Lac-Phe mediates the effects of metformin on food intake and body weight.

Metformin is a widely prescribed anti-diabetic medicine that also reduces body weight. There is ongoing debate about the mechanisms that mediate metformin's effects on energy balance. Here, we show that metformin is a powerful pharmacological inducer of the anorexigenic metabolite N-lactoyl-phenylalanine (Lac-Phe) in cells, in mice and two independent human cohorts. Metformin drives Lac-Phe biosynthesis through the inhibition of complex I, increased glycolytic flux and intracellular lactate mass action. Intestinal epithelial CNDP2+ cells, not macrophages, are the principal in vivo source of basal and metformin-inducible Lac-Phe. Genetic ablation of Lac-Phe biosynthesis in male mice renders animals resistant to the effects of metformin on food intake and body weight. Lastly, mediation analyses support a role for Lac-Phe as a downstream effector of metformin's effects on body mass index in participants of a large population-based observational cohort, the Multi-Ethnic Study of Atherosclerosis. Together, these data establish Lac-Phe as a critical mediator of the body weight-lowering effects of metformin.

Lac-Phe mediates the anti-obesity effect of metformin.

Metformin is a widely prescribed anti-diabetic medicine that also reduces body weight. The mechanisms that mediate metformin's effects on energy balance remain incompletely defined. Here we show that metformin is a powerful pharmacological inducer of the anorexigenic metabolite Lac-Phe in mice as well as in two independent human cohorts. In cell culture, metformin drives Lac-Phe biosynthesis via inhibition of complex I, increased glycolytic flux, and intracellular lactate mass action. Other biguanides and structurally distinct inhibitors of oxidative phosphorylation also increase Lac-Phe levels in vitro. Genetic ablation of CNDP2, the principal biosynthetic enzyme for Lac-Phe, in mice renders animals resistant to metformin's anorexigenic and anti-obesity effects. Mediation analyses also support a role for Lac-Phe in metformin's effect on body mass index in humans. These data establish the CNDP2/Lac-Phe pathway as a critical mediator of the effects of metformin on energy balance.

Metabolomic epidemiology offers insights into disease aetiology.

Metabolomic epidemiology is the high-throughput study of the relationship between metabolites and health-related traits. This emerging and rapidly growing field has improved our understanding of disease aetiology and contributed to advances in precision medicine. As the field continues to develop, metabolomic epidemiology could lead to the discovery of diagnostic biomarkers predictive of disease risk, aiding in earlier disease detection and better prognosis. In this Review, we discuss key advances facilitated by the field of metabolomic epidemiology for a range of conditions, including cardiometabolic diseases, cancer, Alzheimer's disease and COVID-19, with a focus on potential clinical utility. Core principles in metabolomic epidemiology, including study design, causal inference methods and multi-omic integration, are briefly discussed. Future directions required for clinical translation of metabolomic epidemiology findings are summarized, emphasizing public health implications. Further work is needed to establish which metabolites reproducibly improve clinical risk prediction in diverse populations and are causally related to disease progression.

The Relationship of Duffy Gene Polymorphism, High Sensitivity C-Reactive Protein, and Long-term Outcomes.

Background: Black adults have higher incidence of all-cause death and worse cardiovascular outcomes when compared to other populations. The Duffy chemokine receptor is not expressed in a large majority of Black adults and the clinical implications of this are unclear. Methods: Here, we investigated the relationship of Duffy receptor status, high-sensitivity C-reactive protein (hs-CRP), and long-term cardiovascular outcomes in Black members of two contemporary, longitudinal cohort studies (the Jackson Heart Study and Multi-Ethnic Study of Atherosclerosis). Data on 4,307 Black participants (2,942 Duffy null and 1,365 Duffy receptor positive, as defined using Single Nucleotide Polymorphism (SNP) rs2814778) were included in this analysis. Results: Duffy null was not independently associated with elevated levels of serum hs-CRP levels once conditioning for known CRP locus alleles in linkage disequilibrium with the Duffy gene. Duffy null status was not found to be independently associated with higher incidence of all-cause mortality or secondary outcomes after adjusting for possible confounders in Black participants. Conclusions: These findings suggest that increased levels of hs-CRP found in Duffy null individuals is due to co-inheritance of CRP alleles known to influence circulating levels hs-CRP and that Duffy null status was not associated with worse adverse outcomes over the follow-up period in this cohort of well-balanced Black participants.

Development and Validation of the DOAC Score: A Novel Bleeding Risk Prediction Tool for Patients With Atrial Fibrillation on Direct-Acting Oral Anticoagulants.

BACKGROUND: Current clinical decision tools for assessing bleeding risk in individuals with atrial fibrillation (AF) have limited performance and were developed for individuals treated with warfarin. This study develops and validates a clinical risk score to personalize estimates of bleeding risk for individuals with atrial fibrillation taking direct-acting oral anticoagulants (DOACs). METHODS: Among individuals taking dabigatran 150 mg twice per day from 44 countries and 951 centers in this secondary analysis of the RE-LY trial (Randomized Evaluation of Long-Term Anticoagulation Therapy), a risk score was developed to determine the comparative risk for bleeding on the basis of covariates derived in a Cox proportional hazards model. The risk prediction model was internally validated with bootstrapping. The model was then further developed in the GARFIELD-AF registry (Global Anticoagulant Registry in the Field-Atrial Fibrillation), with individuals taking dabigatran, edoxaban, rivaroxaban, and apixaban. To determine generalizability in external cohorts and among individuals on different DOACs, the risk prediction model was validated in the COMBINE-AF (A Collaboration Between Multiple Institutions to Better Investigate Non-Vitamin K Antagonist Oral Anticoagulant Use in Atrial Fibrillation) pooled clinical trial cohort and the Quebec Régie de l'Assurance Maladie du Québec and Med-Echo Administrative Databases (RAMQ) administrative database. The primary outcome was major bleeding. The risk score, termed the DOAC Score, was compared with the HAS-BLED score. RESULTS: Of the 5684 patients in RE-LY, 386 (6.8%) experienced a major bleeding event, within a median follow-up of 1.74 years. The prediction model had an optimism-corrected C statistic of 0.73 after internal validation with bootstrapping and was well-calibrated based on visual inspection of calibration plots (goodness-of-fit P=0.57). The DOAC Score assigned points for age, creatinine clearance/glomerular filtration rate, underweight status, stroke/transient ischemic attack/embolism history, diabetes, hypertension, antiplatelet use, nonsteroidal anti-inflammatory use, liver disease, and bleeding history, with each additional point scored associated with a 48.7% (95% CI, 38.9%-59.3%; P<0.001) increase in major bleeding in RE-LY. The score had superior performance to the HAS-BLED score in RE-LY (C statistic, 0.73 versus 0.60; P for difference <0.001) and among 12 296 individuals in GARFIELD-AF (C statistic, 0.71 versus 0.66; P for difference = 0.025). The DOAC Score had stronger predictive performance than the HAS-BLED score in both validation cohorts, including 25 586 individuals in COMBINE-AF (C statistic, 0.67 versus 0.63; P for difference <0.001) and 11 945 individuals in RAMQ (C statistic, 0.65 versus 0.58; P for difference <0.001). CONCLUSIONS: In individuals with atrial fibrillation potentially eligible for DOAC therapy, the DOAC Score can help stratify patients on the basis of expected bleeding risk.

Differences in the Circulating Proteome in Individuals with versus without Sickle Cell Trait.

BACKGROUND: Sickle cell trait affects approximately 8% of Black individuals in the United States, along with many other individuals with ancestry from malaria-endemic regions worldwide. While traditionally considered a benign condition, recent evidence suggests that sickle cell trait is associated with lower eGFR and higher risk of kidney diseases, including kidney failure. The mechanisms underlying these associations remain poorly understood. We used proteomic profiling to gain insight into the pathobiology of sickle cell trait. METHODS: We measured proteomics ( N =1285 proteins assayed by Olink Explore) using baseline plasma samples from 592 Black participants with sickle cell trait and 1:1 age-matched Black participants without sickle cell trait from the prospective Women's Health Initiative cohort. Age-adjusted linear regression was used to assess the association between protein levels and sickle cell trait. RESULTS: In age-adjusted models, 35 proteins were significantly associated with sickle cell trait after correction for multiple testing. Several of the sickle cell trait-protein associations were replicated in Black participants from two independent cohorts (Atherosclerosis Risk in Communities study and Jackson Heart Study) assayed using an orthogonal aptamer-based proteomic platform (SomaScan). Many of the validated sickle cell trait-associated proteins are known biomarkers of kidney function or injury ( e.g. , hepatitis A virus cellular receptor 1 [HAVCR1]/kidney injury molecule-1 [KIM-1], uromodulin [UMOD], ephrins), related to red cell physiology or hemolysis (erythropoietin [EPO], heme oxygenase 1 [HMOX1], and α -hemoglobin stabilizing protein) and/or inflammation (fractalkine, C-C motif chemokine ligand 2/monocyte chemoattractant protein-1 [MCP-1], and urokinase plasminogen activator surface receptor [PLAUR]). A protein risk score constructed from the top sickle cell trait-associated biomarkers was associated with incident kidney failure among those with sickle cell trait during Women's Health Initiative follow-up (odds ratio, 1.32; 95% confidence interval, 1.10 to 1.58). CONCLUSIONS: We identified and replicated the association of sickle cell trait with a number of plasma proteins related to hemolysis, kidney injury, and inflammation.

Protein-metabolite association studies identify novel proteomic determinants of metabolite levels in human plasma.

Although many novel gene-metabolite and gene-protein associations have been identified using high-throughput biochemical profiling, systematic studies that leverage human genetics to illuminate causal relationships between circulating proteins and metabolites are lacking. Here, we performed protein-metabolite association studies in 3,626 plasma samples from three human cohorts. We detected 171,800 significant protein-metabolite pairwise correlations between 1,265 proteins and 365 metabolites, including established relationships in metabolic and signaling pathways such as the protein thyroxine-binding globulin and the metabolite thyroxine, as well as thousands of new findings. In Mendelian randomization (MR) analyses, we identified putative causal protein-to-metabolite associations. We experimentally validated top MR associations in proof-of-concept plasma metabolomics studies in three murine knockout strains of key protein regulators. These analyses identified previously unrecognized associations between bioactive proteins and metabolites in human plasma. We provide publicly available data to be leveraged for studies in human metabolism and disease.

Molecular Biomarkers for Cardiometabolic Disease: Risk Assessment in Young Individuals.

Cardiometabolic diseases, including cardiovascular disease and diabetes, are major causes of morbidity and mortality worldwide. Despite progress in prevention and treatment, recent trends show a stalling in the reduction of cardiovascular disease morbidity and mortality, paralleled by increasing rates of cardiometabolic disease risk factors in young adults, underscoring the importance of risk assessments in this population. This review highlights the evidence for molecular biomarkers for early risk assessment in young individuals. We examine the utility of traditional biomarkers in young individuals and discuss novel, nontraditional biomarkers specific to pathways contributing to early cardiometabolic disease risk. Additionally, we explore emerging omic technologies and analytical approaches that could enhance risk assessment for cardiometabolic disease.

Whole-Genome Sequencing Analysis of Human Metabolome in Multi-Ethnic Populations.

Circulating metabolite levels may reflect the state of the human organism in health and disease, however, the genetic architecture of metabolites is not fully understood. We have performed a whole-genome sequencing association analysis of both common and rare variants in up to 11,840 multi-ethnic participants from five studies with up to 1666 circulating metabolites. We have discovered 1985 novel variant-metabolite associations, and validated 761 locus-metabolite associations reported previously. Seventy-nine novel variant-metabolite associations have been replicated, including three genetic loci located on the X chromosome that have demonstrated its involvement in metabolic regulation. Gene-based analysis have provided further support for seven metabolite-replicated loci pairs and their biologically plausible genes. Among those novel replicated variant-metabolite pairs, follow-up analyses have revealed that 26 metabolites have colocalized with 21 tissues, seven metabolite-disease outcome associations have been putatively causal, and 7 metabolites might be regulated by plasma protein levels. Our results have depicted the genetic contribution to circulating metabolite levels, providing additional insights into understanding human disease.

Plasma proteomic changes in response to exercise training are associated with cardiorespiratory fitness adaptations.

Regular exercise leads to widespread salutary effects, and there is increasing recognition that exercise-stimulated circulating proteins can impart health benefits. Despite this, limited data exist regarding the plasma proteomic changes that occur in response to regular exercise. Here, we perform large-scale plasma proteomic profiling in 654 healthy human study participants before and after a supervised, 20-week endurance exercise training intervention. We identify hundreds of circulating proteins that are modulated, many of which are known to be secreted. We highlight proteins involved in angiogenesis, iron homeostasis, and the extracellular matrix, many of which are novel, including training-induced increases in fibroblast activation protein (FAP), a membrane-bound and circulating protein relevant in body-composition homeostasis. We relate protein changes to training-induced maximal oxygen uptake adaptations and validate our top findings in an external exercise cohort. Furthermore, we show that FAP is positively associated with survival in 3 separate, population-based cohorts.

CYP4F2 is a human-specific determinant of circulating N-acyl amino acid levels.

N-acyl amino acids are a large family of circulating lipid metabolites that modulate energy expenditure and fat mass in rodents. However, little is known about the regulation and potential cardiometabolic functions of N-acyl amino acids in humans. Here, we analyze the cardiometabolic phenotype associations and genomic associations of four plasma N-acyl amino acids (N-oleoyl-leucine, N-oleoyl-phenylalanine, N-oleoyl-serine, and N-oleoyl-glycine) in 2351 individuals from the Jackson Heart Study. We find that plasma levels of specific N-acyl amino acids are associated with cardiometabolic disease endpoints independent of free amino acid plasma levels and in patterns according to the amino acid head group. By integrating whole genome sequencing data with N-acyl amino acid levels, we identify that the genetic determinants of N-acyl amino acid levels also cluster according to the amino acid head group. Furthermore, we identify the CYP4F2 locus as a genetic determinant of plasma N-oleoyl-leucine and N-oleoyl-phenylalanine levels in human plasma. In experimental studies, we demonstrate that CYP4F2-mediated hydroxylation of N-oleoyl-leucine and N-oleoyl-phenylalanine results in metabolic diversification and production of many previously unknown lipid metabolites with varying characteristics of the fatty acid tail group, including several that structurally resemble fatty acid hydroxy fatty acids. These studies provide a structural framework for understanding the regulation and disease associations of N-acyl amino acids in humans and identify that the diversity of this lipid signaling family can be significantly expanded through CYP4F-mediated ω-hydroxylation.

An atlas of genetic scores to predict multi-omic traits.

The use of omic modalities to dissect the molecular underpinnings of common diseases and traits is becoming increasingly common. But multi-omic traits can be genetically predicted, which enables highly cost-effective and powerful analyses for studies that do not have multi-omics1. Here we examine a large cohort (the INTERVAL study2; n = 50,000 participants) with extensive multi-omic data for plasma proteomics (SomaScan, n = 3,175; Olink, n = 4,822), plasma metabolomics (Metabolon HD4, n = 8,153), serum metabolomics (Nightingale, n = 37,359) and whole-blood Illumina RNA sequencing (n = 4,136), and use machine learning to train genetic scores for 17,227 molecular traits, including 10,521 that reach Bonferroni-adjusted significance. We evaluate the performance of genetic scores through external validation across cohorts of individuals of European, Asian and African American ancestries. In addition, we show the utility of these multi-omic genetic scores by quantifying the genetic control of biological pathways and by generating a synthetic multi-omic dataset of the UK Biobank3 to identify disease associations using a phenome-wide scan. We highlight a series of biological insights with regard to genetic mechanisms in metabolism and canonical pathway associations with disease; for example, JAK-STAT signalling and coronary atherosclerosis. Finally, we develop a portal ( https://www.omicspred.org/ ) to facilitate public access to all genetic scores and validation results, as well as to serve as a platform for future extensions and enhancements of multi-omic genetic scores.

CYP4F2 is a human-specific determinant of circulating N-acyl amino acid levels.

N-acyl amino acids are a large family of circulating lipid metabolites that modulate energy expenditure and fat mass in rodents. However, little is known about the regulation and potential cardiometabolic functions of N-acyl amino acids in humans. Here, we analyze the cardiometabolic phenotype associations and genetic regulation of four plasma N-fatty acyl amino acids (N-oleoyl-leucine, N-oleoyl-phenylalanine, N-oleoyl-serine, and N-oleoyl-glycine) in 2,351 individuals from the Jackson Heart Study. N-oleoyl-leucine and N-oleoyl-phenylalanine were positively associated with traits related to energy balance, including body mass index, waist circumference, and subcutaneous adipose tissue. In addition, we identify the CYP4F2 locus as a human-specific genetic determinant of plasma N-oleoyl-leucine and N-oleoyl-phenylalanine levels. In vitro, CYP4F2-mediated hydroxylation of N-oleoyl-leucine and N-oleoyl-phenylalanine results in metabolic diversification and production of many previously unknown lipid metabolites with varying characteristics of the fatty acid tail group, including several that structurally resemble fatty acid hydroxy fatty acids (FAHFAs). By contrast, FAAH-regulated N-oleoyl-glycine and N-oleoyl-serine were inversely associated with traits related to glucose and lipid homeostasis. These data uncover a human-specific enzymatic node for the metabolism of a subset of N-fatty acyl amino acids and establish a framework for understanding the cardiometabolic roles of individual N-fatty acyl amino acids in humans.

Nasal biomarkers of immune function differ based on smoking and respiratory disease status.

Respiratory biomarkers have the potential to identify airway injury by revealing inflammatory processes within the respiratory tract. Currently, there are no respiratory biomarkers suitable for clinical use to identify patients that warrant further diagnostic work-up, counseling, and treatment for toxic inhalant exposures or chronic airway disease. Using a novel, noninvasive method of sampling the nasal epithelial lining fluid, we aimed to investigate if nasal biomarker patterns could distinguish healthy nonsmoking adults from active smokers and those with chronic upper and lower airway disease in this exploratory study. We compared 28 immune mediators from healthy nonsmoking adults (n = 32), former smokers with COPD (n = 22), chronic rhinosinusitis (CRS) (n = 22), and smoking adults without airway disease (n = 13). Using ANOVA, multinomial logistic regressions, and weighted gene co-expression network analysis (WGCNA), we determined associations between immune mediators and each cohort. Six mediators (IL-7, IL-10, IL-13, IL-12p70, IL-15, and MCP-1) were lower among disease groups compared to healthy controls. Participants with lower levels of IL-10, IL-12p70, IL-13, and MCP-1 in the nasal fluid had a higher odds of being in the COPD or CRS group. The cluster analysis identified groups of mediators that correlated with disease status. Specifically, the cluster of IL-10, IL-12p70, and IL-13, was positively correlated with healthy and negatively correlated with COPD groups, and two clusters were correlated with active smoking. In this exploratory study, we preliminarily identified groups of nasal mucosal mediators that differed by airway disease and smoking status. Future prospective, age-matched studies that control for medication use are needed to validate these patterns and determine if nasosorption has diagnostic utility for upper and lower airway disease or injury.

Protein Markers of Diabetes Discovered in an African American Cohort.

Proteomics has been used to study type 2 diabetes, but the majority of available data are from White participants. Here, we extend prior work by analyzing a large cohort of self-identified African Americans in the Jackson Heart Study (n = 1,313). We found 325 proteins associated with incident diabetes after adjusting for age, sex, and sample batch (false discovery rate q < 0.05) measured using a single-stranded DNA aptamer affinity-based method on fasting plasma samples. A subset was independent of established markers of diabetes development pathways, such as adiposity, glycemia, and/or insulin resistance, suggesting potential novel biological processes associated with disease development. Thirty-six associations remained significant after additional adjustments for BMI, fasting plasma glucose, cholesterol levels, hypertension, statin use, and renal function. Twelve associations, including the top associations of complement factor H, formimidoyltransferase cyclodeaminase, serine/threonine-protein kinase 17B, and high-mobility group protein B1, were replicated in a meta-analysis of two self-identified White cohorts-the Framingham Heart Study and the Malmö Diet and Cancer Study-supporting the generalizability of these biomarkers. A selection of these diabetes-associated proteins also improved risk prediction. Thus, we uncovered both novel and broadly generalizable associations by studying a diverse population, providing a more complete understanding of the diabetes-associated proteome.

Congenital Long QT Syndrome: A Review of Genetic and Pathophysiologic Etiologies, Phenotypic Subtypes, and Clinical Management.

Congenital Long QT Syndrome (CLQTS) is the most common inherited arrhythmia. The QT interval, which marks the duration of ventricular depolarization and repolarization in the myocardium, can be prolonged due to mutations in genes coding for the ion channel proteins that govern the cardiac action potential. The lengthening of the QT interval can lead to a wide range of clinical symptoms, including seizures, torsades de pointes, and fatal arrhythmias. There is a growing body of evidence that has revealed the genetic mutations responsible for the pathophysiology of CLQTS, and this has led to hypotheses regarding unique triggers and clinical features associated with specific gene mutations. Epidemiologic evidence has revealed a 1-year mortality rate of approximately 20% in untreated CLQTS patients, and a <1% of 1-year mortality rate in treated patients, underscoring the importance of timely diagnosis and effective clinical management. There are many phenotypic syndromes that constitute CLQTS, including but not limited to, Jervell and Lange-Nielsen syndrome, Romano and Ward syndrome, Andersen-Tawil syndrome, and Timothy syndrome. In this review, we aim to (1) summarize the genetic, epidemiologic, and pathophysiological basis of CLQTS and (2) outline the unique features of the phenotypic subtypes and their clinical management.

Protein biomarkers of cardiac remodeling and inflammation associated with HFpEF and incident events.

There is increasing evidence that HFpEF is a heterogeneous clinical entity and distinct molecular pathways may contribute to pathophysiology. Leveraging unbiased proteomics to identify novel biomarkers, this study seeks to understand the underlying molecular mechanisms of HFpEF. The discovery cohort consisted of HFpEF cases and non-HF controls from the CATHGEN study (N = 176); the validation cohort consisted of participants from the TECOS trial of patients with diabetes (N = 109). Proteins associated with HFpEF were included in a LASSO model to create a discriminative multi-protein model and assessed in the validation cohort. Survival models and meta-analysis were used to test the association of proteins with incident clinical outcomes, including HF hospitalization, mortality and HFpEF hospitalization in CATHGEN, TECOS and the Jackson Heart Study. In the derivation set, 190 proteins were associated with HFpEF in univariate analysis, of which 65 remained significant in the multivariate model. Twenty (30.8%) of these proteins validated in TECOS, including LCN2, U-PAR, IL-1ra, KIM1, CSTB and Gal-9 (OR 1.93-2.77, p < 0.01). LASSO regression yielded a 13-protein model which, when added to a clinical model inclusive of NT-proBNP, improved the AUC from 0.82 to 0.92 (p = 1.5 × 10-4). Five proteins were associated with incident HF hospitalization, four with HFpEF hospitalization and eleven with mortality (p < 0.05). We identified and validated multiple circulating biomarkers associated with HFpEF as well as HF outcomes. These biomarkers added incremental discriminative capabilities beyond clinical factors and NT-proBNP.

Proteomic profiling platforms head to head: Leveraging genetics and clinical traits to compare aptamer- and antibody-based methods.

High-throughput proteomic profiling using antibody or aptamer-based affinity reagents is used increasingly in human studies. However, direct analyses to address the relative strengths and weaknesses of these platforms are lacking. We assessed findings from the SomaScan1.3K (N = 1301 reagents), the SomaScan5K platform (N = 4979 reagents), and the Olink Explore (N = 1472 reagents) profiling techniques in 568 adults from the Jackson Heart Study and 219 participants in the HERITAGE Family Study across four performance domains: precision, accuracy, analytic breadth, and phenotypic associations leveraging detailed clinical phenotyping and genetic data. Across these studies, we show evidence supporting more reliable protein target specificity and a higher number of phenotypic associations for the Olink platform, while the Soma platforms benefit from greater measurement precision and analytic breadth across the proteome.