Translational biomarker discovery in clinical metabolomics: an introductory tutorial

Xia, Jianguo; Broadhurst, David; Wilson, Michael; Wishart, David S.

doi:10.1007/s11306-012-0482-9

Cited by 803 publications

(759 citation statements)

References 59 publications

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“…Metabolites were considered significant if their q values were #0.2, and if their fold changes were .1.2 or ,0.8. The area under the curve (AUC) in receiver operating characteristic (ROC) analysis was calculated to evaluate the discriminating power of the metabolite markers (35). Logistic regression models were fit to evaluate the association of metabolite peak areas with the presence of DR.…”

Section: Discussionmentioning

confidence: 99%

Plasma Metabonomic Profiling of Diabetic Retinopathy

et al. 2016

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Diabetic retinopathy (DR) is the most common microvascular complication of diabetes and the leading cause of visual impairment in working-age adults. Patients with diabetes often develop DR despite appropriate control of systemic risk factors, suggesting the involvement of other pathogenic factors. We hypothesize that the plasma metabolic signature of DR is distinct and resolvable from that of diabetes alone. A nested populationbased case-control metabonomic study was first performed on 40 DR cases and 40 control subjects with diabetes using gas chromatography-mass spectrometry. Eleven metabolites were found to be correlated with DR, and the majority were robust when adjusted for metabolic risk factors and confounding kidney disease. The metabolite markers 2-deoxyribonic acid; 3,4-dihydroxybutyric acid; erythritol; gluconic acid; and ribose were validated in an independent sample set with 40 DR cases, 40 control subjects with diabetes, and 40 individuals without diabetes. DR cases and control subjects with diabetes were matched by HbA 1c in the validation set. Activation of the pentose phosphate pathway was identified from the list of DR metabolite markers. The identification of novel metabolite markers for DR provides insights into potential new pathogenic pathways for this microvascular complication and holds translational value in DR risk stratification and the development of new therapeutic measures.Diabetic retinopathy (DR) is the most common microvascular complication of diabetes and the leading cause of visual impairment in working-age adults worldwide (1,2). The global prevalence of diabetes is rising and the number of people with diabetes is projected to increase by 54% in 2030, compared with 2010 (3). The public health burden of diabetes and DR would thus increase correspondingly. The major risk factors of DR are poor glycemic control and hypertension, as well as the duration of diabetes (4,5), but their relative importance varies between studies (2,6). Although the risks of DR progression and vision loss are reduced with intensive control of risk factors (7,8), many patients with diabetes continue to develop complications despite tight glycemic and blood pressure control. There is increasing evidence to suggest that "metabolic memory" is responsible for this observation. The term metabolic memory refers to the persistent epigenetic modifications caused by early exposure to hyperglycemia that, in turn, predispose individuals to the development of diabetes complications even after good glycemic control

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Section: Discussionmentioning

confidence: 99%

Plasma Metabonomic Profiling of Diabetic Retinopathy

et al. 2016

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“…The discriminatory ability of neurogranin to correctly allocate participants to different diagnostic groups was investigated by comparisons of areas under the receiver operating characteristic (AUROCs) curves. The higher the AUROCs values the better was the discriminatory ability, as follows: "excellent" (AUROC 0.90-1.00), "good" (AUROC 0.80-0.89), "fair" (AUROC 0.70-0.79), "poor" (AUROC 0.60-0.69), or "fail"/no discriminatory capacity (AUROC 0.50-0.59) [30]. We initially calculated and compared the AUROCs for Table 1 summarizes the concentrations of CSF neurogranin and core AD biomarkers (A␤ 42 , t-tau, and p-tau) in the four study groups.…”

Section: Discussionmentioning

confidence: 99%

Cerebrospinal Fluid Neurogranin as a Biomarker of Neurodegenerative Diseases: A Cross-Sectional Study

Lista¹,

Toschi

Baldacci

et al. 2017

JAD

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Abstract. We investigated cerebrospinal fluid (CSF) concentrations of the postsynaptic biomarker neurogranin at baseline in cognitively healthy controls (HC) compared to individuals with mild cognitive impairment (MCI), patients with Alzheimer's disease (AD) dementia, and patients with frontotemporal dementia (FTD). CSF neurogranin was quantified using an in-house immunoassay in a cross-sectional multicenter study of 108 participants [AD dementia (n = 35) S. Lista et al. / CSF Neurogranin in Neurodegenerative Diseasescognitively HC (n = 23)]. CSF neurogranin concentrations were significantly higher in AD patients compared with both HC subjects and FTD patients, suggesting that increased CSF neurogranin concentrations may indicate AD-related pathophysiology. CSF neurogranin was independently associated with both total tau and hyperphosphorylated tau proteins, whereas a non-significant correlation with the 42-amino acid-long amyloid-␤ peptide was evident. CSF neurogranin, however, was not superior to core AD biomarkers in differentiating HC from the three diagnostic groups, and it did not improve their diagnostic accuracy. We conclude that further classification and longitudinal studies are required to shed more light into the potential role of neurogranin as a pathophysiological biomarker of neurodegenerative diseases.

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“…Given that we do not have an independent population to validate the biomarker model, nested cross‐validation using the Monte‐Carlo method was performed to examine the ability of a chosen model to discriminate between depressed and control patients 23. In Monte Carlo cross‐validation the study population is split into a training set (two‐thirds of study population) and a testing set (the remaining one‐third).…”

Section: Methodsmentioning

confidence: 99%

Novel Phospholipid Signature of Depressive Symptoms in Patients With Coronary Artery Disease

Chan

Suridjan

Mohammad

et al. 2018

JAHA

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BackgroundDepression in patients with coronary artery disease (CAD) is associated with increased cardiovascular morbidity. Given the proinflammatory actions of phospholipids, aberrant phospholipid metabolism may be an etiological mechanism linking CAD and depression. Our primary objective was to identify a phospholipid biomarker panel that characterizes CAD patients with significant depressive symptoms from those without.Methods and ResultsWe performed a targeted lipidomic analysis on CAD patients with significant depressive symptoms (n=37, Center for Epidemiologic Studies Depression score ≥16) and those without (n=49). Phospholipid species were selected using partial least‐square discriminant analysis, and the ability of the resulting model to discriminate between groups was evaluated using receiver operator characteristic curves. Biosignature scores were calculated from this model, and analyses of covariance were performed to compare intergroup differences in biosignature scores, with adjustment for clinical differences between patients. Those with significant depressive symptoms had lower cardiopulmonary fitness, more prevalent history of depression, and a greater number of vascular risk factors. A model of 10 phospholipid species had an area under the curve value of 0.84 (95% confidence interval 0.72‐0.95), sensitivity of 0.73, and specificity of 0.71. This model passed permutation testing (n=1000, P<0.001). Biosignature scores were higher in those with significant depressive symptoms after adjustment for potential confounders (F[1.86]=14.39, P<0.0005).ConclusionsThe present findings support the role of proinflammatory phospholipid species in the presence of depression in CAD patients from the CAROTID trial (Coronary Artery Disease Randomized Omega‐3 Trial in Depression). Future investigations should aim to replicate findings in larger data sets and clarify possible pathophysiological mechanisms.Clinical Trial Registration URL: https://www.clinicaltrials.gov. Unique identifier: NCT00981383.

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Translational biomarker discovery in clinical metabolomics: an introductory tutorial

Cited by 803 publications

References 59 publications

Plasma Metabonomic Profiling of Diabetic Retinopathy

Plasma Metabonomic Profiling of Diabetic Retinopathy

Cerebrospinal Fluid Neurogranin as a Biomarker of Neurodegenerative Diseases: A Cross-Sectional Study

Novel Phospholipid Signature of Depressive Symptoms in Patients With Coronary Artery Disease

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