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Diagnostics
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Biomarkers in Psychiatry
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Biomarkers in Psychiatry

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Pathology and Molecular Diagnostics".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 11280

Special Issue Editor

Dr. Cyrus S. H. Ho

E-Mail Website
Guest Editor
1. Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore
2. Department of Psychological Medicine, National University Health System, Singapore 119228, Singapore
Interests: psychiatry; biomarkers; mood disorders; neuropsychiatry; near-infrared spectroscopy

Special Issue Information

Dear Colleagues,

There is currently no standard biomarker in psychiatric disorders that complements diagnosis or predicts treatment response and prognosis. The conventional “one-drug-fits-all” approach involving trial and error inevitably delays finding the appropriate treatment and increases healthcare costs. Advances in neuroscience and technology have facilitated our understanding of psychiatric disorders as complex biological disorders with intricate interactions with the environment and expanded our search for viable biomarkers. Our hope is that our colleagues can share with the community their research in the areas of omics (genomics, proteomics, metabolomics etc.), neuroimaging, and many other modalities of measurement, which can potentially transform the practice of Psychiatry.

Dr. Cyrus S. H. Ho
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Psychiatry
  • Biomarker
  • Omics
  • Neuroimaging
  • Machine learning
  • Personalized medicine

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Published Papers (5 papers)

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Research

15 pages, 1245 KiB  
Article
Salivary Brain-Derived Neurotrophic Factor and Cortisol Associated with Psychological Alterations in University Students
by María Luisa Ballestar-Tarín, Vanessa Ibáñez-del Valle, Mayra Alejandra Mafla-España, Rut Navarro-Martínez and Omar Cauli
Diagnostics 2024, 14(4), 447; https://doi.org/10.3390/diagnostics14040447 - 18 Feb 2024
Viewed by 1588
Abstract
Introduction: Recent evidence reported mental health issues in university students such as anxiety and depressive symptoms and poor sleep quality. Decreased plasma brain-derived neurotrophic factor (BDNF) levels have been proposed as a biomarker of depressive symptoms, whereas cortisol levels are an index of [...] Read more.
Introduction: Recent evidence reported mental health issues in university students such as anxiety and depressive symptoms and poor sleep quality. Decreased plasma brain-derived neurotrophic factor (BDNF) levels have been proposed as a biomarker of depressive symptoms, whereas cortisol levels are an index of energy mobilization and stress and have been linked to sleep quality. Given that salivary biomarkers represent an interesting new field of research, the aim of this cross-sectional study was to evaluate salivary BDNF and cortisol levels in university students to assess whether they have associations with psychological disturbances such as anxiety and depressive symptoms, sleep quality, and stress level. Methods: Salivary BDNF and cortisol levels were measured by specific immunoassays in 70 students whose mental health was also evaluated on the same day through the evaluation of anxiety and depression symptoms (Goldberg scale), sleep quality (Pittsburg Sleep Quality Index and Athens Insomnia Scale), and stress (self-perceived stress scale) and healthy lifestyle habits (alcohol consumption, smoking, regular exercise, and body mass index) were also measured. Multivariate regression analyses were performed in order to identify the strengths of associations between psychological alterations and the concentrations of BDNF, cortisol, and other variables. Results: Salivary BDNF levels were significantly higher in students with more depressive symptoms, whereas no significant differences were found for cortisol levels. When performing the binary logistic regression model, BDNF levels are included as a predictor variable for a high-depressive-symptoms burden (p < 0.05). Students with worse sleep quality on the Pittsburg Scale had higher cortisol levels (p < 0.05). The subdomains of sleep latency and sleep medication were those significantly associated with salivary cortisol levels in logistic regression analyses (OR = 15.150, p = 0.028). Sleep medication only appeared to be related to cortisol levels (OR = 185.142, p = 0.019). Perceived stress levels and anxiety symptoms were not associated with BDNF or cortisol levels. Conclusions: BDNF could play a key role in the pathophysiology of mood-related disorders, and elevation of its peripheral levels could contribute to protecting neurons from the development of mental illness. Higher salivary cortisol levels measured in the morning are accompanied by poorer sleep quality. More research is needed, focusing on salivary biomarkers of disorders related to depressive symptoms and poor sleep quality as a potential tool for the diagnosis and prevention of mental illness. Full article
(This article belongs to the Special Issue Biomarkers in Psychiatry)
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16 pages, 1785 KiB  
Article
Application of Machine Learning to Diagnostics of Schizophrenia Patients Based on Event-Related Potentials
by Nadezhda Shanarova, Marina Pronina, Mikhail Lipkovich, Valery Ponomarev, Andreas Müller and Juri Kropotov
Diagnostics 2023, 13(3), 509; https://doi.org/10.3390/diagnostics13030509 - 30 Jan 2023
Cited by 5 | Viewed by 1729
Abstract
Schizophrenia is a major psychiatric disorder that significantly reduces the quality of life. Early treatment is extremely important in order to mitigate the long-term negative effects. In this paper, a machine learning based diagnostics of schizophrenia was designed. Classification models were applied to [...] Read more.
Schizophrenia is a major psychiatric disorder that significantly reduces the quality of life. Early treatment is extremely important in order to mitigate the long-term negative effects. In this paper, a machine learning based diagnostics of schizophrenia was designed. Classification models were applied to the event-related potentials (ERPs) of patients and healthy subjects performing the visual cued Go/NoGo task. The sample consisted of 200 adult individuals ranging in age from 18 to 50 years. In order to apply the machine learning models, various features were extracted from the ERPs. The process of feature extraction was parametrized through a special procedure and the parameters of this procedure were selected through a grid-search technique along with the model hyperparameters. Feature extraction was followed by sequential feature selection transformation in order to prevent overfitting and reduce the computational complexity. Various models were trained on the resulting feature set. The best model was support vector machines with a sensitivity and specificity of 91% and 90.8%, respectively. Full article
(This article belongs to the Special Issue Biomarkers in Psychiatry)
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11 pages, 644 KiB  
Article
The Plasma Levels of 3-Hydroxybutyrate, Dityrosine, and Other Markers of Oxidative Stress and Energy Metabolism in Major Depressive Disorder
by Michaela Krivosova, Eduard Gondas, Radovan Murin, Matus Dohal, Igor Ondrejka, Ingrid Tonhajzerova, Peter Hutka, Nikola Ferencova, Zuzana Visnovcova, Igor Hrtanek and Juraj Mokry
Diagnostics 2022, 12(4), 813; https://doi.org/10.3390/diagnostics12040813 - 26 Mar 2022
Cited by 10 | Viewed by 2565
Abstract
Major depressive disorder (MDD) is a serious mental disease with a pathophysiology that is not yet fully clarified. An increasing number of studies show an association of MDD with energy metabolism alteration and the presence of oxidative stress. We aimed to evaluate plasma [...] Read more.
Major depressive disorder (MDD) is a serious mental disease with a pathophysiology that is not yet fully clarified. An increasing number of studies show an association of MDD with energy metabolism alteration and the presence of oxidative stress. We aimed to evaluate plasma levels of 3-hydroxybutyrate (3HB), NADH, myeloperoxidase, and dityrosine (di-Tyr) in adolescent and adult patients with MDD, compare them with healthy age-matched controls, and assess the effect of antidepressant treatment during hospitalisation on these levels. In our study, plasmatic levels of 3HB were elevated in both adolescents (by 55%; p = 0.0004) and adults (by 88%; p < 0.0001) with MDD compared to controls. Levels of dityrosine were increased in MDD adults (by 19%; p = 0.0092) but not adolescents. We have not found any significant effect of antidepressants on the selected parameters during the short observation period. Our study supports the findings suggesting altered energy metabolism in MDD and demonstrates its presence independently of the age of the patients. Full article
(This article belongs to the Special Issue Biomarkers in Psychiatry)
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9 pages, 254 KiB  
Article
Premenopausal Singaporean Women Suffering from Major Depressive Disorder Treated with Selective Serotonin Reuptake Inhibitors Had Similar Bone Mineral Density as Compared with Healthy Controls
by Roger C. Ho, Anna N. Chua, Syeda Fabeha Husain, Wanqiu Tan, Fengyi Hao, Giang T. Vu, Bach X. Tran, Hien Thu Nguyen, Roger S. McIntyre and Cyrus S. Ho
Diagnostics 2022, 12(1), 96; https://doi.org/10.3390/diagnostics12010096 - 3 Jan 2022
Cited by 5 | Viewed by 1673
Abstract
The association between selective serotonin reuptake inhibitor (SSRI) treatment and lower bone mineral density (BMD) remains controversial, and further research is required. This study aimed to compare the BMD, levels of bone formation and bone metabolism markers in medicated premenopausal Singaporean women with [...] Read more.
The association between selective serotonin reuptake inhibitor (SSRI) treatment and lower bone mineral density (BMD) remains controversial, and further research is required. This study aimed to compare the BMD, levels of bone formation and bone metabolism markers in medicated premenopausal Singaporean women with major depressive disorder (MDD) and matched healthy controls. We examined 45 women with MDD who received SSRI treatment (mean age: 37.64 ± 7) and 45 healthy controls (mean age: 38.1 ± 9.2). BMD at the lumbar spine, total hip and femoral neck were measured using dual-energy X-ray absorptiometry. We also measured bone formation markers, procollagen type 1 N-terminal propeptide (P1NP) and bone metabolism markers, osteoprotegerin (OPG) and receptor activator of nuclear factor-kappa-Β ligand (RANKL). There were no significant differences in the mean BMD in the lumbar spine (healthy controls: 1.04 ± 0.173 vs. MDD patients: 1.024 ± 0.145, p = 0.617, left hip (healthy controls: 0.823 ± 0.117 vs. MDD patients: 0.861 ± 0.146, p = 0.181) and right hip (healthy controls: 0.843 ± 0.117 vs. MDD patients: 0.85 ± 0.135, p = 0.784) between healthy controls and medicated patients with MDD. There were no significant differences in median P1NP (healthy controls: 35.9 vs. MDD patients: 37.3, p = 0.635), OPG (healthy controls: 2.6 vs. MDD patients: 2.7, p = 0.545), RANKL (healthy controls: 23.4 vs. MDD patients: 2178.93, p = 0.279) and RANKL/OPG ratio (healthy controls: 4.1 vs. MDD patients: 741.4, p = 0.279) between healthy controls and medicated patients with MDD. Chronic SSRI treatment might not be associated with low BMD in premenopausal Singaporean women who suffered from MDD. This finding may help female patients with MDD make an informed decision when considering the risks and benefits of SSRI treatment. Full article
(This article belongs to the Special Issue Biomarkers in Psychiatry)
9 pages, 1027 KiB  
Article
Distributions of Aβ42 and Aβ42/40 in the Cerebrospinal Fluid in View of the Probability Theory
by Piotr Lewczuk, Jens Wiltfang, Johannes Kornhuber and Anneleen Verhasselt
Diagnostics 2021, 11(12), 2372; https://doi.org/10.3390/diagnostics11122372 - 16 Dec 2021
Cited by 11 | Viewed by 2396
Abstract
Amyloid β 42/40 concentration quotient has been empirically shown to improve accuracy of the neurochemical diagnostics of Alzheimer’s Disease (AD) compared to the Aβ42 concentration alone, but this improvement in diagnostic performance has not been backed up by a theoretical argumentation so far. [...] Read more.
Amyloid β 42/40 concentration quotient has been empirically shown to improve accuracy of the neurochemical diagnostics of Alzheimer’s Disease (AD) compared to the Aβ42 concentration alone, but this improvement in diagnostic performance has not been backed up by a theoretical argumentation so far. In this report we show that better accuracy of Aβ42/40 compared to Aβ1-42 is granted by fundamental laws of probability. In particular, it can be shown that the dispersion of a distribution of a quotient of two random variables (Aβ42/40) is smaller than the dispersion of the random variable in the numerator (Aβ42), provided that the two variables are proportional. Further, this concept predicts and explains presence of outlying observations, i.e., AD patients with falsely negatively high Aβ42/40 ratio, and non-AD subjects with extremely low, falsely positive, Aβ42/40 ratio. Full article
(This article belongs to the Special Issue Biomarkers in Psychiatry)
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