Abstract
Background
Metabolomics, the comprehensive profile of small molecule metabolites found in biological specimens, has the potential to provide insights into the pathogenesis of disease states and lead to identification of new biomarkers.
Methods and Results
We analyzed 451 plasma metabolites by liquid chromatography/mass spectroscopy and gas chromatography/mass spectroscopy in 39 patients with primary dilated cardiomyopathy (DCM) and 31 age-, sex- and body mass index-matched controls. Sixty-one metabolites were significantly different between primary DCM and control individuals (FDR < 0.05). Plasma levels of steroid metabolites, glutamine, threonine and histidine were reduced while levels of citric acid cycle intermediates and lipid β-oxidation products were increased in patients with primary DCM as compared to controls. Medications, particularly furosemide and angiotensin-1 converting enzyme-1 inhibitors, had significant effects on the plasma metabolites. Reduced levels of glutamine in conjunction with increased 3-methyhistidine and prolylhydroxyproline levels suggested enhanced myofibrillar and collagen degradation in DCM patients. Likewise, increased stachydrine and reduced indole-3-propionate implicated a role for intestinal derived anti-oxidant molecules. Changes in steroid metabolites were notable for the loss of metabolic distinction between males and females in patients with primary DCM. Cortisol and cortisone levels were increased while androgen metabolites were decreased significantly, implying metabolic “feminization” of primary DCM males.
Conclusions
Metabolomic profiling identifies biologically active metabolites that could serve as markers of primary DCM and impart protective or harmful effects on cardiac structure and function.
Keywords: Heart Failure, Cardiomyopathy, Metabolites
Heart failure affects approximately 23 million individuals worldwide and more than five million Americans [1]. Heart failure is responsible for over one million hospitalizations and over a quarter of million deaths per year [1]. It is the only cardiovascular disease for which the incidence continues to increase [1]. During the past two decades, there have been considerable advances in the treatment of systolic heart failure. The advents of angiotensin-1 converting enzyme-1 (ACE-1) inhibitors and β blockers have reduced mortality by 20% and 30%, respectively [2-4]. Despite the advances, mortality and morbidity of patients with heart failure remain high and comparable to many cancers [1].
Primary dilated cardiomyopathy (DCM) is the prototypic form of systolic heart failure, which is characterized by cardiac dilatation in conjunction with reduced left ventricular ejection fraction (LVEF). Primary DCM, often caused by mutations in cytoskeletal and sarcomeric proteins [5]. DCM also represents common phenotypic responses of the heart to various form of injury or stress, namely, cardiac dilatation and dysfunction.
The metabolome has been defined as the complete profile of small molecule metabolites found in a specific cell, organ or organism [6]. Metabolomic analysis has the potential to provide insights into metabolic pathways in specific cells, organs or organisms [7]. Metabolomics is the high-throughput identification, quantification and characterization of the small molecule metabolites simultaneously [6]. The metabolome could represent the cumulative end product of gene expression, environmental factors and the complex multi-faceted interactions between them. It has the potential to lead to elucidation of molecular pathways involved in the pathogenesis of the phenotype and hence, identification of novel diagnostic markers and therapeutic targets. In the present study, we analyzed the plasma metabolites in patients with primary DCM and normal individuals.
METHODS
Study population
The Institutional Review Board approved the study and the participants gave informed consent. The study population included 70 individuals, comprising 39 cases with primary DCM and 31 normal individuals (controls). Primary DCM was diagnosed based on the conventional criteria of a LVEF of less than 45%, a dilated left ventricle (an end diastolic diameter of greater than 2.7 cm/m2) and no known causes of myocardial disease [8]. Accordingly, various secondary causes of heart failure including coronary artery disease and valvular diseases were excluded in order to diminish the potential confounding effects of etiological heterogeneity of heart failure. A control group of normal individuals, defined as asymptomatic age- and sex- matched individuals with normal electrocardiogram and echocardiograms was included. A normal echocardiogram excludes the diagnosis of DCM in the control individuals. To reduce the potential confounding effects of race and diabetes mellitus, the study was conducted in the Caucasians only group and those with diabetes mellitus were excluded.
Sample accessioning
Each sample was accessioned into the Metabolon, Inc. (Research Triangle, NC) Laboratory Information Management System (LIMS). Each sample was assigned by the LIMS a unique identifier. All samples were maintained at −80 °C until processed.
Metabolomic analysis
Detailed procedure for sample extraction and metabolomic analysis is described in a recent technical manuscript [9]. Briefly, the extracted sample was split for analysis on three analytical platforms, Gas Chromatography/Mass Spectroscopy (GC/MS), Ultra High Performance Liquid Chromatography (UHPLC)/MS-Positive, and UHPLC/MS-Negative. Following peak identification and quality control filtering, integrated peak ion counts for each compound in each sample were used for statistical analysis.
Statistical analysis
We analyzed the distributions of the baseline phenotypic characteristics of the study populations by Shapiro-Wilk normality test. We expressed those that followed the Gaussian distribution as mean ± SD. We compared the mean values between the two groups by Student’s t test and analyzed the non-parametric variables by Fisher exact test. The parametric variables that deviated from normality distribution were analyzed by Kuskal-Wallis test. For this set of analysis we used STATA 10.1 software for Macintosh.
The statistical analysis program “R” was used for analysis of metabolites (R Development Core Team, R Foundation for Statistical Computing, Vienna, Austria URL:http://www.R-project.org). Whenever a compound level was below the level of detection in some samples (missing values) and not others, we provided an imputed value equal to the minimum observed among all the samples of the study (including DCM and controls). While this may lead to an artificially high mean in a group with multiple imputed values, it is a conservative substitution, which underestimates the fold-change between the test and control groups. Analysts take this into account when interpreting data in the context of metabolic pathways.
The mean values for the metabolites were determined based on a table of median scaled data for each compound; i.e. each data point is divided by the median of all detected values for that compound on that day. Day-block normalization requires balanced numbers of case and control samples in each day set. To accomplish a balanced number, samples were coded such that sets of approximately 30 samples (one day’s run) contain equal numbers of cases and controls. These data sets are provided in a blinded fashion to the analytical laboratory. The day-block sets are then randomized for analysis within each day. This procedure was done to remove any day-to-day instrument drift, and as a result, each data point is represented as a fraction of the median value for that day. The fold-changes represent ratios of the means.
Welch’s two-sample t-test was performed on the log-transformed data. To account for multiple comparisons, we used the false discovery rate (FDR) method [10], and we estimated the q-value using the method of Storey and Tibshirani [11], using a cut-off point for statistical significance of <0.05 (i.e. FDR < 5%).
RESULTS
Baseline characteristics of the study populations
Baseline characteristics of the study populations including their phenotypic data are presented in Table 1. The groups were matched for age, sex, height, weight and body mass index (BMI). Per inclusion criteria, all participants were Caucasians and there was no individual with diabetes mellitus. Primary DCM patients and controls differed in several baseline characteristics including systolic blood pressure (lower in those with DCM) and the New York Heart Association (NYHA) functional class (higher in DCM). In addition, one third of patients with primary DCM were in normal sinus rhythm, as opposed to 100% of controls. There were no smokers in primary DCM group, as compared to 10% in the control group. As anticipated, patients with primary DCM were on treatment with β blockers, inhibitors of the renin-angiotensin-aldosterone system (RAAS) and diuretics (Table 1). Finally, as per study design, the echocardiographic indices of cardiac dilatation and function were significantly different between the cases and controls.
TABLE 1.
Baseline Characteristics of the Study Population
| Characteristics | Controls (normal) | Primary Dilated Cardiomyopathy |
p |
|---|---|---|---|
| N | 31 | 39 | NA |
| Male /Female (%) | 14 / 17 (45 / 55) | 18 / 21 (46 / 54) | 0.563 |
| Age (Mean ± SD) | 46.7 ± 11.1 | 48.1 ± 11.2 | 0.613 |
| Height (cm) | 171.8 ± 8.7 | 173.5 ± 11.2 | 0.491 |
| Weight (Kg) | 82.3 ± 18.8 | 83.4 ± 21.3 | 0.826 |
| BMI (Kg/m2) | 27.7 ± 5.3 | 27.5 ± 5.6 | 0.869 |
| Heart rate (bpm) | 73.1 ± 12.1 | 79.6 ± 15.8 | 0.063 |
| Systolic BP (mmHg) | 118.8 ± 9.5 | 110.4 ± 14.3 | 0.007 |
| Diastolic BP (mmHg) | 74.1 ± 7.9 | 69.6 ± 12.6 | 0.088 |
| Normal Sinus Rhythm (%) | 31 (100) | 12 (31) | <0.001 |
| Current cigarette smoking (%) |
3 (10) | 0 (0) | 0.077 |
| Class I – II (%) | 0 (0) (asymptmatic) | 18 (46) | <0.001 |
| Class III-IV (%) | 0 (0) | 21 (54) | |
| Β Blockers (%) | 0 (0) | 32 (84) | <0.001 |
| ACE – Inhibitors (%) | 1 (3) | 26 (68) | <0.001 |
| ATR blockers (%) | 0 (0) | 3 (8) | 0.176 |
| Aldosterone receptor blockers (%) |
0 (0) | 13 (34) | <0.001 |
| Furosemide (%) | 0 (0) | 26 (68) | <0.001 |
| Digoxin (%) | 0 (0) | 16 (42) | <0.001 |
| ST (mm) | 9.2 ± 1.6 | 9.6 ± 1.7 | 0.440 |
| PWT (mm) | 9.2 ± 1.6 | 10.2 ± 1.7 | 0.023 |
| LVEDD (mm) | 45.3 ± 4.5 | 62.3 ± 11.9 | 0.0001* |
| LVESD (mm) | 32.2 ± 5.3 | 51.1 ± 10.4 | 0.0003 |
| LVEF (%) | 63.9 ± 3.4 | 22.9 ± 6.8 | 0.0001* |
| LV Mass (g) | 178.1 ± 49.2 | 332.9 ± 143.5 | 0.0001* |
| LV Mass index (g/m2) | 87.7 ± 18.5 | 165.6 ± 58.7 | 0.0001* |
Abbreviations: SD: Standard deviation; cm: Centimeter; Kg: Kilogram; BMI (Kg/m2): Body mass index in Kilogram per meter square; bpm: Beats per minute; BP: Blood pressure; ACE: Angiotensin-1 converting enzyme-1; ATR: Angiotensin II receptor; ST: Septal thickness; PWT: Posterior wall thickness; LVEDD: Left ventricular end diastolic diameter; LVESD: Left ventricular end systolic diameter; LVEF: Left ventricular ejection fraction; LV Mass; left ventricular mass
Unequal variance, p values by Welch’s approximation.
Compound summary and process evaluation
451 compounds passed criteria for analytical quality control (QC), data curation, and curation QC (Online supplementary material-Table 1). 281 compounds matched a purified standard compound entry in the Metabolon@ reference library [9](Online supplementary material-Table 1) and are thus referred to as “named” compounds.. The remainder matched parent ion and fragmentation ion spectra observed recurrently in Metabolon@ plasma projects, and thus represent unnamed compounds rather than merely observable individual ions.
Analytical process control was viewed at two levels; 1) variation in the instrument process only, and 2) variation in the overall process (Online supplementary material Table 2). The median relative standard deviation (RSD = 100×CV) for measuring 30 internal standard compounds was 6.5% (variation in instrument process only). The median RSD of combined variation of all processes, including extraction, derivatization, recovery, and the instrument process for 280 compounds which were detected in a series of 24 technical replicate plasma samples embedded within the sample runs (MTRX samples), was 14.4%.
In contrast to the MTRX, the median RSD for 346 compounds detected in 80% or more of the control group study samples was 36% (i.e. process plus background biological variation), while the median RSD over all the study groups was 51.5%. The findings indicate a large phenotype contribution to the data.
Metabolomic distinction of primary DCM patients
Plasma levels of 61 named compounds were changed significantly in primary DCM patients, as compared to controls (q<0.05). Plasma levels of 41 named compounds were increased, including methylglutaroylcarnitine, taurocholenate sulfate, 4-acetamidobutanoate, alpha-ketoglutarate, pro-hydroxy-pro and cortisol, which were increased by ~ 2- to 3- fold (Table 2). In contrast, plasma levels of 20 metabolites were decreased significantly (Table 3). Among the notable reductions were plasma levels of 5α-pregnan-3 β, 20α-diol disulfate, iminodiacetate (IDA), deoxycholate, paraxanthine, and dehydroisoandrosterone sulfate (DHEA-S), which were reduced by about 50% or more (Table 3).
TABLE 2.
Plasma metabolites increased in patients with primary dilated cardiomyopathy
| HMDB ID | Super Pathway | Pathway | Name | DCM / Control |
p | q |
|---|---|---|---|---|---|---|
| HMDB03681 | Amino acid | Guanidino and acetamido metabolism |
4-acetamidobutanoate | 2.2 | 6.33947E- 06 |
0.0004 |
| HMDB04827 | Amino acid | Urea cycle; arginine-, proline-, metabolism |
Stachydrine | 2.03 | 0.0033 | 0.0112 |
|
HMDB00479,
HMDB00001 |
Amino acid | Histidine metabolism | 3-methylhistidine | 1.75 | 0.0048 | 0.0145 |
| HMDB03339 | Amino acid | Glutamate metabolism | Glutamate | 1.73 | 0.002 | 0.0087 |
| Amino acid | Glutamate metabolism | Pyroglutamine | 1.66 | 0.024 | 0.0431 | |
| HMDB06344 | Amino acid | Phenylalanine & tyrosine metabolism |
Phenylacetylglutamine | 1.64 | 0.0116 | 0.0256 |
| Amino acid | Tryptophan metabolism | C-glycosyltryptophan | 1.63 | 0.0001 | 0.0015 | |
| HMDB00755 | Amino acid | Phenylalanine & tyrosine metabolism |
3-(4-hydroxyphenyl)lactate | 1.63 | 0.0003 | 0.0024 |
| HMDB00064 | Amino acid | Creatine metabolism | Creatine | 1.56 | 0.0294 | 0.0463 |
| HMDB00407 | Amino acid | Valine, leucine and isoleucine metabolism |
Alpha-hydroxyisovalerate | 1.49 | 0.0127 | 0.0269 |
| HMDB01434 | Amino acid | Phenylalanine & tyrosine metabolism |
3-methoxytyrosine | 1.44 | 0.0134 | 0.0275 |
| HMDB00008 | Amino acid | Cysteine, methionine, SAM, taurine metabolism |
2-hydroxybutyrate (AHB) | 1.38 | 0.0244 | 0.0431 |
| HMDB00684 | Amino acid | Tryptophan metabolism | Kynurenine | 1.33 | 0.0067 | 0.0181 |
|
HMDB00336
HMDB00023 |
Amino acid | Valine, leucine and isoleucine metabolism |
3-hydroxyisobutyrate | 1.24 | 0.0276 | 0.0446 |
| HMDB00158 | Amino acid | Phenylalanine & tyrosine metabolism |
Tyrosine | 1.17 | 0.0288 | 0.046 |
| HMDB00159 | Amino acid | Phenylalanine & tyrosine metabolism |
Phenylalanine | 1.14 | 0.0211 | 0.0397 |
| HMDB00613 | Carbohydrate | Aminosugars metabolism | Erythronate | 1.37 | 0.0016 | 0.0073 |
| HMDB00243 | Carbohydrate | Glycolysis, gluconeogenesis, pyruvate metabolism |
Pyruvate | 1.31 | 0.0261 | 0.0442 |
| HMDB00169 | Carbohydrate | Fructose, mannose, galactose, starch, and sucrose metabolism |
Mannose | 1.29 | 0.0063 | 0.0173 |
| HMDB00054 | Cofactors and vitamins |
Hemoglobin and porphyrin metabolism |
Bilirubin (Z,Z) | 1.48 | 0.0336 | 0.0485 |
| HMDB00208 | Energy | Krebs cycle | Alpha-ketoglutarate | 2.04 | 0.0006 | 0.0038 |
| HMDB00156 | Energy | Krebs cycle | Malate | 1.51 | 0.0101 | 0.0233 |
| HMDB00552 | Lipid | Carnitine metabolism | Methylglutaroylcarnitine | 2.77 | 0.0003 | 0.0023 |
| Lipid | Bile acid metabolism | Taurocholenate sulfate | 2.37 | 0.0012 | 0.0063 | |
| HMDB00063 | Lipid | Sterol/Steroid | Cortisol | 1.8 | 0.0007 | 0.0041 |
| Lipid | Bile acid metabolism | Glycocholenate sulfate | 1.74 | 0.0037 | 0.0119 | |
| HMDB00211 | Lipid | Inositol metabolism | Myo-inositol | 1.69 | 0.0006 | 0.0035 |
| Lipid | Sterol/Steroid | 7-alpha-hydroxy-3-oxo-4- cholestenoate (7-Hoca) |
1.5 | 0.0002 | 0.0023 | |
| HMDB00097 | Lipid | Glycerolipid metabolism | Choline | 1.27 | 0.0002 | 0.0017 |
| Lipid | Carnitine metabolism | 3-dehydrocarnitine | 1.27 | 0.012 | 0.0257 | |
| HMDB02802 | Lipid | Sterol/Steroid | Cortisone | 1.2 | 0.0308 | 0.0474 |
| HMDB00201 | Lipid | Carnitine metabolism | Acetylcarnitine | 1.17 | 0.025 | 0.0431 |
| HMDB00767 | Nucleotide | Pyrimidine metabolism, uracil containing |
Pseudouridine | 1.55 | 3.7338E- 05 |
0.001 |
| HMDB00292 | Nucleotide | Purine metabolism, (hypo)xanthine/inosine containing |
Xanthine | 1.38 | 0.009 | 0.0213 |
| HMDB00289 | Nucleotide | Purine metabolism, urate metabolism |
Urate | 1.15 | 0.027 | 0.0446 |
| HMDB06695 | Peptide | Dipeptide | Pro-hydroxy-pro | 1.99 | 0.0002 | 0.0023 |
| Peptide | γ-glutamyl | Gamma-glutamylisoleucine | 1.27 | 0.0056 | 0.0157 | |
| Peptide | γ-glutamyl | Gamma-glutamyltyrosine | 1.26 | 0.0115 | 0.0256 | |
| HMDB00594 | Peptide | γ-glutamyl | Gamma- glutamylphenylalanine |
1.24 | 0.0197 | 0.0376 |
| Peptide | Γ-glutamyl | Gamma-glutamylvaline | 1.21 | 0.0276 | 0.0446 | |
| HMDB02994 | Xenobiotics | Sugar, sugar substitute, starch |
Erythritol | 1.66 | 0.0026 | 0.01 |
Table legend: The ratio is the mean value of each metabolite in DCM group divided to that in the control group. The mean values are based on a table of median scaled data for each compound. Accordingly, each data point is divided by the median of all detected values for that compound on that day. The procedure removes any instrument drift from day-to-day. Each data point is represented as a fraction of the median value for that day. All run days thus have the same median (1.00). The mean value is the average of all the values for the data points in a group.
TABLE 3.
Plasma metabolites decreased in patients with primary dilated cardiomyopathy
| HMDB ID | Super Pathway |
Pathway | Name | DCM / Control |
p | q |
|---|---|---|---|---|---|---|
| HMDB00641 | Amino acid | Glutamate metabolism | Glutamine | 0.9 | 0.0082 | 0.0202 |
| HMDB02302 | Amino acid | Tryptophan metabolism | Indolepropionate | 0.6 | 0.0004 | 0.0027 |
| HMDB00167 | Amino acid | Glycine, serine and threonine metabolism |
Threonine | 0.75 | 0.0001 | 0.0015 |
| HMDB00177 | Amino acid | Histidine metabolism | Histidine | 0.91 | 0.0179 | 0.0352 |
| Lipid | Sterol/Steroid | 4-androsten-3β,17β-diol monosulfate 1 |
0.59 | 0.003 | 0.0106 | |
| HMDB01032 | Lipid | Sterol/Steroid | Dehydroisoandrosterone sulfate (DHEA-S) |
0.53 | 0.0001 | 0.0011 |
| HMDB00626 | Lipid | Bile acid metabolism | Deoxycholate | 0.47 | 0.0001 | 0.0015 |
| Lipid | Sterol/Steroid | 5α-pregnan-3 β, 20 α-diol disulfate | 0.34 | 0.0101 | 0.0233 | |
| Lipid | Lysolipid | 2- Linoleoylglycerophosphoethanolam ine |
0.61 | 0.0026 | 0.01 | |
| Lipid | Sterol/Steroid | Epiandrosterone sulfate | 0.65 | 0.0021 | 0.0088 | |
| Lipid | Sterol/Steroid | Pregn steroid monosulfate | 0.66 | 0.003 | 0.0106 | |
| Lipid | Lysolipid | 1- oleoylglycerophosphoethanolamine |
0.66 | 0.0131 | 0.0273 | |
| Lipid | Lysolipid | 1-linoleoylglycerophosphocholine | 0.74 | 0.0001 | 0.0011 | |
| Lipid | Lysolipid | 1- Linoleoylglycerophosphoethanolam ine |
0.74 | 0.0018 | 0.008 | |
| HMDB02759 | Lipid | Sterol/Steroid | Androsterone sulfate | 0.75 | 0.0055 | 0.0157 |
| HMDB00772 | Lipid | Long chain fatty acid | Nonadecanoate (19:0) | 0.81 | 0.025 | 0.0431 |
| HMDB00827 | Lipid | Long chain fatty acid | Stearate (18:0) | 0.82 | 0.0269 | 0.0446 |
| Lipid | Lysolipid | 1-stearoylglycerophosphocholine | 0.85 | 0.0335 | 0.0485 | |
| HMDB11753 | Xenobiotics | Chemical | Iminodiacetate (IDA) | 0.45 | 0.004 | 0.0126 |
| HMDB01860 | Xenobiotics | Xanthine metabolism | Paraxanthine | 0.5 | 0.0021 | 0.0088 |
Sex-dependent changes in plasma metabolites in DCM patients
There were significant differences in the plasma metabolites between male and female individuals in the control group (Table 4). For example, plasma levels of 4-androsten-3β,17β-diol monosulfate 1, 4-androsten-3β,17β-diol disulfate 1, DHEA-S, 4-androsten-3β,17β-diol disulfate 2, Pregn steroid monosulfate, 5α-androstan-3β,17β-diol disulfate and Epiandrosterone sulfate were significantly different between males and females in the control group (Table 4). However, individuals with primary DCM exhibited no significant differences between males and females for these plasma metabolites (at q<0.05). That is, comparing the same plasma metabolites separately in females and males, no significant differences were detected between control and primary DCM groups for females, but the metabolites were significantly different between the control and primary DCM groups for males (Table 5). In male individuals with primary DCM, plasma metabolites of sterol/steroid pathway 4-androsten-3β,17β-diol monosulfate 1, DHEA-S, Pregn steroid monosulfate, Epiandrosterone sulfate, 1-eicosatrienoylglycerophosphocholine were significantly reduced as compared to controls. By contrast, Choline, Acetylcarnitine, Isobutyrylcarnitine, Methylglutaroylcarnitine, γ-glutamylisoleucine, γ-glutamyltyrosine, Dimethylarginine (SDMA + ADMA) and several others were increased significantly in male individuals with primary DCM (Table 5).
TABLE 4.
Absence of sex –dependent differences in the plasma metabolites levels in patients with primary dilated cardiomyopathy
| Female / Male | ||||
|---|---|---|---|---|
| Control | DCM | |||
| Name | Ratio | q | Ratio | q |
| Dehydroisoandrosterone sulfate (DHEA-S) |
0.46 | 0.0023 | 0.79 | 0.8594 |
| 4-androsten-3β,17β-diol monosulfate 1 |
0.34 | 0.0004 | 0.78 | 0.8594 |
| Epiandrosterone sulfate | 0.48 | 0.0151 | 0.77 | 0.826 |
| Pregn steroid monosulfate | 0.44 | 0.0063 | 0.76 | 0.826 |
| Pyroglutamine | 0.44 | 0.0075 | 0.66 | 0.4433 |
| Urate | 0.78 | 0.0275 | 0.84 | 0.6845 |
Table legend: Blue color indicates plasma metabolites that were significantly reduced in females as compared to males
TABLE 5.
Sex-dependent differences in the plasma metabolites according to the phenotype
| DCM / Control | ||||
|---|---|---|---|---|
| Females | Males | |||
| Name | Ratio | q | Ratio | q |
| Dehydroisoandrosterone sulfate (DHEA-S) |
0.73 | 0.0812 | 0.42 | 0.0117 |
| 4-androsten-3β,17β-diol monosulfate 1 |
0.99 | 0.4055 | 0.43 | 0.0114 |
| Epiandrosterone sulfate | 0.85 | 0.2133 | 0.53 | 0.0267 |
| Pregn steroid monosulfate | 0.91 | 0.2385 | 0.52 | 0.0267 |
| 1-linoleoylglycerophosphocholine | 0.78 | 0.0774 | 0.69 | 0.0267 |
| Acetylcarnitine | 1.06 | 0.5834 | 1.33 | 0.0367 |
| γ-glutamyltyrosine | 1.05 | 0.5306 | 1.54 | 0.0300 |
| Choline | 1.25 | 0.0774 | 1.29 | 0.0481 |
| γ-glutamylisoleucine | 1.08 | 0.5127 | 1.51 | 0.0267 |
| C-glycosyltryptophan | 1.3 | 0.2065 | 2.11 | 0.0267 |
| Pseudouridine | 1.44 | 0.0774 | 1.69 | 0.0267 |
| Myo-inositol | 1.62 | 0.1729 | 1.78 | 0.0453 |
| Pro-hydroxy-pro | 1.84 | 0.1545 | 2.18 | 0.0296 |
| 4-acetamidobutanoate | 1.81 | 0.0753 | 2.68 | 0.0367 |
| Methylglutaroylcarnitine | 2.38 | 0.1515 | 3.28 | 0.0367 |
Table legend: Blue and red colors indicate plasma metabolites that were significantly reduced or increased, respectively, in male patients with primary DCM as compared to male individuals in the control group.
Effects of medications
The majority of the individuals with primary DCM were taking β blockers, ACE inhibitors and/or furosemide (Table 1). To determine the impacts of the medications on plasma metabolites, we analyzed differences in the plasma metabolites in individuals not taking a specific drug and controls. As would be expected, removal of subjects treated with each class of medications decreased the number of metabolites that were significantly altered in primary DCM group, partly because of the effects of the medications and in part because of reduced sample size (reduced power). Treatment with β blockers had modest effects on plasma levels of metabolites. Plasma levels of 23 metabolites were significantly different between control individuals and 7 individuals with primary DCM who were not treated with β blockers (Table 6). Treatment with ACE inhibitors and furosemide had the strongest effects. Plasma level of only 1-linoleoylglycerophosphocholine was significantly reduced (~ 40%) in the cases with primary DCM not treated with ACE inhibitors (N=13) as compared to controls (N=31). Likewise, only plasma glutamine level was significantly reduced in the primary DCM individuals not treated with furosemide (N=13) as compared to controls (N=31). The complete results are shown in Table 6.
TABLE 6.
Plasma metabolites levels in patients with primary DCM that were not treated with a specific heart failure medication
| No β blockers (N=7) | No ACE inhibitor (N=13) |
No Furosemide (N=13) |
No aldosterone receptor blockers (N=36) |
No Digoxin (N=23) |
|---|---|---|---|---|
| Androsterone sulfate | 1- linoleoylglycerop hosphocholine |
Glutamine | 5alpha-pregnan-3beta,20alpha- diol disulfate |
5alpha-pregnan- 3beta,20alpha-diol disulfate |
| Dehydroisoandrosterone sulfate (DHEA-S) |
Iminodiacetate (IDA) | Stearidonate (18:4n3) | ||
| Epiandrosterone sulfate | Deoxycholate | Deoxycholate | ||
| 4-androsten-3beta,17beta- diol monosulfate 1 |
Stearidonate (18:4n3) | Iminodiacetate (IDA) | ||
| Deoxycholate | Paraxanthine | Paraxanthine | ||
| 4-androsten-3beta,17beta- diol disulfate 1 |
2- linoleoylglycerophosphoethanol amine |
Linolenate [α or γ; (18:3n3 or 6)] |
||
| Pregn steroid monosulfate | Dehydroisoandrosterone sulfate (DHEA-S) |
docosapentaenoate (n3 DPA; 22:5n3) |
||
| Histidine | Indolepropionate | Dehydroisoandrosterone sulfate (DHEA-S) |
||
| Gamma-glutamylisoleucine | 1- heptadecanoylglycerophosphoc holine |
dihomo-linoleate (20:2n6) | ||
| Acetylcarnitine | 1- oleoylglycerophosphoethanola mine |
epiandrosterone sulfate | ||
| Choline | Linolenate [α or γ; (18:3n3 or 6)] |
2- linoleoylglycerophosphoethano lamine* |
||
| 2-methylbutyroylcarnitine | γ-tocopherol | oleate (18:1n9) | ||
| Erythronate | Pregn steroid monosulfate | Linoleate (18:2n6) | ||
| Erythritol | 1- linoleoylglycerophosphocholine |
Margarate (17:0) | ||
| Pseudouridine | 1- linoleoylglycerophosphoethanol amine |
10-heptadecenoate (17:1n7) | ||
| Bilirubin (Z,Z) | Stearate (18:0) | Indolepropionate | ||
| Glycocholenate sulfate* | 1- stearoylglycerophosphocholine |
Pregn steroid monosulfate | ||
| Pro-hydroxy-pro | Linoleate (18:2n6) | Stearate (18:0) | ||
| 4-acetamidobutanoate | Nonadecanoate (19:0) | Myristate (14:0) | ||
| Myo-inositol | Threonine | 1- linoleoylglycerophosphocholin e |
||
| 3-methylhistidine | 1-oleoylglycerophosphocholine | 1- eicosatrienoylglycerophosphoc holine |
||
| Taurocholenate sulfate | Glutamine | Palmitate (16:0) | ||
| Stachydrine | Phenylalanine | 1-palmitoylglycerol (1- monopalmitin) |
||
| Methylglutaroylcarnitine | Choline | Nonadecanoate (19:0) | ||
| 7-alpha-hydroxy-3-oxo-4- cholestenoate (7-Hoca) |
Threonine | |||
| Erythronate | Dihomo-linolenate (20:3n3 or n6) |
|||
| Kynurenine | Glutamine | |||
| Pseudouridine | Choline | |||
| 2-hydroxybutyrate (AHB) | 7-α-hydroxy-3-oxo-4- cholestenoate (7-Hoca) |
|||
| 3-(4-hydroxyphenyl)lactate | Xanthine | |||
| C-glycosyltryptophan | Erythronate | |||
| 4-acetamidobutanoate | Pyruvate | |||
| Pro-hydroxy-pro | Erythritol | |||
| Creatine | Pseudouridine | |||
| 3-methylhistidine | Urea | |||
| Myo-inositol | 3-(4-hydroxyphenyl)lactate | |||
| α-ketoglutarate | C-glycosyltryptophan | |||
| Cortisol | Creatine | |||
| Glutamate | Pro-hydroxy-pro | |||
| [H]HWESASLLR[OH] | 4-acetamidobutanoate | |||
| Stachydrine | Myo-inositol | |||
| Taurocholenate sulfate | α-ketoglutarate | |||
| Methylglutaroylcarnitine | Cortisol | |||
| Taurocholenate sulfate | ||||
| Methylglutaroylcarnitine |
Figure legend: Blue and red colors indicate plasma metabolites that were reduced or increased, respectively, in patients with primary DCM who were not treated with a specific heart failure medication as compared to controls (q<0.05).
DISCUSSION
We analyzed plasma metabolites in Caucasian patients with primary DCM and detected significant differences between primary DCM patients and the control individuals. Metabolomic profile of primary DCM patients was characterized by decreased levels of steroid metabolites, glutamine, threonine and histidine and increased levels of citric acid cycle intermediates and lipid β-oxidation products. In addition, the sex-dependent differences in the plasma metabolites were largely absent in the primary DCM group. Notably, females in the control and primary DCM groups had a similar plasma metabolite profile, while, androgen metabolites, such as DHEA-S and epiandrosterone sulfate were significantly reduced in male patients with primary DCM, as compared to controls. Consequently, metabolic profile of male patients with primary DCM, as regards the androgenic metabolites, largely resembled the profile in normal females. These findings imply metabolic “feminization” of male patients with primary DCM.
Metabolism, as reflected in the metaoblome, is a dynamic process subject to the influence of numerous intrinsic and external factors, such as food intake and medications. The measurement of plasma metabolites, while practical, may only partially reflect changes in the myocardial metabolites in primary DCM. The differences in the plasma metabolites, nevertheless, strongly differentiated primary DCM patients from the controls individuals in various metabolic pathways. Plasma levels of several amino acids were reduced significantly, including glutamine, which is the most abundant amino acid in the body [12]. By contrast, plasma level of glutamate, which is converted to glutamine by the cytosolic enzyme glutamine synthetase was increased. The decrease in the glutamate/glutamine ratio may reflect suppression of glutamine synthetase enzymatic activity or the overwhelming of the capacity to produce glutamine by catabolic stress in patients with primary DCM. The biological significance of the changes in glutamate/glutamine is noteworthy, as glutamine is a key regulator of protein homeostasis and inhibits protein degradation [13]. Depletion of glutamine through inhibition of glutamine synthetase markedly reduces protein synthesis in cultured cells [14], whereas, replenishment of glutamine improves nitrogen balance during metabolic stress and limits amino acid oxidation [15]. In accord with the pivotal role of glutamine in protein homeostasis, plasma level of 3-methylhistidine, which is an index of myofibrillar protein degradation [16], was increased significantly in DCM patients. Likewise, plasma level of dipeptide prolylhydroxyproline, a marker of collagen degradation, was also increased. The changes likely reflect increased myofibrillar and collagen proteins degradation in the heart and may contribute to sarcopenia and impaired extracellular matrix (ECM) integrity in primary DCM. In addition, the changes may reflect metabolic abnormalities in skeletal muscles in patients with primary DCM, either due to shared underling mechanisms and/or secondary skeletal myopathy because of heart failure [17]. In view of these findings, one may postulate that glutamine deficiency contributes to degradation of myofibrillar and ECM proteins in patients with primary DCM and that glutamine replenishment could reverse protein degradation and influence the clinical course of heart failure.
Changes in the levels of plasma metabolites not only may reflect the molecular phenotype in metabolically active tissues but the metabolites could also impart significant biological effects on organ function. Notable among the active metabolites is indole-3-propionate (IPA), a scavenger of hydroxyl radicals, which was decreased by 40%. IPA is known to reduce cellular oxidative stress and death [18]. Hence, reduced level of IPA in DCM would be expected to increase the susceptibility of the myocardium to oxidative stress. In contrast, stachydrine or proline betaine, a phytochemical, was increased significantly in primary DCM patients. Stachydrine is a free radical scavenger that exerts protective effects in the ischemic myocardium [19]. The fascinating aspect of the findings of reduced plasma IPA in primary DCM patients is that IPA is a deamination product of tryptophan formed by symbiotic bacteria in the gastrointestinal tract. The finding suggest that in primary DCM production of IPA by the gastrointestinal bacteria is reduced, probably due to changes in the gastrointestinal microbial flora, either consequent to mucosal congestion or because of medications. The finding implicates a potential role of the gastrointestinal tract in heart failure. In accord with this notion, plasma level of α-ketoglutarate, which is produced from glutamine in the intestine, was increased and glutamine level was reduced in patients with primary DCM. The intestine utilizes glutamine as the main energy fuel in the fasting state and converts glutamine to ammonia and α-ketoglutarate via the action of intestinal glutaminase and glutamate dehydrogenase. Thus, one may speculate that intestine, through reduced generation of IPA, a cardioprotective agent, and increased utilization of glutamine, a regulator of protein homeostasis, contributes to the pathogenesis and/or progression of heart failure. This notion is in accord with the increasing recognition of the role of glut flora not only in heart failure but also in other pathological conditions [20, 21].
The majority of the primary DCM patients were taking multiple medications. Many, but not all, of the apparent metabolomic differences observed in the entire study group may be the result of treatment with heart failure medications. Among the commonly used medications, β-blockers had a minor contribution to plasma metabolome, while ACE inhibitors and furosemide had the most drastic contribution. Because of the small number of primary DCM patients who were not on a specific medication, the results in those not being treated are subject to the possibility of type II statistical error (β error). Nevertheless, glutamine was significant decreased even in those not treated with furosemide and the general trend (q= 0.05 to 0.10) remained when the analysis was performed on those not treated with medications, despite a loss of statistical significance in some cases. Overall, a number of metabolites were still significantly different between primary DCM patients and the control individuals, after exclusion of those on specific medications.
The study has several limitations. Despite our criteria for the selection of the cases and the inclusion of those without known secondary causes of cardiomyopathy, primary DCM is a genetically heterogeneous disease. The causal mutations/genes in the majority of our cases are not known but likely to encompass rare or “private” mutations in several genes. Thus, genetic heterogeneity of the cases is a potential confounder that could influence the plasma metabolome. Likewise, the use of the medications compounds the ability to discern the direct effects of primary DCM on plasma metabolites. Moreover, there were no specific controls for the content of the diet or physical activities of the participants. The study is also not designed to determine the potential effects of plasma metabolites on early identification of primary DCM patients, prognostication or individualization of their therapy. Additionally, we did not have access to cardiac tissue to correlate the changes in plasma metabolites with those in the myocardium.
Metabolomic profiling is an emerging field that has the potential to provide significant insight into cardiac metabolism under different pathological conditions [22-24]. Our findings show significant changes in plasma metabolites in patients with primary DCM, including changes in several metabolites with known active biological effects on the myocardium. The findings merit replication and studies to delineate the utility of plasma metabolites in early disease detection, prognostication and treatment of patients with heart failure.
Supplementary Material
ACKNOWLEDGEMENTS
None
SOURCES OF RESEARCH SUPPORT The authors are supported in part by grants from the National Heart, Lung, and Blood Institute, Clinician-Scientist Award in Translation Research from Burroughs Wellcome Fund (#1005907) and Greater Houston Community Foundation (TexGen)
Footnotes
DISCLOSURE Danny Alexander and Matthew Mitchells are employees of Metabolon, Inc.
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