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.

Transcriptional Dysregulation Underlies Both Monogenic Arrhythmia Syndrome and Common Modifiers of Cardiac Repolarization.

BACKGROUND: Brugada syndrome (BrS) is an inherited arrhythmia syndrome caused by loss-of-function variants in the cardiac sodium channel gene SCN5A (sodium voltage-gated channel alpha subunit 5) in ≈20% of subjects. We identified a family with 4 individuals diagnosed with BrS harboring the rare G145R missense variant in the cardiac transcription factor TBX5 (T-box transcription factor 5) and no SCN5A variant. METHODS: We generated induced pluripotent stem cells (iPSCs) from 2 members of a family carrying TBX5-G145R and diagnosed with Brugada syndrome. After differentiation to iPSC-derived cardiomyocytes (iPSC-CMs), electrophysiologic characteristics were assessed by voltage- and current-clamp experiments (n=9 to 21 cells per group) and transcriptional differences by RNA sequencing (n=3 samples per group), and compared with iPSC-CMs in which G145R was corrected by CRISPR/Cas9 approaches. The role of platelet-derived growth factor (PDGF)/phosphoinositide 3-kinase (PI3K) pathway was elucidated by small molecule perturbation. The rate-corrected QT (QTc) interval association with serum PDGF was tested in the Framingham Heart Study cohort (n=1893 individuals). RESULTS: TBX5-G145R reduced transcriptional activity and caused multiple electrophysiologic abnormalities, including decreased peak and enhanced "late" cardiac sodium current (INa), which were entirely corrected by editing G145R to wild-type. Transcriptional profiling and functional assays in genome-unedited and -edited iPSC-CMs showed direct SCN5A down-regulation caused decreased peak INa, and that reduced PDGF receptor (PDGFRA [platelet-derived growth factor receptor α]) expression and blunted signal transduction to PI3K was implicated in enhanced late INa. Tbx5 regulation of the PDGF axis increased arrhythmia risk due to disruption of PDGF signaling and was conserved in murine model systems. PDGF receptor blockade markedly prolonged normal iPSC-CM action potentials and plasma levels of PDGF in the Framingham Heart Study were inversely correlated with the QTc interval (P<0.001). CONCLUSIONS: These results not only establish decreased SCN5A transcription by the TBX5 variant as a cause of BrS, but also reveal a new general transcriptional mechanism of arrhythmogenesis of enhanced late sodium current caused by reduced PDGF receptor-mediated PI3K signaling.

Whole Genome Sequence Analysis of the Plasma Proteome in Black Adults Provides Novel Insights Into Cardiovascular Disease.

BACKGROUND: Plasma proteins are critical mediators of cardiovascular processes and are the targets of many drugs. Previous efforts to characterize the genetic architecture of the plasma proteome have been limited by a focus on individuals of European descent and leveraged genotyping arrays and imputation. Here we describe whole genome sequence analysis of the plasma proteome in individuals with greater African ancestry, increasing our power to identify novel genetic determinants. METHODS: Proteomic profiling of 1301 proteins was performed in 1852 Black adults from the Jackson Heart Study using aptamer-based proteomics (SomaScan). Whole genome sequencing association analysis was ascertained for all variants with minor allele count ≥5. Results were validated using an alternative, antibody-based, proteomic platform (Olink) as well as replicated in the Multi-Ethnic Study of Atherosclerosis and the HERITAGE Family Study (Health, Risk Factors, Exercise Training and Genetics). RESULTS: We identify 569 genetic associations between 479 proteins and 438 unique genetic regions at a Bonferroni-adjusted significance level of 3.8×10-11. These associations include 114 novel locus-protein relationships and an additional 217 novel sentinel variant-protein relationships. Novel cardiovascular findings include new protein associations at the APOE gene locus including ZAP70 (sentinel single nucleotide polymorphism [SNP] rs7412-T, ß=0.61±0.05, P=3.27×10-30) and MMP-3 (ß=-0.60±0.05, P=1.67×10-32), as well as a completely novel pleiotropic locus at the HPX gene, associated with 9 proteins. Further, the associations suggest new mechanisms of genetically mediated cardiovascular disease linked to African ancestry; we identify a novel association between variants linked to APOL1-associated chronic kidney and heart disease and the protein CKAP2 (rs73885319-G, ß=0.34±0.04, P=1.34×10-17) as well as an association between ATTR amyloidosis and RBP4 levels in community-dwelling individuals without heart failure. CONCLUSIONS: Taken together, these results provide evidence for the functional importance of variants in non-European populations, and suggest new biological mechanisms for ancestry-specific determinants of lipids, coagulation, and myocardial function.

Would You Recommend a Statin to This Patient for Primary Prevention of Cardiovascular Disease? : Grand Rounds Discussion From Beth Israel Deaconess Medical Center.

Cardiovascular disease (CVD) is the leading cause of death in the United States. Hypercholesterolemia is a principal modifiable risk factor for the primary prevention of CVD. In addition to lifestyle modification, statins are an important tool to reduce risk for CVD in selected patients. A useful strategy to identify candidates for statins is to estimate the 10-year risk for CVD through the use of a validated risk calculator. Commonly used calculators include the Framingham risk score and the pooled cohort equation. Multiple randomized controlled trials have shown that statins reduce the risk for CVD in patients without known CVD. Two recent guidelines have proposed an approach to the use of statins in primary prevention of CVD. The American College of Cardiology/American Heart Association and the U.S. Department of Veterans Affairs guidelines form the basis for this discussion. The guidelines differ on the use of advanced testing to modify the 10-year CVD risk estimate and on the need for low-density lipoprotein cholesterol targets to establish the efficacy of statins. Advanced testing with coronary artery calcium measurement may be helpful for patients who are potentially eligible for statin therapy but who are uncertain if they wish to take a statin. In this paper, 2 experts, a preventive cardiologist and a general internist, discuss their approach to the use of statins for primary prevention of CVD and how they would apply the guidelines to an individual patient.

Circulating testican-2 is a podocyte-derived marker of kidney health.

In addition to their fundamental role in clearance, the kidneys release select molecules into the circulation, but whether any of these anabolic functions provides insight on kidney health is unknown. Using aptamer-based proteomics, we characterized arterial (A)-to-renal venous (V) gradients for >1,300 proteins in 22 individuals who underwent invasive sampling. Although most of the proteins that changed significantly decreased from A to V, consistent with renal clearance, several were found to increase, the most significant of which was testican-2. To assess the clinical implications of these physiologic findings, we examined proteomic data in the Jackson Heart Study (JHS), an African-American cohort (n = 1,928), with replication in the Framingham Heart Study (FHS), a White cohort (n = 1,621). In both populations, testican-2 had a strong, positive correlation with estimated glomerular filtration rate (eGFR). In addition, higher baseline testican-2 levels were associated with a lower rate of eGFR decline in models adjusted for age, gender, hypertension, type 2 diabetes, body mass index, baseline eGFR, and albuminuria. Glomerular expression of testican-2 in human kidneys was demonstrated by immunohistochemistry, immunofluorescence, and electron microscopy, while single-cell RNA sequencing of human kidneys showed expression of the cognate gene, SPOCK2, exclusively in podocytes. In vitro, testican-2 increased glomerular endothelial tube formation and motility, raising the possibility that its secretion has a functional role within the glomerulus. Taken together, our findings identify testican-2 as a podocyte-derived biomarker of kidney health and prognosis.

Population health management of low-density lipoprotein cholesterol via a remote, algorithmic, navigator-executed program.

BACKGROUND: Implementation of guideline-directed cholesterol management remains low despite definitive evidence establishing such measures reduce cardiovascular (CV) events, especially in high atherosclerotic CV disease (ASCVD) risk patients. Modern electronic resources now exist that may help improve health care delivery. While electronic medical records (EMR) allow for population health screening, the potential for coupling EMR screening to remotely delivered algorithmic population-based management has been less studied as a way of overcoming barriers to optimal cholesterol management. METHODS: In an academically affiliated healthcare system, using EMR screening, we sought to identify 1,000 high ASCVD risk patients not meeting guideline-directed low-density lipoprotein-cholesterol (LDL-C) goals within specific system-affiliated primary care practices. Contacted patients received cholesterol education and were offered a remote, guideline-directed, algorithmic cholesterol management program executed by trained but non-licensed "navigators" under professional supervision. Navigators used telephone, proprietary software and internet resources to facilitate algorithm-driven, guideline-based medication initiation/titration, and laboratory testing until patients achieved LDL-C goals or exited the program. As a clinical effectiveness program for cholesterol guideline implementation, comparison was made to those contacted patients who declined program-based medication management, and received education only, along with their usual care. RESULTS: 1021 patients falling into guideline-defined high ASCVD risk groups warranting statin therapy (ASCVD, type 2 diabetes, LDL ≥ 190 mg/dL, calculated 10-year ASCVD risk ≥7.5%) and not achieving guideline-defined target LDL-C levels and/or therapy were identified and contacted. Among the 698 such patients who opted for program medication management, significant LDL-C reductions occurred in the total cohort (mean -65.4 mg/dL, 45% decrease), and each high ASCVD risk subgroup: ASCVD (-57.2 mg/dL, -48.0%); diabetes mellitus (-53.1 mg/dL, -40.0%); severe hypercholesterolemia (-76.3 mg/dL, -45.7%); elevated ASCVD 10-year risk (-62.8 mg/dL, -41.1%) (P<0.001 for all), without any significant complications. Among 20% of participants with reported statin intolerance, average LDL-C decreased from baseline 143 mg/dL to 85 mg/dL using mainly statins and ezetimibe, with limited PCSK9 inhibitor use. In comparison, eligible high ASCVD risk patients who were contacted but opted for education only, a 17% LDL-C decrease occurred over a similar timeframe, with 80% remaining with an LDL-C over 100 mg/dL. CONCLUSIONS: A remote, algorithm-driven, navigator-executed cholesterol management program successfully identified high ASCVD risk undertreated patients using EMR screening and was associated with significantly improved guideline-directed LDL-C control, supporting this approach as a novel strategy for improving health care access and delivery.

Functional Screening of Candidate Causal Genes for Insulin Resistance in Human Preadipocytes and Adipocytes.

Rationale: Genome-wide association studies have identified genetic loci associated with insulin resistance (IR) but pinpointing the causal genes of a risk locus has been challenging. Objective: To identify candidate causal genes for IR, we screened regional and biologically plausible genes (16 in total) near the top 10 IR-loci in risk-relevant cell types, namely preadipocytes and adipocytes. Methods and Results: We generated 16 human Simpson-Golabi-Behmel syndrome preadipocyte knockout lines each with a single IR-gene knocked out by lentivirus-mediated CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 system. We evaluated each gene knockout by screening IR-relevant phenotypes in the 3 insulin-sensitizing mechanisms, including adipogenesis, lipid metabolism, and insulin signaling. We performed genetic analyses using data on the genotype-tissue expression portal expression quantitative trait loci database and accelerating medicines partnership type 2 diabetes mellitus Knowledge Portal to evaluate whether candidate genes prioritized by our in vitro studies were expression quantitative trait loci genes in human subcutaneous adipose tissue, and whether expression of these genes is associated with risk of IR, type 2 diabetes mellitus, and cardiovascular diseases. We further validated the functions of 3 new adipose IR genes by overexpression-based phenotypic rescue in the Simpson-Golabi-Behmel syndrome preadipocyte knockout lines. Twelve genes, PPARG, IRS-1, FST, PEPD, PDGFC, MAP3K1, GRB14, ARL15, ANKRD55, RSPO3, COBLL1, and LYPLAL1, showed diverse phenotypes in the 3 insulin-sensitizing mechanisms, and the first 7 of these genes could affect all the 3 mechanisms. Five out of 6 expression quantitative trait loci genes are among the top candidate causal genes and the abnormal expression levels of these genes (IRS-1, GRB14, FST, PEPD, and PDGFC) in human subcutaneous adipose tissue could be associated with increased risk of IR, type 2 diabetes mellitus, and cardiovascular disease. Phenotypic rescue by overexpression of the candidate causal genes (FST, PEPD, and PDGFC) in the Simpson-Golabi-Behmel syndrome preadipocyte knockout lines confirmed their function in adipose IR. Conclusions: Twelve genes showed diverse phenotypes indicating differential roles in insulin sensitization, suggesting mechanisms bridging the association of their genomic loci with IR. We prioritized PPARG, IRS-1, GRB14, MAP3K1, FST, PEPD, and PDGFC as top candidate genes. Our work points to novel roles for FST, PEPD, and PDGFC in adipose tissue, with consequences for cardiometabolic diseases.

Application of Large-Scale Aptamer-Based Proteomic Profiling to Planned Myocardial Infarctions.

BACKGROUND: Emerging proteomic technologies using novel affinity-based reagents allow for efficient multiplexing with high-sample throughput. To identify early biomarkers of myocardial injury, we recently applied an aptamer-based proteomic profiling platform that measures 1129 proteins to samples from patients undergoing septal alcohol ablation for hypertrophic cardiomyopathy, a human model of planned myocardial injury. Here, we examined the scalability of this approach using a markedly expanded platform to study a far broader range of human proteins in the context of myocardial injury. METHODS: We applied a highly multiplexed, expanded proteomic technique that uses single-stranded DNA aptamers to assay 4783 human proteins (4137 distinct human gene targets) to derivation and validation cohorts of planned myocardial injury, individuals with spontaneous myocardial infarction, and at-risk controls. RESULTS: We found 376 target proteins that significantly changed in the blood after planned myocardial injury in a derivation cohort (n=20; P<1.05E-05, 1-way repeated measures analysis of variance, Bonferroni threshold). Two hundred forty-seven of these proteins were validated in an independent planned myocardial injury cohort (n=15; P<1.33E-04, 1-way repeated measures analysis of variance); >90% were directionally consistent and reached nominal significance in the validation cohort. Among the validated proteins that were increased within 1 hour after planned myocardial injury, 29 were also elevated in patients with spontaneous myocardial infarction (n=63; P<6.17E-04). Many of the novel markers identified in our study are intracellular proteins not previously identified in the peripheral circulation or have functional roles relevant to myocardial injury. For example, the cardiac LIM protein, cysteine- and glycine-rich protein 3, is thought to mediate cardiac mechanotransduction and stress responses, whereas the mitochondrial ATP synthase F0 subunit component is a vasoactive peptide on its release from cells. Last, we performed aptamer-affinity enrichment coupled with mass spectrometry to technically verify aptamer specificity for a subset of the new biomarkers. CONCLUSIONS: Our results demonstrate the feasibility of large-scale aptamer multiplexing at a level that has not previously been reported and with sample throughput that greatly exceeds other existing proteomic methods. The expanded aptamer-based proteomic platform provides a unique opportunity for biomarker and pathway discovery after myocardial injury.

Genetic Architecture of the Cardiovascular Risk Proteome.

BACKGROUND: We recently identified 156 proteins in human plasma that were each associated with the net Framingham Cardiovascular Disease Risk Score using an aptamer-based proteomic platform in Framingham Heart Study Offspring participants. Here we hypothesized that performing genome-wide association studies and exome array analyses on the levels of each of these 156 proteins might identify genetic determinants of risk-associated circulating factors and provide insights into early cardiovascular pathophysiology. METHODS: We studied the association of genetic variants with the plasma levels of each of the 156 Framingham Cardiovascular Disease Risk Score-associated proteins using linear mixed-effects models in 2 population-based cohorts. We performed discovery analyses on plasma samples from 759 participants of the Framingham Heart Study Offspring cohort, an observational study of the offspring of the original Framingham Heart Study and their spouses, and validated these findings in plasma samples from 1421 participants of the MDCS (Malmö Diet and Cancer Study). To evaluate the utility of this strategy in identifying new biological pathways relevant to cardiovascular disease pathophysiology, we performed studies in a cell-model system to experimentally validate the functional significance of an especially novel genetic association with circulating apolipoprotein E levels. RESULTS: We identified 120 locus-protein associations in genome-wide analyses and 41 associations in exome array analyses, the majority of which have not been described previously. These loci explained up to 66% of interindividual plasma protein-level variation and, on average, accounted for 3 times the amount of variation explained by common clinical factors, such as age, sex, and diabetes mellitus status. We described overlap among many of these loci and cardiovascular disease genetic risk variants. Finally, we experimentally validated a novel association between circulating apolipoprotein E levels and the transcription factor phosphatase 1G. Knockdown of phosphatase 1G in a human liver cell model resulted in decreased apolipoprotein E transcription and apolipoprotein E protein levels in cultured supernatants. CONCLUSIONS: We identified dozens of novel genetic determinants of proteins associated with the Framingham Cardiovascular Disease Risk Score and experimentally validated a new role for phosphatase 1G in lipoprotein biology. Further, genome-wide and exome array data for each protein have been made publicly available as a resource for cardiovascular disease research.

Probing the Virtual Proteome to Identify Novel Disease Biomarkers.

BACKGROUND: Proteomic approaches allow measurement of thousands of proteins in a single specimen, which can accelerate biomarker discovery. However, applying these technologies to massive biobanks is not currently feasible because of the practical barriers and costs of implementing such assays at scale. To overcome these challenges, we used a "virtual proteomic" approach, linking genetically predicted protein levels to clinical diagnoses in >40 000 individuals. METHODS: We used genome-wide association data from the Framingham Heart Study (n=759) to construct genetic predictors for 1129 plasma protein levels. We validated the genetic predictors for 268 proteins and used them to compute predicted protein levels in 41 288 genotyped individuals in the Electronic Medical Records and Genomics (eMERGE) cohort. We tested associations for each predicted protein with 1128 clinical phenotypes. Lead associations were validated with directly measured protein levels and either low-density lipoprotein cholesterol or subclinical atherosclerosis in the MDCS (Malmö Diet and Cancer Study; n=651). RESULTS: In the virtual proteomic analysis in eMERGE, 55 proteins were associated with 89 distinct diagnoses at a false discovery rate q<0.1. Among these, 13 associations involved lipid (n=7) or atherosclerosis (n=6) phenotypes. We tested each association for validation in MDCS using directly measured protein levels. At Bonferroni-adjusted significance thresholds, levels of apolipoprotein E isoforms were associated with hyperlipidemia, and circulating C-type lectin domain family 1 member B and platelet-derived growth factor receptor-ß predicted subclinical atherosclerosis. Odds ratios for carotid atherosclerosis were 1.31 (95% CI, 1.08-1.58; P=0.006) per 1-SD increment in C-type lectin domain family 1 member B and 0.79 (0.66-0.94; P=0.008) per 1-SD increment in platelet-derived growth factor receptor-ß. CONCLUSIONS: We demonstrate a biomarker discovery paradigm to identify candidate biomarkers of cardiovascular and other diseases.

Aptamer-Based Proteomic Profiling Reveals Novel Candidate Biomarkers and Pathways in Cardiovascular Disease.

BACKGROUND: Single-stranded DNA aptamers are oligonucleotides of ≈50 base pairs in length selected for their ability to bind proteins with high specificity and affinity. Emerging DNA aptamer-based technologies may address limitations of existing proteomic techniques, including low sample throughput, which have hindered proteomic analyses of large cohorts. METHODS: To identify early biomarkers of myocardial injury, we applied an aptamer-based proteomic platform that measures 1129 proteins to a clinically relevant perturbational model of planned myocardial infarction (PMI), patients undergoing septal ablation for hypertrophic cardiomyopathy. Blood samples were obtained before and at 10 and 60 minutes after PMI, and protein changes were assessed by repeated-measures analysis of variance. The generalizability of our PMI findings was evaluated in a spontaneous myocardial infarction cohort (Wilcoxon rank-sum). We then tested the platform's ability to detect associations between proteins and Framingham Risk Score components in the Framingham Heart Study, performing regression analyses for each protein versus each clinical trait. RESULTS: We found 217 proteins that significantly changed in the peripheral vein blood after PMI in a derivation cohort (n=15; P<5.70E-5). Seventy-nine of these proteins were validated in an independent PMI cohort (n=15; P<2.30E-4); >85% were directionally consistent and reached nominal significance. We detected many protein changes that are novel in the context of myocardial injury, including Dickkopf-related protein 4, a WNT pathway inhibitor (peak increase 124%, P=1.29E-15) and cripto, a growth factor important in cardiac development (peak increase 64%, P=1.74E-4). Among the 40 validated proteins that increased within 1 hour after PMI, 23 were also elevated in patients with spontaneous myocardial infarction (n=46; P<0.05). Framingham Heart Study analyses revealed 156 significant protein associations with the Framingham Risk Score (n=899), including aminoacylase 1 (ß=0.3386, P=2.54E-22) and trigger factor 2 (ß=0.2846, P=5.71E-17). Furthermore, we developed a novel workflow integrating DNA-based immunoaffinity with mass spectrometry to analytically validate aptamer specificity. CONCLUSIONS: Our results highlight an emerging proteomics tool capable of profiling >1000 low-abundance analytes with high sensitivity and high precision, applicable both to well-phenotyped perturbational studies and large human cohorts, as well.

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.

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.

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.

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.

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.

Genetic Risk Assessment for Atherosclerotic Cardiovascular Disease: A Guide for the General Cardiologist.

Genetic testing for cardiovascular (CV) disease has had a profound impact on the diagnosis and evaluation of monogenic causes of CV disease, such as hypertrophic and familial cardiomyopathies, long QT syndrome, and familial hypercholesterolemia. The success in genetic testing for monogenic diseases has prompted special interest in utilizing genetic information in the risk assessment of more common diseases such as atherosclerotic cardiovascular disease (ASCVD). Polygenic risk scores (PRS) have been developed to assess the risk of coronary artery disease, which now include millions of single-nucleotide polymorphisms that have been identified through genomewide association studies. Although these PRS have demonstrated a strong association with coronary artery disease in large cross-sectional population studies, there remains intense debate regarding the added value that PRS contributes to existing clinical risk prediction models such as the pooled cohort equations. In this review, we provide a brief background of genetic testing for monogenic drivers of CV disease and then focus on the recent developments in genetic risk assessment of ASCVD, including the use of PRS. We outline the genetic testing that is currently available to all cardiologists in the clinic and discuss the evolving sphere of specialized cardiovascular genetics programs that integrate the expertise of cardiologists, geneticists, and genetic counselors. Finally, we review the possible implications that PRS and pharmacogenomic data may soon have on clinical practice in the care for patients with or at risk of developing ASCVD.

Metabolomic Analysis of Coronary Heart Disease in an African American Cohort From the Jackson Heart Study.

Importance: African American individuals have disproportionate rates of coronary heart disease (CHD) but lower levels of coronary artery calcium (CAC), a marker of subclinical CHD, than non-Hispanic White individuals. African American individuals may have distinct metabolite profiles associated with incident CHD risk compared with non-Hispanic White individuals, and examination of these differences could highlight important processes that differ between them. Objectives: To identify novel biomarkers of incident CHD and CAC among African American individuals and to replicate incident CHD findings in a multiethnic cohort. Design, Setting, and Participants: This analysis targeted plasma metabolomic profiling of 2346 participants in the Jackson Heart Study (JHS), a prospective population-based cohort study that included 5306 African American participants who were examined at baseline (2000-2004) and 2 follow-up visits. Replication of CHD-associated metabolites was sought among 1588 multiethnic participants from the Women's Health Initiative (WHI), a prospective population-based multiethnic cohort study of 161 808 postmenopausal women who were examined at baseline (1991-1995) and ongoing follow-up visits. Regression analyses were performed for each metabolite to examine the associations with incident CHD and CAC scores. Data were collected from the WHI between 1994 and 2009 and from the JHS between 2000 and 2015. All data were analyzed from November 2020 to August 2021. Exposures: Plasma metabolites. Main Outcomes and Measures: Incident CHD was defined as definite or probable myocardial infarction or definite fatal CHD in both the JHS and WHI cohorts. In the JHS cohort, silent myocardial infarction between examinations (as determined by electrocardiography) and coronary revascularization were included in the incident CHD analysis. Coronary artery calcium was measured using a 16-channel computed tomographic system and reported as an Agatston score. Results: Among 2346 African American individuals in the JHS cohort, the mean (SD) age was 56 (13) years, and 1468 individuals (62.6%) were female. Among 1588 postmenopausal women in the WHI cohort, the mean (SD) age was 67 (7) years; 217 individuals (13.7%) self-identified as African American, 1219 (76.8%) as non-Hispanic White, and 152 (9.6%) as other races or ethnicities. In the fully adjusted model including 1876 individuals, 46 of 303 targeted metabolites were associated with incident CHD (false discovery rate q <0.100). Data for 32 of the 46 metabolites were available in the WHI cohort, and 13 incident CHD-associated metabolites from the JHS cohort were replicated in the WHI cohort. A total of 1439 participants from the JHS cohort with available CAC scores received metabolomic profiling. Nine metabolites were associated with CAC scores. Minimal overlap was found between the results from the incident CHD and CAC analyses, with only 3 metabolites shared between the 2 analyses. Conclusions and Relevance: This cohort study identified metabolites that were associated with incident CHD among African American individuals, including 13 incident CHD-associated metabolites that were replicated in a multiethnic population and 9 novel metabolites that included N-acylamides, leucine, and lipid species. These findings may help to elucidate common and distinct metabolic processes that may be associated with CHD among individuals with different self-identified race.