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Objective: Individuals living with obesity are differentially susceptible to cardiometabolic diseases. We hypothesized that an integrative multi‐omics approach might improve identification of subgroups of individuals with obesity who have distinct cardiometabolic disease patterns. Methods: We performed machine learning‐based, integrative unsupervised clustering to identify proteomics‐ and metabolomics‐defined subpopulations of individuals living with obesity (BMI ≥ 30 kg/m2), leveraging data from 243 individuals in the Multi‐Ethnic Study of Atherosclerosis (MESA) cohort. Omics that contributed to the observed clusters were functionally characterized. We performed multivariate regression to assess whether the individuals in each cluster demonstrated differential patterns of cardiometabolic traits. Results: We identified two distinct clusters (iCluster1 and 2). iCluster2 had significantly higher average BMI values, fasting blood glucose, and inflammation. iCluster1 was associated with higher levels of total cholesterol and high‐density lipoprotein cholesterol. Pathways mediating cell growth, lipogenesis, and energy expenditures were positively associated with iCluster1. Inflammatory response and insulin resistance pathways were positively associated with iCluster2. Conclusions: Although the two identified clusters may represent progressive obesity‐related pathologic processes measured at different stages, other mechanisms in combination could also underpin the identified clusters given no significant age difference between the comparative groups. For instance, clusters may reflect differences in dietary/behavioral patterns or differential rates of metabolic damage. [ABSTRACT FROM AUTHOR]

The identification of protein targets that exhibit anti‐aging clinical potential could inform interventions to lengthen the human health span. Most previous proteomics research has been focused on chronological age instead of longevity. We leveraged two large population‐based prospective cohorts with long follow‐ups to evaluate the proteomic signature of longevity defined by survival to 90 years of age. Plasma proteomics was measured using a SOMAscan assay in 3067 participants from the Cardiovascular Health Study (discovery cohort) and 4690 participants from the Age Gene/Environment Susceptibility‐Reykjavik Study (replication cohort). Logistic regression identified 211 significant proteins in the CHS cohort using a Bonferroni‐adjusted threshold, of which 168 were available in the replication cohort and 105 were replicated (corrected p value <0.05). The most significant proteins were GDF‐15 and N‐terminal pro‐BNP in both cohorts. A parsimonious protein‐based prediction model was built using 33 proteins selected by LASSO with 10‐fold cross‐validation and validated using 27 available proteins in the validation cohort. This protein model outperformed a basic model using traditional factors (demographics, height, weight, and smoking) by improving the AUC from 0.658 to 0.748 in the discovery cohort and from 0.755 to 0.802 in the validation cohort. We also found that the associations of 169 out of 211 proteins were partially mediated by physical and/or cognitive function. These findings could contribute to the identification of biomarkers and pathways of aging and potential therapeutic targets to delay aging and age‐related diseases. [ABSTRACT FROM AUTHOR]

While frailty is a prominent risk factor in an aging population, the underlying biology of frailty is incompletely described. Here, we integrate 979 circulating proteins across a wide range of physiologies with 12 measures of frailty in a prospective discovery cohort of 809 individuals with severe aortic stenosis (AS) undergoing transcatheter aortic valve implantation. Our aim was to characterize the proteomic architecture of frailty in a highly susceptible population and study its relation to clinical outcome and systems‐wide phenotypes to define potential novel, clinically relevant frailty biology. Proteomic signatures (specifically of physical function) were related to post‐intervention outcome in AS, specifying pathways of innate immunity, cell growth/senescence, fibrosis/metabolism, and a host of proteins not widely described in human aging. In published cohorts, the "frailty proteome" displayed heterogeneous trajectories across age (20–100 years, age only explaining a small fraction of variance) and were associated with cardiac and non‐cardiac phenotypes and outcomes across two broad validation cohorts (N > 35,000) over ≈2–3 decades. These findings suggest the importance of precision biomarkers of underlying multi‐organ health status in age‐related morbidity and frailty. [ABSTRACT FROM AUTHOR]

The biological mechanisms underlying decline in physical function with age remain unclear. We examined the plasma proteomic profile associated with longitudinal changes in physical function measured by gait speed and grip strength in community‐dwelling adults. We applied an aptamer‐based platform to assay 1154 plasma proteins on 2854 participants (60% women, aged 76 years) in the Cardiovascular Health Study (CHS) in 1992–1993 and 1130 participants (55% women, aged 54 years) in the Framingham Offspring Study (FOS) in 1991–1995. Gait speed and grip strength were measured annually for 7 years in CHS and at cycles 7 (1998–2001) and 8 (2005–2008) in FOS. The associations of individual protein levels (log‐transformed and standardized) with longitudinal changes in gait speed and grip strength in two populations were examined separately by linear mixed‐effects models. Meta‐analyses were implemented using random‐effects models and corrected for multiple testing. We found that plasma levels of 14 and 18 proteins were associated with changes in gait speed and grip strength, respectively (corrected p < 0.05). The proteins most strongly associated with gait speed decline were GDF‐15 (Meta‐analytic p = 1.58 × 10−15), pleiotrophin (1.23 × 10−9), and TIMP‐1 (5.97 × 10−8). For grip strength decline, the strongest associations were for carbonic anhydrase III (1.09 × 10−7), CDON (2.38 × 10−7), and SMOC1 (7.47 × 10−7). Several statistically significant proteins are involved in the inflammatory responses or antagonism of activin by follistatin pathway. These novel proteomic biomarkers and pathways should be further explored as future mechanisms and targets for age‐related functional decline. [ABSTRACT FROM AUTHOR]

Objective: The mechanisms linking obesity to type 2 diabetes (T2D) are not fully understood. This study aimed to identify obesity‐related metabolomic signatures (MESs) and evaluated their relationships with incident T2D. Methods: In a nested case‐control study of 2076 Chinese adults, 140 plasma metabolites were measured at baseline, linear regression was applied with the least absolute shrinkage and selection operator to identify MESs for BMI and waist circumference (WC), and conditional logistic regression was applied to examine their associations with T2D risk. Results: A total of 32 metabolites associated with BMI or WC were identified and validated, among which 14 showed positive associations and 3 showed inverse associations with T2D; 8 and 18 metabolites were selected to build MESs for BMI and WC, respectively. Both MESs showed strong linear associations with T2D: odds ratio (95% CI) comparing extreme quartiles was 4.26 (2.00‐9.06) for BMI MES and 9.60 (4.22‐21.88) for WC MES (both p‐trend < 0.001). The MES‐T2D associations were particularly evident among individuals with normal WC: odds ratio (95% CI) reached 6.41 (4.11‐9.98) for BMI MES and 10.38 (6.36‐16.94) for WC MES. Adding MESs to traditional risk factors and plasma glucose improved C statistics from 0.79 to 0.83 (p < 0.001). Conclusions: Multiple obesity‐related metabolites and MESs strongly associated with T2D in Chinese adults were identified. [ABSTRACT FROM AUTHOR]

Background: Bronchiolitis is the leading cause of hospitalization in U.S. infants and a major risk factor for childhood asthma. Growing evidence supports clinical heterogeneity within bronchiolitis. We aimed to identify endotypes of infant bronchiolitis by integrating clinical, virus, and serum proteome data, and examine their relationships with asthma development. Methods: This is a multicenter prospective cohort study of infants hospitalized for physician‐diagnosis of bronchiolitis. We identified bronchiolitis endotypes by applying unsupervised machine learning (clustering) approaches to integrated clinical, virus (respiratory syncytial virus [RSV], rhinovirus [RV]), and serum proteome data measured at hospitalization. We then examined their longitudinal association with the risk for developing asthma by age 6 years. Results: In 140 infants hospitalized with bronchiolitis, we identified three endotypes: (1) clinicalatopicvirusRVproteomeNFκB‐dysregulated, (2) clinicalnon‐atopicvirusRSV/RVproteomeTNF‐dysregulated, and (3) clinicalclassicvirusRSVproteomeNFκB/TNF‐regulated endotypes. Endotype 1 infants were characterized by high proportion of IgE sensitization and RV infection. These endotype 1 infants also had dysregulated NFκB pathways (FDR < 0.001) and significantly higher risks for developing asthma (53% vs. 22%; adjOR 4.04; 95% CI, 1.49–11.0; p = 0.006), compared with endotype 3 (clinically resembling "classic" bronchiolitis). Likewise, endotype 2 infants were characterized by low proportion of IgE sensitization and high proportion of RSV or RV infection. These endotype 2 infants had dysregulated tumor necrosis factor (TNF)‐mediated signaling pathway (FDR <0.001) and significantly higher risks for developing asthma (44% vs. 22%; adjOR 2.71; 95% CI, 1.03–7.11, p = 0.04). Conclusion: In this multicenter cohort, integrated clustering of clinical, virus, and proteome data identified biologically distinct endotypes of bronchiolitis that have differential risks of asthma development. [ABSTRACT FROM AUTHOR]

Aims: Heart failure (HF) is associated with several metabolic changes, but it is unknown whether distinct components of the circulating metabolome may be related to cardiac structure and function, and with incident HF in the community. Methods and results: We assayed 217 circulating metabolites in 2336 Framingham Study participants (mean age 55 ± 10 years, 53% women) without HF at baseline. We used linear and Cox regression to relate concentrations of metabolites to left ventricular (LV) diastolic dimension, LV wall thickness, LV ejection fraction, left atrial dimension, LV ventricular mass, and aortic root size cross‐sectionally and to incident HF prospectively. Bonferroni‐adjusted P‐values <0.05 denoted statistical significance. Circulating concentrations of kynurenine [β = −0.12 cm per standard deviation (SD) increment in normalized residual of metabolite, P = 7.3 × 10−8] and aminoadipate (−0.11 cm per SD increment, P = 2.61 × 10−5) were associated with left ventricular diastolic dimension, phosphatidylcholine (carbon:double bound = 38:6) with left atrial dimension (0.10 cm per SD increment, P = 9.7 × 10−6), and cholesterol ester (carbon:double bound = 20:5) with left atrial dimension (0.10 cm per SD increment, P = 1.4 × 10−5) in multivariable‐adjusted models. During an average follow‐up of 15.8 (range 0.02–23.2) years, 113 participants (5%) were diagnosed with HF with reduced ejection fraction and 106 individuals (5%) with HF with preserved ejection fraction. In multivariable analyses, concentrations of phosphatidylcholine (hazard ratio 0.63, P = 1.3 × 10−5) and ornithine (hazard ratio 1.44, P = 0.00014) were associated with HF with reduced ejection fraction. Conclusions: Several metabolites, including the vasoactive metabolite kynurenine, were related to cardiac structure and function in our sample. Additional research is warranted to confirm our observations and investigate if these metabolites can risk stratify ambulatory individuals. [ABSTRACT FROM AUTHOR]

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 is importantly 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 c 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 that HCP is a promising lead compound for development of an intramuscular injectable cyanide antidote for mass casualty scenarios. [ABSTRACT FROM AUTHOR]

Introduction: Metabolite, lipid, and lipoprotein lipid profiling can provide novel insights into mechanisms underlying incident dementia and Alzheimer's disease. Methods: We studied eight prospective cohorts with 22,623 participants profiled by nuclear magnetic resonance or mass spectrometry metabolomics. Four cohorts were used for discovery with replication undertaken in the other four to avoid false positives. For metabolites that survived replication, combined association results are presented. Results: Over 246,698 person‐years, 995 and 745 cases of incident dementia and Alzheimer's disease were detected, respectively. Three branched‐chain amino acids (isoleucine, leucine, and valine), creatinine and two very low density lipoprotein (VLDL)‐specific lipoprotein lipid subclasses were associated with lower dementia risk. One high density lipoprotein (HDL; the concentration of cholesterol esters relative to total lipids in large HDL) and one VLDL (total cholesterol to total lipids ratio in very large VLDL) lipoprotein lipid subclass was associated with increased dementia risk. Branched‐chain amino acids were also associated with decreased Alzheimer's disease risk and the concentration of cholesterol esters relative to total lipids in large HDL with increased Alzheimer's disease risk. Discussion: Further studies can clarify whether these molecules play a causal role in dementia pathogenesis or are merely markers of early pathology. [ABSTRACT FROM AUTHOR]

Introduction The identification of novel biomarkers associated with Alzheimer's disease (AD) could provide key biological insights and permit targeted preclinical prevention. We investigated circulating metabolites associated with incident dementia and AD using metabolomics. Methods Plasma levels of 217 metabolites were assessed in 2067 dementia-free Framingham Offspring Cohort participants (mean age = 55.9 ± 9.7 years; 52.4% women). We studied their associations with future dementia and AD risk in multivariate Cox models. Results Ninety-three participants developed incident dementia (mean follow-up = 15.6 ± 5.2 years). Higher plasma anthranilic acid levels were associated with greater risk of dementia (hazard ratio [HR] = 1.40; 95% confidence interval [CI] = [1.15–1.70]; P = 8.08 × 10 −4 ). Glutamic acid (HR = 1.38; 95% CI = [1.11–1.72]), taurine (HR = 0.74; 95% CI = [0.60–0.92]), and hypoxanthine (HR = 0.74; 95% CI = [0.60–0.92]) levels also showed suggestive associations with dementia risk. Discussion We identified four biologically plausible, candidate plasma biomarkers for dementia. Association of anthranilic acid implicates the kynurenine pathway, which modulates glutamate excitotoxicity. The associations with hypoxanthine and taurine strengthen evidence that uric acid and taurine may be neuroprotective. [ABSTRACT FROM AUTHOR]

Aims. We investigated the relationship between circulating amino acid levels and obesity; to what extent weight loss followed by weight maintenance can correct amino acid abnormalities; and whether amino acids are related to weight loss. Methods. Amino acids associated with waist circumference (WC) and BMI were studied in 804 participants from the Malmö Diet and Cancer Cardiovascular Cohort (MDC-CC). Changes in amino acid levels were analyzed after weight loss and weight maintenance in 12 obese subjects and evaluated in a replication cohort (n=83). Results. Out of the eight identified BMI-associated amino acids from the MDC-CC, alanine, isoleucine, tyrosine, phenylalanine, and glutamate decreased after weight loss, while asparagine increased after weight maintenance. These changes were validated in the replication cohort. Scores that were constructed based on obesity-associated amino acids and known risk factors decreased in the ≥10% weight loss group with an associated change in BMI (R2=0.16–0.22, p<0.002), whereas the scores increased in the <10% weight loss group (p<0.0004). Conclusions. Weight loss followed by weight maintenance leads to differential changes in amino acid levels associated with obesity. Treatment modifiable scores based on epidemiological and interventional data may be used to evaluate the potential metabolic benefit of weight loss. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Exposure to cyanide causes a spectrum of cardiac, neurological, and metabolic dysfunctions that can be fatal. Improved cyanide antidotes are needed, but the ideal biological pathways to target are not known. To understand better the metabolic effects of cyanide and to discover novel cyanide antidotes, we developed a zebrafish model of cyanide exposure and scaled it for high-throughput chemical screening. In a screen of 3120 small molecules, we discovered 4 novel antidotes that block cyanide toxicity. The most potent antidote was riboflavin. Metabolomic profiling of cyanide-treated zebrafish revealed changes in bile acid and purine metabolism, most notably by an increase in inosine levels. Riboflavin normalizes many of the cyanide-induced neurological and metabolic perturbations in zebrafish. The metabolic effects of cyanide observed in zebrafish were conserved in a rabbit model of cyanide toxicity. Further, humans treated with nitroprusside, a drug that releases nitric oxide and cyanide ions, display increased circulating bile acids and inosine. In summary, riboflavin may be a novel treatment for cyanide toxicity and prophylactic measure during nitroprusside treatment, inosine may serve as a biomarker of cyanide exposure, and metabolites in the bile acid and purine metabolism pathways may shed light on the pathways critical to reversing cyanide toxicity. [ABSTRACT FROM AUTHOR]

Glucose ingestion after an overnight fast triggers an insulin-dependent, homeostatic program that is altered in diabetes. The full spectrum of biochemical changes associated with this transition is currently unknown. We have developed a mass spectrometry-based strategy to simultaneously measure 191 metabolites following glucose ingestion. In two groups of healthy individuals (n=22 and 25), 18 plasma metabolites changed reproducibly, including bile acids, urea cycle intermediates, and purine degradation products, none of which were previously linked to glucose homeostasis. The metabolite dynamics also revealed insulin’s known actions along four key axes—proteolysis, lipolysis, ketogenesis, and glycolysis—reflecting a switch from catabolism to anabolism. In pre-diabetics (n=25), we observed a blunted response in all four axes that correlated with insulin resistance. Multivariate analysis revealed that declines in glycerol and leucine/isoleucine (markers of lipolysis and proteolysis, respectively) jointly provide the strongest predictor of insulin sensitivity. This observation indicates that some humans are selectively resistant to insulin’s suppression of proteolysis, whereas others, to insulin’s suppression of lipolysis. Our findings lay the groundwork for using metabolic profiling to define an individual’s ‘insulin response profile’, which could have value in predicting diabetes, its complications, and in guiding therapy. [ABSTRACT FROM AUTHOR]

Background Studies in mice and small patient subsets implicate metabolic dysfunction in cardiac remodeling in aortic stenosis, but no large comprehensive studies of human metabolism in aortic stenosis with long-term follow-up and characterization currently exist. Methods and Results Within a multicenter prospective cohort study, we used principal components analysis to summarize 12 echocardiographic measures of left ventricular structure and function pre-transcatheter aortic valve implantation in 519 subjects (derivation). We used least absolute shrinkage and selection operator regression across 221 metabolites to define metabolic signatures for each structural pattern and measured their relation to death and multimorbidity in the original cohort and up to 2 validation cohorts (N=543 for overall validation). In the derivation cohort (519 individuals; median age, 84 years, 45% women, 95% White individuals), we identified 3 axes of left ventricular remodeling, broadly specifying systolic function, diastolic function, and chamber volumes. Metabolite signatures of each axis specified both known and novel pathways in hypertrophy and cardiac dysfunction. Over a median of 3.1 years (205 deaths), a metabolite score for diastolic function was independently associated with post-transcatheter aortic valve implantation death (adjusted hazard ratio per 1 SD increase in score, 1.54 [95% CI, 1.25-1.90]; P <0.001), with similar effects in each validation cohort. This metabolite score of diastolic function was simultaneously associated with measures of multimorbidity, suggesting a metabolic link between cardiac and noncardiac state in aortic stenosis. Conclusions Metabolite profiles of cardiac structure identify individuals at high risk for death following transcatheter aortic valve implantation and concurrent multimorbidity. These results call for efforts to address potentially reversible metabolic biology associated with risk to optimize post-transcatheter aortic valve implantation recovery, rehabilitation, and survival.

Background Elevated plasma levels of alpha-aminoadipic acid (2-AAA) have been associated with the development of type 2 diabetes and atherosclerosis. However, the nature of the association remains unknown. Methods and Results We identified genetic determinants of plasma 2-AAA through meta-analysis of genome-wide association study data in 5456 individuals of European, African, and Asian ancestry from the Framingham Heart Study, Diabetes Prevention Program, Jackson Heart Study, and Shanghai Women's and Men's Health Studies. No single nucleotide polymorphisms reached genome-wide significance across all samples. However, the top associations from the meta-analysis included single-nucleotide polymorphisms in the known 2-AAA pathway gene DHTKD1 , and single-nucleotide polymorphisms in genes involved in mitochondrial respiration ( NDUFS4 ) and macrophage function ( MSR1 ). We used a Mendelian randomization instrumental variable approach to evaluate relationships between 2-AAA and cardiometabolic phenotypes in large disease genome-wide association studies. Mendelian randomization identified a suggestive inverse association between increased 2-AAA and lower high-density lipoprotein cholesterol ( P =0.005). We further characterized the genetically predicted relationship through measurement of plasma 2-AAA and high-density lipoprotein cholesterol in 2 separate samples of individuals with and without cardiometabolic disease (N=98), and confirmed a significant negative correlation between 2-AAA and high-density lipoprotein ( r s =-0.53, P <0.0001). Conclusions 2-AAA levels in plasma may be regulated, in part, by common variants in genes involved in mitochondrial and macrophage function. Elevated plasma 2-AAA associates with reduced levels of high-density lipoprotein cholesterol. Further mechanistic studies are required to probe this as a possible mechanism linking 2-AAA to future cardiometabolic risk.

Background Prior studies relating proteomics markers to incident AF screened for limited numbers of proteins. Methods and Results We performed proteomics assays among participants from the Framingham Heart Study Offspring attending their fifth examination. Plasma protein levels (n=1373) were measured by the SOMAscan proteomic profiling platform. We used robust inference for the Cox proportional hazards model to relate each protein level with incident AF. In addition, we examined the association between AF-related genetic loci and levels of proteins associated with AF. Our study included 1885 participants (mean age 55±10 years, 54% women) who had proteomic profiles measured. A total of 349 participants developed AF during follow-up (mean follow-up 18.3 years). We observed that 8 proteins were significantly associated with incident AF after adjusting for age, sex, technical covariates, and correction for multiple testing ( P<0.05/1373=3.6×10 -5 ). After additional adjustments for clinical factors associated with AF, ADAMTS13 and N-terminal pro-B-type natriuretic peptide remained significantly associated with the risk of incident AF (hazard ratio, 0.78; 95% CI, 0.70-0.88; and 1.44; 95% CI, 1.22-1.70, respectively; P<3.6×10 -5 for both). None of the 8 proteins were encoded by genes at AF-related genetic loci previously identified by genome-wide association studies. Conclusions We identified 8 proteins associated with risk of incident AF after adjustment for age and sex; 2 proteins were associated with AF after adjustment for AF risk factors. Future studies are needed to replicate our findings, identify whether the markers are mechanistically related to AF development, and whether they are clinically useful for identification of future AF risk.

Background: The marked excess in cardiovascular mortality that results from uremia remains poorly understood., Methods and Results: In 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<0.0003). Oleoylcarnitine, the long-chain acylcarnitine with the strongest association with cardiovascular mortality in unadjusted analysis, remained associated with 1-year cardiovascular death after multivariable adjustment (odds ratio per SD 2.3 [95% confidence interval, 1.4 to 3.8]; P=0.001). The association between oleoylcarnitine and 1-year cardiovascular death was then replicated in an independent sample (n=300, odds ratio per SD 1.4 [95% confidence interval, 1.1 to 1.9]; P=0.008). Addition of oleoylcarnitine to clinical variables improved cardiovascular risk prediction using net reclassification (NRI, 0.38 [95% confidence interval, 0.20 to 0.56]; P<0.0001). In physiologic profiling studies, we demonstrate that the fold change in plasma acylcarnitine levels from the aorta to renal vein and from pre- to posthemodialysis samples exclude renal or dialytic clearance of long-chain acylcarnitines as confounders in our analysis., Conclusions: Our data highlight clinically meaningful alterations in acylcarnitine homeostasis at the time of dialysis initiation, which may represent an early marker, effector, or both of uremic cardiovascular risk.