Dataset Information

Transcriptomic biomarkers for the accurate diagnosis of myocarditis.

ABSTRACT: Lymphocytic myocarditis is a clinically important condition that is difficult to diagnose and distinguish. We hypothesized that the transcriptome obtained from an endomyocardial biopsy would yield clinically relevant and accurate molecular signatures.Microarray analysis was performed on samples from patients with histologically proven lymphocytic myocarditis (n=16) and idiopathic dilated cardiomyopathy (n=32) to develop accurate diagnostic transcriptome-based biomarkers using multiple classification algorithms. We identified 9878 differentially expressed genes in lymphocytic myocarditis versus idiopathic dilated cardiomyopathy (fold change >1.2; false discovery rate <5%) from which a transcriptome-based biomarker containing 62 genes was identified that distinguished myocarditis with 100% sensitivity (95% confidence interval, 46 to 100) and 100% specificity (95% confidence interval, 66 to 100) and was generalizable to a broad range of secondary cardiomyopathies associated with inflammation (n=27), ischemic cardiomyopathy (n=8), and the normal heart (n=11). Multiple classification algorithms and quantitative real-time reverse-transcription polymerase chain reaction analysis further reduced this subset to a highly robust molecular signature of 13 genes, which still performed with 100% accuracy.Together, these findings demonstrate that transcriptomic biomarkers from a single endomyocardial biopsy can improve the clinical detection of patients with inflammatory diseases of the heart. This approach advances the clinical management and treatment of cardiac disorders with highly variable outcome.

SUBMITTER: Heidecker B

PROVIDER: S-EPMC3408077 | biostudies-literature | 2011 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Transcriptomic biomarkers for the accurate diagnosis of myocarditis.

Heidecker Bettina B Kittleson Michelle M MM Kasper Edward K EK Wittstein Ilan S IS Champion Hunter C HC Russell Stuart D SD Hruban Ralph H RH Rodriguez E Rene ER Baughman Kenneth L KL Hare Joshua M JM

Circulation 20110307 11

<h4>Background</h4>Lymphocytic myocarditis is a clinically important condition that is difficult to diagnose and distinguish. We hypothesized that the transcriptome obtained from an endomyocardial biopsy would yield clinically relevant and accurate molecular signatures.<h4>Methods and results</h4>Microarray analysis was performed on samples from patients with histologically proven lymphocytic myocarditis (n=16) and idiopathic dilated cardiomyopathy (n=32) to develop accurate diagnostic transcrip ...[more]

PMID: 21382894

Similar Datasets

Project description:BackgroundImmune checkpoint inhibitors (ICIs) are approved for multiple cancers but can result in ICI-associated myocarditis, an infrequent but life-threatening condition. Elevations in cardiac biomarkers, specifically troponin-I (cTnI), troponin-T (cTnT), and creatine kinase (CK), are used for diagnosis. However, the association between temporal elevations of these biomarkers with disease trajectory and outcomes has not been established.MethodsWe analyzed the diagnostic accuracy and prognostic performances of cTnI, cTnT, and CK in patients with ICI myocarditis (n=60) through 1-year follow-up in 2 cardio-oncology units (APHP Sorbonne, Paris, France and Heidelberg, Germany). A total of 1751 (1 cTnT assay type), 920 (4 cTnI assay types), and 1191 CK sampling time points were available. Major adverse cardiomyotoxic events (MACE) were defined as heart failure, ventricular arrhythmia, atrioventricular or sinus block requiring pacemaker, respiratory muscle failure requiring mechanical ventilation, and sudden cardiac death. Diagnostic performance of cTnI and cTnT was also assessed in an international ICI myocarditis registry.ResultsWithin 72 hours of admission, cTnT, cTnI, and CK were increased compared with upper reference limits (URLs) in 56 of 57 (98%), 37 of 42 ([88%] P=0.03 versus cTnT), and 43 of 57 ([75%] P<0.001 versus cTnT), respectively. This increased rate of positivity for cTnT (93%) versus cTnI ([64%] P<0.001) on admission was confirmed in 87 independent cases from an international registry. In the Franco-German cohort, 24 of 60 (40%) patients developed ≥1 MACE (total, 52; median time to first MACE, 5 [interquartile range, 2-16] days). The highest value of cTnT:URL within the first 72 hours of admission performed best in terms of association with MACE within 90 days (area under the curve, 0.84) than CK:URL (area under the curve, 0.70). A cTnT:URL ≥32 within 72 hours of admission was the best cut-off associated with MACE within 90 days (hazard ratio, 11.1 [95% CI, 3.2-38.0]; P<0.001), after adjustment for age and sex. cTnT was increased in all patients within 72 hours of the first MACE (23 of 23 [100%]), whereas cTnI and CK values were less than the URL in 2 of 19 (11%) and 6 of 22 (27%) of patients (P<0.001), respectively.ConclusionscTnT is associated with MACE and is sensitive for diagnosis and surveillance in patients with ICI myocarditis. A cTnT:URL ratio <32 within 72 hours of diagnosis is associated with a subgroup at low risk for MACE. Potential differences in diagnostic and prognostic performances between cTnT and cTnI as a function of the assays used deserve further evaluation in ICI myocarditis.

Project description:A sensitive assay to identify biomarkers that can accurately diagnose the onset of breast cancer using non-invasively collected clinical specimens is ideal for early detection. In this study, we have conducted a prospective sample collection and retrospective blinded validation (PRoBE design) to evaluate the performance and translational utilities of salivary transcriptomic and proteomic biomarkers for the non-invasive detection of breast cancer. The Affymetrix HG U133 Plus 2.0 Array and 2D-DIGE were used to profile transcriptomes and proteomes in saliva supernatants respectively. Significant variations of salivary transcriptomic and proteomic profiles were observed between breast cancer patients and healthy controls. Eleven transcriptomic biomarker candidates and two proteomic biomarker candidates were selected for a preclinical validation using an independent sample set. Transcriptomic biomarkers were validated by RT-qPCR and proteomic biomarkers were validated by quantitative protein immunoblot. Eight mRNA biomarkers and one protein biomarker have been validated for breast cancer detection, yielding ROC-plot AUC values between 0.665 and 0.959. This report provides proof of concept of salivary biomarkers for the non-invasive detection of breast cancer. The salivary biomarkers’ discriminatory power paves the way for a PRoBE-design definitive validation study. Keywords: Salivary biomarker, Breast cancer, Early detection, Salivary transcriptome, Salivary proteome This study, which was approved by the UCLA and Cedars-Sinai Medical Center Institutional Review Boards (#06-07-043 and #3870, respectively), started sample collection in February 2007. The sample collection followed the PRoBE principle (prospective specimen collection). The saliva bank for breast cancer project at the UCLA Dental Research Institute in collaboration with Cedars Sinai Medical Center has collected 200 saliva samples since 2007 with all subjects recruited from the Saul and Joyce Brandman Breast Cancer Center. Of these, 113 samples, including 41 breast cancer patients and 72 healthy control individuals, were selected for the discovery and validation phase of this study. Inclusion criteria of cancer patients consisted of a confirmed diagnosis of breast cancer. Exclusion criteria of cancer patients included therapy/surgery and/or a diagnosis of other malignancies within 5 years prior to saliva collection. Exclusion criteria of control patients included a diagnosis of any malignancies within 5 years prior to saliva collection. Written informed consents and questionnaire data sheets were obtained from all patients who agreed to serve as saliva donors. Unstimulated saliva samples were consistently collected, stabilized, and preserved as previously described. The sample supernatants were reserved at -80 C prior to assay. This study consisted of a discovery phase, followed by an independent preclinical validation phase. Of the 113 samples, 10 breast cancer samples and 10 healthy control samples were chosen for the discovery phase. All breast cancer cases are invasive ductal carcinoma (IDC), the most common type of breast cancer. Biomarkers identified from the discovery studies were first verified using the discovery sample set. An independent sample set, including 31 breast cancer patients and 62 healthy control subjects, was used for the biomarker validation phase.

Project description:Broad-scale untargeted biochemical phenotyping is a technology that supplements widely accepted assays, such as organic acid, amino acid, and acylcarnitine analyses typically utilized for the diagnosis of inborn errors of metabolism. In this study, we investigate the analyte changes associated with 4-aminobutyrate aminotransferase (ABAT, GABA transaminase) deficiency and treatments that affect GABA metabolism. GABA-transaminase deficiency is a rare neurodevelopmental and neurometabolic disorder caused by mutations in ABAT and resulting in accumulation of GABA in the cerebrospinal fluid (CSF). For that reason, measurement of GABA in CSF is currently the primary approach to diagnosis. GABA-transaminase deficiency results in severe developmental delay with intellectual disability, seizures, and movement disorder, and is often associated with death in childhood. Using an untargeted metabolomics platform, we analyzed EDTA plasma, urine, and CSF specimens from four individuals with GABA-transaminase deficiency to identify biomarkers by comparing the biochemical profile of individual patient samples to a pediatric-centric population cohort. Metabolomic analyses of over 1,000 clinical plasma samples revealed a rich source of biochemical information. Three out of four patients showed significantly elevated levels of the molecule 2-pyrrolidinone (Z-score ≥2) in plasma, and whole exome sequencing revealed variants of uncertain significance in ABAT. Additionally, these same patients also had elevated levels of succinimide in plasma, urine, and CSF and/or homocarnosine in urine and CSF. In the analysis of clinical EDTA plasma samples, the levels of succinimide and 2-pyrrolidinone showed a high level of correlation (R = 0.73), indicating impairment in GABA metabolism and further supporting the association with GABA-transaminase deficiency and the pathogenicity of the ABAT variants. Further analysis of metabolomic data across our patient population revealed the association of elevated levels of 2-pyrrolidinone with administration of vigabatrin, a commonly used anti-seizure medication and a known inhibitor of GABA-transaminase. These data indicate that anti-seizure medications may alter the biochemical and metabolomic data, potentially impacting the interpretation and diagnosis for the patient. Further, these data demonstrate the power of combining broad scale genotyping and phenotyping technologies to diagnose inherited neurometabolic disorders and support the use of metabolic phenotyping of plasma to screen for GABA-transaminase deficiency.

Dataset Information

Transcriptomic biomarkers for the accurate diagnosis of myocarditis.

Publications

Transcriptomic biomarkers for the accurate diagnosis of myocarditis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets