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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.

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.

Additional file 1: Table S1. Characteristics of the study sample by outcome group. Table S2. Comparison of the study subsample to the full FHS Generation 2. Table S3. Changes in metabolites from pre- to post-OGTT. Table S4a. Association of Δmetabolites with incident CVD with additional adjustment for fasting blood glucose and HOMA-IR. Table S4b. Association of Δmetabolites with mortality with additional adjustment for fasting blood glucose and HOMA-IR. Table S5. Spearman Rank Correlation partial coefficients adjusted for age, sex, and fasting metabolite level.

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.

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.

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.

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.

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

The purpose of this study was to assess whether: 1) very small increases in troponin T, measured by a new highly sensitive cardiac troponin T (hs-cTnT), may reflect ischemia without necrosis; and 2) serial changes can discriminate ischemia from other causes of cardiac troponin T (cTnT) release.A new hs-cTnT assay offers greater sensitivity than current assays.Nineteen patients referred for diagnostic catheterization underwent cannulation of the coronary sinus (CS). Serial CS and peripheral plasma samples were obtained at multiple time points during and after incremental rapid atrial pacing. cTnT was quantified using both a standard and a pre-commercial highly sensitive assay. Ischemia was determined by the presence of significant coronary artery disease (CAD) and myocardial lactate release with pacing.cTnT concentrations in CS blood increased from a median of 6.8 pg/ml prior to pacing to 15.6 pg/ml 60 min after termination of rapid atrial pacing (p0.0001), changes that were mirrored at 180 min in peripheral blood (5.1 to 11.8 pg/ml, p0.0001). Although peripheral cTnT concentrations tended to be higher at 180 min following pacing for patients with CAD and lactate elution (n = 7) when compared with those without either marker (n = 5) (25.0 pg/ml vs. 10.2 pg/ml, p = 0.10), relative (1.7-fold vs. 5.2-fold) and absolute (6.8 pg/ml vs. 8.8 pg/ml, p = 0.50) changes were not different between groups.Brief periods of ischemia, without frank infarction, cause low-level cTnT release, and small increases are common after periods of increased myocardial work, even among patients without objective evidence of myocardial ischemia or obstructive CAD. Additional research is needed before hs-cTnT assays are widely adopted in the management of subjects with chest pain syndromes.