Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-13T01:45:41.523Z Has data issue: false hasContentIssue false

Bias in emerging biomarkers for bipolar disorder

Published online by Cambridge University Press:  19 May 2016

A. F. Carvalho*
Affiliation:
Department of Psychiatry and Translational Psychiatry Research Group, Faculty of Medicine, Federal University of Ceará, Fortaleza, CE, Brazil
C. A. Köhler
Affiliation:
Department of Psychiatry and Translational Psychiatry Research Group, Faculty of Medicine, Federal University of Ceará, Fortaleza, CE, Brazil
B. S. Fernandes
Affiliation:
IMPACT Strategic Research Centre, Deakin University, School of Medicine and Barwon Health, Geelong - VIC, Australia Department of Biochemistry, Laboratory of Calcium Binding Proteins in the Central Nervous System, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
J. Quevedo
Affiliation:
Department of Psychiatry and Behavioral Sciences, Center for Experimental Models in Psychiatry, The University of Texas Medical School at Houston, Houston, TX, USA Laboratory of Neurosciences, Graduate Program in Health Sciences, Health Sciences Unit, University of Southern Santa Catarina, Criciúma, SC, Brazil
K. W. Miskowiak
Affiliation:
Psychiatric Centre Copenhagen, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
A. R. Brunoni
Affiliation:
Interdisciplinary Center for Applied Neuromodulation (CINA), University Hospital, University of São Paulo, São Paulo, Brazil Department and Institute of Psychiatry, Service of Interdisciplinary Neuromodulation (SIN), Laboratory of Neurosciences (LIM-27), University of São Paulo, São Paulo, Brazil
R. Machado-Vieira
Affiliation:
Laboratory of Neuroscience, LIM- 27, Institute and Department of Psychiatry, University of Sao Paulo, Sao Paulo, Brazil Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of Sao Paulo, Sao Paulo, Brazil Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, NIH, Bethesda, MD, USA
M. Maes
Affiliation:
IMPACT Strategic Research Centre, Deakin University, School of Medicine and Barwon Health, Geelong - VIC, Australia
E. Vieta
Affiliation:
Bipolar Disorders Unit, Institute of Neuroscience, Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia, Spain
M. Berk
Affiliation:
IMPACT Strategic Research Centre, Deakin University, School of Medicine and Barwon Health, Geelong - VIC, Australia Department of Psychiatry, Florey Institute of Neuroscience and Mental Health, Orygen, The National Centre of Excellence in Youth Mental Health and Orygen Youth Health Research Centre, University of Melbourne, Parkville, VIC, Australia
*
*Address for correspondence: A. F. Carvalho, MD, PhD, Department of Clinical Medicine, Faculty of Medicine, Federal University of Ceará, Rua Prof. Costa Mendes, 1608, 4 andar, 60430-040, Fortaleza, CE, Brazil. (Email: andrefc7@terra.com.br; andrefc7@hotmail.com)

Abstract

Background

To date no comprehensive evaluation has appraised the likelihood of bias or the strength of the evidence of peripheral biomarkers for bipolar disorder (BD). Here we performed an umbrella review of meta-analyses of peripheral non-genetic biomarkers for BD.

Method

The Pubmed/Medline, EMBASE and PsycInfo electronic databases were searched up to May 2015. Two independent authors conducted searches, examined references for eligibility, and extracted data. Meta-analyses in any language examining peripheral non-genetic biomarkers in participants with BD (across different mood states) compared to unaffected controls were included.

Results

Six references, which examined 13 biomarkers across 20 meta-analyses (5474 BD cases and 4823 healthy controls) met inclusion criteria. Evidence for excess of significance bias (i.e. bias favoring publication of ‘positive’ nominally significant results) was observed in 11 meta-analyses. Heterogeneity was high for (I2 ⩾ 50%) 16 meta-analyses. Only two biomarkers met criteria for suggestive evidence namely the soluble IL-2 receptor and morning cortisol. The median power of included studies, using the effect size of the largest dataset as the plausible true effect size of each meta-analysis, was 15.3%.

Conclusions

Our findings suggest that there is an excess of statistically significant results in the literature of peripheral biomarkers for BD. Selective publication of ‘positive’ results and selective reporting of outcomes are possible mechanisms.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

APA (2013). Diagnostic and Statistical Manual of Mental Disorders (DSM-5). American Psychiatric Publishing: Arlington, VA.Google Scholar
Belbasis, L, Bellou, V, Evangelou, E, Ioannidis, JP, Tzoulaki, I (2015). Environmental risk factors and multiple sclerosis: an umbrella review of systematic reviews and meta-analyses. Lancet Neurology 14, 263273.CrossRefGoogle ScholarPubMed
Berk, M, Kapczinski, F, Andreazza, AC, Dean, OM, Giorlando, F, Maes, M, Yucel, M, Gama, CS, Dodd, S, Dean, B, Magalhaes, PV, Amminger, P, McGorry, P, Malhi, GS (2011). Pathways underlying neuroprogression in bipolar disorder: focus on inflammation, oxidative stress and neurotrophic factors. Neuroscience and Biobehavioral Reviews 35, 804817.CrossRefGoogle ScholarPubMed
Birmaher, B, Gill, MK, Axelson, DA, Goldstein, BI, Goldstein, TR, Yu, H, Liao, F, Iyengar, S, Diler, RS, Strober, M, Hower, H, Yen, S, Hunt, J, Merranko, JA, Ryan, ND, Keller, MB (2014). Longitudinal trajectories and associated baseline predictors in youths with bipolar spectrum disorders. American Journal of Psychiatry 171, 990999.CrossRefGoogle ScholarPubMed
Brown, NC, Andreazza, AC, Young, LT (2014). An updated meta-analysis of oxidative stress markers in bipolar disorder. Psychiatry Research 218, 6168.CrossRefGoogle ScholarPubMed
Button, KS, Ioannidis, JP, Mokrysz, C, Nosek, BA, Flint, J, Robinson, ES, Munafo, MR (2013). Power failure: why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience 14, 365376.CrossRefGoogle ScholarPubMed
Cuijpers, P, Smit, F, Bohlmeijer, E, Hollon, SD, Andersson, G (2010). Efficacy of cognitive-behavioural therapy and other psychological treatments for adult depression: meta-analytic study of publication bias. British Journal of Psychiatry 196, 173178.CrossRefGoogle ScholarPubMed
Cuthbert, BN (2014). The RDoC framework: facilitating transition from ICD/DSM to dimensional approaches that integrate neuroscience and psychopathology. World Psychiatry 13, 2835.CrossRefGoogle ScholarPubMed
Dargel, AA, Godin, O, Kapczinski, F, Kupfer, DJ, Leboyer, M (2015). C-reactive protein alterations in bipolar disorder: a meta-analysis. Journal of Clinical Psychiatry 76, 142150.CrossRefGoogle ScholarPubMed
Davis, J, Maes, M, Andreazza, A, McGrath, JJ, Tye, SJ, Berk, M (2015). Towards a classification of biomarkers of neuropsychiatric disease: from encompass to compass. Molecular Psychiatry 20, 152153.CrossRefGoogle ScholarPubMed
Diniz, BS, Sibille, E, Ding, Y, Tseng, G, Aizenstein, HJ, Lotrich, F, Becker, JT, Lopez, OL, Lotze, MT, Klunk, WE, Reynolds, CF, Butters, MA (2015). Plasma biosignature and brain pathology related to persistent cognitive impairment in late-life depression. Molecular Psychiatry 20, 594601.CrossRefGoogle ScholarPubMed
Dupont, WD, Plummer, WD Jr. (1990). Power and sample size calculations. A review and computer program. Controlled Clinical Trials 11, 116128.CrossRefGoogle ScholarPubMed
Egger, M, Davey Smith, G, Schneider, M, Minder, C (1997). Bias in meta-analysis detected by a simple, graphical test. British Medical Journal 315, 629634.CrossRefGoogle ScholarPubMed
Fava, GA (2014). Road to nowhere. World Psychiatry 13, 4950.CrossRefGoogle ScholarPubMed
Fava, GA, Guidi, J, Grandi, S, Hasler, G (2014). The missing link between clinical states and biomarkers in mental disorders. Psychotherapy and Psychosomatics 83, 136141.CrossRefGoogle ScholarPubMed
Fernandes, BS, Gama, CS, Cereser, KM, Yatham, LN, Fries, GR, Colpo, G, de Lucena, D, Kunz, M, Gomes, FA, Kapczinski, F (2011). Brain-derived neurotrophic factor as a state-marker of mood episodes in bipolar disorders: a systematic review and meta-regression analysis. Journal of Psychiatric Research 45, 9951004.CrossRefGoogle ScholarPubMed
Fernandes, BS, Steiner, J, Berk, M, Molendijk, ML, Gonzalez-Pinto, A, Turck, CW, Nardin, P, Goncalves, CA (2015). Peripheral brain-derived neurotrophic factor in schizophrenia and the role of antipsychotics: meta-analysis and implications. Molecular Psychiatry 20, 11081119.CrossRefGoogle ScholarPubMed
First, MB (2014). Preserving the clinician-researcher interface in the age of RDoC: the continuing need for DSM-5/ICD-11 characterization of study populations. World Psychiatry 13, 5354.CrossRefGoogle ScholarPubMed
Flint, J, Cuijpers, P, Horder, J, Koole, SL, Munafo, MR (2015). Is there an excess of significant findings in published studies of psychotherapy for depression? Psychological Medicine 45, 439446.CrossRefGoogle ScholarPubMed
Frey, BN, Andreazza, AC, Houenou, J, Jamain, S, Goldstein, BI, Frye, MA, Leboyer, M, Berk, M, Malhi, GS, Lopez-Jaramillo, C, Taylor, VH, Dodd, S, Frangou, S, Hall, GB, Fernandes, BS, Kauer-Sant'Anna, M, Yatham, LN, Kapczinski, F, Young, LT (2013). Biomarkers in bipolar disorder: a positional paper from the International Society for Bipolar Disorders Biomarkers Task Force. Australian and New Zealand Journal of Psychiatry 47, 321332.CrossRefGoogle ScholarPubMed
Fusar-Poli, P, Radua, J, Frascarelli, M, Mechelli, A, Borgwardt, S, Di Fabio, F, Biondi, M, Ioannidis, JP, David, SP (2014). Evidence of reporting biases in voxel-based morphometry (VBM) studies of psychiatric and neurological disorders. Human Brain Mapping 35, 30523065.CrossRefGoogle ScholarPubMed
Girshkin, L, Matheson, SL, Shepherd, AM, Green, MJ (2014). Morning cortisol levels in schizophrenia and bipolar disorder: a meta-analysis. Psychoneuroendocrinology 49, 187206.CrossRefGoogle ScholarPubMed
Goldstein, BI, Young, LT (2013). Toward clinically applicable biomarkers in bipolar disorder: focus on BDNF, inflammatory markers, and endothelial function. Current Psychiatry Reports 15, 425.CrossRefGoogle ScholarPubMed
Higgins, J, Green, S (2013). Cochrane Handbook for systematic reviews of interventions, version 5.0. 2 (updated September 2009). The Cochrane Collaboration, 2009 (http://www.cochrane-handbook.org/). Accessed 18 August 2014.Google Scholar
Higgins, JP (2008). Commentary: Heterogeneity in meta-analysis should be expected and appropriately quantified. International Journal of Epidemiology 37, 11581160.CrossRefGoogle ScholarPubMed
Higgins, JP, Thompson, SG (2002). Quantifying heterogeneity in a meta-analysis. Statistics in Medicine 21, 15391558.CrossRefGoogle ScholarPubMed
Higgins, JP, Thompson, SG, Spiegelhalter, DJ (2009). A re-evaluation of random-effects meta-analysis. Journal of the Royal Statistical Society. Series A (Statistics in Society) 172, 137159.CrossRefGoogle ScholarPubMed
Huedo-Medina, TB, Sánchez-Meca, J, Marin-Martinez, F, Botella, J (2006). Assessing heterogeneity in meta-analysis: Q statistic or I2 index? Psychological Methods 11, 193.CrossRefGoogle ScholarPubMed
Insel, TR, Landis, SC (2013). Twenty-five years of progress: the view from NIMH and NINDS. Neuron 80, 561567.CrossRefGoogle ScholarPubMed
Ioannidis, JP (2005). Why most published research findings are false. PLoS Medicine 2, e124.CrossRefGoogle ScholarPubMed
Ioannidis, JP (2013). Clarifications on the application and interpretation of the test for excess significance and its extensions. Journal of Mathematical Psychology 57, 184187.CrossRefGoogle Scholar
Ioannidis, JP, Panagiotou, OA (2011). Comparison of effect sizes associated with biomarkers reported in highly cited individual articles and in subsequent meta-analyses. Journal of the American Medical Association 305, 22002210.CrossRefGoogle ScholarPubMed
Ioannidis, JP, Tarone, R, McLaughlin, JK (2011). The false-positive to false-negative ratio in epidemiologic studies. Epidemiology 22, 450456.CrossRefGoogle ScholarPubMed
Ioannidis, JP, Trikalinos, TA (2007). An exploratory test for an excess of significant findings. Clinical Trials (London, England) 4, 245253.CrossRefGoogle ScholarPubMed
Janelidze, S, Ventorp, F, Erhardt, S, Hansson, O, Minthon, L, Flax, J, Samuelsson, M, Traskman-Bendz, L, Brundin, L (2013). Altered chemokine levels in the cerebrospinal fluid and plasma of suicide attempters. Psychoneuroendocrinology 38, 853862.CrossRefGoogle ScholarPubMed
Kapur, S, Phillips, AG, Insel, TR (2012). Why has it taken so long for biological psychiatry to develop clinical tests and what to do about it? Molecular Psychiatry 17, 11741179.CrossRefGoogle Scholar
Lin, PY (2009). State-dependent decrease in levels of brain-derived neurotrophic factor in bipolar disorder: a meta-analytic study. Neuroscience Letters 466, 139143.CrossRefGoogle ScholarPubMed
Looney, SW, el-Mallakh, RS (1997). Meta-analysis of erythrocyte Na,K-ATPase activity in bipolar illness. Depression and Anxiety 5, 5365.3.0.CO;2-6>CrossRefGoogle ScholarPubMed
McGorry, P, Keshavan, M, Goldstone, S, Amminger, P, Allott, K, Berk, M, Lavoie, S, Pantelis, C, Yung, A, Wood, S, Hickie, I (2014). Biomarkers and clinical staging in psychiatry. World Psychiatry 13, 211223.CrossRefGoogle ScholarPubMed
Modabbernia, A, Taslimi, S, Brietzke, E, Ashrafi, M (2013). Cytokine alterations in bipolar disorder: a meta-analysis of 30 studies. Biological Psychiatry 74, 1525.CrossRefGoogle ScholarPubMed
Moher, D, Liberati, A, Tetzlaff, J, Altman, DG (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Journal of Clinical Epidemiology 62, 10061012.CrossRefGoogle ScholarPubMed
Munkholm, K, Brauner, JV, Kessing, LV, Vinberg, M (2013 a). Cytokines in bipolar disorder vs. healthy control subjects: a systematic review and meta-analysis. Journal of Psychiatric Research 47, 11191133.CrossRefGoogle ScholarPubMed
Munkholm, K, Vinberg, M, Vedel Kessing, L (2013 b). Cytokines in bipolar disorder: a systematic review and meta-analysis. Journal of Affective Disorders 144, 1627.CrossRefGoogle ScholarPubMed
Murck, H, Laughren, T, Lamers, F, Picard, R, Walther, S, Goff, D, Sainati, S (2015). Taking personalized medicine seriously: biomarker approaches in phase IIb/III studies in major depression and schizophrenia. Innovations in Clinical Neuroscience 12, 26s40s.Google ScholarPubMed
Parnas, J (2014). The RDoC program: psychiatry without psyche? World Psychiatry 13, 4647.CrossRefGoogle ScholarPubMed
Phillips, ML, Chase, HW, Sheline, YI, Etkin, A, Almeida, JR, Deckersbach, T, Trivedi, MH (2015). Identifying predictors, moderators, and mediators of antidepressant response in major depressive disorder: neuroimaging approaches. American Journal of Psychiatry 172, 124138.CrossRefGoogle ScholarPubMed
Polyakova, M, Stuke, K, Schuemberg, K, Mueller, K, Schoenknecht, P, Schroeter, ML (2015). BDNF as a biomarker for successful treatment of mood disorders: a systematic & quantitative meta-analysis. Journal of Affective Disorders 174, 432440.CrossRefGoogle ScholarPubMed
Rosa, AR, Singh, N, Whitaker, E, de Brito, M, Lewis, AM, Vieta, E, Churchill, GC, Geddes, JR, Goodwin, GM (2014). Altered plasma glutathione levels in bipolar disorder indicates higher oxidative stress; a possible risk factor for illness onset despite normal brain-derived neurotrophic factor (BDNF) levels. Psychological Medicine 44, 24092418.CrossRefGoogle ScholarPubMed
Scola, G, Andreazza, AC (2014). Current state of biomarkers in bipolar disorder. Current Psychiatry Reports 16, 514.CrossRefGoogle ScholarPubMed
Sistrom, CL, Mergo, PJ (2000). A simple method for obtaining original data from published graphs and plots. American Journal of Roentgenology 174, 12411244.CrossRefGoogle ScholarPubMed
Teixeira, AL, Barbosa, IG, Machado-Vieira, R, Rizzo, LB, Wieck, A, Bauer, ME (2013). Novel biomarkers for bipolar disorder. Expert Opinion on Medical Diagnostics 7, 147159.CrossRefGoogle ScholarPubMed
Tsilidis, KK, Papatheodorou, SI, Evangelou, E, Ioannidis, JP (2012). Evaluation of excess statistical significance in meta-analyses of 98 biomarker associations with cancer risk. Journal of the National Cancer Institute 104, 18671878.CrossRefGoogle ScholarPubMed
Tzoulaki, I, Siontis, KC, Evangelou, E, Ioannidis, JP (2013). Bias in associations of emerging biomarkers with cardiovascular disease. JAMA Internal Medicine 173, 664671.CrossRefGoogle ScholarPubMed
Vieta, E (2014). The bipolar maze: a roadmap through translational psychopathology. Acta Psychiatrica Scandinavica 129, 323327.CrossRefGoogle Scholar
WHO (1992). The ICD-10 Classification of Mental and Behavioural Disorders: Clinical Descriptions and Diagnostic Guidelines. World Health Organization: Geneva.Google Scholar
Young, SS, Bang, H (2004). The file-drawer problem, revisited. Science 306, 11331134; author reply 1133–1134.CrossRefGoogle ScholarPubMed
Supplementary material: File

Carvalho supplementary material

Tables S1-S2

Download Carvalho supplementary material(File)
File 38.4 KB