Multianalyte markers of schizophrenia and bipolar disorder: A preliminary study

Dickerson, Faith; Schroeder, Jennifer R.; Stallings, Cassie; Origoni, Andrea; Bahn, Sabine; Yolken, Robert H.

doi:10.1016/j.schres.2015.08.003

Cited by 12 publications

(11 citation statements)

References 25 publications

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“…P <0.05 was considered significant. Multiple regression analysis was used to find the correlation between the selected parameters using SPSS program [4] . In this analysis R 2 describes the proportion or percentage of variance in the dependent variable explained by the variance in the independent variables together which sometimes called the predictor variables.…”

Section: Biochemical Analysesmentioning

confidence: 99%

Data of multiple regressions analysis between selected biomarkers related to glutamate excitotoxicity and oxidative stress in Saudi autistic patients

El‐Ansary

2016

Data in Brief

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This work demonstrates data of multiple regression analysis between nine biomarkers related to glutamate excitotoxicity and impaired detoxification as two mechanisms recently recorded as autism phenotypes. The presented data was obtained by measuring a panel of markers in 20 autistic patients aged 3–15 years and 20 age and gender matching healthy controls. Levels of GSH, glutathione status (GSH/GSSG), glutathione reductase (GR), glutathione-s-transferase (GST), thioredoxin (Trx), thioredoxin reductase (TrxR) and peroxidoxins (Prxs I and III), glutamate, glutamine, glutamate/glutamine ratio glutamate dehydrogenase (GDH) in plasma and mercury (Hg) in red blood cells were determined in both groups. In Multiple regression analysis, R2 values which describe the proportion or percentage of variance in the dependent variable attributed to the variance in the independent variables together were calculated. Moreover, β coefficients values which show the direction either positive or negative and the contribution of the independent variable relative to the other independent variables in explaining the variation of the dependent variable were determined. A panel of inter-related markers was recorded. This paper contains data related to and supporting research articles currently published entitled “Mechanism of nitrogen metabolism-related parameters and enzyme activities in the pathophysiology of autism” [1], “Novel metabolic biomarkers related to sulfur-dependent detoxification pathways in autistic patients of Saudi Arabia [2], and “A key role for an impaired detoxification mechanism in the etiology and severity of autism spectrum disorders” [3].

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Section: Biochemical Analysesmentioning

confidence: 99%

Data of multiple regressions analysis between selected biomarkers related to glutamate excitotoxicity and oxidative stress in Saudi autistic patients

El‐Ansary

2016

Data in Brief

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“…Moreover, previous work by our group in the maternal inflammation model showed that LPS induced foetal microglial inflammatory activation, but also pronounced reductions in foetal microglial genes involved in nervous system development and function, particularly neurite growth and formation [33]. A role for other growth factors in the pathogenesis of mood disorders has also been suggested, including a role for PDGF, which has been shown to be altered in the serum of psychiatric patients [34]. We have reported on abnormal serum levels of BDNF and PDGF in patients prone to mood disorders and thyroid autoimmunity [35,36].…”

Section: Introductionmentioning

confidence: 99%

Exaggerated Increases in Microglia Proliferation, Brain Inflammatory Response and Sickness Behaviour upon Lipopolysaccharide Stimulation in Non-Obese Diabetic Mice

McGuiness

Gibney

Beumer

et al. 2016

Neuroimmunomodulation

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The non-obese diabetic (NOD) mouse, an established model for autoimmune diabetes, shows an exaggerated reaction of pancreas macrophages to inflammatory stimuli. NOD mice also display anxiety when immune-stimulated. Chronic mild brain inflammation and a pro-inflammatory microglial activation is critical in psychiatric behaviour. Objective: To explore brain/microglial activation and behaviour in NOD mice at steady state and after systemic lipopolysaccharide (LPS) injection. Methods: Affymetrix analysis on purified microglia of pre-diabetic NOD mice (8-10 weeks) and control mice (C57BL/6 and CD1 mice, the parental non-autoimmune strain) at steady state and after systemic LPS (100 μg/kg) administration. Quantitative PCR was performed on the hypothalamus for immune activation markers (IL-1β, IFNγ and TNFα) and growth factors (BDNF and PDGF). Behavioural profiling of NOD, CD1, BALB/c and C57BL/6 mice at steady state was conducted and sickness behaviour/anxiety in NOD and CD1 mice was monitored before and after LPS injection. Results: Genome analysis revealed cell cycle/cell death and survival aberrancies of NOD microglia, substantiated as higher proliferation on BrdU staining. Inflammation signs were absent. NOD mice had a hyper-reactive response to novel environments with some signs of anxiety. LPS injection induced a higher expression of microglial activation markers, a higher brain pro-inflammatory set point (IFNγ, IDO) and a reduced expression of BDNF and PDGF after immune stimulation in NOD mice. NOD mice displayed exaggerated and prolonged sickness behaviour after LPS administration. Conclusion: After stimulation with LPS, NOD mice display an increased microglial proliferation and an exaggerated inflammatory brain response with reduced BDNF and PDGF expression and increased sickness behaviour as compared to controls.

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“…While the diagnostic accuracy using our composite marker was moderate, the obtainment of even more analytes for feature selection could potentially have generated a more accurate final biomarker. It is also possible, that other studies, which, up to now, have considered only proteins or gene expression markers separately and only in peripheral blood , could have achieved better results using a multisystem, multi‐tissue approach as we attempted in the current report.…”

Section: Discussionmentioning

confidence: 88%

“…did not analyze other tissues or body fluids than blood and focused on proteins only, one explanation for the high discriminatory power in the study may be the screening of a large quantity of potential biomarkers and the subsequent inclusion of a relatively large number of individual markers. Another study, however, analyzed a total of 166 potential individual markers and used a different data‐driven approach, arriving at a lower discriminatory property of a composite biomarker with an AUC of the ROC curve of 0.77 .…”

Section: Discussionmentioning

confidence: 99%

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A multisystem composite biomarker as a preliminary diagnostic test in bipolar disorder

Munkholm

Vinberg

Pedersen

et al. 2018

Acta Psychiatr Scand

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HE, Ekstrøm CT, Kessing LV. A multisystem composite biomarker as a preliminary diagnostic test in bipolar disorder.Objective: Diagnosis and management of bipolar disorder (BD) are limited by the absence of available laboratory tests. We aimed to combine data from different molecular levels and tissues into a composite diagnostic and state biomarker. Methods: Expression levels of 19 candidate genes in peripheral blood, plasma levels of BDNF, NT-3, IL-6 and IL-18, leukocyte counts, and urinary markers of oxidative damage to DNA and RNA were measured in 37 adult rapid-cycling patients with BD in different affective states during a 6-to 12-month period and in 40 age-and gender-matched healthy individuals in a longitudinal, repeated measures design comprising a total of 211 samples. A composite biomarker was constructed using data-driven variable selection. Results: The composite biomarker discriminated between patients with BD and healthy control individuals with an area under the receiver operating characteristic curve (AUC) of 0.83 and a sensitivity of 73% and specificity of 71% corresponding with a moderately accurate test. Discrimination between manic and depressive states had a moderate accuracy, with an AUC of 0.82 and a sensitivity of 92% and a specificity of 40%. Conclusion: Combining individual biomarkers across tissues and molecular systems could be a promising avenue for research in biomarker models in BD. Significant outcomes• For the first time, we explored the potential of combining data from different molecular levels and tissues into a composite marker of diagnosis and state.• The composite biomarker discriminated moderately well between patients with bipolar disorder and healthy control individuals and between a manic and a depressed state. Limitations• The sample size was modest considering the use of a split-sample design in developing and testing the composite marker.• Medication and differences in behaviour might have influenced the measured analytes. • Our study population consisted of patients with rapid-cycling bipolar disorder and results may therefore not be generalizable to all patients with bipolar disorder.

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Multianalyte markers of schizophrenia and bipolar disorder: A preliminary study

Cited by 12 publications

References 25 publications

Data of multiple regressions analysis between selected biomarkers related to glutamate excitotoxicity and oxidative stress in Saudi autistic patients

Data of multiple regressions analysis between selected biomarkers related to glutamate excitotoxicity and oxidative stress in Saudi autistic patients

Exaggerated Increases in Microglia Proliferation, Brain Inflammatory Response and Sickness Behaviour upon Lipopolysaccharide Stimulation in Non-Obese Diabetic Mice

A multisystem composite biomarker as a preliminary diagnostic test in bipolar disorder

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