-of-origin, cell-type-aware causal effect of abdominal obesity on MASLD consistently with multiple MR methods without significant evidence for pleiotropy or heterogeneity. Single cell data confirm the adipocyte-enriched mean expression of the 17 genes. Our cellular experiments across human adipogenesis identify risk variant -specific epigenetic and transcriptional mechanisms. Knocking down two of the 17 genes, PPP2R5A and SH3PXD2B, shows a marked decrease in adipocyte lipidation and significantly alters adipocyte function and adipogenesis regulator genes, including DGAT2, LPL, ADIPOQ, PPARG, and SREBF1. Furthermore, the 17 genes capture a characteristic MASLD expression signature in subcutaneous adipose tissue.

INTERPRETATION

Overall, we discover a significant cell-type level effect of abdominal obesity on MASLD and trace its biological effect to adipogenesis.

FUNDING

NIH grants R01HG010505, R01DK132775, and R01HL170604; the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (Grant No. 802825), Academy of Finland (Grants Nos. 333021), the Finnish Foundation for Cardiovascular Research the Sigrid Jusélius Foundation and the Jane and Aatos Erkko Foundation; American Association for the Study of Liver Diseases (AASLD) Advanced Transplant Hepatology award and NIH/NIDDK (P30DK41301) Pilot and Feasibility award; NIH/NIEHS F32 award (F32ES034668); Finnish Diabetes Research Foundation, Kuopio University Hospital Project grant (EVO/VTR grants 2005-2021), the Academy of Finland grant (Contract no. 138006); Academy of Finland (Grant Nos 335443, 314383, 272376 and 266286), Sigrid Jusélius Foundation, Finnish Medical Foundation, Finnish Diabetes Research Foundation, Novo Nordisk Foundation (#NNF20OC0060547, NNF17OC0027232, NNF10OC1013354) and Government Research Funds to Helsinki University Hospital; Orion Research Foundation, Maud Kuistila Foundation, Finish Medical Foundation, and University of Helsinki.

Dietary n-3 alpha-linolenic and n-6 linoleic acids modestly lower serum lipoprotein(a) concentration but differentially influence other atherogenic lipoprotein traits: A randomized trial

BACKGROUND AND AIMS

Lipoprotein(a) [Lp(a)] is a causal, genetically determined cardiovascular risk factor. Limited evidence suggests that dietary unsaturated fat may increase serum Lp(a) concentration by 10-15 %. Linoleic acid may increase Lp(a) concentration through its endogenous conversion to arachidonic acid, a process regulated by the fatty acid desaturase (FADS) gene cluster. We aimed to compare the Lp(a) and other lipoprotein trait-modulating effects of dietary alpha-linolenic (ALA) and linoleic acids (LA). Additionally, we examined whether FADS1 rs174550 genotype modifies Lp(a) responses.

METHODS

A genotype-based randomized trial was performed in 118 men homozygous for FADS1 rs174550 SNP (TT or CC). After a 4-week run-in period, the participants were randomized to 8-week intervention diets enriched with either Camelina sativa oil (ALA diet) or sunflower oil (LA diet) 30-50 mL/day based on their BMI. Serum lipid profile was measured at baseline and at the end of the intervention.

RESULTS

ALA diet lowered serum Lp(a) concentration by 7.3 % (p = 0.003) and LA diet by 9.5 % (p < 0.001) (p = 0.089 for between-diet difference). Both diets led to greater absolute decreases in individuals with higher baseline Lp(a) concentration (p < 0.001). Concentrations of LDL cholesterol (LDL-C), non-HDL-C, remnant-C, and apolipoprotein B were lowered more by the ALA diet (p < 0.01). Lipid or lipoprotein responses were not modified by the FADS1 rs174550 genotype.

CONCLUSIONS

A considerable increase in either dietary ALA or LA from vegetable oils has a similar Lp(a)-lowering effect, whereas ALA may lower other major atherogenic lipids and lipoproteins to a greater extent than LA. Genetic differences in endogenous PUFA conversion may not influence serum Lp(a) concentration.

Central Obesity is Associated with Increased Left Ventricular Maximal Wall Thickness and Intrathoracic Adipose Tissue Measured with Cardiac Magnetic Resonance

INTRODUCTION

Central obesity (CO), characterized by an increased waist circumference increases the risk of cardiovascular disease (CVD) and morbidity, yet the underlying mechanisms are not fully understood. CO is often associated with general obesity, hypertension, and abnormal glucose tolerance, confounding the independent contribution of CO to CVD.

AIM

We investigated the relationship of CO (without associated disorders) with left ventricular (LV) characteristics and intrathoracic adipose tissue (IAT) by cardiac magnetic resonance.

METHODS

LV characteristics, epicardial (EAT), and mediastinal adipose tissue (MAT) were measured from 29 normoglycemic, normotensive males with CO but without general obesity (waist circumference >100 cm, body mass index (BMI) <30 kg/m2) and 18 non-obese male controls.

RESULTS

LV maximal wall thickness (LVMWT) and IAT but not LV mass or volumes were increased in CO subjects compared to controls (LVMWT, 12.3±1.2 vs. 10.7±1.5 mm, p < 0.001; EAT, 5.5±3.0 vs. 2.2±2.0 cm2, p = 0.001; MAT, 31.0±12.8 vs. 15.4±10.7 cm2, p < 0.001). The LVMWT was ≥12 mm in 69% of subjects with CO and 22% of controls (p = 0.002). In CO suspects, EAT correlated inversely with LV end-diastolic volume index (r = - 0.403, p = 0.037) and LV stroke volume (SV) (r = - 0.425, p = 0.027). MAT correlated inversely with SV (r = - 0.427, p=0.026) and positively with LVMWT (r = 0.399, p = 0.035). Among CO subjects, the waist-to-hip ratio (WHR) was an independent predictor of LVMWT (B = 22.4, β = 0.617, p < 0.001). The optimal cut-off with Youden's index for LV hypertrophy was identified at WHR 0.98 (sensitivity 85%, specificity 89%).

CONCLUSIONS

CO independent of BMI is associated with LV hypertrophy and intrathoracic adipose tissue contributing to cardiovascular burden.

Myeloid-derived miR-6236 potentiates adipocyte insulin signaling and prevents hyperglycemia during obesity

Adipose tissue macrophages (ATMs) influence obesity-associated metabolic dysfunction, but the mechanisms by which they do so are not well understood. We show that miR-6236 is a bona fide miRNA that is secreted by ATMs during obesity. Global or myeloid cell-specific deletion of miR-6236 aggravates obesity-associated adipose tissue insulin resistance, hyperglycemia, hyperinsulinemia, and hyperlipidemia. miR-6236 augments adipocyte insulin sensitivity by inhibiting translation of negative regulators of insulin signaling, including PTEN. The human genome harbors a miR-6236 homolog that is highly expressed in the serum and adipose tissue of obese people. hsa-MIR-6236 expression negatively correlates with hyperglycemia and glucose intolerance, and positively correlates with insulin sensitivity. Together, our findings establish miR-6236 as an ATM-secreted miRNA that potentiates adipocyte insulin signaling and protects against metabolic dysfunction during obesity.

The Multi-Omic Approach to Newborn Screening: Opportunities and Challenges

Newborn screening programs have seen significant evolution since their initial implementation more than 60 years ago, with the primary goal of detecting treatable conditions within the earliest possible timeframe to ensure the optimal treatment and outcomes for the newborn. New technologies have driven the expansion of screening programs to cover additional conditions. In the current era, the breadth of screened conditions could be further expanded by integrating omic technologies such as untargeted metabolomics and genomics. Genomic screening could offer opportunities for lifelong care beyond the newborn period. For genomic newborn screening to be effective and ready for routine adoption, it must overcome barriers such as implementation cost, public acceptability, and scalability. Metabolomics approaches, on the other hand, can offer insight into disease phenotypes and could be used to identify known and novel biomarkers of disease. Given recent advances in metabolomic technologies, alongside advances in genomics including whole-genome sequencing, the combination of complementary multi-omic approaches may provide an exciting opportunity to leverage the best of both approaches and overcome their respective limitations. These techniques are described, along with the current outlook on multi-omic-based NBS research.

Ribosomal DNA copy number is associated with body mass in humans and other mammals

Body mass results from a complex interplay between genetics and environment. Previous studies of the genetic contribution to body mass have excluded repetitive regions due to the technical limitations of platforms used for population scale studies. Here we apply genome-wide approaches, identifying an association between adult body mass and the copy number (CN) of 47S-ribosomal DNA (rDNA). rDNA codes for the 18 S, 5.8 S and 28 S ribosomal RNA (rRNA) components of the ribosome. In mammals, there are hundreds of copies of these genes. Inter-individual variation in the rDNA CN has not previously been associated with a mammalian phenotype. Here, we show that rDNA CN variation associates with post-pubertal growth rate in rats and body mass index in adult humans. rDNA CN is not associated with rRNA transcription rates in adult tissues, suggesting the mechanistic link occurs earlier in development. This aligns with the observation that the association emerges by early adulthood.

Healthy dietary pattern is associated with lower glycemia independently of the genetic risk of type 2 diabetes: a cross-sectional study in Finnish men

PURPOSE

Hyperglycemia is affected by lifestyle and genetic factors. We investigated if dietary patterns associate with glycemia in individuals with high or low genetic risk for type 2 diabetes (T2D).

METHODS

Men (n = 1577, 51-81 years) without T2D from the Metabolic Syndrome in Men (METSIM) cohort filled a food-frequency questionnaire and participated in a 2-hour oral glucose tolerance test. Polygenetic risk score (PRS) including 76 genetic variants was used to stratify participants into low or high T2D risk groups. We established two data-driven dietary patterns, termed healthy and unhealthy, and investigated their association with plasma glucose concentrations and hyperglycemia risk.

RESULTS

Healthy dietary pattern was associated with lower fasting and 2-hour plasma glucose, glucose area under the curve, and better insulin sensitivity (Matsuda insulin sensitivity index) and insulin secretion (disposition index) in unadjusted and adjusted models, whereas the unhealthy pattern was not. No interaction was observed between the patterns and PRS on glycemic measures. Healthy dietary pattern was negatively associated with the risk for hyperglycemia in an adjusted model (OR 0.69, 95% CI 0.51-0.95, in the highest tertile), whereas unhealthy pattern was not (OR 1.08, 95% CI 0.79-1.47, in the highest tertile). No interaction was found between diet and PRS on the risk for hyperglycemia (p = 0.69 for healthy diet, p = 0.54 for unhealthy diet).

CONCLUSION

Our findings suggest that healthy diet is associated with lower glucose concentrations and lower risk for hyperglycemia in men with no interaction with the genetic risk.

Elevated serum uric acid to creatinine ratio is associated with adverse pregnancy outcomes: a prospective birth cohort study

Purpose: This study evaluated the association between maternal serum uric acid-to-creatinine ratio (SUA/SCr) in the first trimester and adverse maternal and neonatal outcomes. Methods: A prospective birth cohort study was conducted between 2018 and 2021. Logistic regression models and restricted cubic splines were utilized to estimate the associations between the SUA/SCr ratio and feto-maternal pregnancy outcomes. Women were stratified according to maternal age and pre-pregnancy body mass index. Results: This study included 33,030 pregnant women with live singleton pregnancies. The overall prevalence of gestational diabetes mellitus (GDM), pregnancy-induced hypertension (PIH), cesarean delivery, preterm birth, large-for-gestational age (LGA), small-for-gestational age, and low Apgar scores were 15.18%, 7.96%, 37.62%, 4.93%, 9.39%, 4.79% and 0.28%, respectively. The highest quartile of SUA/SCr was associated with the highest risk of GDM (odds ratio [OR] 2.14, 95% CI 1.93-2.36), PIH (OR 1.79, 95% CI 1.58-2.04), cesarean delivery (OR 1.24, 95% CI 1.16-1.33), and preterm birth (OR 1.30, 95% CI 1.12-1.51). The associations between SUA/SCr with adverse pregnancy outcomes showed linear relationships except for GDM (P < 0.001 for all, P < 0.001 for non-linearity). Subgroup analyses revealed that the associations between the SUA/SCr ratio and the risks of PIH and LGA were significantly stronger in younger pregnant women (P = 0.033 and 0.035, respectively). Conclusion: Maternal SUA/SCr levels were associated positively with the risk of adverse pregnancy outcomes. Timely monitoring of SUA and SCr levels during early pregnancy may help reduce the risk of adverse pregnancy outcomes and provide a basis for interventions.

Based on systematic druggable genome-wide Mendelian randomization identifies therapeutic targets for diabetes

Purpose

Diabetes and its complications cause a heavy burden of disease worldwide. In recent years, Mendelian randomization (MR) has been widely used to discover the pathogenesis and epidemiology of diseases, as well as to discover new therapeutic targets. Therefore, based on systematic "druggable" genomics, we aim to identify new therapeutic targets for diabetes and analyze its pathophysiological mechanisms to promote its new therapeutic strategies.

Material and method

We used double sample MR to integrate the identified druggable genomics to evaluate the causal effect of quantitative trait loci (eQTLs) expressed by druggable genes in blood on type 1 and 2 diabetes (T1DM and T2DM). Repeat the study using different data sources on diabetes and its complications to verify the identified genes. Not only that, we also use Bayesian co-localization analysis to evaluate the posterior probabilities of different causal variations, shared causal variations, and co-localization probabilities to examine the possibility of genetic confounding. Finally, using diabetes markers with available genome-wide association studies data, we evaluated the causal relationship between established diabetes markers to explore possible mechanisms.

Result

Overall, a total of 4,477 unique druggable genes have been gathered. After filtering using methods such as Bonferroni significance (P<1.90e-05), the MR Steiger directionality test, Bayesian co-localization analysis, and validation with different datasets, Finally, 7 potential druggable genes that may affect the results of T1DM and 7 potential druggable genes that may affect the results of T2DM were identified. Reverse MR suggests that C4B may play a bidirectional role in the pathogenesis of T1DM, and none of the other 13 target genes have a reverse causal relationship. And the 7 target genes in T2DM may each affect the biomarkers of T2DM to mediate the pathogenesis of T2DM.

Conclusion

This study provides genetic evidence supporting the potential therapeutic benefits of targeting seven druggable genes, namely MAP3K13, KCNJ11, REG4, KIF11, CCNE2, PEAK1, and NRBP1, for T2DM treatment. Similarly, targeting seven druggable genes, namely ERBB3, C4B, CD69, PTPN22, IL27, ATP2A1, and LT-β, has The potential therapeutic benefits of T1DM treatment. This will provide new ideas for the treatment of diabetes and also help to determine the priority of drug development for diabetes.

Multi-tissue transcriptome-wide association study identifies novel candidate susceptibility genes for cataract

Introduction

Cataract is the leading cause of blindness among the elderly worldwide. Twin and family studies support an important role for genetic factors in cataract susceptibility with heritability estimates up to 58%. To date, 55 loci for cataract have been identified by genome-wide association studies (GWAS), however, much work remains to identify the causal genes. Here, we conducted a transcriptome-wide association study (TWAS) of cataract to prioritize causal genes and identify novel ones, and examine the impact of their expression.

Methods

We performed tissue-specific and multi-tissue TWAS analyses to assess associations between imputed gene expression from 54 tissues (including 49 from the Genotype Tissue Expression (GTEx) Project v8) with cataract using FUSION software. Meta-analyzed GWAS summary statistics from 59,944 cataract cases and 478,571 controls, all of European ancestry and from two cohorts (GERA and UK Biobank) were used. We then examined the expression of the novel genes in the lens tissue using the iSyTE database.

Results

Across tissue-specific and multi-tissue analyses, we identified 99 genes for which genetically predicted gene expression was associated with cataract after correcting for multiple testing. Of these 99 genes, 20 (AC007773.1, ANKH, ASIP, ATP13A2, CAPZB, CEP95, COQ6, CREB1, CROCC, DDX5, EFEMP1, EIF2S2, ESRRB, GOSR2, HERC4, INSRR, NIPSNAP2, PICALM, SENP3, and SH3YL1) did not overlap with previously reported cataract-associated loci. Tissue-specific analysis identified 202 significant gene-tissue associations for cataract, of which 166 (82.2%), representing 9 unique genes, were attributed to the previously reported 11q13.3 locus. Tissue-enrichment analysis revealed that gastrointestinal tissues represented one of the highest proportions of the Bonferroni-significant gene-tissue associations (21.3%). Moreover, this gastrointestinal tissue type was the only anatomical category significantly enriched in our results, after correcting for the number of tissue donors and imputable genes for each reference panel. Finally, most of the novel cataract genes (e.g., Capzb) were robustly expressed in iSyTE lens data.

Discussion

Our results provide evidence of the utility of imputation-based TWAS approaches to characterize known GWAS risk loci and identify novel candidate genes that may increase our understanding of cataract etiology. Our findings also highlight the fact that expression of genes associated with cataract susceptibility is not necessarily restricted to lens tissue.

Relationships and Mendelian Randomization of Gut Microbe-Derived Metabolites with Metabolic Syndrome Traits in the METSIM Cohort

The role of gut microbe-derived metabolites in the development of metabolic syndrome (MetS) remains unclear. This study aimed to evaluate the associations of gut microbe-derived metabolites and MetS traits in the cross-sectional Metabolic Syndrome In Men (METSIM) study. The sample included 10,194 randomly related men (age 57.65 ± 7.12 years) from Eastern Finland. Levels of 35 metabolites were tested for associations with 13 MetS traits using lasso and stepwise regression. Significant associations were observed between multiple MetS traits and 32 metabolites, three of which exhibited particularly robust associations. N-acetyltryptophan was positively associated with Homeostatic Model Assessment for Insulin Resistant (HOMA-IR) (β = 0.02, p = 0.033), body mass index (BMI) (β = 0.025, p = 1.3 × 10-16), low-density lipoprotein cholesterol (LDL-C) (β = 0.034, p = 5.8 × 10-10), triglyceride (0.087, p = 1.3 × 10-16), systolic (β = 0.012, p = 2.5 × 10-6) and diastolic blood pressure (β = 0.011, p = 3.4 × 10-6). In addition, 3-(4-hydroxyphenyl) lactate yielded the strongest positive associations among all metabolites, for example, with HOMA-IR (β = 0.23, p = 4.4 × 10-33), and BMI (β = 0.097, p = 5.1 × 10-52). By comparison, 3-aminoisobutyrate was inversely associated with HOMA-IR (β = -0.19, p = 3.8 × 10-51) and triglycerides (β = -0.12, p = 5.9 × 10-36). Mendelian randomization analyses did not provide evidence that the observed associations with these three metabolites represented causal relationships. We identified significant associations between several gut microbiota-derived metabolites and MetS traits, consistent with the notion that gut microbes influence metabolic homeostasis, beyond traditional risk factors.

Distinct and shared genetic architectures of gestational diabetes mellitus and type 2 diabetes

Gestational diabetes mellitus (GDM) is a common metabolic disorder affecting more than 16 million pregnancies annually worldwide1,2. GDM is related to an increased lifetime risk of type 2 diabetes (T2D)1-3, with over a third of women developing T2D within 15 years of their GDM diagnosis. The diseases are hypothesized to share a genetic predisposition1-7, but few studies have sought to uncover the genetic underpinnings of GDM. Most studies have evaluated the impact of T2D loci only8-10, and the three prior genome-wide association studies of GDM11-13 have identified only five loci, limiting the power to assess to what extent variants or biological pathways are specific to GDM. We conducted the largest genome-wide association study of GDM to date in 12,332 cases and 131,109 parous female controls in the FinnGen study and identified 13 GDM-associated loci, including nine new loci. Genetic features distinct from T2D were identified both at the locus and genomic scale. Our results suggest that the genetics of GDM risk falls into the following two distinct categories: one part conventional T2D polygenic risk and one part predominantly influencing mechanisms disrupted in pregnancy. Loci with GDM-predominant effects map to genes related to islet cells, central glucose homeostasis, steroidogenesis and placental expression.

Genetic influences on circulating retinol and its relationship to human health

Retinol is a fat-soluble vitamin that plays an essential role in many biological processes throughout the human lifespan. Here, we perform the largest genome-wide association study (GWAS) of retinol to date in up to 22,274 participants. We identify eight common variant loci associated with retinol, as well as a rare-variant signal. An integrative gene prioritisation pipeline supports novel retinol-associated genes outside of the main retinol transport complex (RBP4:TTR) related to lipid biology, energy homoeostasis, and endocrine signalling. Genetic proxies of circulating retinol were then used to estimate causal relationships with almost 20,000 clinical phenotypes via a phenome-wide Mendelian randomisation study (MR-pheWAS). The MR-pheWAS suggests that retinol may exert causal effects on inflammation, adiposity, ocular measures, the microbiome, and MRI-derived brain phenotypes, amongst several others. Conversely, circulating retinol may be causally influenced by factors including lipids and serum creatinine. Finally, we demonstrate how a retinol polygenic score could identify individuals more likely to fall outside of the normative range of circulating retinol for a given age. In summary, this study provides a comprehensive evaluation of the genetics of circulating retinol, as well as revealing traits which should be prioritised for further investigation with respect to retinol related therapies or nutritional intervention.

Comparison of the gut microbiome composition between men with erectile dysfunction and a matched cohort: a pilot study

BACKGROUND

To-date there have been minimal studies to investigate an association between the gut microbiome and erectile dysfunction. There have been many inflammatory diseases linked to gut microbiome dysbiosis; such as cardiovascular disease and metabolic syndrome. These same inflammatory diseases have been heavily linked to erectile dysfunction. Given the correlations between both conditions and cardiovascular disease and the metabolic syndrome, we believe that it is worthwhile to investigate a link between the two.

OBJECTIVE

To investigate the potential association between the gut microbiome and erectile dysfunction.

METHODS

Stool samples were collected from 28 participants with erectile dysfunction and 32 age-matched controls. Metatranscriptome sequencing was used to analyze the samples.

RESULTS

No significant differences were found in the gut microbiome characteristics, including Kyoto Encyclopedia of Genes and Genomes richness (p = 0.117), Kyoto Encyclopedia of Genes and Genomes diversity (p = 0.323), species richness (p = 0.364), and species diversity (p = 0.300), between the erectile dysfunction and control groups.

DISCUSSION

The association of gut microbiome dysbiosis and pro-inflammatory conditions has been well studied and further literature continues to add to this evidence. Our main limitation for this study was our small-sample size due to recruitment issues. We believe that a study with a larger population size may find an association between the gut microbiome and erectile dysfunction.

CONCLUSIONS

The results of this study do not support a significant association between the gut microbiome and erectile dysfunction. Further research is needed to fully understand the relationship between these two conditions.

Age-dependent genes in adipose stem and precursor cells affect regulation of fat cell differentiation and link aging to obesity via cellular and genetic interactions

BACKGROUND

Age and obesity are dominant risk factors for several common cardiometabolic disorders, and both are known to impair adipose tissue function. However, the underlying cellular and genetic factors linking aging and obesity on adipose tissue function have remained elusive. Adipose stem and precursor cells (ASPCs) are an understudied, yet crucial adipose cell type due to their deterministic adipocyte differentiation potential, which impacts the capacity to store fat in a metabolically healthy manner.

METHODS

We integrated subcutaneous adipose tissue (SAT) bulk (n=435) and large single-nucleus RNA sequencing (n=105) data with the UK Biobank (UKB) (n=391,701) data to study age-obesity interactions originating from ASPCs by performing cell-type decomposition, differential expression testing, cell-cell communication analyses, and construction of polygenic risk scores for body mass index (BMI).

RESULTS

We found that the SAT ASPC proportions significantly decrease with age in an obesity-dependent way consistently in two independent cohorts, both showing that the age dependency of ASPC proportions is abolished by obesity. We further identified 76 genes (72 SAT ASPC marker genes and 4 transcription factors regulating ASPC marker genes) that are differentially expressed by age in SAT and functionally enriched for developmental processes and adipocyte differentiation (i.e., adipogenesis). The 76 age-perturbed ASPC genes include multiple negative regulators of adipogenesis, such as RORA, SMAD3, TWIST2, and ZNF521, form tight clusters of longitudinally co-expressed genes during human adipogenesis, and show age-based differences in cellular interactions between ASPCs and adipose cell types. Finally, our genetic data demonstrate that cis-regional variants of these genes interact with age as predictors of BMI in an obesity-dependent way in the large UKB, while no such gene-age interaction on BMI is observed with non-age-dependent ASPC marker genes, thus independently confirming our cellular ASPC results at the biobank level.

CONCLUSIONS

Overall, we discover that obesity prematurely induces a decrease in ASPC proportions and identify 76 developmentally important ASPC genes that implicate altered negative regulation of fat cell differentiation as a mechanism for aging and directly link aging to obesity via significant cellular and genetic interactions.

PNPLA3 Genotype and Dietary Fat Modify Concentrations of Plasma and Fecal Short Chain Fatty Acids and Plasma Branched-Chain Amino Acids

The GG genotype of the Patatin-like phosphatase domain-containing 3 (PNPLA3), dietary fat, short-chain fatty acids (SCFA) and branched-chain amino acids (BCAA) are linked with non-alcoholic fatty liver disease. We studied the impact of the quality of dietary fat on plasma (p) and fecal (f) SCFA and p-BCAA in men homozygous for the PNPLA3 rs738409 variant (I148M). Eighty-eight randomly assigned men (age 67.8 ± 4.3 years, body mass index 27.1 ± 2.5 kg/m2) participated in a 12-week diet intervention. The recommended diet (RD) group followed the National and Nordic nutrition recommendations for fat intake. The average diet (AD) group followed the average fat intake in Finland. The intervention resulted in a decrease in total p-SCFAs and iso-butyric acid in the RD group (p = 0.041 and p = 0.002). Valeric acid (p-VA) increased in participants with the GG genotype regardless of the diet (RD, 3.6 ± 0.6 to 7.0 ± 0.6 µmol/g, p = 0.005 and AD, 3.8 ± 0.3 to 9.7 ± 8.5 µmol/g, p = 0.015). Also, genotype relation to p-VA was seen statistically significantly in the RD group (CC: 3.7 ± 0.4 to 4.2 ± 1.7 µmol/g and GG: 3.6 ± 0.6 to 7.0 ± 0.6 µmol/g, p = 0.0026 for time and p = 0.004 for time and genotype). P-VA, unlike any other SCFA, correlated positively with plasma gamma-glutamyl transferase (r = 0.240, p = 0.025). Total p-BCAAs concentration changed in the AD group comparing PNPLA3 CC and GG genotypes (CC: 612 ± 184 to 532 ± 149 µmol/g and GG: 587 ± 182 to 590 ± 130 µmol/g, p = 0.015 for time). Valine decreased in the RD group (p = 0.009), and leucine decreased in the AD group (p = 0.043). RD decreased total fecal SCFA, acetic acid (f-AA), and butyric acid (f-BA) in those with CC genotype (p = 0.006, 0.013 and 0.005, respectively). Our results suggest that the PNPLA3 genotype modifies the effect of dietary fat modification for p-VA, total f-SCFA, f-AA and f-BA, and total p-BCAA.

A cross-ancestry genome-wide meta-analysis, fine-mapping, and gene prioritization approach to characterize the genetic architecture of adiponectin

Previous genome-wide association studies (GWASs) for adiponectin, a complex trait linked to type 2 diabetes and obesity, identified >20 associated loci. However, most loci were identified in populations of European ancestry, and many of the target genes underlying the associations remain unknown. We conducted a cross-ancestry adiponectin GWAS meta-analysis in ≤46,434 individuals from the Metabolic Syndrome in Men (METSIM) cohort and the ADIPOGen and AGEN consortiums. We combined study-specific association summary statistics using a fixed-effects, inverse variance-weighted approach. We identified 22 loci associated with adiponectin (p < 5×10-8), including 15 known and seven previously unreported loci. Among individuals of European ancestry, Genome-wide Complex Traits Analysis joint conditional analysis (GCTA-COJO) identified 14 additional distinct signals at the ADIPOQ, CDH13, HCAR1, and ZNF664 loci. Leveraging the cross-ancestry data, FINEMAP + SuSiE identified 45 causal variants (PP > 0.9), which also exhibited potential pleiotropy for cardiometabolic traits. To prioritize target genes at associated loci, we propose a combinatorial likelihood scoring formalism (Gene Priority Score [GPScore]) based on measures derived from 11 gene prioritization strategies and the physical distance to the transcription start site. With GPScore, we prioritize the 30 most probable target genes underlying the adiponectin-associated variants in the cross-ancestry analysis, including well-known causal genes (e.g., ADIPOQ, CDH13) and additional genes (e.g., CSF1, RGS17). Functional association networks revealed complex interactions of prioritized genes, their functionally connected genes, and their underlying pathways centered around insulin and adiponectin signaling, indicating an essential role in regulating energy balance in the body, inflammation, coagulation, fibrinolysis, insulin resistance, and diabetes. Overall, our analyses identify and characterize adiponectin association signals and inform experimental interrogation of target genes for adiponectin.

Transcriptional determinants of lipid mobilization in human adipocytes

Defects in adipocyte lipolysis drive multiple aspects of cardiometabolic disease, but the transcriptional framework controlling this process has not been established. To address this, we performed a targeted perturbation screen in primary human adipocytes. Our analyses identified 37 transcriptional regulators of lipid mobilization, which we classified as (i) transcription factors, (ii) histone chaperones, and (iii) mRNA processing proteins. On the basis of its strong relationship with multiple readouts of lipolysis in patient samples, we performed mechanistic studies on one hit, ZNF189, which encodes the zinc finger protein 189. Using mass spectrometry and chromatin profiling techniques, we show that ZNF189 interacts with the tripartite motif family member TRIM28 and represses the transcription of an adipocyte-specific isoform of phosphodiesterase 1B (PDE1B2). The regulation of lipid mobilization by ZNF189 requires PDE1B2, and the overexpression of PDE1B2 is sufficient to attenuate hormone-stimulated lipolysis. Thus, our work identifies the ZNF189-PDE1B2 axis as a determinant of human adipocyte lipolysis and highlights a link between chromatin architecture and lipid mobilization.

CD163 as a Potential Biomarker-associated Immune Inflammation in Diabetes Mellitus: A Systematic Review and Bioinformatics Analysis

BACKGROUND

Several studies have identified CD163 as a potential mediator of diabetes mellitus through an immune-inflammation. Further study is necessary to identify its specific mechanism.

OBJECTIVES

In this study, we aimed to investigate CD163 as a potential biomarker associated with immune inflammation in diabetes mellitus through a systematic review and bioinformatics analysis.

METHODS

We searched PubMed, Web of Science, the Cochrane Library, and Embase databases with a time limit of September 2, 2022. Furthermore, we conducted a systematic search and review based on PRISMA guidelines. Additionally, diabetic gene expression microarray datasets GSE29221, GSE30528, GSE30529, and GSE20966 were downloaded from the GEO database (http://www.ncbi.nlm.nih.gov/geo) for bioinformatics analysis. The PROSPERO number for this study is CRD420222347160.

RESULTS

Following the inclusion and exclusion criteria, seven articles included 1607 patients, comprising 912 diabetic patients and 695 non-diabetic patients. This systematic review found significantly higher levels of CD163 in diabetic patients compared to non-diabetic patients. People with diabetes had higher levels of CRP expression compared to the control group. Similarly, two of the three papers that used TNF- α as an outcome indicator showed higher expression levels in diabetic patients. Furthermore, IL-6 expression levels were higher in diabetic patients than in the control group. A total of 62 samples were analyzed by bioinformatics (33 case controls and 29 experimental groups), and 85 differential genes were identified containing CD163. According to the immune cell correlation analysis, CD163 was associated with macrophage M2, γδ T lymphocytes, macrophage M1, and other immune cells. Furthermore, to evaluate the diagnostic performance of CD163, we validated it using the GSE20966 dataset. In the validation set, CD163 showed high diagnostic accuracy.

CONCLUSION

This study suggests CD163 participates in the inflammatory immune response associated with diabetes mellitus and its complications by involving several immune cells. Furthermore, the results suggest CD163 may be a potential biomarker reflecting immune inflammation in diabetic mellitus.

Omega-3 Blood Levels and Stroke Risk: A Pooled and Harmonized Analysis of 183 291 Participants From 29 Prospective Studies

BACKGROUND

The effect of marine omega-3 PUFAs on risk of stroke remains unclear.

METHODS

We investigated the associations between circulating and tissue omega-3 PUFA levels and incident stroke (total, ischemic, and hemorrhagic) in 29 international prospective cohorts. Each site conducted a de novo individual-level analysis using a prespecified analytical protocol with defined exposures, covariates, analytical methods, and outcomes; the harmonized data from the studies were then centrally pooled. Multivariable-adjusted HRs and 95% CIs across omega-3 PUFA quintiles were computed for each stroke outcome.

RESULTS

Among 183 291 study participants, there were 10 561 total strokes, 8220 ischemic strokes, and 1142 hemorrhagic strokes recorded over a median of 14.3 years follow-up. For eicosapentaenoic acid, comparing quintile 5 (Q5, highest) with quintile 1 (Q1, lowest), total stroke incidence was 17% lower (HR, 0.83 [CI, 0.76-0.91]; P<0.0001), and ischemic stroke was 18% lower (HR, 0.82 [CI, 0.74-0.91]; P<0.0001). For docosahexaenoic acid, comparing Q5 with Q1, there was a 12% lower incidence of total stroke (HR, 0.88 [CI, 0.81-0.96]; P=0.0001) and a 14% lower incidence of ischemic stroke (HR, 0.86 [CI, 0.78-0.95]; P=0.0001). Neither eicosapentaenoic acid nor docosahexaenoic acid was associated with a risk for hemorrhagic stroke. These associations were not modified by either baseline history of AF or prevalent CVD.

CONCLUSIONS

Higher omega-3 PUFA levels are associated with lower risks of total and ischemic stroke but have no association with hemorrhagic stroke.

Metabolites as Risk Factors for Diabetic Retinopathy in Patients With Type 2 Diabetes: A 12-Year Follow-up Study

CONTEXT

Diabetic retinopathy (DR) is a specific microvascular complication in patients with diabetes and the leading cause of blindness. Recent advances in omics, especially metabolomics, offer the possibility identifying novel potential biomarkers for DR.

OBJECTIVE

The aim was to identify metabolites associated with DR.

METHODS

We performed a 12-year follow-up study including 1349 participants with type 2 diabetes (1021 without DR, 328 with DR) selected from the METSIM cohort. Individuals who had retinopathy before the baseline study were excluded (n = 63). The diagnosis of retinopathy was based on fundus photography examination. We performed nontargeted metabolomics profiling to identify metabolites.

RESULTS

We found 17 metabolites significantly associated with incident DR after adjustment for confounding factors. Among amino acids, N-lactoyl isoleucine, N-lactoyl valine, N-lactoyl tyrosine, N-lactoyl phenylalanine, N-(2-furoyl) glycine, and 5-hydroxylysine were associated with an increased risk of DR, and citrulline with a decreased risk of DR. Among the fatty acids N,N,N-trimethyl-5-aminovalerate was associated with an increased risk of DR, and myristoleate (14:1n5), palmitoleate (16:1n7), and 5-dodecenoate (12:1n7) with a decreased risk of DR. Sphingomyelin (d18:2/24:2), a sphingolipid, was significantly associated with a decreased risk of DR. Carboxylic acid maleate and organic compounds 3-hydroxypyridine sulfate, 4-vinylphenol sulfate, 4-ethylcatechol sulfate, and dimethyl sulfone were significantly associated with an increased risk of DR.

CONCLUSION

Our study is the first large population-based longitudinal study to identify metabolites for DR. We found multiple metabolites associated with an increased and decreased risk for DR from several different metabolic pathways.

Cell-Type Composition Affects Adipose Gene Expression Associations With Cardiometabolic Traits

Understanding differences in adipose gene expression between individuals with different levels of clinical traits may reveal the genes and mechanisms leading to cardiometabolic diseases. However, adipose is a heterogeneous tissue. To account for cell-type heterogeneity, we estimated cell-type proportions in 859 subcutaneous adipose tissue samples with bulk RNA sequencing (RNA-seq) using a reference single-nuclear RNA-seq data set. Cell-type proportions were associated with cardiometabolic traits; for example, higher macrophage and adipocyte proportions were associated with higher and lower BMI, respectively. We evaluated cell-type proportions and BMI as covariates in tests of association between >25,000 gene expression levels and 22 cardiometabolic traits. For >95% of genes, the optimal, or best-fit, models included BMI as a covariate, and for 79% of associations, the optimal models also included cell type. After adjusting for the optimal covariates, we identified 2,664 significant associations (P ≤ 2e-6) for 1,252 genes and 14 traits. Among genes proposed to affect cardiometabolic traits based on colocalized genome-wide association study and adipose expression quantitative trait locus signals, 25 showed a corresponding association between trait and gene expression levels. Overall, these results suggest the importance of modeling cell-type proportion when identifying gene expression associations with cardiometabolic traits.

ARTICLE HIGHLIGHTS

Adipose tissue eQTL meta-analysis reveals the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits

Complete characterization of the genetic effects on gene expression is needed to elucidate tissue biology and the etiology of complex traits. Here, we analyzed 2,344 subcutaneous adipose tissue samples and identified 34K conditionally distinct expression quantitative trait locus (eQTL) signals in 18K genes. Over half of eQTL genes exhibited at least two eQTL signals. Compared to primary signals, non-primary signals had lower effect sizes, lower minor allele frequencies, and less promoter enrichment; they corresponded to genes with higher heritability and higher tolerance for loss of function. Colocalization of eQTL with conditionally distinct genome-wide association study signals for 28 cardiometabolic traits identified 3,605 eQTL signals for 1,861 genes. Inclusion of non-primary eQTL signals increased colocalized signals by 46%. Among 30 genes with ≥2 pairs of colocalized signals, 21 showed a mediating gene dosage effect on the trait. Thus, expanded eQTL identification reveals more mechanisms underlying complex traits and improves understanding of the complexity of gene expression regulation.

Identifying G protein-coupled receptors involved in adipose tissue function using the innovative RNA-seq database FATTLAS

G protein-coupled receptors (GPCRs) modulate the function of adipose tissue (AT) in general and of adipocytes, specifically. Although it is well-established that GPCRs are widely expressed in AT, their repertoire as well as their regulation and function in (patho)physiological conditions (e.g., obesity) is not fully resolved. Here, we established FATTLAS, an interactive public database, for improved access and analysis of RNA-seq data of mouse and human AT. After extracting the GPCRome of non-obese and obese individuals, highly expressed and differentially regulated GPCRs were identified. Exemplarily, we describe four receptors (GPR146, MRGPRF, FZD5, PTGER2) and analyzed their functions in a (pre)adipocyte cell model. Besides all receptors being involved in adipogenesis, MRGPRF is essential for adipocyte viability and regulates cAMP levels, while GPR146 modulates adipocyte lipolysis via constitutive activation of Gi proteins. Taken together, by implementing and using FATTLAS we describe four hitherto unrecognized GPCRs associated with AT function and adipogenesis.

Heterogeneous effects on type 2 diabetes and cardiovascular outcomes of genetic variants and traits associated with fasting insulin

Hyperinsulinemia is a complex and heterogeneous phenotype that characterizes molecular alterations that precede the development of type 2 diabetes (T2D). It results from a complex combination of molecular processes, including insulin secretion and insulin sensitivity, that differ between individuals. To better understand the physiology of hyperinsulinemia and ultimately T2D, we implemented a genetic approach grouping fasting insulin (FI)-associated genetic variants based on their molecular and phenotypic similarities. We identified seven distinctive genetic clusters representing different physiologic mechanisms leading to rising FI levels, ranging from clusters of variants with effects on increased FI, but without increased risk of T2D (non-diabetogenic hyperinsulinemia), to clusters of variants that increase FI and T2D risk with demonstrated strong effects on body fat distribution, liver, lipid, and inflammatory processes (diabetogenic hyperinsulinemia). We generated cluster-specific polygenic scores in 1,104,258 individuals from five multi-ancestry cohorts to show that the clusters differed in associations with cardiometabolic traits. Among clusters characterized by non-diabetogenic hyperinsulinemia, there was both increased and decreased risk of coronary artery disease despite the non-increased risk of T2D. Similarly, the clusters characterized by diabetogenic hyperinsulinemia were associated with an increased risk of T2D, yet had differing risks of cardiovascular conditions, including coronary artery disease, myocardial infarction, and stroke. The strongest cluster-T2D associations were observed with the same direction of effect in non-Hispanic Black, Hispanic, non-Hispanic White, and non-Hispanic East Asian populations. These genetic clusters provide important insights into granular metabolic processes underlying the physiology of hyperinsulinemia, notably highlighting specific processes that decouple increasing FI levels from T2D and cardiovascular risk. Our findings suggest that increasing FI levels are not invariably associated with adverse cardiometabolic outcomes.

Statins and risk of type 2 diabetes: mechanism and clinical implications

Statins are widely used to prevent cardiovascular disease events. Cardiovascular diseases and type 2 diabetes are tightly connected since type 2 diabetes is a major risk factor for cardiovascular diseases. Additionally, cardiovascular diseases often precede the development of type 2 diabetes. These two diseases have common genetic and environmental antecedents. Statins are effective in the lowering of cardiovascular disease events. However, they have also important side effects, including an increased risk of type 2 diabetes. The first study reporting an association of statin treatment with the risk of type 2 diabetes was the WOSCOPS trial (West of Scotland Coronary Prevention Study) in 2001. Other primary and secondary cardiovascular disease prevention studies as well as population-based studies have confirmed original findings. The purpose of our review is to examine and summarize the most important findings of these studies as well as to describe the mechanisms how statins increase the risk of type 2 diabetes.

Plasma cortisol-linked gene networks in hepatic and adipose tissues implicate corticosteroid-binding globulin in modulating tissue glucocorticoid action and cardiovascular risk

Genome-wide association meta-analysis (GWAMA) by the Cortisol Network (CORNET) consortium identified genetic variants spanning the SERPINA6/SERPINA1 locus on chromosome 14 associated with morning plasma cortisol, cardiovascular disease (CVD), and SERPINA6 mRNA expression encoding corticosteroid-binding globulin (CBG) in the liver. These and other findings indicate that higher plasma cortisol levels are causally associated with CVD; however, the mechanisms by which variations in CBG lead to CVD are undetermined. Using genomic and transcriptomic data from The Stockholm Tartu Atherosclerosis Reverse Networks Engineering Task (STARNET) study, we identified plasma cortisol-linked single-nucleotide polymorphisms (SNPs) that are trans-associated with genes from seven different vascular and metabolic tissues, finding the highest representation of trans-genes in the liver, subcutaneous fat, and visceral abdominal fat, [false discovery rate (FDR) = 15%]. We identified a subset of cortisol-associated trans-genes that are putatively regulated by the glucocorticoid receptor (GR), the primary transcription factor activated by cortisol. Using causal inference, we identified GR-regulated trans-genes that are responsible for the regulation of tissue-specific gene networks. Cis-expression Quantitative Trait Loci (eQTLs) were used as genetic instruments for identification of pairwise causal relationships from which gene networks could be reconstructed. Gene networks were identified in the liver, subcutaneous fat, and visceral abdominal fat, including a high confidence gene network specific to subcutaneous adipose (FDR = 10%) under the regulation of the interferon regulatory transcription factor, IRF2. These data identify a plausible pathway through which variation in the liver CBG production perturbs cortisol-regulated gene networks in peripheral tissues and thereby promote CVD.

Genetic evidence that high BMI in childhood has a protective effect on intermediate diabetes traits, including measures of insulin sensitivity and secretion, after accounting for BMI in adulthood

AIMS/HYPOTHESIS

Determining how high BMI at different time points influences the risk of developing type 2 diabetes and affects insulin secretion and insulin sensitivity is critical.

METHODS

By estimating childhood BMI in 441,761 individuals in the UK Biobank, we identified which genetic variants had larger effects on adulthood BMI than on childhood BMI, and vice versa. All genome-wide significant genetic variants were then used to separate the independent genetic effects of high childhood BMI from those of high adulthood BMI on the risk of type 2 diabetes and insulin-related phenotypes using Mendelian randomisation. We performed two-sample MR using external studies of type 2 diabetes, and oral and intravenous measures of insulin secretion and sensitivity.

RESULTS

We found that a childhood BMI that was one standard deviation (1.97 kg/m2) higher than the mean, corrected for the independent genetic liability to adulthood BMI, was associated with a protective effect for seven measures of insulin sensitivity and secretion, including increased insulin sensitivity index (β=0.15; 95% CI 0.067, 0.225; p=2.79×10-4) and reduced fasting glucose levels (β=-0.053; 95% CI -0.089, -0.017; p=4.31×10-3). However, there was little to no evidence of a direct protective effect on type 2 diabetes (OR 0.94; 95% CI 0.85, 1.04; p=0.228) independently of genetic liability to adulthood BMI.

CONCLUSIONS/INTERPRETATION

Our results provide evidence of the protective effect of higher childhood BMI on insulin secretion and sensitivity, which are crucial intermediate diabetes traits. However, we stress that our results should not currently lead to any change in public health or clinical practice, given the uncertainty regarding the biological pathway of these effects and the limitations of this type of study.

Transcriptome-wide association study identifies novel candidate susceptibility genes for migraine

Genome-wide association studies (GWASs) have identified more than 130 genetic susceptibility loci for migraine; however, how most of these loci impact migraine development is unknown. To identify novel genes associated with migraine and interpret the transcriptional products of those genes, we conducted a transcriptome-wide association study (TWAS). We performed tissue-specific and multi-tissue TWAS analyses to assess associations between imputed gene expression from 53 tissues and migraine susceptibility using FUSION software. Meta-analyzed GWAS summary statistics from 26,052 migraine cases and 487,214 controls, all of European ancestry and from two cohorts (the Kaiser Permanente GERA and the UK Biobank), were used. We evaluated the associations for genes after conditioning on variant-level effects from GWAS, and we tested for colocalization of GWAS migraine-associated loci and expression quantitative trait loci (eQTLs). Across tissue-specific and multi-tissue analyses, we identified 53 genes for which genetically predicted gene expression was associated with migraine after correcting for multiple testing. Of these 53 genes, 10 (ATF5, CNTNAP1, KTN1-AS1, NEIL1, NEK4, NNT, PNKP, RUFY2, TUBG2, and VAT1) did not overlap known migraine-associated loci identified from GWAS. Tissue-specific analysis identified 45 gene-tissue pairs and cardiovascular tissues represented the highest proportion of the Bonferroni-significant gene-tissue pairs (n = 22 [49%]), followed by brain tissues (n = 6 [13%]), and gastrointestinal tissues (n = 4 [9%]). Colocalization analyses provided evidence of shared genetic variants underlying eQTL and GWAS signals in 18 of the gene-tissue pairs (40%). Our TWAS reports novel genes for migraine and highlights the important contribution of brain, cardiovascular, and gastrointestinal tissues in migraine susceptibility.

Metabolome-wide Mendelian randomization characterizes heterogeneous and shared causal effects of metabolites on human health

Metabolites are small molecules that are useful for estimating disease risk and elucidating disease biology. Nevertheless, their causal effects on human diseases have not been evaluated comprehensively. We performed two-sample Mendelian randomization to systematically infer the causal effects of 1,099 plasma metabolites measured in 6,136 Finnish men from the METSIM study on risk of 2,099 binary disease endpoints measured in 309,154 Finnish individuals from FinnGen. We identified evidence for 282 causal effects of 70 metabolites on 183 disease endpoints (FDR<1%). We found 25 metabolites with potential causal effects across multiple disease domains, including ascorbic acid 2-sulfate affecting 26 disease endpoints in 12 disease domains. Our study suggests that N-acetyl-2-aminooctanoate and glycocholenate sulfate affect risk of atrial fibrillation through two distinct metabolic pathways and that N-methylpipecolate may mediate the causal effect of N6, N6-dimethyllysine on anxious personality disorder. This study highlights the broad causal impact of plasma metabolites and widespread metabolic connections across diseases.

Predicting mechanisms of action at genetic loci associated with discordant effects on type 2 diabetes and abdominal fat accumulation

Obesity is a major risk factor for cardiovascular disease, stroke, and type 2 diabetes (T2D). Excessive accumulation of fat in the abdomen further increases T2D risk. Abdominal obesity is measured by calculating the ratio of waist-to-hip circumference adjusted for the body-mass index (WHRadjBMI), a trait with a significant genetic inheritance. Genetic loci associated with WHRadjBMI identified in genome-wide association studies are predicted to act through adipose tissues, but many of the exact molecular mechanisms underlying fat distribution and its consequences for T2D risk are poorly understood. Further, mechanisms that uncouple the genetic inheritance of abdominal obesity from T2D risk have not yet been described. Here we utilize multi-omic data to predict mechanisms of action at loci associated with discordant effects on abdominal obesity and T2D risk. We find six genetic signals in five loci associated with protection from T2D but also with increased abdominal obesity. We predict the tissues of action at these discordant loci and the likely effector Genes (eGenes) at three discordant loci, from which we predict significant involvement of adipose biology. We then evaluate the relationship between adipose gene expression of eGenes with adipogenesis, obesity, and diabetic physiological phenotypes. By integrating these analyses with prior literature, we propose models that resolve the discordant associations at two of the five loci. While experimental validation is required to validate predictions, these hypotheses provide potential mechanisms underlying T2D risk stratification within abdominal obesity.

Cross-tissue omics analysis discovers ten adipose genes encoding secreted proteins in obesity-related non-alcoholic fatty liver disease

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is a fast-growing, underdiagnosed, epidemic. We hypothesise that obesity-related inflammation compromises adipose tissue functions, preventing efficient fat storage, and thus driving ectopic fat accumulation into the liver.

METHODS

To identify adipose-based mechanisms and potential serum biomarker candidates (SBCs) for NAFLD, we utilise dual-tissue RNA-sequencing (RNA-seq) data in adipose tissue and liver, paired with histology-based NAFLD diagnosis, from the same individuals in a cohort of obese individuals. We first scan for genes that are differentially expressed (DE) for NAFLD in obese individuals' subcutaneous adipose tissue but not in their liver; encode proteins secreted to serum; and show preferential adipose expression. Then the identified genes are filtered to key adipose-origin NAFLD genes by best subset analysis, knockdown experiments during human preadipocyte differentiation, recombinant protein treatment experiments in human liver HepG2 cells, and genetic analysis.

FINDINGS

We discover a set of genes, including 10 SBCs, that may modulate NAFLD pathogenesis by impacting adipose tissue function. Based on best subset analysis, we further follow-up on two SBCs CCDC80 and SOD3 by knockdown in human preadipocytes and subsequent differentiation experiments, which show that they modulate crucial adipogenesis genes, LPL, SREBPF1, and LEP. We also show that treatment of the liver HepG2 cells with the CCDC80 and SOD3 recombinant proteins impacts genes related to steatosis and lipid processing, including PPARA, NFE2L2, and RNF128. Finally, utilizing the adipose NAFLD DE gene cis-regulatory variants associated with serum triglycerides (TGs) in extensive genome-wide association studies (GWASs), we demonstrate a unidirectional effect of serum TGs on NAFLD with Mendelian Randomization (MR) analysis. We also demonstrate that a single SNP regulating one of the SBC genes, rs2845885, produces a significant MR result by itself. This supports the conclusion that genetically regulated adipose expression of the NAFLD DE genes may contribute to NAFLD through changes in serum TG levels.

INTERPRETATION

Our results from the dual-tissue transcriptomics screening improve the understanding of obesity-related NAFLD by providing a targeted set of 10 adipose tissue-active genes as new serum biomarker candidates for the currently grossly underdiagnosed fatty liver disease.

FUNDING

The work was supported by NIH grants R01HG010505 and R01DK132775. The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. The KOBS study (J. P.) was supported by the Finnish Diabetes Research Foundation, Kuopio University Hospital Project grant (EVO/VTR grants 2005-2019), and the Academy of Finland grant (Contract no. 138006). This study was funded by the European Research Council under the European Union's Horizon 2020 research and innovation program (Grant No. 802825 to M. U. K.). K. H. P. was funded by the Academy of Finland (grant numbers 272376, 266286, 314383, and 335443), the Finnish Medical Foundation, Gyllenberg Foundation, Novo Nordisk Foundation (grant numbers NNF10OC1013354, NNF17OC0027232, and NNF20OC0060547), Finnish Diabetes Research Foundation, Finnish Foundation for Cardiovascular Research, University of Helsinki, and Helsinki University Hospital and Government Research Funds. I. S. was funded by the Instrumentarium Science Foundation. Personal grants to U. T. A. were received from the Matti and Vappu Maukonen Foundation, Ella och Georg Ehrnrooths Stiftelse and the Finnish Foundation for Cardiovascular Research.

Rare and Common Variants in GALNT3 May Affect Bone Mass Independently of Phosphate Metabolism

Anabolic treatment options for osteoporosis remain limited. One approach to discovering novel anabolic drug targets is to identify genetic causes of extreme high bone mass (HBM). We investigated a pedigree with unexplained HBM within the UK HBM study, a national cohort of probands with HBM and their relatives. Whole exome sequencing (WES) in a family with HBM identified a rare heterozygous missense variant (NM_004482.4:c.1657C > T, p.Arg553Trp) in GALNT3, segregating appropriately. Interrogation of data from the UK HBM study and the Anglo-Australasian Osteoporosis Genetics Consortium (AOGC) revealed an unrelated individual with HBM with another rare heterozygous variant (NM_004482.4:c.831 T > A, p.Asp277Glu) within the same gene. In silico protein modeling predicted that p.Arg553Trp would disrupt salt-bridge interactions, causing instability of GALNT3, and that p.Asp277Glu would disrupt manganese binding and consequently GALNT3 catalytic function. Bi-allelic loss-of-function GALNT3 mutations alter FGF23 metabolism, resulting in hyperphosphatemia and causing familial tumoral calcinosis (FTC). However, bone mineral density (BMD) in FTC cases, when reported, has been either normal or low. Common variants in the GALNT3 locus show genome-wide significant associations with lumbar, femoral neck, and total body BMD. However, no significant associations with BMD are observed at loci coding for FGF23, its receptor FGFR1, or coreceptor klotho. Mendelian randomization analysis, using expression quantitative trait loci (eQTL) data from primary human osteoblasts and genome-wide association studies data from UK Biobank, suggested increased expression of GALNT3 reduces total body, lumbar spine, and femoral neck BMD but has no effect on phosphate concentrations. In conclusion, rare heterozygous loss-of-function variants in GALNT3 may cause HBM without altering phosphate concentration. These findings suggest that GALNT3 may affect BMD through pathways other than FGF23 regulation, the identification of which may yield novel anabolic drug targets for osteoporosis. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

The Type 2 Diabetes Knowledge Portal: An open access genetic resource dedicated to type 2 diabetes and related traits

Associations between human genetic variation and clinical phenotypes have become a foundation of biomedical research. Most repositories of these data seek to be disease-agnostic and therefore lack disease-focused views. The Type 2 Diabetes Knowledge Portal (T2DKP) is a public resource of genetic datasets and genomic annotations dedicated to type 2 diabetes (T2D) and related traits. Here, we seek to make the T2DKP more accessible to prospective users and more useful to existing users. First, we evaluate the T2DKP's comprehensiveness by comparing its datasets with those of other repositories. Second, we describe how researchers unfamiliar with human genetic data can begin using and correctly interpreting them via the T2DKP. Third, we describe how existing users can extend their current workflows to use the full suite of tools offered by the T2DKP. We finally discuss the lessons offered by the T2DKP toward the goal of democratizing access to complex disease genetic results.

The potential of integrating human and mouse discovery platforms to advance our understanding of cardiometabolic diseases

Cardiometabolic diseases encompass a range of interrelated conditions that arise from underlying metabolic perturbations precipitated by genetic, environmental, and lifestyle factors. While obesity, dyslipidaemia, smoking, and insulin resistance are major risk factors for cardiometabolic diseases, individuals still present in the absence of such traditional risk factors, making it difficult to determine those at greatest risk of disease. Thus, it is crucial to elucidate the genetic, environmental, and molecular underpinnings to better understand, diagnose, and treat cardiometabolic diseases. Much of this information can be garnered using systems genetics, which takes population-based approaches to investigate how genetic variance contributes to complex traits. Despite the important advances made by human genome-wide association studies (GWAS) in this space, corroboration of these findings has been hampered by limitations including the inability to control environmental influence, limited access to pertinent metabolic tissues, and often, poor classification of diseases or phenotypes. A complementary approach to human GWAS is the utilisation of model systems such as genetically diverse mouse panels to study natural genetic and phenotypic variation in a controlled environment. Here, we review mouse genetic reference panels and the opportunities they provide for the study of cardiometabolic diseases and related traits. We discuss how the post-GWAS era has prompted a shift in focus from discovery of novel genetic variants to understanding gene function. Finally, we highlight key advantages and challenges of integrating complementary genetic and multi-omics data from human and mouse populations to advance biological discovery.

Distinct and shared genetic architectures of Gestational diabetes mellitus and Type 2 Diabetes Mellitus

Gestational diabetes mellitus (GDM) affects more than 16 million pregnancies annually worldwide and is related to an increased lifetime risk of Type 2 diabetes (T2D). The diseases are hypothesized to share a genetic predisposition, but there are few GWAS studies of GDM and none of them is sufficiently powered to assess whether any variants or biological pathways are specific to GDM. We conducted the largest genome-wide association study of GDM to date in 12,332 cases and 131,109 parous female controls in the FinnGen Study and identified 13 GDM-associated loci including 8 novel loci. Genetic features distinct from T2D were identified both at the locus and genomic scale. Our results suggest that the genetics of GDM risk falls into two distinct categories - one part conventional T2D polygenic risk and one part predominantly influencing mechanisms disrupted in pregnancy. Loci with GDM-predominant effects map to genes related to islet cells, central glucose homeostasis, steroidogenesis, and placental expression. These results pave the way for an improved biological understanding of GDM pathophysiology and its role in the development and course of T2D.

Plasma Metabolite Signatures in Male Carriers of Genetic Variants Associated with Non-Alcoholic Fatty Liver Disease

Both genetic and non-genetic factors are important in the pathophysiology of non-alcoholic fatty liver disease (NAFLD). The aim of our study was to identify novel metabolites and pathways associated with NAFLD by including both genetic and non-genetic factors in statistical analyses. We genotyped six genetic variants in the PNPLA3, TM6SF2, MBOAT7, GCKR, PPP1R3B, and HSD17B13 genes reported to be associated with NAFLD. Non-targeted metabolomic profiling was performed from plasma samples. We applied a previously validated fatty liver index to identify participants with NAFLD. First, we associated the six genetic variants with 1098 metabolites in 2 339 men without NAFLD to determine the effects of the genetic variants on metabolites, and then in 2 535 men with NAFLD to determine the joint effects of genetic variants and non-genetic factors on metabolites. We identified several novel metabolites and metabolic pathways, especially for PNPLA3, GCKR, and PPP1R38 variants relevant to the pathophysiology of NAFLD. Importantly, we showed that each genetic variant for NAFLD had a specific metabolite signature. The plasma metabolite signature was unique for each genetic variant, suggesting that several metabolites and different pathways are involved in the risk of NAFLD. The FLI index reliably identifies metabolites for NAFLD in large population-based studies.

Finnish-specific AKT2 gene variant leads to impaired insulin signalling in myotubes

Finnish-specific gene variant p.P50T/AKT2 (minor allele frequency (MAF) = 1.1%) is associated with insulin resistance and increased predisposition to type 2 diabetes. Here, we have investigated in vitro the impact of the gene variant on glucose metabolism and intracellular signalling in human primary skeletal muscle cells, which were established from 14 male p.P50T/AKT2 variant carriers and 14 controls. Insulin-stimulated glucose uptake and glucose incorporation into glycogen were detected with 2-[1,2-3H]-deoxy-D-glucose and D-[14C]-glucose, respectively, and the rate of glycolysis was measured with a Seahorse XFe96 analyzer. Insulin signalling was investigated with Western blotting. The binding of variant and control AKT2-PH domains to phosphatidylinositol (3,4,5)-trisphosphate (PI(3,4,5)P3) was assayed using PIP StripsTM Membranes. Protein tyrosine kinase and serine-threonine kinase assays were performed using the PamGene® kinome profiling system. Insulin-stimulated glucose uptake and glycogen synthesis in myotubes in vitro were not significantly affected by the genotype. However, the insulin-stimulated glycolytic rate was impaired in variant myotubes. Western blot analysis showed that insulin-stimulated phosphorylation of AKT-Thr308, AS160-Thr642 and GSK3β-Ser9 was reduced in variant myotubes compared to controls. The binding of variant AKT2-PH domain to PI(3,4,5)P3 was reduced as compared to the control protein. PamGene® kinome profiling revealed multiple differentially phosphorylated kinase substrates, e.g. calmodulin, between the genotypes. Further in silico upstream kinase analysis predicted a large-scale impairment in activities of kinases participating, for example, in intracellular signal transduction, protein translation and cell cycle events. In conclusion, myotubes from p.P50T/AKT2 variant carriers show multiple signalling alterations which may contribute to predisposition to insulin resistance and T2D in the carriers of this signalling variant.

Mediation analysis of multiple mediators with incomplete omics data

There is an increasing interest in using multiple types of omics features (e.g., DNA sequences, RNA expressions, methylation, protein expressions, and metabolic profiles) to study how the relationships between phenotypes and genotypes may be mediated by other omics markers. Genotypes and phenotypes are typically available for all subjects in genetic studies, but typically, some omics data will be missing for some subjects, due to limitations such as cost and sample quality. In this article, we propose a powerful approach for mediation analysis that accommodates missing data among multiple mediators and allows for various interaction effects. We formulate the relationships among genetic variants, other omics measurements, and phenotypes through linear regression models. We derive the joint likelihood for models with two mediators, accounting for arbitrary patterns of missing values. Utilizing computationally efficient and stable algorithms, we conduct maximum likelihood estimation. Our methods produce unbiased and statistically efficient estimators. We demonstrate the usefulness of our methods through simulation studies and an application to the Metabolic Syndrome in Men study.

Multi-ancestry study of the genetics of problematic alcohol use in >1 million individuals

Problematic alcohol use (PAU) is a leading cause of death and disability worldwide. To improve our understanding of the genetics of PAU, we conducted a large cross-ancestry meta-analysis of PAU in 1,079,947 individuals. We observed a high degree of cross-ancestral similarity in the genetic architecture of PAU and identified 110 independent risk variants in within- and cross-ancestry analyses. Cross-ancestry fine-mapping improved the identification of likely causal variants. Prioritizing genes through gene expression and/or chromatin interaction in brain tissues identified multiple genes associated with PAU. We identified existing medications for potential pharmacological studies by drug repurposing analysis. Cross-ancestry polygenic risk scores (PRS) showed better performance in independent sample than single-ancestry PRS. Genetic correlations between PAU and other traits were observed in multiple ancestries, with other substance use traits having the highest correlations. The analysis of diverse ancestries contributed significantly to the findings, and fills an important gap in the literature.

Features of the cytogram and cytokine profile of bronchoalveolar lavage fluid in experimental metabolic syndrome

The aim of the study was to identify the features of the cellular composition and cytokine profile of bronchoalveolar lavage fluid in rats in a model of diet-induced metabolic syndrome.

Materials and methods. In an experiment on animals (rats), a model of metabolic syndrome (MS) induced by a high-fat and high-carbohydrate diet was reproduced. To assess the viability of the reproduced model, biochemical and morphometric methods were used, such as measurement of body weight, specific gravity of liver and visceral fat, and blood pressure, determination of glucose concentration in the blood (including a glucose tolerance test), as well as determination of blood lipid parameters. To assess the intensity of the inflammatory response in the blood, the concentration of total protein, the total number of leukocytes, and the levels of immunocytokines (interleukin (IL)-6, IL-10, tumor necrosis factor (TNF)α, monocyte chemoattractant protein (MCP)-1) were determined. Open bronchoalveolar lavage was performed on the isolated heart – lung complex. The concentration of protein, immunocytokines (IL-6, IL-10, TNFα, MCP-1), the total number of leukocytes, and the ratio of their morphological types were determined in the bronchoalveolar lavage fluid (BALF).

Results. In animals with MS, an increase in the total number of leukocytes in the blood due to granulocytes and a rise in the concentration of protein, TNFα, and IL-10 were revealed compared with the parameters in the controls. BALF analysis revealed an increase in the concentration of protein, the total number of leukocytes, and the absolute number of alveolar macrophages, neutrophil granulocytes, and lymphocytes. The levels of IL-6 and MCP-1 were more than 1.5 times higher.

Conclusion. Changes in the qualitative and quantitative parameters of BALF are inflammatory in nature and are formed during a systemic inflammatory response accompanying metabolic disorders in modeling MS in rats in the experiment.

Multi-omic integration reveals cell-type-specific regulatory networks of insulin resistance in distinct ancestry populations

Our knowledge of the cell-type-specific mechanisms of insulin resistance remains limited. To dissect the cell-type-specific molecular signatures of insulin resistance, we performed a multiscale gene network analysis of adipose and muscle tissues in African and European ancestry populations. In adipose tissues, a comparative analysis revealed ethnically conserved cell-type signatures and two adipocyte subtype-enriched modules with opposite insulin sensitivity responses. The modules enriched for adipose stem and progenitor cells as well as immune cells showed negative correlations with insulin sensitivity. In muscle tissues, the modules enriched for stem cells and fibro-adipogenic progenitors responded to insulin sensitivity oppositely. The adipocyte and muscle fiber-enriched modules shared cellular-respiration-related genes but had tissue-specific rearrangements of gene regulations in response to insulin sensitivity. Integration of the gene co-expression and causal networks further pinpointed key drivers of insulin resistance. Together, this study revealed the cell-type-specific transcriptomic networks and signaling maps underlying insulin resistance in major glucose-responsive tissues. A record of this paper's transparent peer review process is included in the supplemental information.

Long-range chromosomal interactions increase and mark repressed gene expression during adipogenesis

Obesity perturbs central functions of human adipose tissue, centred on differentiation of preadipocytes to adipocytes, i.e., adipogenesis. The large environmental component of obesity makes it important to elucidate epigenetic regulatory factors impacting adipogenesis. Promoter Capture Hi-C (pCHi-C) has been used to identify chromosomal interactions between promoters and associated regulatory elements. However, long range interactions (LRIs) greater than 1 Mb are often filtered out of pCHi-C datasets, due to technical challenges and their low prevalence. To elucidate the unknown role of LRIs in adipogenesis, we investigated preadipocyte differentiation to adipocytes using pCHi-C and bulk and single nucleus RNA-seq data. We first show that LRIs are reproducible between biological replicates, and they increase >2-fold in frequency across adipogenesis. We further demonstrate that genomic loci containing LRIs are more epigenetically repressed than regions without LRIs, corresponding to lower gene expression in the LRI regions. Accordingly, as preadipocytes differentiate into adipocytes, LRI regions are more likely to contain repressed preadipocyte marker genes; whereas these same LRI regions are depleted of actively expressed adipocyte marker genes. Finally, we show that LRIs can be used to restrict multiple testing of the long-range cis-eQTL analysis to identify variants that regulate genes via LRIs. We exemplify this by identifying a putative long range cis regulatory mechanism at the LYPLAL1/TGFB2 obesity locus. In summary, we identify LRIs that mark repressed regions of the genome, and these interactions increase across adipogenesis, pinpointing developmental regions that need to be repressed in a cell-type specific way for adipogenesis to proceed.

Effects of SLCO1B1 Genetic Variant on Metabolite Profile in Participants on Simvastatin Treatment

Organic-anion-transporting polypeptide 1B1 (OATP1B1), encoded by the solute carrier organic anion transporter family member 1B1 gene (SLCO1B1), is highly expressed in the liver and transports several endogenous metabolites into the liver, including statins. Previous studies have not investigated the association of SLCO1B1 rs4149056 variant with the risk of type 2 diabetes (T2D) or determined the metabolite signature of the C allele of SLCO1B1 rs4149056 (SLCO1B1 rs4149056-C allele) in a large randomly selected population. SLCO1B1 rs4149056-C inhibits OATP1B1 transporter and is associated with increased levels of blood simvastatin concentrations. Our study is to first to show that SLCO1B1 rs4149056 variant is not significantly associated with the risk of T2D, suggesting that simvastatin has a direct effect on the risk of T2D. Additionally, we investigated the effects of SLCO1B1 rs4149056-C on plasma metabolite concentrations in 1373 participants on simvastatin treatment and in 1368 age- and body-mass index (BMI)-matched participants without any statin treatment. We found 31 novel metabolites significantly associated with SLCO1B1 rs4149056-C in the participants on simvastatin treatment and in the participants without statin treatment. Simvastatin decreased concentrations of dicarboxylic acids, such as docosadioate and dodecanedioate, that may increase beta- and peroxisomal oxidation and increased the turnover of cholesterol into bile acids, resulting in a decrease in steroidogenesis due to limited availability of cholesterol for steroid synthesis. Our findings suggest that simvastatin exerts its effects on the lowering of low-density lipoprotein (LDL) cholesterol concentrations through several distinct pathways in the carriers of SLCO1B1 rs4149056-C, including dicarboxylic acids, bile acids, steroids, and glycerophospholipids.

Integrating transcriptomics, metabolomics, and GWAS helps reveal molecular mechanisms for metabolite levels and disease risk

Transcriptomics data have been integrated with genome-wide association studies (GWASs) to help understand disease/trait molecular mechanisms. The utility of metabolomics, integrated with transcriptomics and disease GWASs, to understand molecular mechanisms for metabolite levels or diseases has not been thoroughly evaluated. We performed probabilistic transcriptome-wide association and locus-level colocalization analyses to integrate transcriptomics results for 49 tissues in 706 individuals from the GTEx project, metabolomics results for 1,391 plasma metabolites in 6,136 Finnish men from the METSIM study, and GWAS results for 2,861 disease traits in 260,405 Finnish individuals from the FinnGen study. We found that genetic variants that regulate metabolite levels were more likely to influence gene expression and disease risk compared to the ones that do not. Integrating transcriptomics with metabolomics results prioritized 397 genes for 521 metabolites, including 496 previously identified gene-metabolite pairs with strong functional connections and suggested 33.3% of such gene-metabolite pairs shared the same causal variants with genetic associations of gene expression. Integrating transcriptomics and metabolomics individually with FinnGen GWAS results identified 1,597 genes for 790 disease traits. Integrating transcriptomics and metabolomics jointly with FinnGen GWAS results helped pinpoint metabolic pathways from genes to diseases. We identified putative causal effects of UGT1A1/UGT1A4 expression on gallbladder disorders through regulating plasma (E,E)-bilirubin levels, of SLC22A5 expression on nasal polyps and plasma carnitine levels through distinct pathways, and of LIPC expression on age-related macular degeneration through glycerophospholipid metabolic pathways. Our study highlights the power of integrating multiple sets of molecular traits and GWAS results to deepen understanding of disease pathophysiology.

Single-cell dissection of the obesity-exercise axis in adipose-muscle tissues implies a critical role for mesenchymal stem cells

Exercise training is critical for the prevention and treatment of obesity, but its underlying mechanisms remain incompletely understood given the challenge of profiling heterogeneous effects across multiple tissues and cell types. Here, we address this challenge and opposing effects of exercise and high-fat diet (HFD)-induced obesity at single-cell resolution in subcutaneous and visceral white adipose tissue and skeletal muscle in mice with diet and exercise training interventions. We identify a prominent role of mesenchymal stem cells (MSCs) in obesity and exercise-induced tissue adaptation. Among the pathways regulated by exercise and HFD in MSCs across the three tissues, extracellular matrix remodeling and circadian rhythm are the most prominent. Inferred cell-cell interactions implicate within- and multi-tissue crosstalk centered around MSCs. Overall, our work reveals the intricacies and diversity of multi-tissue molecular responses to exercise and obesity and uncovers a previously underappreciated role of MSCs in tissue-specific and multi-tissue beneficial effects of exercise.

Role of gut microbe-derived metabolites in cardiometabolic diseases: Systems based approach

BACKGROUND

The gut microbiome influences host physiology and cardiometabolic diseases by interacting directly with intestinal cells or by producing molecules that enter the host circulation. Given the large number of microbial species present in the gut and the numerous factors that influence gut bacterial composition, it has been challenging to understand the underlying biological mechanisms that modulate risk of cardiometabolic disease.

SCOPE OF THE REVIEW

Here we discuss a systems-based approach that involves simultaneously examining individuals in populations for gut microbiome composition, molecular traits using "omics" technologies, such as circulating metabolites quantified by mass spectrometry, and clinical traits. We summarize findings from landmark studies using this approach and discuss future applications.

MAJOR CONCLUSIONS

Population-based integrative approaches have identified a large number of microbe-derived or microbe-modified metabolites that are associated with cardiometabolic traits. The knowledge gained from these studies provide new opportunities for understanding the mechanisms involved in gut microbiome-host interactions and may have potentially important implications for developing novel therapeutic approaches.