Frieder Haenisch1, Murtada Alsaif1, Paul C Guest1, Hassan Rahmoune1, Robert H Yolken2, Faith Dickerson3, Sabine Bahn4. 1. Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom. 2. Johns Hopkins University School of Medicine, Baltimore, USA. 3. Sheppard Pratt Health System, Baltimore, USA. Electronic address: faithbdickerson@gmail.com. 4. Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom. Electronic address: sb209@cam.ac.uk.
Abstract
BACKGROUND: The molecular understanding of bipolar disorder (BD) aetiology has advanced over the last years through the identification of peripheral disease biomarkers. Here, we have attempted to identify plasma biomarkers associated with distinct BD mood states. METHODS: Plasma from BD patients with either a current manic (n=29) or mixed (n=17) mood state and healthy controls (n=53) were analysed using a multiplex immunoassay platform. A total of 145 hormones, growth factors, transport proteins and inflammatory factors were measured. RESULTS: Plasma levels of the hormones C-peptide, progesterone and insulin, and the inflammatory protein cancer antigen 125 were altered in both mood states. The hormone peptide YY and the growth factor trafficking protein sortilin were changed only in mania patients. Finally, the inflammatory factors haptoglobin, chemokine CC4 and matrix metalloproteinase 7 were altered specifically in mixed mood patients. LIMITATIONS: This study was limited by a small sample size, potential confounding effects of multiple drug treatments in the patient groups, and lack of dietary restrictions at sampling. CONCLUSIONS: Plasma from mania and mixed mood BD patients revealed similar changes in proteins related to insulin signalling, suggesting that these could be trait biomarkers. However, mania patients showed specific changes in hormonal and growth factor functions and mixed mood patients had a higher number of changes in inflammation-related molecules. Further studies of these and other biomarker candidates will increase our understanding of the systemic biological pathways affected in different BD mood states. This could lead to the identification of differential surrogate readouts and potential new drug targets for improved treatment outcomes.
BACKGROUND: The molecular understanding of bipolar disorder (BD) aetiology has advanced over the last years through the identification of peripheral disease biomarkers. Here, we have attempted to identify plasma biomarkers associated with distinct BD mood states. METHODS: Plasma from BDpatients with either a current manic (n=29) or mixed (n=17) mood state and healthy controls (n=53) were analysed using a multiplex immunoassay platform. A total of 145 hormones, growth factors, transport proteins and inflammatory factors were measured. RESULTS: Plasma levels of the hormones C-peptide, progesterone and insulin, and the inflammatory protein cancer antigen 125 were altered in both mood states. The hormone peptide YY and the growth factor trafficking protein sortilin were changed only in maniapatients. Finally, the inflammatory factors haptoglobin, chemokine CC4 and matrix metalloproteinase 7 were altered specifically in mixed mood patients. LIMITATIONS: This study was limited by a small sample size, potential confounding effects of multiple drug treatments in the patient groups, and lack of dietary restrictions at sampling. CONCLUSIONS: Plasma from mania and mixed mood BDpatients revealed similar changes in proteins related to insulin signalling, suggesting that these could be trait biomarkers. However, maniapatients showed specific changes in hormonal and growth factor functions and mixed mood patients had a higher number of changes in inflammation-related molecules. Further studies of these and other biomarker candidates will increase our understanding of the systemic biological pathways affected in different BD mood states. This could lead to the identification of differential surrogate readouts and potential new drug targets for improved treatment outcomes.
Authors: Christoph W Turck; Paul C Guest; Giuseppina Maccarrone; Marcus Ising; Stefan Kloiber; Susanne Lucae; Florian Holsboer; Daniel Martins-de-Souza Journal: Front Mol Neurosci Date: 2017-08-31 Impact factor: 5.639
Authors: Ning O Zhao; Natasha Topolski; Massimo Tusconi; Erika M Salarda; Christopher W Busby; Camila N N C Lima; Anilkumar Pillai; Joao Quevedo; Tatiana Barichello; Gabriel R Fries Journal: Brain Behav Immun Health Date: 2022-03-05