Search

Blood lipid traits are treatable and heritable risk factors for heart disease, a leading cause of mortality worldwide. Although genome-wide association studies (GWASs) have discovered hundreds of variants associated with lipids in humans, most of the causal mechanisms of lipids remain unknown. To better understand the biological processes underlying lipid metabolism, we investigated the associations of plasma protein levels with total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol in blood. We trained protein prediction models based on samples in the Multi-Ethnic Study of Atherosclerosis (MESA) and applied them to conduct proteome-wide association studies (PWASs) for lipids using the Global Lipids Genetics Consortium (GLGC) data. Of the 749 proteins tested, 42 were significantly associated with at least one lipid trait. Furthermore, we performed transcriptome-wide association studies (TWASs) for lipids using 9,714 gene expression prediction models trained on samples from peripheral blood mononuclear cells (PBMCs) in MESA and 49 tissues in the Genotype-Tissue Expression (GTEx) project. We found that although PWASs and TWASs can show different directions of associations in an individual gene, 40 out of 49 tissues showed a positive correlation between PWAS and TWAS signed p values across all the genes, which suggests high-level consistency between proteome-lipid associations and transcriptome-lipid associations.

Physical activity, including structured exercise, is associated with favorable health-related chronic disease outcomes. Although there is evidence of various molecular pathways that affect these responses, a comprehensive molecular map of these molecular responses to exercise has not been developed. The Molecular Transducers of Physical Activity Consortium (MoTrPAC) is a multicenter study designed to isolate the effects of structured exercise training on the molecular mechanisms underlying the health benefits of exercise and physical activity. MoTrPAC contains both a preclinical and human component. The details of the human studies component of MoTrPAC that include the design and methods are presented here. The human studies contain both an adult and pediatric component. In the adult component, sedentary participants are randomized to 12 wk of Control, Endurance Exercise Training, or Resistance Exercise Training with outcomes measures completed before and following the 12 wk. The adult component also includes recruitment of highly active endurance-trained or resistance-trained participants who only complete measures once. A similar design is used for the pediatric component; however, only endurance exercise is examined. Phenotyping measures include weight, body composition, vital signs, cardiorespiratory fitness, muscular strength, physical activity and diet, and other questionnaires. Participants also complete an acute rest period (adults only) or exercise session (adults, pediatrics) with collection of biospecimens (blood only for pediatrics) to allow for examination of the molecular responses. The design and methods of MoTrPAC may inform other studies. Moreover, MoTrPAC will provide a repository of data that can be used broadly across the scientific community.NEW & NOTEWORTHY The Molecular Transducers of Physical Activity Consortium (MoTrPAC) will be the first large trial to isolate the effects of structured exercise training on the molecular mechanisms underlying the health benefits of exercise and physical activity. By generating a compendium of the molecular responses to exercise, MoTrPAC will lay the foundation for a new era of biomedical research on Precision Exercise Medicine. Presented here is the design, protocols, and procedures for the MoTrPAC human studies.

Regular exercise promotes whole-body health and prevents disease, but the underlying molecular mechanisms are incompletely understood1-3. Here, the Molecular Transducers of Physical Activity Consortium4 profiled the temporal transcriptome, proteome, metabolome, lipidome, phosphoproteome, acetylproteome, ubiquitylproteome, epigenome and immunome in whole blood, plasma and 18 solid tissues in male and female Rattus norvegicus over eight weeks of endurance exercise training. The resulting data compendium encompasses 9,466 assays across 19 tissues, 25 molecular platforms and 4 training time points. Thousands of shared and tissue-specific molecular alterations were identified, with sex differences found in multiple tissues. Temporal multi-omic and multi-tissue analyses revealed expansive biological insights into the adaptive responses to endurance training, including widespread regulation of immune, metabolic, stress response and mitochondrial pathways. Many changes were relevant to human health, including non-alcoholic fatty liver disease, inflammatory bowel disease, cardiovascular health and tissue injury and recovery. The data and analyses presented in this study will serve as valuable resources for understanding and exploring the multi-tissue molecular effects of endurance training and are provided in a public repository ( https://motrpac-data.org/ ).

Background: Black adults have higher incidence of all-cause mortality and worse cardiovascular disease (CVD) outcomes when compared to other U.S. populations. The Duffy chemokine receptor is not expressed on erythrocytes in a large majority of Black adults, but 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 mortality and incident CVD events (coronary heart disease, stroke, and heart failure) in self-identified Black members of three contemporary, longitudinal cohort studies (the Women's Health Initiative, Jackson Heart Study, and Multi-Ethnic Study of Atherosclerosis). Data on 14,358 Black participants (9023 Duffy-null and 5335 Duffy-receptor-positive, as defined using single-nucleotide polymorphism (SNP) rs2814778) were included in this analysis. Results: Duffy null was strongly associated with higher hs-CRP (meta-analysis p = 2.62 × 10-9), but the association was largely attenuated, though still marginally significant (p = 0.005), after conditioning on known CRP locus alleles in linkage disequilibrium with the Duffy gene. In our discovery cohorts, Duffy-null status appeared to be associated with a higher risk of all-cause mortality and incident stroke, though these associations were attenuated and non-significant following adjustment for traditional risk factors including hs-CRP. Moreover, the association of Duffy-null status with mortality could not be replicated in an independent sample of Black adults from the UK Biobank. Conclusions: These findings suggest that the higher levels of hs-CRP found in Duffy-null individuals may be in part independent of CRP alleles known to influence circulating levels of hs-CRP. During the follow-up of this community-based sample of Black participants, Duffy-null status was not associated with mortality or incident CVD events independently of traditional risk factors including hs-CRP.

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.

Cyanide-a fast-acting poison-is easy to obtain given its widespread use in manufacturing industries. It is a high-threat chemical agent that poses a risk of occupational exposure in addition to being a terrorist agent. FDA-approved cyanide antidotes must be given intravenously, which is not practical in a mass casualty setting due to the time and skill required to obtain intravenous access. Glyoxylate is an endogenous metabolite that binds cyanide and reverses cyanide-induced redox imbalances independent of chelation. Efficacy and biochemical mechanistic studies in an FDA-approved preclinical animal model have not been reported. Therefore, in a swine model of cyanide poisoning, we evaluated the efficacy of intramuscular glyoxylate on clinical, metabolic, and biochemical endpoints. Animals were instrumented for continuous hemodynamic monitoring and infused with potassium cyanide. Following cyanide-induced apnea, saline control or glyoxylate was administered intramuscularly. Throughout the study, serial blood samples were collected for pharmacokinetic, metabolite, and biochemical studies, in addition, vital signs, hemodynamic parameters, and laboratory values were measured. Survival in glyoxylate-treated animals was 83% compared with 12% in saline-treated control animals (p

BackgroundAlzheimer's disease and related dementias (ADRD) involve biological processes that begin years to decades before onset of clinical symptoms. The plasma proteome can offer insight into brain aging and risk of incident dementia among cognitively healthy adults.ObjectiveTo identify biomarkers and biological pathways associated with neuroimaging measures and incident dementia in two large community-based cohorts by applying a correlation-based network analysis to the plasma proteome.MethodsWeighted co-expression network analysis of 1,305 plasma proteins identified four modules of co-expressed proteins, which were related to MRI brain volumes and risk of incident dementia over a median 20-year follow-up in Framingham Heart Study (FHS) Offspring cohort participants (n = 1,861). Analyses were replicated in the Cardiovascular Health Study (CHS) (n = 2,117, mean 6-year follow-up).ResultsTwo proteomic modules, one related to protein clearance and synaptic maintenance (M2) and a second to inflammation (M4), were associated with total brain volume in FHS (M2: p = 0.014; M4: p = 4.2×10-5). These modules were not significantly associated with hippocampal volume, white matter hyperintensities, or incident all-cause or AD dementia. Associations with TCBV did not replicate in CHS, an older cohort with a greater burden of comorbidities.ConclusionsProteome networks implicate an early role for biological pathways involving inflammation and synaptic function in preclinical brain atrophy, with implications for clinical dementia.

Identifying circulating proteins associated with cognitive function may point to biomarkers and molecular process of cognitive impairment. Few studies have investigated the association between circulating proteins and cognitive function. We identify 246 protein measures quantified by the SomaScan assay as associated with cognitive function (p

Integrative approaches that simultaneously model multi-omics data have gained increasing popularity because they provide holistic system biology views of multiple or all components in a biological system of interest. Canonical correlation analysis (CCA) is a correlation-based integrative method designed to extract latent features shared between multiple assays by finding the linear combinations of features-referred to as canonical variables (CVs)-within each assay that achieve maximal across-assay correlation. Although widely acknowledged as a powerful approach for multi-omics data, CCA has not been systematically applied to multi-omics data in large cohort studies, which has only recently become available. Here, we adapted sparse multiple CCA (SMCCA), a widely-used derivative of CCA, to proteomics and methylomics data from the Multi-Ethnic Study of Atherosclerosis (MESA) and Jackson Heart Study (JHS). To tackle challenges encountered when applying SMCCA to MESA and JHS, our adaptations include the incorporation of the Gram-Schmidt (GS) algorithm with SMCCA to improve orthogonality among CVs, and the development of Sparse Supervised Multiple CCA (SSMCCA) to allow supervised integration analysis for more than two assays. Effective application of SMCCA to the two real datasets reveals important findings. Applying our SMCCA-GS to MESA and JHS, we identified strong associations between blood cell counts and protein abundance, suggesting that adjustment of blood cell composition should be considered in protein-based association studies. Importantly, CVs obtained from two independent cohorts also demonstrate transferability across the cohorts. For example, proteomic CVs learned from JHS, when transferred to MESA, explain similar amounts of blood cell count phenotypic variance in MESA, explaining 39.0% ~ 50.0% variation in JHS and 38.9% ~ 49.1% in MESA. Similar transferability was observed for other omics-CV-trait pairs. This suggests that biologically meaningful and cohort-agnostic variation is captured by CVs. We anticipate that applying our SMCCA-GS and SSMCCA on various cohorts would help identify cohort-agnostic biologically meaningful relationships between multi-omics data and phenotypic traits.

Nontargeted metabolomics methods have increased potential to identify new disease biomarkers, but assessments of the additive information provided in large human cohorts by these less biased techniques are limited. To diversify our knowledge of diabetes-associated metabolites, we leveraged a method that measures 305 targeted or "known" and 2,342 nontargeted or "unknown" compounds in fasting plasma samples from 2,750 participants (315 incident cases) in the Jackson Heart Study (JHS)-a community cohort of self-identified African Americans-who are underrepresented in omics studies. We found 307 unique compounds (82 known) associated with diabetes after adjusting for age and sex at a false discovery rate of

BackgroundRacial differences in metabolomic profiles may reflect underlying differences in social determinants of health by self-reported race and may be related to racial disparities in coronary heart disease (CHD) among women in the United States. However, the magnitude of differences in metabolomic profiles between Black and White women in the United States has not been well-described. It also remains unknown whether such differences are related to differences in CHD risk.MethodsPlasma metabolomic profiles were analyzed using liquid chromatography-tandem mass spectrometry in the WHI-OS (Women's Health Initiative-Observational Study; 138 Black and 696 White women), WHI-HT trials (WHI-Hormone Therapy; 156 Black and 1138 White women), MESA (Multi-Ethnic Study of Atherosclerosis; 114 Black and 219 White women), JHS (Jackson Heart Study; 1465 Black women with 107 incident CHD cases), and NHS (Nurses' Health Study; 2506 White women with 136 incident CHD cases). First, linear regression models were used to estimate associations between self-reported race and 472 metabolites in WHI-OS (discovery); findings were replicated in WHI-HT and validated in MESA. Second, we used elastic net regression to construct a racial difference metabolomic pattern (RDMP) representing differences in the metabolomic patterns between Black and White women in the WHI-OS; the RDMP was validated in the WHI-HT and MESA. Third, using conditional logistic regressions in the WHI (717 CHD cases and 719 matched controls), we examined associations of metabolites with large differences in levels by race and the RDMP with risk of CHD, and the results were replicated in Black women from the JHS and White women from the NHS.ResultsOf the 472 tested metabolites, levels of 259 (54.9%) metabolites, mostly lipid metabolites and amino acids, significantly differed between Black and White women in both WHI-OS and WHI-HT after adjusting for baseline characteristics, socioeconomic status, lifestyle factors, baseline health conditions, and medication use (false discovery rate

ObjectiveTryptophan can be catabolised to various metabolites through host kynurenine and microbial indole pathways. We aimed to examine relationships of host and microbial tryptophan metabolites with incident type 2 diabetes (T2D), host genetics, diet and gut microbiota.MethodWe analysed associations between circulating levels of 11 tryptophan metabolites and incident T2D in 9180 participants of diverse racial/ethnic backgrounds from five cohorts. We examined host genome-wide variants, dietary intake and gut microbiome associated with these metabolites.ResultsTryptophan, four kynurenine-pathway metabolites (kynurenine, kynurenate, xanthurenate and quinolinate) and indolelactate were positively associated with T2D risk, while indolepropionate was inversely associated with T2D risk. We identified multiple host genetic variants, dietary factors, gut bacteria and their potential interplay associated with these T2D-relaetd metabolites. Intakes of fibre-rich foods, but not protein/tryptophan-rich foods, were the dietary factors most strongly associated with tryptophan metabolites. The fibre-indolepropionate association was partially explained by indolepropionate-associated gut bacteria, mostly fibre-using Firmicutes. We identified a novel association between a host functional LCT variant (determining lactase persistence) and serum indolepropionate, which might be related to a host gene-diet interaction on gut Bifidobacterium, a probiotic bacterium significantly associated with indolepropionate independent of other fibre-related bacteria. Higher milk intake was associated with higher levels of gut Bifidobacterium and serum indolepropionate only among genetically lactase non-persistent individuals.ConclusionHigher milk intake among lactase non-persistent individuals, and higher fibre intake were associated with a favourable profile of circulating tryptophan metabolites for T2D, potentially through the host-microbial cross-talk shifting tryptophan metabolism toward gut microbial indolepropionate production.

BackgroundPlasma 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.MethodsProteomic 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).ResultsWe 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, β=0.61±0.05, P=3.27×10-30) and MMP-3 (β=-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, β=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.ConclusionsTaken 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.

Deficiency of the immune checkpoint lymphocyte activation gene-3 (LAG3) protein is significantly associated with both elevated HDL-cholesterol (HDL-C) and myocardial infarction risk. We determined the association of genetic variants within ±500 kb of LAG3 with plasma LAG3 and defined LAG3-associated plasma proteins with HDL-C and clinical outcomes. Whole genome sequencing and plasma proteomics were obtained from the Multi-Ethnic Study of Atherosclerosis (MESA) and the Framingham Heart Study (FHS) cohorts as part of the Trans-Omics for Precision Medicine program. In situ Hi-C chromatin capture was performed in EBV-transformed cell lines isolated from four MESA participants. Genetic association analyses were performed in MESA using multivariate regression models, with validation in FHS. A LAG3-associated protein network was tested for association with HDL-C, coronary heart disease, and all-cause mortality. We identify an association between the LAG3 rs3782735 variant and plasma LAG3 protein. Proteomics analysis reveals 183 proteins significantly associated with LAG3 with four proteins associated with HDL-C. Four proteins discovered for association with all-cause mortality in FHS shows nominal associations in MESA. Chromatin capture analysis reveals significant cis interactions between LAG3 and C1S, LRIG3, TNFRSF1A, and trans interactions between LAG3 and B2M. A LAG3-associated protein network has significant associations with HDL-C and mortality.

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.

Although cyanide's biological effects are pleiotropic, its most obvious effects are as a metabolic poison. Cyanide potently inhibits cytochrome c oxidase and potentially other metabolic enzymes, thereby unleashing a cascade of metabolic perturbations that are believed to cause lethality. From systematic screens of human metabolites using a zebrafish model of cyanide toxicity, we have identified the TCA-derived small molecule glyoxylate as a potential cyanide countermeasure. Following cyanide exposure, treatment with glyoxylate in both mammalian and non-mammalian animal models confers resistance to cyanide toxicity with greater efficacy and faster kinetics than known cyanide scavengers. Glyoxylate-mediated cyanide resistance is accompanied by rapid pyruvate consumption without an accompanying increase in lactate concentration. Lactate dehydrogenase is required for this effect which distinguishes the mechanism of glyoxylate rescue as distinct from countermeasures based solely on chemical cyanide scavenging. Our metabolic data together support the hypothesis that glyoxylate confers survival at least in part by reversing the cyanide-induced redox imbalances in the cytosol and mitochondria. The data presented herein represent the identification of a potential cyanide countermeasure operating through a novel mechanism of metabolic modulation.

Many common and rare variants associated with hematologic traits have been discovered through imputation on large-scale reference panels. However, the majority of genome-wide association studies (GWASs) have been conducted in Europeans, and determining causal variants has proved challenging. We performed a GWAS of total leukocyte, neutrophil, lymphocyte, monocyte, eosinophil, and basophil counts generated from 109,563,748 variants in the autosomes and the X chromosome in the Trans-Omics for Precision Medicine (TOPMed) program, which included data from 61,802 individuals of diverse ancestry. We discovered and replicated 7 leukocyte trait associations, including (1) the association between a chromosome X, pseudo-autosomal region (PAR), noncoding variant located between cytokine receptor genes (CSF2RA and CLRF2) and lower eosinophil count; and (2) associations between single variants found predominantly among African Americans at the S1PR3 (9q22.1) and HBB (11p15.4) loci and monocyte and lymphocyte counts, respectively. We further provide evidence indicating that the newly discovered eosinophil-lowering chromosome X PAR variant might be associated with reduced susceptibility to common allergic diseases such as atopic dermatitis and asthma. Additionally, we found a burden of very rare FLT3 (13q12.2) variants associated with monocyte counts. Together, these results emphasize the utility of whole-genome sequencing in diverse samples in identifying associations missed by European-ancestry-driven GWASs.

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.

Novel proteomics platforms, such as the aptamer-based SOMAscan platform, can quantify large numbers of proteins efficiently and cost-effectively and are rapidly growing in popularity. However, comparisons to conventional immunoassays remain underexplored, leaving investigators unsure when cross-assay comparisons are appropriate. The correlation of results from immunoassays with relative protein quantification is explored by SOMAscan. For 63 proteins assessed in two chronic obstructive pulmonary disease (COPD) cohorts, subpopulations and intermediate outcome measures in COPD Study (SPIROMICS), and COPDGene, using myriad rules based medicine multiplex immunoassays and SOMAscan, Spearman correlation coefficients range from -0.13 to 0.97, with a median correlation coefficient of ≈0.5 and consistent results across cohorts. A similar range is observed for immunoassays in the population-based Multi-Ethnic Study of Atherosclerosis and for other assays in COPDGene and SPIROMICS. Comparisons of relative quantification from the antibody-based Olink platform and SOMAscan in a small cohort of myocardial infarction patients also show a wide correlation range. Finally, cis pQTL data, mass spectrometry aptamer confirmation, and other publicly available data are integrated to assess relationships with observed correlations. Correlation between proteomics assays shows a wide range and should be carefully considered when comparing and meta-analyzing proteomics data across assays and studies.

Fibroblast growth factor 23 (FGF23) is a bone-derived hormone that controls blood phosphate levels by increasing renal phosphate excretion and reducing 1,25-dihydroxyvitamin D3 [1,25(OH)2D] production. Disorders of FGF23 homeostasis are associated with significant morbidity and mortality, but a fundamental understanding of what regulates FGF23 production is lacking. Because the kidney is the major end organ of FGF23 action, we hypothesized that it releases a factor that regulates FGF23 synthesis. Using aptamer-based proteomics and liquid chromatography-mass spectrometry-based (LC-MS-based) metabolomics, we profiled more than 1600 molecules in renal venous plasma obtained from human subjects. Renal vein glycerol-3-phosphate (G-3-P) had the strongest correlation with circulating FGF23. In mice, exogenous G-3-P stimulated bone and bone marrow FGF23 production through local G-3-P acyltransferase-mediated (GPAT-mediated) lysophosphatidic acid (LPA) synthesis. Further, the stimulatory effect of G-3-P and LPA on FGF23 required LPA receptor 1 (LPAR1). Acute kidney injury (AKI), which increases FGF23 levels, rapidly increased circulating G-3-P in humans and mice, and the effect of AKI on FGF23 was abrogated by GPAT inhibition or Lpar1 deletion. Together, our findings establish a role for kidney-derived G-3-P in mineral metabolism and outline potential targets to modulate FGF23 production during kidney injury.

While conventional nutrition research has yielded biomarkers such as doubly labeled water for energy metabolism and 24-h urinary nitrogen for protein intake, a critical need exists for additional, equally robust biomarkers that allow for objective assessment of specific food intake and dietary exposure. Recent advances in high-throughput MS combined with improved metabolomics techniques and bioinformatic tools provide new opportunities for dietary biomarker development. In September 2018, the NIH organized a 2-d workshop to engage nutrition and omics researchers and explore the potential of multiomics approaches in nutritional biomarker research. The current Perspective summarizes key gaps and challenges identified, as well as the recommendations from the workshop that could serve as a guide for scientists interested in dietary biomarkers research. Topics addressed included study designs for biomarker development, analytical and bioinformatic considerations, and integration of dietary biomarkers with other omics techniques. Several clear needs were identified, including larger controlled feeding studies, testing a variety of foods and dietary patterns across diverse populations, improved reporting standards to support study replication, more chemical standards covering a broader range of food constituents and human metabolites, standardized approaches for biomarker validation, comprehensive and accessible food composition databases, a common ontology for dietary biomarker literature, and methodologic work on statistical procedures for intake biomarker discovery. Multidisciplinary research teams with appropriate expertise are critical to moving forward the field of dietary biomarkers and producing robust, reproducible biomarkers that can be used in public health and clinical research.

Activin type II receptor (ActRII) ligands have been implicated in muscle wasting in aging and disease. However, the role of these ligands and ActRII signaling in the heart remains unclear. Here, we investigated this catabolic pathway in human aging and heart failure (HF) using circulating follistatin-like 3 (FSTL3) as a potential indicator of systemic ActRII activity. FSTL3 is a downstream regulator of ActRII signaling, whose expression is up-regulated by the major ActRII ligands, activin A, circulating growth differentiation factor-8 (GDF8), and GDF11. In humans, we found that circulating FSTL3 increased with aging, frailty, and HF severity, correlating with an increase in circulating activins. In mice, increasing circulating activin A increased cardiac ActRII signaling and FSTL3 expression, as well as impaired cardiac function. Conversely, ActRII blockade with either clinical-stage inhibitors or genetic ablation reduced cardiac ActRII signaling while restoring or preserving cardiac function in multiple models of HF induced by aging, sarcomere mutation, or pressure overload. Using unbiased RNA sequencing, we show that activin A, GDF8, and GDF11 all induce a similar pathologic profile associated with up-regulation of the proteasome pathway in mammalian cardiomyocytes. The E3 ubiquitin ligase, Smurf1, was identified as a key downstream effector of activin-mediated ActRII signaling, which increased proteasome-dependent degradation of sarcoplasmic reticulum Ca2+ ATPase (SERCA2a), a critical determinant of cardiomyocyte function. Together, our findings suggest that increased activin/ActRII signaling links aging and HF pathobiology and that targeted inhibition of this catabolic pathway holds promise as a therapeutic strategy for multiple forms of HF.

Cyanide is a highly toxic industrial chemical that is widely used by manufactures. Smoke inhalation during household fires is the most common source of cyanide poisoning while additional risks to civilians include industrial accidents and terrorist attacks. Despite the risks to large numbers of individuals, an antidote capable of administration at scale adequate for a mass casualty, prehospital scenario does not yet exist. Previously, we demonstrated that intravenous cisplatin analogues accelerate recovery from cyanide poisoning in mice and rabbits. Of the dozens of platinum-based organometallic complexes tested, hexachloroplatinate (HCP) emerged as a promising lead compound, exhibiting strong affinity for cyanide and efficacy across model systems. Here, we show HCP is an antidote to lethal cyanide exposure and importantly is effective when delivered intramuscularly. The pharmacokinetic profile of HCP exhibited bioavailability in the systemic circulation 2.5 minutes post-treatment and subsequent renal clearance of HCP-cyanide. HCP restored parameters of cellular physiology including cytochrome oxidase redox state and TCA cycle metabolism. We next validated these findings in a large animal model (swine). Finally, preclinical safety studies in mice revealed minimal toxicity. Cumulatively, these findings demonstrate hexachloroplatinate is a promising lead compound for development of an intramuscular injectable cyanide antidote for mass casualty scenarios.

Cyanide is a potent toxic agent, and the few available antidotes are not amenable to rapid deployment in mass exposures. As a result, there are ongoing efforts to exploit different animal models to identify novel countermeasures. We have created a pipeline that combines high-throughput screening in zebrafish with subsequent validation in two mammalian small animal models as well as a porcine large animal model. We found that zebrafish embryos in the first 3 days post fertilization (dpf) are highly resistant to cyanide, becoming progressively more sensitive thereafter. Unbiased analysis of gene expression in response to several hours of ultimately lethal doses of cyanide in both 1 and 7 dpf zebrafish revealed modest changes in iron-related proteins associated with the age-dependent cyanide resistance. Metabolomics measurements demonstrated significant age-dependent differences in energy metabolism during cyanide exposure which prompted us to test modulators of the tricarboxylic acid cycle and related metabolic processes as potential antidotes. In cyanide-sensitive 7 dpf larvae, we identified several such compounds that offer significant protection against cyanide toxicity. Modulators of the pyruvate dehydrogenase complex, as well as the small molecule sodium glyoxylate, consistently protected against cyanide toxicity in 7 dpf zebrafish larvae. Together, our results indicate that the resistance of zebrafish embryos to cyanide toxicity during early development is related to an altered regulation of cellular metabolism, which we propose may be exploited as a potential target for the development of novel antidotes against cyanide poisoning.

Cisplatin holds an illustrious position in the history of chemistry most notably for its role in the virtual cure of testicular cancer. Here we describe a role for this small molecule in cyanide detoxification in vivo. Cyanide kills organisms as diverse as insects, fish, and humans within seconds to hours. Current antidotes exhibit limited efficacy and are not amenable to mass distribution requiring the development of new classes of antidotes. The binding affinity of the cyanide anion for the positively charged metal platinum is known to create an extremely stable complex in vitro. We therefore screened a panel of diverse cisplatin analogs and identified compounds that conferred protection from cyanide poisoning in zebrafish, mice, and rabbits. Cumulatively, this discovery pipeline begins to establish the characteristics of platinum ligands that influence their solubility, toxicity, and efficacy, and provides proof of concept that platinum-based complexes are effective antidotes for cyanide poisoning.

The striking rise of obesity-related metabolic disorders has focused attention on adipocytes as critical mediators of disease phenotypes. To better understand the role played by excess adipose in metabolic dysfunction it is crucial to decipher the transcriptional underpinnings of the low-grade adipose inflammation characteristic of diseases such as type 2 diabetes. Through employing a comparative transcriptomics approach, we identified IRF1 as differentially regulated between primary and in vitro-derived genetically matched adipocytes. This suggests a role as a mediator of adipocyte inflammatory phenotypes, similar to its function in other tissues. Utilizing adipose-derived mesenchymal progenitors we subsequently demonstrated that expression of IRF1 in adipocytes indeed contributes to upregulation of inflammatory processes, both in vitro and in vivo. This highlights IRF1's relevance to obesity-related inflammation and the resultant metabolic dysregulation.

Through the measure of thousands of small-molecule metabolites in diverse biological systems, metabolomics now offers the potential for new insights into the factors that contribute to complex human diseases such as cardiovascular disease. Targeted metabolomics methods have already identified new molecular markers and metabolomic signatures of cardiovascular disease risk (including branched-chain amino acids, select unsaturated lipid species, and trimethylamine-N-oxide), thus in effect linking diverse exposures such as those from dietary intake and the microbiota with cardiometabolic traits. As technologies for metabolomics continue to evolve, the depth and breadth of small-molecule metabolite profiling in complex systems continue to advance rapidly, along with prospects for ongoing discovery. Current challenges facing the field of metabolomics include scaling throughput and technical capacity for metabolomics approaches, bioinformatic and chemoinformatic tools for handling large-scale metabolomics data, methods for elucidating the biochemical structure and function of novel metabolites, and strategies for determining the true clinical relevance of metabolites observed in association with cardiovascular disease outcomes. Progress made in addressing these challenges will allow metabolomics the potential to substantially affect diagnostics and therapeutics in cardiovascular medicine.

We have developed an integrated pipeline for countermeasure discovery that, under the auspices of the National Institutes of Health Countermeasures Against Chemical Threats network, is one of the few efforts within academia that by design spans the spectrum from discovery to phase I. The successful implementation of this approach for cyanide would enable efficient proof-of-concept studies that would lay the foundation for a generalizable strategy for parallel mechanistic studies and accelerated countermeasure development in the face of new and emerging chemical threats.

Cardiometabolic diseases are the leading cause of death worldwide and are strongly linked to both genetic and nutritional factors. The field of nutrigenomics encompasses multiple approaches aimed at understanding the effects of diet on health or disease development, including nutrigenetic studies investigating the relationship between genetic variants and diet in modulating cardiometabolic risk, as well as the effects of dietary components on multiple "omic" measures, including transcriptomics, metabolomics, proteomics, lipidomics, epigenetic modifications, and the microbiome. Here, we describe the current state of the field of nutrigenomics with respect to cardiometabolic disease research and outline a direction for the integration of multiple omics techniques in future nutrigenomic studies aimed at understanding mechanisms and developing new therapeutic options for cardiometabolic disease treatment and prevention.

BackgroundAcute kidney injury (AKI) occurs commonly after transcatheter aortic valve replacement (TAVR) and is associated with markedly increased postoperative mortality. We previously identified plasma metabolites predictive of incident chronic kidney disease, but whether metabolite profiles can identify those at risk of AKI is unknown.Methods and resultsWe performed liquid chromatography-mass spectrometry-based metabolite profiling on plasma from patients undergoing TAVR and subjects from the community-based Framingham Heart Study (N=2164). AKI was defined by using the Valve Academic Research Consortium-2 criteria. Of 44 patients (mean age 82±9 years, 52% female) undergoing TAVR, 22 (50%) had chronic kidney disease and 9 (20%) developed AKI. Of 85 metabolites profiled, we detected markedly concordant cross-sectional metabolic changes associated with chronic kidney disease in the hospital-based TAVR and Framingham Heart Study cohorts. Baseline levels of 5-adenosylhomocysteine predicted AKI after TAVR, despite adjustment for baseline glomerular filtration rate (odds ratio per 1-SD increase 5.97, 95% CI 1.62-22.0; P=0.007). Of the patients who had AKI, 6 (66.7%) subsequently died, compared with 3 (8.6%) deaths among those patients who did not develop AKI (P=0.0008) over a median follow-up of 7.8 months. 5-adenosylhomocysteine was predictive of all-cause mortality after TAVR (hazard ratio per 1-SD increase 2.96, 95% CI 1.33-6.58; P=0.008), independent of baseline glomerular filtration rate.ConclusionsIn an elderly population with severe aortic stenosis undergoing TAVR, metabolite profiling improves the prediction of AKI. Given the multifactorial nature of AKI after TAVR, metabolite profiles may identify those patients with reduced renal reserve.

BackgroundWhereas several longitudinal metabolomics studies have been conducted in individuals with normal estimated glomerular filtration rate (eGFR) at baseline, disease progression among individuals with established chronic kidney disease (CKD) has not been rigorously examined.MethodsWe performed a nested case-control study of rapid CKD progression in the Chronic Renal Insufficiency Cohort Study, profiling baseline plasma from 200 individuals each with eGFR slope

The beneficial effects of physical activity (PA) are well documented, yet the mechanisms by which PA prevents disease and improves health outcomes are poorly understood. To identify major gaps in knowledge and potential strategies for catalyzing progress in the field, the NIH convened a workshop in late October 2014 entitled "Understanding the Cellular and Molecular Mechanisms of Physical Activity-Induced Health Benefits." Presentations and discussions emphasized the challenges imposed by the integrative and intermittent nature of PA, the tremendous discovery potential of applying "-omics" technologies to understand interorgan crosstalk and biological networking systems during PA, and the need to establish an infrastructure of clinical trial sites with sufficient expertise to incorporate mechanistic outcome measures into adequately sized human PA trials. Identification of the mechanisms that underlie the link between PA and improved health holds extraordinary promise for discovery of novel therapeutic targets and development of personalized exercise medicine.

Insulin resistance (IR) is a complex trait with multiple genetic and environmental components. Confounded by large differences between the sexes, environment, and disease pathology, the genetic basis of IR has been difficult to dissect. Here we examine IR and related traits in a diverse population of more than 100 unique male and female inbred mouse strains after feeding a diet rich in fat and refined carbohydrates. Our results show dramatic variation in IR among strains of mice and widespread differences between sexes that are dependent on genotype. We uncover more than 15 genome-wide significant loci and validate a gene, Agpat5, associated with IR. We also integrate plasma metabolite levels and global gene expression from liver and adipose tissue to identify metabolite quantitative trait loci (mQTL) and expression QTL (eQTL), respectively. Our results provide a resource for analysis of interactions between diet, sex, and genetic background in IR.

ObjectiveTo determine whether increases in cardiac work lead to alterations in the plasma metabolome and whether such changes arise from the heart or peripheral organs.BackgroundThere is growing evidence that the heart influences systemic metabolism through endocrine effects and affecting pathways involved in energy homeostasis.MethodsNineteen patients referred for cardiac catheterization were enrolled. Peripheral and selective coronary sinus (CS) blood sampling was performed at serial timepoints following the initiation of pacing, and metabolite profiling was performed by liquid chromatography-mass spectrometry (LC-MS).ResultsPacing-stress resulted in a 225% increase in the median rate·pressure product from baseline. Increased myocardial work induced significant changes in the peripheral concentration of 43 of 125 metabolites assayed, including large changes in purine [adenosine (+99%, p = 0.006), ADP (+42%, p = 0.01), AMP (+79%, p = 0.004), GDP (+69%, p = 0.003), GMP (+58%, p = 0.01), IMP (+50%, p = 0.03), xanthine (+61%, p = 0.0006)], and several bile acid metabolites. The CS changes in metabolites qualitatively mirrored those in the peripheral blood in both timing and magnitude, suggesting the heart was not the major source of the metabolite release.ConclusionsIsolated increases in myocardial work can induce changes in the plasma metabolome, but these changes do not appear to be directly cardiac in origin. A number of these dynamic metabolites have known signaling functions. Our study provides additional evidence to a growing body of literature on metabolic 'cross-talk' between the heart and other organs.

BackgroundThe marked excess in cardiovascular mortality that results from uremia remains poorly understood.Methods and resultsIn 2 independent, nested case-control studies, we applied liquid chromatography-mass spectrometry-based metabolite profiling to plasma obtained from participants of a large cohort of incident hemodialysis patients. First, 100 individuals who died of a cardiovascular cause within 1 year of initiating hemodialysis (cases) were randomly selected along with 100 individuals who survived for at least 1 year (controls), matched for age, sex, and race. Four highly intercorrelated long-chain acylcarnitines achieved the significance threshold adjusted for multiple testing (P