[Show abstract][Hide abstract] ABSTRACT: While aspirin is generally effective for prevention of cardiovascular disease, considerable variation in drug response exists, resulting in some individuals displaying high on-treatment platelet reactivity. We used pharmacometabolomics to define pathways implicated in variation of response to treatment. We profiled serum samples from healthy subjects pre- and postaspirin (14 days, 81 mg/day) using mass spectrometry. We established a strong signature of aspirin exposure independent of response (15/34 metabolites changed). In our discovery (N = 80) and replication (N = 125) cohorts, higher serotonin levels pre- and postaspirin correlated with high, postaspirin, collagen-induced platelet aggregation. In a third cohort, platelets from subjects with the highest levels of serotonin preaspirin retained higher reactivity after incubation with aspirin than platelets from subjects with the lowest serotonin levels preaspirin (72 ± 8 vs. 61 ± 11%, P = 0.02, N = 20). Finally, ex vivo, serotonin strongly increased platelet reactivity after platelet incubation with aspirin (+20%, P = 4.9 × 10(-4), N = 12). These results suggest that serotonin is implicated in aspirin response variability.
CPT: pharmacometrics & systems pharmacology. 07/2014; 3:e125.
[Show abstract][Hide abstract] ABSTRACT: Previous research has shown an association between hostility and fasting glucose in African American women. Central nervous system serotonin activity is implicated both in metabolic processes and in hostility related traits.
The purpose of this study is to determine whether central nervous system serotonin influences the association between hostility and fasting glucose in African American women.
The study consisted of 119 healthy volunteers (36 African American women, 27 White women, 21 White males, and 35 African American males, mean age 34 ± 8.5 years). Serotonin related compounds were measured in cerebrospinal fluid. Hostility was measured by the Cook-Medley Hostility Scale.
Hostility was associated with fasting glucose and central nervous system serotonin related compounds in African American women only. Controlling for the serotonin related compounds significantly reduced the association of hostility to glucose.
The positive correlation between hostility and fasting glucose in African American women can partly be explained by central nervous system serotonin function.
Annals of Behavioral Medicine 05/2014; · 4.20 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: -The five amino acid (AA) signature including isoleucine (Ile), leucine (Leu), valine (Val), tyrosine (Tyr), and phenylalanine (Phe) has been associated with incident diabetes and insulin resistance. We investigated whether this same AA signature, single nucleotide polymorphisms (SNPs) in genes in their catabolic pathway, were associated with development of impaired fasting glucose (IFG) after atenolol treatment.
-Among 234 European American participants enrolled in the Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR) study and treated with atenolol for 9 weeks, we prospectively followed a nested cohort that had both metabolomics profiling and genotype data available, for the development of IFG. We assessed the association between baseline circulating levels of Ile, Leu, Val, Tyr and Phe, as well as SNPs in BCAT1 and PAH with development of IFG. All baseline AA levels were strongly associated with IFG development. Each increment in standard deviation of the five AAs was associated with the following odds ratio and 95% confidence interval for IFG based on fully adjusted model: Ile 2.29 (1.31-4.01), Leu 1.80 (1.10-2.96), Val 1.77 (1.07-2.92), Tyr 2.13 (1.20-3.78) and Phe 2.04 (1.16-3.59). The composite p value was 2x10(-5). Those with PAH (rs2245360) AA genotype had the highest incidence of IFG (p for trend=0.0003).
-Our data provide important insight into the metabolic and genetic mechanisms underlying atenolol associated adverse metabolic effects. Clinical Trial Registration-clinicaltrials.gov; Unique Identifier: NCT00246519.
[Show abstract][Hide abstract] ABSTRACT: Metabolomics, the study of metabolism at an "omic" level, has the potential to transform our understanding of mechanisms of drug action and the molecular basis for variation in drug response. It is now possible to define metabolic signatures of drug exposure that can identify pathways involved in both drug efficacy and adverse drug reactions. Additionally the "metabotype", the metabolic "signature" of a patient, is a unique identity that contains information about drug response and disease heterogeneity. The application of metabolomics for the study of drug effects and variation in drug response is creating "pharmacometabolomics", a discipline that will contribute to personalized drug therapy and will compliment pharmacogenomics by capturing environmental and microbiome influences on response to drug therapy. This field has the potential to transform pharmacology and clinical pharmacology in significant ways and will contribute to efforts for personalized therapy. This overview highlights developments in the new discipline of pharmacometabolomics.Clinical Pharmacology & Therapeutics (2013); accepted article preview online 5 November 2013 doi:10.1038/clpt.2013.217.
[Show abstract][Hide abstract] ABSTRACT: Statins reduce risk of cardiovascular disease (CVD) by decreasing plasma LDL concentrations, as well as reducing inflammation and improving endothelial function. Despite their documented efficacy, there is considerable interindividual variation in effects of statins on CVD biomarkers. In the studies summarized here we used complementary metabolomics platforms to define global effects of a statin (simvastatin) on metabolism and to identify markers indicative of mechanisms that contribute to variation in plasma LDL response to statin treatment.Clinical Pharmacology & Therapeutics (2013); accepted article preview online 14 August 2013 doi:10.1038/clpt.2013.164.
[Show abstract][Hide abstract] ABSTRACT: Background
A critical and as-yet unmet need in Alzheimer disease (AD) research is the development of novel markers that can identify individuals at risk for cognitive decline due to AD. This would aid intervention trials designed to slow the progression of AD by increasing diagnostic certainty, and provide new pathophysiologic clues and potential drug targets.
We used two metabolomics platforms (gas chromatography-time of flight mass spectrometry [GC-TOF] and liquid chromatography LC-ECA array [LC-ECA]) to measure a number of metabolites in cerebrospinal fluid (CSF) from patients with AD dementia and from cognitively normal controls. We used stepwise logistic regression models with cross-validation to assess the ability of metabolite markers to discriminate between clinically diagnosed AD participants and cognitively normal controls and we compared these data with traditional CSF Luminex immunoassay amyloid-β and tau biomarkers. Aβ and tau biomarkers had high accuracy to discriminate cases and controls (testing area under the curve: 0.92). The accuracy of GC-TOF metabolites and LC-ECA metabolites by themselves to discriminate clinical AD participants from controls was high (testing area under the curve: 0.70 and 0.96, respectively).
Our study identified several CSF small-molecule metabolites that discriminated especially well between clinically diagnosed AD and control groups. They appear to be suitable for further confirmatory and validation studies, and show the potential to provide predictive performance for AD.
[Show abstract][Hide abstract] ABSTRACT: Although aspirin is a well-established antiplatelet agent, the mechanisms of aspirin resistance remain poorly understood. Metabolomics allows for measurement of hundreds of small molecules in biological samples, enabling detailed mapping of pathways involved in drug response. We defined the metabolic signature of aspirin exposure in subjects from the Heredity and Phenotype Intervention Heart Study. Many metabolites, including known aspirin catabolites, changed on exposure to aspirin, and pathway enrichment analysis identified purine metabolism as significantly affected by drug exposure. Furthermore, purines were associated with aspirin response, and poor responders had higher postaspirin adenosine and inosine levels than did good responders (n = 76; both P < 4 × 10(-3)). Using our established "pharmacometabolomics-informed pharmacogenomics" approach, we identified genetic variants in adenosine kinase associated with aspirin response. Combining metabolomics and genomics allowed for more comprehensive interrogation of mechanisms of variation in aspirin response-an important step toward personalized treatment approaches for cardiovascular disease.Clinical Pharmacology & Therapeutics (2013); advance online publication 10 July 2013. doi:10.1038/clpt.2013.119.
[Show abstract][Hide abstract] ABSTRACT: The pathogenic mechanisms of Alzheimer's disease (AD) remain largely unknown and clinical trials have not demonstrated significant benefit. Biochemical characterization of AD and its prodromal phase may provide new diagnostic and therapeutic insights. We used targeted metabolomics platform to profile cerebrospinal fluid (CSF) from AD (n=40), mild cognitive impairment (MCI, n=36) and control (n=38) subjects; univariate and multivariate analyses to define between-group differences; and partial least square-discriminant analysis models to classify diagnostic groups using CSF metabolomic profiles. A partial correlation network was built to link metabolic markers, protein markers and disease severity. AD subjects had elevated methionine (MET), 5-hydroxyindoleacetic acid (5-HIAA), vanillylmandelic acid, xanthosine and glutathione versus controls. MCI subjects had elevated 5-HIAA, MET, hypoxanthine and other metabolites versus controls. Metabolite ratios revealed changes within tryptophan, MET and purine pathways. Initial pathway analyses identified steps in several pathways that appear altered in AD and MCI. A partial correlation network showed total tau most directly related to norepinephrine and purine pathways; amyloid-beta (Ab42) was related directly to an unidentified metabolite and indirectly to 5-HIAA and MET. These findings indicate that MCI and AD are associated with an overlapping pattern of perturbations in tryptophan, tyrosine, MET and purine pathways, and suggest that profound biochemical alterations are linked to abnormal Ab42 and tau metabolism. Metabolomics provides powerful tools to map interlinked biochemical pathway perturbations and study AD as a disease of network failure.
[Show abstract][Hide abstract] ABSTRACT: In this study, we characterized early biochemical changes associated with sertraline and placebo administration and changes associated with a reduction in depressive symptoms in patients with major depressive disorder (MDD). MDD patients received sertraline or placebo in a double-blind 4-week trial; baseline, 1 week, and 4 weeks serum samples were profiled using a gas chromatography time of flight mass spectrometry metabolomics platform. Intermediates of TCA and urea cycles, fatty acids and intermediates of lipid biosynthesis, amino acids, sugars and gut-derived metabolites were changed after 1 and 4 weeks of treatment. Some of the changes were common to the sertraline- and placebo-treated groups. Changes after 4 weeks of treatment in both groups were more extensive. Pathway analysis in the sertraline group suggested an effect of drug on ABC and solute transporters, fatty acid receptors and transporters, G signaling molecules and regulation of lipid metabolism. Correlation between biochemical changes and treatment outcomes in the sertraline group suggested a strong association with changes in levels of branched chain amino acids (BCAAs), lower BCAAs levels correlated with better treatment outcomes; pathway analysis in this group revealed that methionine and tyrosine correlated with BCAAs. Lower levels of lactic acid, higher levels of TCA/urea cycle intermediates, and 3-hydroxybutanoic acid correlated with better treatment outcomes in placebo group. Results of this study indicate that biochemical changes induced by drug continue to evolve over 4 weeks of treatment and that might explain partially delayed response. Response to drug and response to placebo share common pathways but some pathways are more affected by drug treatment. BCAAs seem to be implicated in mechanisms of recovery from a depressed state following sertraline treatment.
[Show abstract][Hide abstract] ABSTRACT: Schizophrenia (SZ) is a biochemically complex disorder characterized by widespread defects in multiple metabolic pathways whose dynamic interactions, until recently, have been difficult to examine. Rather, evidence for these alterations has been collected piecemeal, limiting the potential to inform our understanding of the interactions amongst relevant biochemical pathways. We herein review perturbations in purine and neurotransmitter metabolism observed in early SZ using a metabolomic approach. Purine catabolism is an underappreciated, but important component of the homeostatic response of mitochondria to oxidant stress. We have observed a homeostatic imbalance of purine catabolism in first-episode neuroleptic-naïve patients with SZ (FENNS). Precursor and product relationships within purine pathways are tightly correlated. Although some of these correlations persist across disease or medication status, others appear to be lost among FENNS suggesting that steady formation of the antioxidant uric acid (UA) via purine catabolism is altered early in the course of illness. As is the case for within-pathway correlations, there are also significant cross-pathway correlations between respective purine and tryptophan (TRP) pathway metabolites. By contrast, purine metabolites show significant cross-pathway correlation only with tyrosine, and not with its metabolites. Furthermore, several purine metabolites (UA, guanosine, or xanthine) are each significantly correlated with 5-hydroxyindoleacetic acid (5-HIAA) in healthy controls, but not in FENNS at baseline or 4-week after antipsychotic treatment. Taken together, the above findings suggest that purine catabolism strongly associates with the TRP pathways leading to serotonin (5-hydroxytryptamine, 5-HT) and kynurenine metabolites. The lack of a significant correlation between purine metabolites and 5-HIAA, suggests alterations in key 5-HT pathways that may both be modified by and contribute to oxidative stress via purine catabolism in FENNS.
Frontiers in Cellular Neuroscience 01/2013; 7:90. · 4.47 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Therapeutic response to selective serotonin (5-HT) reuptake inhibitors in Major Depressive Disorder (MDD) varies considerably among patients, and the onset of antidepressant therapeutic action is delayed until after 2 to 4 weeks of treatment. The objective of this study was to analyze changes within methoxyindole and kynurenine (KYN) branches of tryptophan pathway to determine whether differential regulation within these branches may contribute to mechanism of variation in response to treatment. Metabolomics approach was used to characterize early biochemical changes in tryptophan pathway and correlated biochemical changes with treatment outcome. Outpatients with MDD were randomly assigned to sertraline (n = 35) or placebo (n = 40) in a double-blind 4-week trial; response to treatment was measured using the 17-item Hamilton Rating Scale for Depression (HAMD17). Targeted electrochemistry based metabolomic platform (LCECA) was used to profile serum samples from MDD patients. The response rate was slightly higher for sertraline than for placebo (21/35 [60%] vs. 20/40 [50%], respectively, χ(2)(1) = 0.75, p = 0.39). Patients showing a good response to sertraline had higher pretreatment levels of 5-methoxytryptamine (5-MTPM), greater reduction in 5-MTPM levels after treatment, an increase in 5-Methoxytryptophol (5-MTPOL) and Melatonin (MEL) levels, and decreases in the (KYN)/MEL and 3-Hydroxykynurenine (3-OHKY)/MEL ratios post-treatment compared to pretreatment. These changes were not seen in the patients showing poor response to sertraline. In the placebo group, more favorable treatment outcome was associated with increases in 5-MTPOL and MEL levels and significant decreases in the KYN/MEL and 3-OHKY/MEL; changes in 5-MTPM levels were not associated with the 4-week response. These results suggest that recovery from a depressed state due to treatment with drug or with placebo could be associated with preferential utilization of serotonin for production of melatonin and 5-MTPOL.
PLoS ONE 01/2013; 8(7):e68283. · 3.53 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Antihypertensive drugs are among the most commonly prescribed drugs for chronic disease worldwide. The response to antihypertensive drugs varies substantially between individuals and important factors such as race that contribute to this heterogeneity are poorly understood. In this study we use metabolomics, a global biochemical approach to investigate biochemical changes induced by the beta-adrenergic receptor blocker atenolol in Caucasians and African Americans. Plasma from individuals treated with atenolol was collected at baseline (untreated) and after a 9 week treatment period and analyzed using a GC-TOF metabolomics platform. The metabolomic signature of atenolol exposure included saturated (palmitic), monounsaturated (oleic, palmitoleic) and polyunsaturated (arachidonic, linoleic) free fatty acids, which decreased in Caucasians after treatment but were not different in African Americans (p<0.0005, q<0.03). Similarly, the ketone body 3-hydroxybutyrate was significantly decreased in Caucasians by 33% (p<0.0001, q<0.0001) but was unchanged in African Americans. The contribution of genetic variation in genes that encode lipases to the racial differences in atenolol-induced changes in fatty acids was examined. SNP rs9652472 in LIPC was found to be associated with the change in oleic acid in Caucasians (p<0.0005) but not African Americans, whereas the PLA2G4C SNP rs7250148 associated with oleic acid change in African Americans (p<0.0001) but not Caucasians. Together, these data indicate that atenolol-induced changes in the metabolome are dependent on race and genotype. This study represents a first step of a pharmacometabolomic approach to phenotype patients with hypertension and gain mechanistic insights into racial variability in changes that occur with atenolol treatment, which may influence response to the drug.
PLoS ONE 01/2013; 8(3):e57639. · 3.53 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: There is a critical need for mapping early metabolic changes in schizophrenia to capture failures in regulation of biochemical pathways and networks. This information could provide valuable insights about disease mechanisms, trajectory of disease progression, and diagnostic biomarkers. We used a lipidomics platform to measure individual lipid species in 20 drug-naïve patients with a first episode of schizophrenia (FE group), 20 patients with chronic schizophrenia that had not adhered to prescribed medications (RE group), and 29 race-matched control subjects without schizophrenia. Lipid metabolic profiles were evaluated and compared between study groups and within groups before and after treatment with atypical antipsychotics, risperidone and aripiprazole. Finally, we mapped lipid profiles to n3 and n6 fatty acid synthesis pathways to elucidate which enzymes might be affected by disease and treatment. Compared to controls, the FE group showed significant down-regulation of several n3 polyunsaturated fatty acids (PUFAs), including 20:5n3, 22:5n3, and 22:6n3 within the phosphatidylcholine and phosphatidylethanolamine lipid classes. Differences between FE and controls were only observed in the n3 class PUFAs; no differences where noted in n6 class PUFAs. The RE group was not significantly different from controls, although some compositional differences within PUFAs were noted. Drug treatment was able to correct the aberrant PUFA levels noted in FE patients, but changes in re patients were not corrective. Treatment caused increases in both n3 and n6 class lipids. These results supported the hypothesis that phospholipid n3 fatty acid deficits are present early in the course of schizophrenia and tend not to persist throughout its course. These changes in lipid metabolism could indicate a metabolic vulnerability in patients with schizophrenia that occurs early in development of the disease.
PLoS ONE 01/2013; 8(7):e68717. · 3.53 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: We have shown that lithium treatment improves motor coordination in a spinocerebellar ataxia type 1 (SCA1) disease mouse model (Sca1(154Q/+) ). To learn more about disease pathogenesis and molecular contributions to the neuroprotective effects of lithium, we investigated metabolomic profiles of cerebellar tissue and plasma from SCA1-model treated and untreated mice. Metabolomic analyses of wild-type and Sca1(154Q/+) mice, with and without lithium treatment, were performed using gas chromatography time-of-flight mass spectrometry and BinBase mass spectral annotations. We detected 416 metabolites, of which 130 were identified. We observed specific metabolic perturbations in Sca1(154Q/+) mice and major effects of lithium on metabolism, centrally and peripherally. Compared to wild-type, Sca1(154Q/+) cerebella metabolic profile revealed changes in glucose, lipids, and metabolites of the tricarboxylic acid cycle and purines. Fewer metabolic differences were noted in Sca1(154Q/+) mouse plasma versus wild-type. In both genotypes, the major lithium responses in cerebellum involved energy metabolism, purines, unsaturated free fatty acids, and aromatic and sulphur-containing amino acids. The largest metabolic difference with lithium was a 10-fold increase in ascorbate levels in wild-type cerebella (p<0.002), with lower threonate levels, a major ascorbate catabolite. In contrast, Sca1(154Q/+) mice that received lithium showed no elevated cerebellar ascorbate levels. Our data emphasize that lithium regulates a variety of metabolic pathways, including purine, oxidative stress and energy production pathways. The purine metabolite level, reduced in the Sca1(154Q/+) mice and restored upon lithium treatment, might relate to lithium neuroprotective properties.
PLoS ONE 01/2013; 8(8):e70610. · 3.53 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Targeted metabolomics provides an approach to quantify metabolites involved in specific molecular pathways. We applied an electrochemistry-based, targeted metabolomics platform to define changes in tryptophan, tyrosine, purine and related pathways in the depressed and remitted phases of major depressive disorder (MDD). Biochemical profiles in the cerebrospinal fluid of unmedicated depressed (n514; dMDD) or remitted MDD subjects (n514; rMDD) were compared against those in healthy controls (n518; HC). The rMDD group showed differences in tryptophan and tyrosine metabolism relative to the other groups. The rMDD group also had higher methionine levels and larger methionine-to-glutathione ratios than the other groups, implicating methylation and oxidative stress pathways. The dMDD sample showed nonsignificant differences in the same direction in several of the metabolic branches assessed. The reductions in metabolites associated with tryptophan and tyrosine pathways in rMDD may relate to the vulnerability this population shows for developing depressive symptoms under tryptophan or catecholamine depletion.
[Show abstract][Hide abstract] ABSTRACT: Plasmalogens are a subclass of glycerophospholipids and ubiquitous constituents of cellular membranes and serum lipoproteins. Several neurological disorders show decreased level of plasmogens. An earlier study found differences in plasma phospholipids between unmedicated patients with schizophrenia and matched healthy control subjects. We here report a comparison of plasma plasmalogen levels across 20 drug-naïve patients experiencing first psychotic episodes, 20 recently unmedicated patients experiencing psychotic relapses after failing to comply with prescribed medications, and 17 matched healthy control subjects. Multiple plasma phosphatidylcholine and phosphatidylethanolamine plasmalogen levels were significantly lower in first episode patients and patients with recurrent disease compared to healthy controls. Reduced plasmalogen levels appear to be a trait evident at the onset of psychotic illness and after multiple psychotic relapses. It is implied that reductions in plasmalogen levels are not related to antipsychotic treatment but due to the illness itself. Reduced plasmalogen levels suggest impairments in membrane structure and function in patients with schizophrenia that might happen early in development. This may serve as a clue to the neurobiology of schizophrenia and should be studied as a potential biomarker for individuals at risk for schizophrenia.
[Show abstract][Hide abstract] ABSTRACT: We set out to test the hypothesis that pharmacometabolomic data could be efficiently merged with pharmacogenomic data by single-nucleotide polymorphism (SNP) imputation of metabolomic-derived pathway data on a 'scaffolding' of genome-wide association (GWAS) SNP data to broaden and accelerate 'pharmacometabolomics-informed pharmacogenomic' studies by eliminating the need for initial genotyping and by making broader SNP association testing possible.
We previously genotyped 131 tag SNPs for six genes encoding enzymes in the glycine synthesis and degradation pathway using DNA from 529 depressed patients treated with citalopram/escitalopram to pursue a glycine metabolomics 'signal' associated with selective serotonine reuptake inhibitor response. We identified a significant SNP in the glycine dehydrogenase gene. Subsequently, GWAS SNP data were generated for the same patients. In this study, we compared SNP imputation within 200 kb of these same six genes with the results of the previous tag SNP strategy as a rapid strategy for merging pharmacometabolomic and pharmacogenomic data.
Imputed genotype data provided greater coverage and higher resolution than did tag SNP genotyping, with a higher average genotype concordance between genotyped and imputed SNP data for '1000 Genomes' (96.4%) than HapMap 2 (93.2%) imputation. Many low P-value SNPs with novel locations within genes were observed for imputed compared with tag SNPs, thus altering the focus for subsequent functional genomic studies.
These results indicate that the use of GWAS data to impute SNPs for genes in pathways identified by other 'omics' approaches makes it possible to rapidly and cost efficiently identify SNP markers to 'broaden' and accelerate pharmacogenomic studies.
Pharmacogenetics and Genomics 02/2012; 22(4):247-53. · 3.61 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The omega-3 fatty acid (FA) concentration is low in patients with coronary heart disease (CHD). Supplement of omega-3 FA improves cardiovascular outcomes in patients with CHD and heart failure (HF). However, plasma omega-3 FA and its role for prognosis in HF patients have not been examined previously. In this study, we explore the prognostic value of omega-3 polyunsaturated FA in HF patients with major depressive disorder (MDD). Plasma was obtained from HF patients with MDD who participated in the Sertraline Against Depression and Heart Disease in Chronic Heart Failure trial. FA methyl esters were analyzed by the method of a flame ionization detector. Weight percent is the unit of the omega compounds. The primary outcome was survival which was analyzed using Cox proportional hazards regression modeling. A total of 109 depressed HF patients had adequate volume for completion of the FA assays. Plasma total omega-3 (hazard ratio [HR] 0.65, 95% confidence interval [CI] 0.43-0.98) and EPA_(0.1 unit) (HR 0.73, 95% CI 0.56-0.96) were significantly associated with survival of patients with HF and co-morbid MDD. The results suggest that low plasma omega-3 FA is a significant factor for reduced survival in HF patients with MDD.
Journal of Cardiovascular Translational Research 02/2012; 5(1):92-9. · 3.06 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Statins are widely prescribed for reducing LDL-cholesterol (C) and risk for cardiovascular disease (CVD), but there is considerable variation in therapeutic response. We used a gas chromatography-time-of-flight mass-spectrometry-based metabolomics platform to evaluate global effects of simvastatin on intermediary metabolism. Analyses were conducted in 148 participants in the Cholesterol and Pharmacogenetics study who were profiled pre and six weeks post treatment with 40 mg/day simvastatin: 100 randomly selected from the full range of the LDL-C response distribution and 24 each from the top and bottom 10% of this distribution ("good" and "poor" responders, respectively). The metabolic signature of drug exposure in the full range of responders included essential amino acids, lauric acid (p<0.0055, q<0.055), and alpha-tocopherol (p<0.0003, q<0.017). Using the HumanCyc database and pathway enrichment analysis, we observed that the metabolites of drug exposure were enriched for the pathway class amino acid degradation (p<0.0032). Metabolites whose change correlated with LDL-C lowering response to simvastatin in the full range responders included cystine, urea cycle intermediates, and the dibasic amino acids ornithine, citrulline and lysine. These dibasic amino acids share plasma membrane transporters with arginine, the rate-limiting substrate for nitric oxide synthase (NOS), a critical mediator of cardiovascular health. Baseline metabolic profiles of the good and poor responders were analyzed by orthogonal partial least square discriminant analysis so as to determine the metabolites that best separated the two response groups and could be predictive of LDL-C response. Among these were xanthine, 2-hydroxyvaleric acid, succinic acid, stearic acid, and fructose. Together, the findings from this study indicate that clusters of metabolites involved in multiple pathways not directly connected with cholesterol metabolism may play a role in modulating the response to simvastatin treatment. TRIAL REGISTRATION: ClinicalTrials.gov NCT00451828.
PLoS ONE 01/2012; 7(7):e38386. · 3.53 Impact Factor