External control arm analysis: an evaluation of propensity score approaches, G-computation, and doubly debiased machine learning

BACKGROUND

An external control arm is a cohort of control patients that are collected from data external to a single-arm trial. To provide an unbiased estimation of efficacy, the clinical profiles of patients from single and external arms should be aligned, typically using propensity score approaches. There are alternative approaches to infer efficacy based on comparisons between outcomes of single-arm patients and machine-learning predictions of control patient outcomes. These methods include G-computation and Doubly Debiased Machine Learning (DDML) and their evaluation for External Control Arms (ECA) analysis is insufficient.

METHODS

We consider both numerical simulations and a trial replication procedure to evaluate the different statistical approaches: propensity score matching, Inverse Probability of Treatment Weighting (IPTW), G-computation, and DDML. The replication study relies on five type 2 diabetes randomized clinical trials granted by the Yale University Open Data Access (YODA) project. From the pool of five trials, observational experiments are artificially built by replacing a control arm from one trial by an arm originating from another trial and containing similarly-treated patients.

RESULTS

Among the different statistical approaches, numerical simulations show that DDML has the smallest bias followed by G-computation. In terms of mean squared error, G-computation usually minimizes mean squared error. Compared to other methods, DDML has varying Mean Squared Error performances that improves with increasing sample sizes. For hypothesis testing, all methods control type I error and DDML is the most conservative. G-computation is the best method in terms of statistical power, and DDML has comparable power at [Formula: see text] but inferior ones for smaller sample sizes. The replication procedure also indicates that G-computation minimizes mean squared error whereas DDML has intermediate performances in between G-computation and propensity score approaches. The confidence intervals of G-computation are the narrowest whereas confidence intervals obtained with DDML are the widest for small sample sizes, which confirms its conservative nature.

CONCLUSIONS

For external control arm analyses, methods based on outcome prediction models can reduce estimation error and increase statistical power compared to propensity score approaches.

Comprehensive characterization of putative genetic influences on plasma metabolome in a pediatric cohort

BACKGROUND

The human exposome is composed of diverse metabolites and small chemical compounds originated from endogenous and exogenous sources, respectively. Genetic and environmental factors influence metabolite levels, while the extent of genetic contributions across metabolic pathways is not yet known. Untargeted profiling of human metabolome using high-resolution mass spectrometry (HRMS) combined with genome-wide genotyping allows comprehensive identification of genetically influenced metabolites. As such previous studies of adults discovered and replicated genotype-metabotype associations. However, these associations have not been characterized in children.

RESULTS

We conducted the largest genome by metabolome-wide association study to date of children (N = 441) using 619,688 common genetic variants and 14,342 features measured by HRMS. Narrow-sense heritability (h²) estimates of plasma metabolite concentrations using genomic relatedness matrix restricted maximum likelihood (GREML) method showed a bimodal distribution with high h² (> 0.8) for 15.9% of features and low h² (< 0.2) for most of features (62.0%). The features with high h² were enriched for amino acid and nucleic acid metabolism, while carbohydrate and lipid concentrations showed low h². For each feature, a metabolite quantitative trait loci (mQTL) analysis was performed to identify genetic variants that were potentially associated with plasma levels. Fifty-four associations among 29 features and 43 genetic variants were identified at a genome-wide significance threshold p < 3.5 × 10^-12 (= 5 × 10^-8/14,342 features). Previously reported associations such as UGT1A1 and bilirubin; PYROXD2 and methyl lysine; and ACADS and butyrylcarnitine were successfully replicated in our pediatric cohort. We found potential candidates for novel associations including CSMD1 and a monostearyl alcohol triglyceride (m/z 781.7483, retention time (RT) 89.3 s); CALN1 and Tridecanol (m/z 283.2741, RT 27.6). A gene-level enrichment analysis using MAGMA revealed highly interconnected modules for dADP biosynthesis, sterol synthesis, and long-chain fatty acid transport in the gene-feature network.

CONCLUSION

Comprehensive profiling of plasma metabolome across age groups combined with genome-wide genotyping revealed a wide range of genetic influence on diverse chemical species and metabolic pathways. The developmental trajectory of a biological system is shaped by gene-environment interaction especially in early life. Therefore, continuous efforts on generating metabolomics data in diverse human tissue types across age groups are required to understand gene-environment interaction toward healthy aging trajectories.

Quantifying the role of transcript levels in mediating DNA methylation effects on complex traits and diseases

High-dimensional omics datasets provide valuable resources to determine the causal role of molecular traits in mediating the path from genotype to phenotype. Making use of molecular quantitative trait loci (QTL) and genome-wide association study (GWAS) summary statistics, we propose a multivariable Mendelian randomization (MVMR) framework to quantify the proportion of the impact of the DNA methylome (DNAm) on complex traits that is propagated through the assayed transcriptome. Evaluating 50 complex traits, we find that on average at least 28.3% (95% CI: [26.9%-29.8%]) of DNAm-to-trait effects are mediated through (typically multiple) transcripts in the cis-region. Several regulatory mechanisms are hypothesized, including methylation of the promoter probe cg10385390 (chr1:8'022'505) increasing the risk for inflammatory bowel disease by reducing PARK7 expression. The proposed integrative framework can be extended to other omics layers to identify causal molecular chains, providing a powerful tool to map and interpret GWAS signals.

Reduced gluteofemoral (subcutaneous) fat mass in young Japanese women with family history of type 2 diabetes: an exploratory analysis

Limited expandability of subcutaneous adipose tissue may be characteristics of first-degree relatives of type 2 diabetes. We tested the hypothesis that family history of type 2 diabetes (FHD) may be associated with reduced peripheral fat mass. Body composition and metabolic variables were compared between 18 and 111 Japanese female collegiate athletes, and between 55 and 148 nonathletes with positive (FHD +) and negative FHD (FHD-), respectively. We had multivariate logistic regression analyses for FHD + as dependent variable in a total population.BMI averaged < 21 kg/m2 and did not differ between FHD + and FHD- nonathletes. Despite comparable BMI, body fat percentage and serum leptin were lower in FHD + nonathletes. This was due to lower arm and gluteofemoral fat percentage (both p = 0.02) whereas the difference in trunk fat percentage was not significant (p = 0.08). These differences were not found between two groups of athletes. FHD + women had lower HDL cholesterol despite lower BMI in a total population. Fasting insulin, serum adiponectin and high-sensitivity C-reactive protein did not differ between FHD + and FHD- athletes or nonathletes. Multivariate logistic regression analyses revealed independent associations of FHD + with BMI (odds ratio, 0.869; 95% confidential interval, 0.768–0.984; p = 0.02) and HDL cholesterol (odds ratio, 0.977; 95% confidential interval, 0.957–0.997, p = 0.02). In conclusion, FHD may be associated with reduced subcutaneous fat mass in young Japanese women, suggesting impaired adipose tissue expandability.

The negative association of lower body fat mass with cardiometabolic disease risk factors is partially mediated by adiponectin

Gluteofemoral fat correlates negatively with a number of cardiometabolic disease risk factors, but the mechanisms involved in these relationships are unknown. The aim of this study was to test the hypothesis that gluteofemoral fat attenuates the risk of cardiometabolic disease by increasing blood adiponectin levels. This was a cross-sectional study in which arm, leg, gluteofemoral, abdominal s.c. and visceral fat levels were measured by dual-energy X-ray absorptiometry in 648 African females. Fasting serum adiponectin, lipid, insulin and plasma glucose levels and blood pressure were measured. Relationships between variables were analysed using multivariable linear regression and structural equation modelling. Adiponectin correlated positively (β = 0.45, P < 0.0001) with gluteofemoral fat in a multivariable regression model that included age, height, and arm, s.c. and visceral fat levels. In further regression models, there was a negative correlation of gluteofemoral fat with fasting glucose (β = -0.28; P < 0.0001) and triglyceride levels (β = -0.29; P < 0.0001) and insulin resistance (HOMA; β = -0.26; P < 0.0001). Structural equation modelling demonstrated that adiponectin mediated 20.7% (P < 0.01) of the association of gluteofemoral fat with insulin resistance and 16.1% (P < 0.01) of the association with triglyceride levels but only 6.67% (P = 0.31) of the association with glucose levels. These results demonstrate that gluteofemoral and leg fat are positively associated with adiponectin levels and that the negative association of lower body fat with insulin resistance and triglyceride levels may partially be mediated by this adipokine. Further studies are required to determine other factors that mediate the effect of lower body fat on cardiometabolic disease risk factors.

ER-associated RNA silencing promotes ER quality control

The endoplasmic reticulum (ER) coordinates mRNA translation and processing of secreted and endomembrane proteins. ER-associated degradation (ERAD) prevents the accumulation of misfolded proteins in the ER, but the physiological regulation of this process remains poorly characterized. Here, in a genetic screen using an ERAD model substrate in Caenorhabditis elegans, we identified an anti-viral RNA interference pathway, referred to as ER-associated RNA silencing (ERAS), which acts together with ERAD to preserve ER homeostasis and function. Induced by ER stress, ERAS is mediated by the Argonaute protein RDE-1/AGO2, is conserved in mammals and promotes ER-associated RNA turnover. ERAS and ERAD are complementary, as simultaneous inactivation of both quality-control pathways leads to increased ER stress, reduced protein quality control and impaired intestinal integrity. Collectively, our findings indicate that ER homeostasis and organismal health are protected by synergistic functions of ERAS and ERAD.

Hepatocyte- or macrophage-specific SREBP-1a deficiency in mice exacerbates methionine- and choline-deficient diet-induced nonalcoholic fatty liver disease

Sterol regulatory element-binding proteins (SREBPs) are master transcription factors for lipid synthesis, and SREBP-1 is important for fatty acid and triglyceride synthesis. SREBP-1 has two isoforms, SREBP-1a and SREBP-1c, which are splicing variants transcribed from the Srebf1 gene. Although SREBP-1a exhibits stronger transcriptional activity than SREBP-1c, hepatic SREBP-1c is considered more physiologically important. We generated SREBP-1a flox mice using the CRISPR/Cas9 system and hepatocyte- and macrophage-specific SREBP-1a knockout (KO) mice (LKO, liver-knockout; and mΦKO, macrophage-knockout). There were no significant differences among all the mouse genotypes upon feeding with a normal diet. However, feeding with a methionine- and choline-deficient (MCD) diet resulted in exacerbated liver injury in both KO mice. In LKO mice, fatty liver was unexpectedly exacerbated, leading to macrophage infiltration and inflammation. In contrast, in mΦKO mice, the fatty liver state was similar to that in flox mice, but the polarity of the macrophages in the liver was transformed into a proinflammatory M1 subtype, resulting in the exacerbation of inflammation. Taken together, we found that SREBP-1a does not contribute to hepatic lipogenesis, but in either hepatocytes or macrophages distinctly controls the onset of pathological conditions in MCD diet-induced hepatitis.NEW & NOTEWORTHY Hepatocyte- and macrophage-specific SREBP-1a knockout mice were generated for the first time. This study reveals that SREBP-1a does not contribute to hepatic lipogenesis, but in either hepatocytes or macrophages distinctly controls the onset of pathological conditions in methionine- and choline-deficient diet-induced hepatitis.

Exploring the Genetic Association between Obesity and Serum Lipid Levels Using Bivariate Methods

It is crucial to understand the genetic mechanisms and biological pathways underlying the relationship between obesity and serum lipid levels. Structural equation models (SEMs) were constructed to calculate heritability for body mass index (BMI), total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and the genetic connections between BMI and the four classes of lipids using 1197 pairs of twins from the Chinese National Twin Registry (CNTR). Bivariate genomewide association studies (GWAS) were performed to identify genetic variants associated with BMI and lipids using the records of 457 individuals, and the results were further validated in 289 individuals. The genetic background affecting BMI may differ by gender, and the heritability of males and females was 71% (95% CI [.66, .75]) and 39% (95% CI [.15, .71]) respectively. BMI was positively correlated with TC, TG and LDL-C in phenotypic and genetic correlation, while negatively correlated with HDL-C. There were gender differences in the correlation between BMI and lipids. Bivariate GWAS analysis and validation stage found 7 genes (LOC105378740, LINC02506, CSMD1, MELK, FAM81A, ERAL1 and MIR144) that were possibly related to BMI and lipid levels. The significant biological pathways were the regulation of cholesterol reverse transport and the regulation of high-density lipoprotein particle clearance (p < .001). BMI and blood lipid levels were affected by genetic factors, and they were genetically correlated. There might be gender differences in their genetic correlation. Bivariate GWAS analysis found MIR144 gene and its related biological pathways may influence obesity and lipid levels.

Genetically personalised organ-specific metabolic models in health and disease

Understanding how genetic variants influence disease risk and complex traits (variant-to-function) is one of the major challenges in human genetics. Here we present a model-driven framework to leverage human genome-scale metabolic networks to define how genetic variants affect biochemical reaction fluxes across major human tissues, including skeletal muscle, adipose, liver, brain and heart. As proof of concept, we build personalised organ-specific metabolic flux models for 524,615 individuals of the INTERVAL and UK Biobank cohorts and perform a fluxome-wide association study (FWAS) to identify 4312 associations between personalised flux values and the concentration of metabolites in blood. Furthermore, we apply FWAS to identify 92 metabolic fluxes associated with the risk of developing coronary artery disease, many of which are linked to processes previously described to play in role in the disease. Our work demonstrates that genetically personalised metabolic models can elucidate the downstream effects of genetic variants on biochemical reactions involved in common human diseases.

Type 2 diabetes

Type 2 diabetes accounts for nearly 90% of the approximately 537 million cases of diabetes worldwide. The number affected is increasing rapidly with alarming trends in children and young adults (up to age 40 years). Early detection and proactive management are crucial for prevention and mitigation of microvascular and macrovascular complications and mortality burden. Access to novel therapies improves person-centred outcomes beyond glycaemic control. Precision medicine, including multiomics and pharmacogenomics, hold promise to enhance understanding of disease heterogeneity, leading to targeted therapies. Technology might improve outcomes, but its potential is yet to be realised. Despite advances, substantial barriers to changing the course of the epidemic remain. This Seminar offers a clinically focused review of the recent developments in type 2 diabetes care including controversies and future directions.

Identification of 969 protein quantitative trait loci in an African American population with kidney disease attributed to hypertension

Investigations into the causal underpinnings of disease processes can be aided by the incorporation of genetic information. Genetic studies require populations varied in both ancestry and prevalent disease in order to optimize discovery and ensure generalizability of findings to the global population. Here, we report the genetic determinants of the serum proteome in 466 African Americans with chronic kidney disease attributed to hypertension from the richly phenotyped African American Study of Kidney Disease and Hypertension (AASK) study. Using the largest aptamer-based protein profiling platform to date (6,790 proteins or protein complexes), we identified 969 genetic associations with 900 unique proteins; including 52 novel cis (local) associations and 379 novel trans (distant) associations. The genetic effects of previously published cis-protein quantitative trait loci (pQTLs) were found to be highly reproducible, and we found evidence that our novel genetic signals colocalize with gene expression and disease processes. Many trans- pQTLs were found to reflect associations mediated by the circulating cis protein, and the common trans-pQTLs are enriched for processes involving extracellular vesicles, highlighting a plausible mechanism for distal regulation of the levels of secreted proteins. Thus, our study generates a valuable resource of genetic associations linking variants to protein levels and disease in an understudied patient population to inform future studies of drug targets and physiology.

Metabolic diversity in human populations and correlation with genetic and ancestral geographic distances

DNA polymorphic markers and self-defined ethnicity groupings are used to group individuals with shared ancient geographic ancestry. Here we studied whether ancestral relationships between individuals could be identified from metabolic screening data reported by the California newborn screening (NBS) program. NBS data includes 41 blood metabolites measured by tandem mass spectrometry from singleton babies in 17 parent-reported ethnicity groupings. Ethnicity-associated differences identified for 71% of NBS metabolites (29 of 41, Cohen's d &gt; 0.5) showed larger differences in blood levels of acylcarnitines than of amino acids (P &lt; 1e-4). A metabolic distance measure, developed to compare ethnic groupings based on metabolic differences, showed low positive correlation with genetic and ancient geographic distances between the groups' ancestral world populations. Several outlier group pairs were identified with larger genetic and smaller metabolic distances (Black versus White) or with smaller genetic and larger metabolic distances (Chinese versus Japanese) indicating the influence of genetic and of environmental factors on metabolism. Using machine learning, comparison of metabolic profiles between all pairs of ethnic groupings distinguished individuals with larger genetic distance (Black versus Chinese, AUC = 0.96), while genetically more similar individuals could not be separated metabolically (Hispanic versus Native American, AUC = 0.51). Additionally, we identified metabolites informative for inferring metabolic ancestry in individuals from genetically similar populations, which included biomarkers for inborn metabolic disorders (C10:1, C12:1, C3, C5OH, Leucine-Isoleucine). This work sheds new light on metabolic differences in healthy newborns in diverse populations, which could have implications for improving genetic disease screening.

Rare and common genetic determinants of metabolic individuality and their effects on human health

Garrod's concept of 'chemical individuality' has contributed to comprehension of the molecular origins of human diseases. Untargeted high-throughput metabolomic technologies provide an in-depth snapshot of human metabolism at scale. We studied the genetic architecture of the human plasma metabolome using 913 metabolites assayed in 19,994 individuals and identified 2,599 variant-metabolite associations (P < 1.25 × 10^-11) within 330 genomic regions, with rare variants (minor allele frequency ≤ 1%) explaining 9.4% of associations. Jointly modeling metabolites in each region, we identified 423 regional, co-regulated, variant-metabolite clusters called genetically influenced metabotypes. We assigned causal genes for 62.4% of these genetically influenced metabotypes, providing new insights into fundamental metabolite physiology and clinical relevance, including metabolite-guided discovery of potential adverse drug effects (DPYD and SRD5A2). We show strong enrichment of inborn errors of metabolism-causing genes, with examples of metabolite associations and clinical phenotypes of non-pathogenic variant carriers matching characteristics of the inborn errors of metabolism. Systematic, phenotypic follow-up of metabolite-specific genetic scores revealed multiple potential etiological relationships.

Proteomic signatures for identification of impaired glucose tolerance

The implementation of recommendations for type 2 diabetes (T2D) screening and diagnosis focuses on the measurement of glycated hemoglobin (HbA1c) and fasting glucose. This approach leaves a large number of individuals with isolated impaired glucose tolerance (iIGT), who are only detectable through oral glucose tolerance tests (OGTTs), at risk of diabetes and its severe complications. We applied machine learning to the proteomic profiles of a single fasted sample from 11,546 participants of the Fenland study to test discrimination of iIGT defined using the gold-standard OGTTs. We observed significantly improved discriminative performance by adding only three proteins (RTN4R, CBPM and GHR) to the best clinical model (AUROC = 0.80 (95% confidence interval: 0.79-0.86), P = 0.004), which we validated in an external cohort. Increased plasma levels of these candidate proteins were associated with an increased risk for future T2D in an independent cohort and were also increased in individuals genetically susceptible to impaired glucose homeostasis and T2D. Assessment of a limited number of proteins can identify individuals likely to be missed by current diagnostic strategies and at high risk of T2D and its complications.

APOE alleles modulate associations of plasma metabolites with variants from multiple genes on chromosome 19q13.3

The APOE ε2, ε3, and ε4 alleles differentially impact various complex diseases and traits. We examined whether these alleles modulated associations of 94 single-nucleotide polymorphisms (SNPs) harbored by 26 genes in 19q13.3 region with 217 plasma metabolites using Framingham Heart Study data. The analyses were performed in the E2 (ε2ε2 or ε2ε3 genotype), E3 (ε3ε3 genotype), and E4 (ε3ε4 or ε4ε4 genotype) groups separately. We identified 31, 17, and 22 polymorphism-metabolite associations in the E2, E3, and E4 groups, respectively, at a false discovery rate P FDR < 0.05. These entailed 51 and 19 associations with 20 lipid and 12 polar analytes. Contrasting the effect sizes between the analyzed groups showed 20 associations with group-specific effects at Bonferroni-adjusted P < 7.14E-04. Three associations with glutamic acid or dimethylglycine had significantly larger effects in the E2 than E3 group and 12 associations with triacylglycerol 56:5, lysophosphatidylethanolamines 16:0, 18:0, 20:4, or phosphatidylcholine 38:6 had significantly larger effects in the E2 than E4 group. Two associations with isocitrate or propionate and three associations with phosphatidylcholines 32:0, 32:1, or 34:0 had significantly larger effects in the E4 than E3 group. Nine of 70 SNP-metabolite associations identified in either E2, E3, or E4 groups attained P FDR < 0.05 in the pooled sample of these groups. However, none of them were among the 20 group-specific associations. Consistent with the evolutionary history of the APOE alleles, plasma metabolites showed higher APOE-cluster-related variations in the E4 than E2 and E3 groups. Pathway enrichment mainly highlighted lipids and amino acids metabolism and citrate cycle, which can be differentially impacted by the APOE alleles. These novel findings expand insights into the genetic heterogeneity of plasma metabolites and highlight the importance of the APOE-allele-stratified genetic analyses of the APOE-related diseases and traits.

Improved survival of non-small cell lung cancer patients after introducing patient navigation: A retrospective cohort study with propensity score weighted historic control

OnkoNetwork is a patient navigation program established in the Moritz Kaposi General Hospital to improve the timeliness and completeness of cancer investigations and treatment. The H2020 SELFIE consortium selected OnkoNetwork as a promising integrated care initiative in Hungary and conducted a multicriteria decision analysis based on health, patient experience, and cost outcomes. In this paper, a more detailed analysis of clinical impacts is provided in the largest subgroup, non-small cell lung cancer (NSCLC) patients. A retrospective cohort study was conducted, enrolling new cancer suspect patients with subsequently confirmed NSCLC in two annual periods, before and after OnkoNetwork implementation (control and intervention cohorts, respectively). To control for selection bias and confounding, baseline balance was improved via propensity score weighting. Overall survival was analyzed in univariate and multivariate weighted Cox regression models and the effect was further characterized in a counterfactual analysis. Our analysis included 123 intervention and 173 control NSCLC patients from early to advanced stage, with significant between-cohort baseline differences. The propensity score-based weighting resulted in good baseline balance. A large survival benefit was observed in the intervention cohort, and intervention was an independent predictor of longer survival in a multivariate analysis when all baseline characteristics were included (HR = 0.63, p = 0.039). When post-baseline variables were included in the model, belonging to the intervention cohort was not an independent predictor of survival, but the survival benefit was explained by slightly better stage distribution and ECOG status at treatment initiation, together with trends for broader use of PET-CT and higher resectability rate. In conclusion, patient navigation is a valuable tool to improve cancer outcomes by facilitating more timely and complete cancer diagnostics. Contradictory evidence in the literature may be explained by common sources of bias, including the wait-time paradox and adjustment to intermediate outcomes.

The Genetic Basis for the Increased Prevalence of Metabolic Syndrome among Post-Traumatic Stress Disorder Patients

Post-traumatic stress disorder (PTSD) is a highly debilitating psychiatric disorder that can be triggered by exposure to extreme trauma. Even if PTSD is primarily a psychiatric condition, it is also characterized by adverse somatic comorbidities. One illness commonly co-occurring with PTSD is Metabolic syndrome (MetS), which is defined by a set of health risk/resilience factors including obesity, elevated blood pressure, lower high-density lipoprotein cholesterol, higher low-density lipoprotein cholesterol, higher triglycerides, higher fasting blood glucose and insulin resistance. Here, phenotypic association between PTSD and components of MetS are tested on a military veteran cohort comprising chronic PTSD presentation (n = 310, 47% cases, 83% male). Consistent with previous observations, we found significant phenotypic correlation between the various components of MetS and PTSD severity scores. To examine if this observed symptom correlations stem from a shared genetic background, we conducted genetic correlation analysis using summary statistics data from large-scale genetic studies. Our results show robust positive genetic correlation between PTSD and MetS (r_g[SE] = 0.33 [0.056], p = 4.74E-09), and obesity-related components of MetS (r_g = 0.25, SE = 0.05, p = 6.4E-08). Prioritizing genomic regions with larger local genetic correlation implicate three significant loci. Overall, these findings show significant genetic overlap between PTSD and MetS, which may in part account for the markedly increased occurrence of MetS among PTSD patients.

The Sexual Dimorphism of Human Adipose Depots

The amount and the distribution of body fat exhibit trajectories that are sex- and human species-specific and both are determinants for health. The enhanced accumulation of fat in the truncal part of the body as a risk factor for cardiovascular and metabolic diseases is well supported by epidemiological studies. In addition, a possible independent protective role of the gluteofemoral fat compartment and of the brown adipose tissue is emerging. The present narrative review summarizes the current knowledge on sexual dimorphism in fat depot amount and repartition and consequences on cardiometabolic and reproductive health. The drivers of the sex differences and fat depot repartition, considered to be the results of complex interactions between sex determination pathways determined by the sex chromosome composition, genetic variability, sex hormones and the environment, are discussed. Finally, the inter- and intra-depot heterogeneity in adipocytes and progenitors, emphasized recently by unbiased large-scale approaches, is highlighted.

Constructing an atlas of associations between polygenic scores from across the human phenome and circulating metabolic biomarkers

Background

Polygenic scores (PGS) are becoming an increasingly popular approach to predict complex disease risk, although they also hold the potential to develop insight into the molecular profiles of patients with an elevated genetic predisposition to disease.

Methods

We sought to construct an atlas of associations between 125 different PGS derived using results from genome-wide association studies and 249 circulating metabolites in up to 83,004 participants from the UK Biobank.

Results

As an exemplar to demonstrate the value of this atlas, we conducted a hypothesis-free evaluation of all associations with glycoprotein acetyls (GlycA), an inflammatory biomarker. Using bidirectional Mendelian randomization, we find that the associations highlighted likely reflect the effect of risk factors, such as adiposity or liability towards smoking, on systemic inflammation as opposed to the converse direction. Moreover, we repeated all analyses in our atlas within age strata to investigate potential sources of collider bias, such as medication usage. This was exemplified by comparing associations between lipoprotein lipid profiles and the coronary artery disease PGS in the youngest and oldest age strata, which had differing proportions of individuals undergoing statin therapy. Lastly, we generated all PGS-metabolite associations stratified by sex and separately after excluding 13 established lipid-associated loci to further evaluate the robustness of findings.

Conclusions

We envisage that the atlas of results constructed in our study will motivate future hypothesis generation and help prioritize and deprioritize circulating metabolic traits for in-depth investigations. All results can be visualized and downloaded at http://mrcieu.mrsoftware.org/metabolites_PRS_atlas.

Funding

This work is supported by funding from the Wellcome Trust, the British Heart Foundation, and the Medical Research Council Integrative Epidemiology Unit.

Constructing an atlas of associations between polygenic scores from across the human phenome and circulating metabolic biomarkers

BACKGROUND

Polygenic scores (PGS) are becoming an increasingly popular approach to predict complex disease risk, although they also hold the potential to develop insight into the molecular profiles of patients with an elevated genetic predisposition to disease.

METHODS

We sought to construct an atlas of associations between 125 different PGS derived using results from genome-wide association studies and 249 circulating metabolites in up to 83,004 participants from the UK Biobank.

RESULTS

As an exemplar to demonstrate the value of this atlas, we conducted a hypothesis-free evaluation of all associations with glycoprotein acetyls (GlycA), an inflammatory biomarker. Using bidirectional Mendelian randomization, we find that the associations highlighted likely reflect the effect of risk factors, such as adiposity or liability towards smoking, on systemic inflammation as opposed to the converse direction. Moreover, we repeated all analyses in our atlas within age strata to investigate potential sources of collider bias, such as medication usage. This was exemplified by comparing associations between lipoprotein lipid profiles and the coronary artery disease PGS in the youngest and oldest age strata, which had differing proportions of individuals undergoing statin therapy. Lastly, we generated all PGS-metabolite associations stratified by sex and separately after excluding 13 established lipid-associated loci to further evaluate the robustness of findings.

CONCLUSIONS

We envisage that the atlas of results constructed in our study will motivate future hypothesis generation and help prioritize and deprioritize circulating metabolic traits for in-depth investigations. All results can be visualized and downloaded at http://mrcieu.mrsoftware.org/metabolites_PRS_atlas.

FUNDING

This work is supported by funding from the Wellcome Trust, the British Heart Foundation, and the Medical Research Council Integrative Epidemiology Unit.

Multi-Omic analyses characterize the ceramide/sphingomyelin pathway as a therapeutic target in Alzheimer's disease

Dysregulation of sphingomyelin and ceramide metabolism have been implicated in Alzheimer's disease. Genome-wide and transcriptome-wide association studies have identified various genes and genetic variants in lipid metabolism that are associated with Alzheimer's disease. However, the molecular mechanisms of sphingomyelin and ceramide disruption remain to be determined. We focus on the sphingolipid pathway and carry out multi-omics analyses to identify central and peripheral metabolic changes in Alzheimer's patients, correlating them to imaging features. Our multi-omics approach is based on (a) 2114 human post-mortem brain transcriptomics to identify differentially expressed genes; (b) in silico metabolic flux analysis on context-specific metabolic networks identified differential reaction fluxes; (c) multimodal neuroimaging analysis on 1576 participants to associate genetic variants in sphingomyelin pathway with Alzheimer's disease pathogenesis; (d) plasma metabolomic and lipidomic analysis to identify associations of lipid species with dysregulation in Alzheimer's; and (e) metabolite genome-wide association studies to define receptors within the pathway as a potential drug target. We validate our hypothesis in amyloidogenic APP/PS1 mice and show prolonged exposure to fingolimod alleviated synaptic plasticity and cognitive impairment in mice. Our integrative multi-omics approach identifies potential targets in the sphingomyelin pathway and suggests modulators of S1P metabolism as possible candidates for Alzheimer's disease treatment.

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.

Lipidome- and Genome-Wide Study to Understand Sex Differences in Circulatory Lipids

Background Despite well-recognized differences in the atherosclerotic cardiovascular disease risk between men and women, sex differences in risk factors and sex-specific mechanisms in the pathophysiology of atherosclerotic cardiovascular disease remain poorly understood. Lipid metabolism plays a central role in the development of atherosclerotic cardiovascular disease. Understanding sex differences in lipids and their genetic determinants could provide mechanistic insights into sex differences in atherosclerotic cardiovascular disease and aid in precise risk assessment. Herein, we examined sex differences in plasma lipidome and heterogeneity in genetic influences on lipidome in men and women through sex-stratified genome-wide association analyses. Methods and Results We used data consisting of 179 lipid species measured by shotgun lipidomics in 7266 individuals from the Finnish GeneRISK cohort and sought for replication using independent data from 2045 participants. Significant sex differences in the levels of 141 lipid species were observed (P<7.0×10^-4). Interestingly, 121 lipid species showed significant age-sex interactions, with opposite age-related changes in 39 lipid species. In general, most of the cholesteryl esters, ceramides, lysophospholipids, and glycerides were higher in 45- to 50-year-old men compared with women of same age, but the sex differences narrowed down or reversed with age. We did not observe any major differences in genetic effect in the sex-stratified genome-wide association analyses, which suggests that common genetic variants do not have a major role in sex differences in lipidome. Conclusions Our study provides a comprehensive view of sex differences in circulatory lipids pointing to potential sex differences in lipid metabolism and highlights the need for sex- and age-specific prevention strategies.

Effects of general and central adiposity on circulating lipoprotein, lipid, and metabolite levels in UK Biobank: A multivariable Mendelian randomization study

Background

The direct effects of general adiposity (body mass index (BMI)) and central adiposity (waist-to-hip-ratio (WHR)) on circulating lipoproteins, lipids, and metabolites are unknown.

Methods

We used new metabolic data from UK Biobank (N=109,532, a five-fold higher N over previous studies). EDTA-plasma was used to quantify 249 traits with nuclear-magnetic-resonance spectroscopy including subclass-specific lipoprotein concentrations and lipid content, plus pre-glycemic and inflammatory metabolites. We used univariable and multivariable two-stage least-squares regression models with genetic risk scores for BMI and WHR as instruments to estimate total (unadjusted) and direct (mutually-adjusted) effects of BMI and WHR on metabolic traits; plus effects on statin use and interaction by sex, statin use, and age (proxy for medication use).

Findings

Higher BMI decreased apolipoprotein B and low-density lipoprotein cholesterol (LDL-C) before and after WHR-adjustment, whilst BMI increased triglycerides only before WHR-adjustment. These effects of WHR were larger and BMI-independent. Direct effects differed markedly by sex, e.g., triglycerides increased only with BMI among men, and only with WHR among women. Adiposity measures increased statin use and showed metabolic effects which differed by statin use and age. Among the youngest (38-53y, statins-5%), BMI and WHR (per-SD) increased LDL-C (total effects: 0.04-SD, 95%CI=-0.01,0.08 and 0.10-SD, 95%CI=0.02,0.17 respectively), but only WHR directly. Among the oldest (63-73y, statins-29%), BMI and WHR directly lowered LDL-C (-0.19-SD, 95%CI=-0.27,-0.11 and -0.05-SD, 95%CI=-0.16,0.06 respectively).

Interpretation

Excess adiposity likely raises atherogenic lipid and metabolite levels exclusively via adiposity stored centrally, particularly among women. Apparent effects of adiposity on lowering LDL-C are likely explained by an effect of adiposity on statin use.

Funding

UK Medical Research Council; British Heart Foundation; Novo Nordisk; National Institute for Health Research; Wellcome Trust; Cancer Research UK.

The Regulation of Triacylglycerol Metabolism and Lipoprotein Lipase Activity

Triacylglycerol (TG) metabolism is tightly regulated to maintain a pool of TG within circulating lipoproteins that can be hydrolyzed in a tissue-specific manner by lipoprotein lipase (LPL) to enable the delivery of fatty acids to adipose or oxidative tissues as needed. Elevated serum TG concentrations, which result from a deficiency of LPL activity or, more commonly, an imbalance in the regulation of tissue-specific LPL activities, have been associated with an increased risk of atherosclerotic cardiovascular disease through multiple studies. Among the most critical LPL regulators are the angiopoietin-like (ANGPTL) proteins ANGPTL3, ANGPTL4, and ANGPTL8, and a number of different apolipoproteins including apolipoprotein A5 (ApoA5), apolipoprotein C2 (ApoC2), and apolipoprotein C3 (ApoC3). These ANGPTLs and apolipoproteins work together to orchestrate LPL activity and therefore play pivotal roles in TG partitioning, hydrolysis, and utilization. This review summarizes the mechanisms of action, epidemiological findings, and genetic data most relevant to these ANGPTLs and apolipoproteins. The interplay between these important regulators of TG metabolism in both fasted and fed states is highlighted with a holistic view toward understanding key concepts and interactions. Strategies for developing safe and effective therapeutics to reduce circulating TG by selectively targeting these ANGPTLs and apolipoproteins are also discussed.

The REEP family of proteins: molecular targets and role in pathophysiology

Receptor expression-enhancing proteins (REEPs) are an evolutionarily conserved protein family that is pivotal to the structure and function of the endoplasmic reticulum (ER). The REEP family can be classified into two major subfamilies in higher species, the REEP1-4 and REEP5-6 subfamilies. Within the REEP1-4 subfamily, REEP1 and REEP2 are closely related, and REEP3 and REEP4 are similarly related. The REEP family is widely distributed in various tissues. Recent studies indicate that the REEP family is involved in many pathological and physiological processes, such as ER morphogenesis and remodeling, microtubule cytoskeleton regulation, and the trafficking and expression of G protein-coupled receptors (GPCRs). Moreover, the REEP family plays crucial roles in the occurrence and development of many diseases, including neurological diseases, diabetes, retinal diseases, cardiac diseases, infertility, obesity, oligoarticular juvenile idiopathic arthritis (OJIA), COVID-19, and cancer. In the present review, we describe the distribution and structure of the REEP family. Furthermore, we summarize the functions and the associated diseases of this family. Based on the pleiotropic actions of the REEP family, the study of its family members is crucial to understanding the relevant pathophysiological processes and developing strategies to modulate and control these related diseases. AVAILABILITY OF DATA AND MATERIAL: The datasets used or analyzed during the current study are available from the corresponding author on reasonable request.

Sex hormones, intestinal inflammation, and the gut microbiome: Major influencers of the sexual dimorphisms in obesity

Obesity is defined as the excessive accumulation of body fat and is associated with an increased risk of developing major health problems such as cardiovascular disease, diabetes and stroke. There are clear sexual dimorphisms in the epidemiology, pathophysiology and sequelae of obesity and its accompanying metabolic disorders, with females often better protected compared to males. This protection has predominantly been attributed to the female sex hormone estrogen and differences in fat distribution. More recently, the sexual dimorphisms of obesity have also been attributed to the differences in the composition and function of the gut microbiota, and the intestinal immune system. This review will comprehensively summarize the pre-clinical and clinical evidence for these sexual dimorphisms and discuss the interplay between sex hormones, intestinal inflammation and the gut microbiome in obesity. Major gaps and limitations of this rapidly growing area of research will also be highlighted in this review.

Genetically predicted circulating levels of glycine, glutamate, and serotonin in relation to the risks of three major neurodegenerative diseases: A Mendelian randomization analysis

It has been previously postulated that blood neurotransmitters might affect risks of neurodegenerative diseases. Here, a Mendelian Randomization (MR) study was conducted to explore whether genetically predicted concentrations of glycine, glutamate and serotonin were associated with risks of Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS). From three genome-wide association studies of European ancestry, single nucleotide polymorphisms strongly associated with glycine, glutamate and serotonin were selected as genetic instrumental variables. Corresponding summary statistics were also obtained from the latest genome-wide association meta-analyses of AD, PD and ALS. The inverse-variance weighted MR and multiple sensitivity analyses were performed to evaluate causal effects of genetically predicted levels of neurotransmitters on risks of neurodegenerative diseases. The statistical significance threshold was set at P < 0.0056 using the Bonferroni-correction, while 0.0056 < P < 0.05 was considered suggestive evidence for a causal association. There was a causal association of elevated blood glutamate levels with higher AD risks. The odds ratio (OR) of AD was 1.311 [95% confidence interval (CI), 1.087-1.580; P = 0.004] per one standard deviation increase in genetically predicted glutamate concentrations. There was suggestive evidence in support of a protective effect of blood serotonin on AD (OR = 0.607; 95% CI, 0.396-0.932; P = 0.022). Genetically predicted glycine levels were not associated with the risk of AD (OR = 1.145; 95% CI, 0.939-1.396; P = 0.180). Besides, MR analyses indicated no causal roles of three blood neurotransmitters in PD or ALS. In conclusion, the MR study provided evidence supporting the association of elevated blood glutamate levels with higher AD risks and the association of increased blood serotonin levels with lower AD risks. Triangulating evidence across further study designs is still warranted to elucidate the role of blood neurotransmitters in risks of neurodegenerative diseases.

Obesity and cancer-extracellular matrix, angiogenesis, and adrenergic signaling as unusual suspects linking the two diseases

Obesity is an established risk factor for several human cancers. Given the association between excess body weight and cancer, the increasing rates of obesity worldwide are worrisome. A variety of obesity-related factors has been implicated in cancer initiation, progression, and response to therapy. These factors include circulating nutritional factors, hormones, and cytokines, causing hyperinsulinemia, inflammation, and adipose tissue dysfunction. The impact of these conditions on cancer development and progression has been the focus of extensive literature. In this review, we concentrate on processes that can link obesity and cancer, and which provide a novel perspective: extracellular matrix remodeling, angiogenesis, and adrenergic signaling. We describe molecular mechanisms involved in these processes, which represent putative targets for intervention. Liver, pancreas, and breast cancers were chosen as exemplary disease models. In view of the expanding epidemic of obesity, a better understanding of the tumorigenic process in obese individuals might lead to more effective treatments and preventive measures.

Integrative analysis of metabolite GWAS illuminates the molecular basis of pleiotropy and genetic correlation

Pleiotropy and genetic correlation are widespread features in genome-wide association studies (GWAS), but they are often difficult to interpret at the molecular level. Here, we perform GWAS of 16 metabolites clustered at the intersection of amino acid catabolism, glycolysis, and ketone body metabolism in a subset of UK Biobank. We utilize the well-documented biochemistry jointly impacting these metabolites to analyze pleiotropic effects in the context of their pathways. Among the 213 lead GWAS hits, we find a strong enrichment for genes encoding pathway-relevant enzymes and transporters. We demonstrate that the effect directions of variants acting on biology between metabolite pairs often contrast with those of upstream or downstream variants as well as the polygenic background. Thus, we find that these outlier variants often reflect biology local to the traits. Finally, we explore the implications for interpreting disease GWAS, underscoring the potential of unifying biochemistry with dense metabolomics data to understand the molecular basis of pleiotropy in complex traits and diseases.

L-carnitine, a friend or foe for cardiovascular disease? A Mendelian randomization study

BACKGROUND

L-carnitine is emerging as an item of interest for cardiovascular disease (CVD) prevention and treatment, but controversy exists. To examine the effectiveness and safety of L-carnitine, we assessed how genetically different levels of L-carnitine are associated with CVD risk and its risk factors. Given higher CVD incidence and L-carnitine in men, we also examined sex-specific associations.

METHODS

We used Mendelian randomization to obtain unconfounded estimates. Specifically, we used genetic variants to predict L-carnitine, and obtained their associations with coronary artery disease (CAD), ischemic stroke, heart failure, and atrial fibrillation, as well as CVD risk factors (type 2 diabetes, glucose, HbA1c, insulin, lipid profile, blood pressure and body mass index) in large consortia and established cohorts, as well as sex-specific association in the UK Biobank. We obtained the Wald estimates (genetic association with CVD and its risk factors divided by the genetic association with L-carnitine) and combined them using inverse variance weighting. In sensitivity analysis, we used different analysis methods robust to pleiotropy and replicated using an L-carnitine isoform, acetyl-carnitine.

RESULTS

Genetically predicted L-carnitine was nominally associated with higher risk of CAD overall (OR 1.07 per standard deviation (SD) increase in L-carnitine, 95% CI 1.02 to 1.11) and in men (OR 1.09, 95% CI 1.02 to 1.16) but had a null association in women (OR 1.00, 95% CI 0.92 to 1.09). These associations were also robust to different methods and evident for acetyl-carnitine.

CONCLUSIONS

Our findings do not support a beneficial association of L-carnitine with CVD and its risk factors but suggest potential harm. L-carnitine may also exert a sex-specific role in CAD. Consideration of the possible sex disparity and exploration of the underlying pathways would be worthwhile.

Insulin Response to Oral Glucose and Cardiometabolic Disease: A Mendelian Randomization Study to Assess Potential Causality

Mendelian randomization (MR) suggests that postprandial hyperinsulinemia (unadjusted for plasma glucose) increases BMI, but its impact on cardiometabolic disease, a leading cause for mortality and morbidity in people with obesity, is not established. Fat distribution i.e., increased centripetal and/or reduced femoro-gluteal adiposity, is causally associated with and better predicts cardiometabolic disease than BMI. We therefore undertook bidirectional MR to assess the effect of corrected insulin response (CIR) (insulin 30 min after a glucose challenge adjusted for plasma glucose) on BMI, waist-to-hip ratio (WHR), leg fat, type 2 diabetes (T2D), triglyceride (TG), HDL, liver fat, hypertension (HTN), and coronary artery disease (CAD) in people of European descent. Inverse variance-weighted MR suggests a potential causal association between increased CIR and increased BMI (b = 0.048 ± 0.02, P = 0.03), increased leg fat (b = 0.029 ± 0.012, P = 0.01), reduced T2D (b = -0.73 ± 0.15, P = 6 × 10-7, odds ratio [OR] 0.48 [95% CI 0.36-0.64]), reduced TG (b = -0.07 ± 0.02, P = 0.003), and increased HDL (b = 0.04 ± 0.01, P = 0.006) with some evidence of horizontal pleiotropy. CIR had neutral effects on WHR (b = 0.009 ± 0.02, P = 0.69), liver fat (b = -0.08 ± 0.04, P = 0.06), HTN (b = -0.001 ± 0.004, P = 0.7, OR 1.00 [95% CI 0.99-1.01]), and CAD (b = -0.002 ± 0.002, P = 0.48, OR 0.99 [95% CI 0.81-1.21]). T2D decreased CIR (b -0.22 ± 0.04, P = 1.3 × 10-7), with no evidence that BMI, TG, HDL, liver fat, HTN, and CAD modulate CIR. In conclusion, we did not find evidence that increased CIR increases cardiometabolic disease. It might increase BMI with favorable fat distribution, reduce T2D, and improve lipids.

The UK Biobank: A Shining Example of Genome-Wide Association Study Science with the Power to Detect the Murky Complications of Real-World Epidemiology

Genome-wide association studies (GWASs) have successfully identified thousands of genetic variants that are reliably associated with human traits. Although GWASs are restricted to certain variant frequencies, they have improved our understanding of the genetic architecture of complex traits and diseases. The UK Biobank (UKBB) has brought substantial analytical opportunity and performance to association studies. The dramatic expansion of many GWAS sample sizes afforded by the inclusion of UKBB data has improved the power of estimation of effect sizes but, critically, has done so in a context where phenotypic depth and precision enable outcome dissection and the application of epidemiological approaches. However, at the same time, the availability of such a large, well-curated, and deeply measured population-based collection has the capacity to increase our exposure to the many complications and inferential complexities associated with GWASs and other analyses. In this review, we discuss the impact that UKBB has had in the GWAS era, some of the opportunities that it brings, and exemplar challenges that illustrate the reality of using data from this world-leading resource.

Depression increased risk of coronary heart disease: A meta-analysis of prospective cohort studies

Background

Depression, as an independent risk factor, can lead to a substantially increased risk of coronary heart disease (CHD). The overall body of evidence involving depression and CHD is not consistent. Therefore, we performed an update meta-analysis to evaluate the association between depression and the risk of patients with CHD.

Methods

Studies were identified through a comprehensive literature search of the PubMed, Embase, and the Cochrane Library database from its inception to 28 September 2021 for titles/abstracts with restricted to English language articles. The literature was screened according to the inclusion and exclusion criteria. Along with data extraction, we evaluated the quality of eligible studies using the Newcastle-Ottawa Scale (NOS). The primary outcome was fatal or non-fatal CHD. We calculated relative risk (RR) with 95% confidence intervals (CIs) using a random-effects models. The protocol was registered in the PROSPERO registration (registration number CRD42021271259).

Results

From 9,151 records, we included 26 prospective cohort studies published from 1998 to 2018, consisting of 402,597 patients. Either in depression-exposured group or non-depression-exposured group, the mean age of all participants ranged from 18 to 99 years. Moreover, the NOS scores of these studies are eventually indicated that the quality of these eligible studies was reliable. In general, the pooled results showed that patients with depression had a higher risk of CHD compared to patients without depression (RR = 1.21, 95% CI: 1.14–1.29). Additionally, the funnel plot appeared to be asymmetry, indicating there existing publication bias for the pooled results between depression and CHD. A sensitivity analysis was used to assess the stability of the relationship between depression and CHD that indicating the results robust (RR = 1.15, 95% CI: 1.09–1.21).

Conclusion

Depression may increase risk of CHD. Future studies on the share pathogenic mechanisms of both depression and CHD may develop novel therapies.

Multiancestry exome sequencing reveals INHBE mutations associated with favorable fat distribution and protection from diabetes

Body fat distribution is a major, heritable risk factor for cardiometabolic disease, independent of overall adiposity. Using exome-sequencing in 618,375 individuals (including 160,058 non-Europeans) from the UK, Sweden and Mexico, we identify 16 genes associated with fat distribution at exome-wide significance. We show 6-fold larger effect for fat-distribution associated rare coding variants compared with fine-mapped common alleles, enrichment for genes expressed in adipose tissue and causal genes for partial lipodystrophies, and evidence of sex-dimorphism. We describe an association with favorable fat distribution (p = 1.8 × 10^-09), favorable metabolic profile and protection from type 2 diabetes (~28% lower odds; p = 0.004) for heterozygous protein-truncating mutations in INHBE, which encodes a circulating growth factor of the activin family, highly and specifically expressed in hepatocytes. Our results suggest that inhibin βE is a liver-expressed negative regulator of adipose storage whose blockade may be beneficial in fat distribution-associated metabolic disease.

Transverse endoplasmic reticulum expansion in hereditary spastic paraplegia corticospinal axons

Hereditary spastic paraplegias (HSPs) comprise a large group of inherited neurologic disorders affecting the longest corticospinal axons (SPG1-86 plus others), with shared manifestations of lower extremity spasticity and gait impairment. Common autosomal dominant HSPs are caused by mutations in genes encoding the microtubule-severing ATPase spastin (SPAST; SPG4), the membrane-bound GTPase atlastin-1 (ATL1; SPG3A) and the reticulon-like, microtubule-binding protein REEP1 (REEP1; SPG31). These proteins bind one another and function in shaping the tubular endoplasmic reticulum (ER) network. Typically, mouse models of HSPs have mild, later onset phenotypes, possibly reflecting far shorter lengths of their corticospinal axons relative to humans. Here, we have generated a robust, double mutant mouse model of HSP in which atlastin-1 is genetically modified with a K80A knock-in (KI) missense change that abolishes its GTPase activity, whereas its binding partner Reep1 is knocked out. Atl1KI/KI/Reep1-/- mice exhibit early onset and rapidly progressive declines in several motor function tests. Also, ER in mutant corticospinal axons dramatically expands transversely and periodically in a mutation dosage-dependent manner to create a ladder-like appearance, on the basis of reconstructions of focused ion beam-scanning electron microscopy datasets using machine learning-based auto-segmentation. In lockstep with changes in ER morphology, axonal mitochondria are fragmented and proportions of hypophosphorylated neurofilament H and M subunits are dramatically increased in Atl1KI/KI/Reep1-/- spinal cord. Co-occurrence of these findings links ER morphology changes to alterations in mitochondrial morphology and cytoskeletal organization. Atl1KI/KI/Reep1-/- mice represent an early onset rodent HSP model with robust behavioral and cellular readouts for testing novel therapies.

Whole Genome Association Study of the Plasma Metabolome Identifies Metabolites Linked to Cardiometabolic Disease in Black Individuals

Integrating genetic information with metabolomics has provided new insights into genes affecting human metabolism. However, gene-metabolite integration has been primarily studied in individuals of European Ancestry, limiting the opportunity to leverage genomic diversity for discovery. In addition, these analyses have principally involved known metabolites, with the majority of the profiled peaks left unannotated. Here, we perform a whole genome association study of 2,291 metabolite peaks (known and unknown features) in 2,466 Black individuals from the Jackson Heart Study. We identify 519 locus-metabolite associations for 427 metabolite peaks and validate our findings in two multi-ethnic cohorts. A significant proportion of these associations are in ancestry specific alleles including findings in APOE, TTR and CD36. We leverage tandem mass spectrometry to annotate unknown metabolites, providing new insight into hereditary diseases including transthyretin amyloidosis and sickle cell disease. Our integrative omics approach leverages genomic diversity to provide novel insights into diverse cardiometabolic diseases.

Sex Differences in Adiposity and Cardiovascular Diseases

Body fat distribution is a well-established predictor of adverse medical outcomes, independent of overall adiposity. Studying body fat distribution sheds insights into the causes of obesity and provides valuable information about the development of various comorbidities. Compared to total adiposity, body fat distribution is more closely associated with risks of cardiovascular diseases. The present review specifically focuses on the sexual dimorphism in body fat distribution, the biological clues, as well as the genetic traits that are distinct from overall obesity. Understanding the sex determinations on body fat distribution and adiposity will aid in the improvement of the prevention and treatment of cardiovascular diseases (CVD).

The impact of health status, diet and lifestyle on non-alcoholic fatty liver disease: Narrative review

Non-alcoholic fatty liver disease (NAFLD) is defined as the abnormal accumulation of triglycerides in the liver. NAFLD has a global prevalence of almost 30%, while incidence is rising with increasing levels of obesity, type 2 diabetes mellitus (T2DM) and metabolic syndrome. Nutrition plays a significant role in both the prevention and treatment of NAFLD. Therefore, the aim of this literature review is to explore the associations between dietary, lifestyle and other risk factors and the risk for developing NAFLD. Dietary patterns, lifestyle behaviours, comorbidities, or a combination of any may contribute to either the progression or prevention of NAFLD. Having diabetes, hypertension, or having obesity might increase the progression of NAFLD if not well treated and controlled. Diet influences the progression of NAFLD; following a western diet or simply a high-fat diet may contribute to the worsening of NAFLD and further progression to non-alcoholic steatohepatitis (NASH) and cirrhosis in later stages. On the other hand, the Mediterranean diet is the gold standard for both the treatment and prevention of NAFLD. Social behaviours, such as smoking, caffeine consumption and physical activity also play a role in the pathophysiology of NAFLD. Nutrition contributes significantly to the prevention or treatment of NAFLD, since this disease can be managed by diet and physical activity. However, further studies are still needed for a better understanding of the mechanisms of action. Randomized control trials are also needed to confirm findings in observational studies.

Activating cannabinoid receptor 2 preserves axonal health through GSK-3β/NRF2 axis in adrenoleukodystrophy

Aberrant endocannabinoid signaling accompanies several neurodegenerative disorders, including multiple sclerosis. Here, we report altered endocannabinoid signaling in X-linked adrenoleukodystrophy (X-ALD), a rare neurometabolic demyelinating syndrome caused by malfunction of the peroxisomal ABCD1 transporter, resulting in the accumulation of very long-chain fatty acids (VLCFAs). We found abnormal levels of cannabinoid receptor 2 (CB2r) and related endocannabinoid enzymes in the brain and peripheral blood mononuclear cells (PBMCs) of X-ALD patients and in the spinal cord of a murine model of X-ALD. Preclinical treatment with a selective agonist of CB2r (JWH133) halted axonal degeneration and associated locomotor deficits, along with normalization of microgliosis. Moreover, the drug improved the main metabolic disturbances underlying this model, particularly in redox and lipid homeostatic pathways, including increased lipid droplets in motor neurons, through the modulation of the GSK-3β/NRF2 axis. JWH133 inhibited Reactive Oxygen Species elicited by excess VLCFAs in primary microglial cultures of Abcd1-null mice. Furthermore, we uncovered intertwined redox and CB2r signaling in the murine spinal cords and in patient PBMC samples obtained from a phase II clinical trial with antioxidants (NCT01495260). These findings highlight CB2r signaling as a potential therapeutic target for X-ALD and perhaps other neurodegenerative disorders that present with dysregulated redox and lipid homeostasis.

A minority of somatically mutated genes in pre-existing fatty liver disease have prognostic importance in the development of NAFLD

BACKGROUND

Understanding the genetics of liver disease has the potential to facilitate clinical risk stratification. We recently identified acquired somatic mutations in six genes and one lncRNA in pre-existing fatty liver disease. We hypothesised that germline variation in these genes might be associated with the risk of developing steatosis and contribute to the prediction of disease severity.

METHODS

Genome-wide association study (GWAS) summary statistics were extracted from seven studies (>1.7 million participants) for variants near ACVR2A, ALB, CIDEB, FOXO1, GPAM, NEAT1 and TNRC6B for: aminotransferases, liver fat, HbA1c, diagnosis of NAFLD, ARLD and cirrhosis. Findings were replicated using GWAS data from multiple independent cohorts. A phenome-wide association study was performed to examine for related metabolic traits, using both common and rare variants, including gene-burden testing.

RESULTS

There was no evidence of association between rare germline variants or SNPs near five genes (ACVR2A, ALB, CIDEB, FOXO1 and TNRC6B) and risk or severity of liver disease. Variants in GPAM (proxies for p.Ile43Val) were associated with liver fat (p = 3.6 × 10-13 ), ALT (p = 2.8 × 10-39 ) and serum lipid concentrations. Variants in NEAT1 demonstrated borderline significant associations with ALT (p = 1.9 × 10-11 ) and HbA1c, but not with liver fat, as well as influencing waist-to-hip ratio, adjusted for BMI.

CONCLUSIONS

Despite the acquisition of somatic mutations at these loci during progressive fatty liver disease, we did not find associations between germline variation and markers of liver disease, except in GPAM. In the future, larger sample sizes may identify associations. Currently, germline polygenic risk scores will not capture data from genes affected by somatic mutations.

TM4SF5-Mediated Regulation of Hepatocyte Transporters during Metabolic Liver Diseases

Nonalcoholic fatty liver disease (NAFLD) is found in up to 30% of the world’s population and can lead to hepatocellular carcinoma (HCC), which has a poor 5-year relative survival rate of less than 40%. Clinical therapeutic strategies are not very successful. The co-occurrence of metabolic disorders and inflammatory environments during the development of steatohepatitis thus needs to be more specifically diagnosed and treated to prevent fatal HCC development. To improve diagnostic and therapeutic strategies, the identification of molecules and/or pathways responsible for the initiation and progression of chronic liver disease has been explored in many studies, but further study is still required. Transmembrane 4 L six family member 5 (TM4SF5) has been observed to play roles in the regulation of metabolic functions and activities in hepatocytes using in vitro cell and in vivo animal models without or with TM4SF5 expression in addition to clinical liver tissue samples. TM4SF5 is present on the membranes of different organelles or vesicles and cooperates with transporters for fatty acids, amino acids, and monocarbohydrates, thus regulating nutrient uptake into hepatocytes and metabolism and leading to phenotypes of chronic liver diseases. In addition, TM4SF5 can remodel the immune environment by interacting with immune cells during TM4SF5-mediated chronic liver diseases. Because TM4SF5 may act as an NAFLD biomarker, this review summarizes crosstalk between TM4SF5 and nutrient transporters in hepatocytes, which is related to chronic liver diseases.

Rare loss of function variants in the hepatokine gene INHBE protect from abdominal obesity

Identifying genetic variants associated with lower waist-to-hip ratio can reveal new therapeutic targets for abdominal obesity. We use exome sequences from 362,679 individuals to identify genes associated with waist-to-hip ratio adjusted for BMI (WHRadjBMI), a surrogate for abdominal fat that is causally linked to type 2 diabetes and coronary heart disease. Predicted loss of function (pLOF) variants in INHBE associate with lower WHRadjBMI and this association replicates in data from AMP-T2D-GENES. INHBE encodes a secreted protein, the hepatokine activin E. In vitro characterization of the most common INHBE pLOF variant in our study, indicates an in-frame deletion resulting in a 90% reduction in secreted protein levels. We detect associations with lower WHRadjBMI for variants in ACVR1C, encoding an activin receptor, further highlighting the involvement of activins in regulating fat distribution. These findings highlight activin E as a potential therapeutic target for abdominal obesity, a phenotype linked to cardiometabolic disease.

The Relationship of Maternal Gestational Mass Spectrometry-Derived Metabolites with Offspring Congenital Heart Disease: Results from Multivariable and Mendelian Randomization Analyses

Background: It is plausible that maternal pregnancy metabolism influences the risk of offspring congenital heart disease (CHD). We sought to explore this through a systematic approach using different methods and data. Methods: We undertook multivariable logistic regression of the odds of CHD for 923 mass spectrometry (MS)-derived metabolites in a sub-sample of a UK birth cohort (Born in Bradford (BiB); N = 2605, 46 CHD cases). We considered metabolites reaching a p-value threshold <0.05 to be suggestively associated with CHD. We sought validation of our findings, by repeating the multivariable regression analysis within the BiB cohort for any suggestively associated metabolite that was measured by nuclear magnetic resonance (NMR) or clinical chemistry (N = 7296, 87 CHD cases), and by using genetic risk scores (GRS: weighted genetic risk scores of single nucleotide polymorphisms (SNPs) that were associated with any suggestive metabolite) in Mendelian randomization (MR) analyses. The MR analyses were performed in BiB and two additional European birth cohorts (N = 38,662, 319 CHD cases). Results: In the main multivariable analyses, we identified 44 metabolites suggestively associated with CHD, including those from the following super pathways: amino acids, lipids, co-factors and vitamins, xenobiotics, nucleotides, energy, and several unknown molecules. Of these 44, isoleucine and leucine were available in the larger BiB cohort (NMR), and for these the results were validated. The MR analyses were possible for 27/44 metabolites and for 11 there was consistency with the multivariable regression results. Conclusions: In summary, we have used complimentary data sources and statistical techniques to construct layers of evidence. We found that pregnancy amino acid metabolism, androgenic steroid lipids, and levels of succinylcarnitine could be important contributing factors for CHD.

HOTAIR interacts with PRC2 complex regulating the regional preadipocyte transcriptome and human fat distribution

Mechanisms governing regional human adipose tissue (AT) development remain undefined. Here, we show that the long non-coding RNA HOTAIR (HOX transcript antisense RNA) is exclusively expressed in gluteofemoral AT, where it is essential for adipocyte development. We find that HOTAIR interacts with polycomb repressive complex 2 (PRC2) and we identify core HOTAIR-PRC2 target genes involved in adipocyte lineage determination. Repression of target genes coincides with PRC2 promoter occupancy and H3K27 trimethylation. HOTAIR is also involved in modifying the gluteal adipocyte transcriptome through alternative splicing. Gluteal-specific expression of HOTAIR is maintained by defined regions of open chromatin across the HOTAIR promoter. HOTAIR expression levels can be modified by hormonal (estrogen, glucocorticoids) and genetic variation (rs1443512 is a HOTAIR eQTL associated with reduced gynoid fat mass). These data identify HOTAIR as a dynamic regulator of the gluteal adipocyte transcriptome and epigenome with functional importance for human regional AT development.

Association of Physical Activity With Bioactive Lipids and Cardiovascular Events

BACKGROUND

To clarify the mechanisms underlying physical activity (PA)-related cardioprotection, we examined the association of PA with plasma bioactive lipids (BALs) and cardiovascular disease (CVD) events. We additionally performed genome-wide associations.

METHODS

PA-bioactive lipid associations were examined in VITAL (VITamin D and OmegA-3 TriaL)-clinical translational science center (REGISTRATION: URL: https://www.

CLINICALTRIALS

gov; Unique identifier: NCT01169259; N=1032) and validated in JUPITER (Justification for the Use of statins in Prevention: an Intervention Trial Evaluating Rosuvastatin)-NC (NCT00239681; N=589), using linear models adjusted for age, sex, race, low-density lipoprotein-cholesterol, total-C, and smoking. Significant BALs were carried over to examine associations with incident CVD in 2 nested CVD case-control studies: VITAL-CVD (741 case-control pairs) and JUPITER-CVD (415 case-control pairs; validation).

RESULTS

We detected 145 PA-bioactive lipid validated associations (false discovery rate <0.1). Annotations were found for 6 of these BALs: 12,13-diHOME, 9,10-diHOME, lysoPC(15:0), oxymorphone-3b-D-glucuronide, cortisone, and oleoyl-glycerol. Genetic analysis within JUPITER-NC showed associations of 32 PA-related BALs with 22 single-nucleotide polymorphisms. From PA-related BALs, 12 are associated with CVD.

CONCLUSIONS

We identified a PA-related bioactive lipidome profile out of which 12 BALs also had opposite associations with incident CVD events.

Approach to Patients with Obesity and Other Cardiovascular Risk Factors in Primary Care Using the Delphi Methodology

BACKGROUND

Implementing preventive strategies for patients with obesity would improve the future burden of cardiovascular diseases. The objective was to present the opinions of experts on the approach to treating patients with obesity and other cardiovascular risk factors from a primary care perspective in Spain; Methods: Using the Delphi technique, a 42-question questionnaire was developed based on results from the scientific literature, and sent to 42 experts in primary care. Two rounds of participation were held; Results: There is a close relationship between obesity and cardiovascular risk factors among primary care physicians. It is necessary to use a checklist in primary care that includes metabolic parameters such as body mass index, waist circumference, and levels of C-reactive protein and ferritin. It is also useful to combine pharmacological treatment, such as liraglutide, with a change in lifestyle to achieve therapeutic goals in this population; Conclusions: There is a high level of awareness among experts in Spain regarding obesity and other cardiovascular risk factors, and the need to address this pathology comprehensively. The need to incorporate specific tools in primary care consultations that allow for better assessment and follow-up of these patients, such as cuffs adapted to arm size or imaging techniques to assess body fat, is evident. Teleconsultation is imposed as a helpful tool for follow-up. Experts recommend that patients with obesity and associated comorbidities modify their lifestyle, incorporate a Mediterranean diet, and administer liraglutide.

Membrane shaping proteins, lipids, and cytoskeleton: Recipe for nascent lipid droplet formation

Lipid droplets (LDs) are ubiquitous, neutral lipidorganelles that act as hubs of metabolic processes. LDs are structurally unique with a hydrophobic core that mainly consists of neutral lipids, sterol esters, and triglycerides, enclosed within a phospholipid monolayer. Nascent LD formation begins with the accumulation of neutral lipids in the endoplasmic reticulum (ER) bilayer. The ER membrane proteins such as seipin, LDAF1, FIT, and MCTPs are reported to play an important role in the formation of nascent LDs. As the LDs grow, they unmix from the highly charged ER membrane to form mature LDs. LD biogenesis is an exciting, emerging research area, and herein, we discuss the recent progress in our understanding of the formation of eukaryotic nascent LDs. We focus on the role of ER membrane shaping proteins such as reticulons and reticulon-like proteins, membrane lipids, and cytoskeleton proteins such as septin in the formation of nascent LDs.