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 Table of Contents  
Year : 2022  |  Volume : 8  |  Issue : 1  |  Page : 3-6

Biomarkers in psychiatry: Do we have a test in psychiatry, yet?

1 Department of Psychiatry, Government Medical College, Nizamabad, Telangana, India
2 Department of Psychiatry, Prathima Institute of Medical Sciences, Karimnagar, Telangana, India

Date of Submission22-Feb-2022
Date of Decision14-Apr-2022
Date of Acceptance15-Apr-2022
Date of Web Publication30-May-2022

Correspondence Address:
Dr. Raviteja Innamuri
5-6-90, Teja Hospital Building, Dwaraka Nagar, Nizamabad - 503 001, Telangana
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/tjp.tjp_10_22

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Unlike most medical conditions, psychiatric disorders do not have any established tests to diagnose, treat, monitor, or predict prognosis. In this article, we attempt to explain biomarkers, their categorization, and their current status in psychiatry. We explore the technologies that are currently being employed to study various prospective biomarkers in psychiatry. Hitherto, there are no established biomarkers in psychiatry, but with emerging artificial intelligence, there is a reason for hope.

Keywords: Biomarkers, precision psychiatry, advances in psychiatry

How to cite this article:
Innamuri R, Thodupunuri S, Puli SK. Biomarkers in psychiatry: Do we have a test in psychiatry, yet?. Telangana J Psychiatry 2022;8:3-6

How to cite this URL:
Innamuri R, Thodupunuri S, Puli SK. Biomarkers in psychiatry: Do we have a test in psychiatry, yet?. Telangana J Psychiatry [serial online] 2022 [cited 2022 Nov 28];8:3-6. Available from: https://tjpipstsb.org/text.asp?2022/8/1/3/346232

  Introduction Top

Psychiatry, unlike other branches of medicine, is plagued with stigma and anti-psychiatry movements even till date.[1] One of the biggest reasons for this is the lack of clear biological correlates in the human brain.[2]

Several scientific efforts are being directed toward brain and mind-related research. Beginning with the “decade of the brain” under the Bush administration (1990–2000), several major projects working on psychiatric disorders include the brain project, the Human Genome Project (culminated with decoding of the entire human genome in May 2021), Human Connectome Project, the blue brain, brain/minds (Japan), China Brain Project, and Human Mind Project.

  Reflections on the Current Practice of Psychiatry Top

In the absence of biomarkers, the diagnosis and prognostication of psychiatric disorders are different when compared to other branches of medicine. Mental health professionals continue to rely on symptoms (as per client history), capsulate them into syndromes, and map them to the International Classification of Diseases and Diagnostic Statistical Manual to offer diagnoses that are comprehensible to both peers and clients.

While this may sound very rudimentary to other medical specialties, the history of several branches of medicine has threaded more or less on similar paths – symptoms later clustered under syndromes until an etiological explanation was found. This approach of “taxonomy first, biomarkers second” has dominated psychology and psychiatry and is expected to change to “biomarkers first” with more scientific advancements.[3]

  Into the Past-The Cancerous Valentine Top

Psychiatry and cancer share a very intimate history that is not often reflected. One of the first explanatory models (Galen's humoral theory) hypothesized disease as a result of the imbalance of humors. Black bile was said to be responsible for cancer and depression. Several years later, Vesalius stole human bodies from cemeteries in Paris and secretly dissected them but could never find the black bile. This black bile remains an enigma till date.[4]

The history of oncology saw similar conflicts that psychiatrists see today. For several decades, conferences in oncology saw groupism based on biological oncologists who emphasized on the genes and other etiological factors, and clinical oncologists who rather preferred to focus on cocktails of chemotherapeutic agents for various cancers. The merger between the groups and the growth of oncology happened after the discovery of a monoclonal antibody that could target a gene-trastuzumab (monoclonal Ab) for human epidermal growth factor 2 receptor-positive cancer.[5]

Perhaps, psychiatry would witness a similar growth if we found similar molecules, say, a monoclonal antibody of BRD1 (gene associated with depression).[6] Also, finding measurable markers in the blood or brain could help diagnose, predict and deliver personalised psychiatry treatment to our clients.

  What are Biomarkers? Top

The Food and Drug Administration-NIH Biomarker Working Group, 2016, defines biomarker as a “A general characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure or intervention.”

A good biomarker has clinical use, high reproducibility, sizeable signal-to-noise ratio, accessible for detection and measurement (histological or neuroimaging techniques), and as disease progresses, is modified in a dynamic and reliable way.[7]

Various types of biomarkers include diagnostic, monitoring, pharmacodynamic, predictive, prognostic, safety, and susceptibility/risk biomarkers. While this categorization helps with theoretical and research purposes, there may be overlapping functions of the biomarker types. For example, pharmacodynamic biomarker (helps to decide to continue or not continue a particular drug) can also be understood as a monitoring biomarker.

The samples used in searching biomarkers can be peripheral (lymphocytes in the blood) or central (functioning neuroimaging of the brain). There is a lot of focus on peripheral biomarkers such as cerebrospinal fluid (CSF) and saliva as they can be easily sampled and are more dynamic and time-sensitive than proteome and genome. Recent studies have demonstrated the association of CSF metabolites with psychopathic traits and with early life stress and hippocampal volume.[8],[9] There is increasing recognition of saliva as a diagnostic (depression and anxiety) and drug monitoring biomarker (concentrations of valproic acid, methadone, etc.) in neuropsychiatry.[10],[11] Availability of such biomarkers and application into clinical practice may bring the paradigm shift that is much awaited.

  Into the Future-Role of Emerging Technologies Top

The fate of a branch of medicine is largely decided by emerging technologies. The case in point is radiology which has arguably become an extremely sought after branch with the introduction of imaging modalities such as computerized tomography (CT) and magnetic resonance imaging (MRI).

Various technologies referred to as “OMICS” are being used to search biomarkers including genomics, transcriptomics, proteomics, metabolomics, and epigenetics.[7] The Human Genome Project did not reveal any candidate gene for psychiatric disorders. It instead confirmed polygenic-genetic heterogeneity-involvement of multiple genes (SNiPs with low penetrance), and more interestingly, pleiotropy, i.e., the same gene contributing to multiple diseases, for example., disrupted in schizophrenia 1 involved in schizophrenia, bipolar disorder, and major depressive disorder. We remain unsure if these variances are acting as a network or are manifesting after accumulation over a period of time.

Since they were multiple genes (DNA) involved, an intelligent approach was undertaken to focus on the RNA synthesized from the DNA material that could be more reliable and valid targets. This brought transcriptomics into the fore. Similarly, focusing on the proteins synthesized from the RNA material is proteomics and the study of the metabolites of these proteins has emerged into metabolomics. These molecules would understandably be more dynamic than the genes involved but can be more easily accessed and collected. Epigenetic biomarkers are dynamic variations in DNA structure modifying gene expression without changing sequence and have received focus with autism spectrum disorders.

Various studies continue to exploit functional imaging tools such as positron emission tomography, single-photon emission CT, and functional MRI using techniques such as reward task activation features to predict treatment outcomes.[12] Quantitative electroencephalography (EEG) is being used to generate complex algorithms to predict response, for example., Antidepressant Treatment Response (ATR) Index. However, EEG is being commercially marketed and is currently not well supported as a biomarker.[13]

Increased use of smartphones, wearable gadgets, and other mobile-connected technologies are easily providing details about circadian rhythms and physical activity that are critical parameters in psychiatric disorders. These emerging “digital behavioral biomarkers” may fill and complement the gaps left by the current biological markers.[14]

  Way Forward Top

We must accept the complex origins of psychiatric disorders and account for the genetic, epigenetic, and environmental factors. The current research is revealing “biotypes” for each positive and negative valences that are quite different from the clinical categorization of psychiatric disorders.[15] NIH has only been funding psychiatry research that has adopted RDoC to help understand findings better in terms of biological research.[16]

At present, biomarkers discussed in the curriculum are limited and repetitive across various psychiatric disorders such as monoamine hypothesis, structural abnormalities including cortical atrophy, dilated ventricles, involvement of the limbic system, compromised immunity, and impaired dexamethasone test. The current examination pattern dedicates paper 4 of the MD curriculum to recent advances to keep students up to date with the rapid progress. Recent conferences and Continuing Medical Education(CME) activities are being dedicated to neurobiology. However, these are hardly seen to have relevance in clinical practice except for clinical data points such as history of response of a particular drug in a first-degree relative. Not only psychiatrists dedicated to research, even practicing private psychiatrists may also need to take additional responsibility in the progress of psychiatry. They could be encouraged to conduct feasible studies that can help gather more clinically relevant data points that can be correlated with response. This could help to gather the vast reservoir of data that are needed to develop computational algorithms.

  Implications Top

The implications of breakthroughs in finding more biomarkers in neuropsychiatry will result in the complete transformation in the way we diagnose, treat, monitor, and prognosticate. We will need to integrate all possible data sources – imaging, electrophysiology, genome-wide association study studies, behavioral studies, animal models, EEG, data from OMICS, clinical data, and others to produce reliable and valid data. Advancing bioinformatics tools and use of artificial intelligence to integrate the plethora of data from all “omics” to reach the holistic realization of a “systems biology” will certainly help in understanding the unanswered biological questions, while the process may seem lengthy, complex, and with various ethical and legal challenges of the large data mined from each client. With the help of computational genomics and artificial intelligence (including machine learning and deep learning), we will be able to individualize treatment. With the advancement of precision or prediction psychiatry, we will be able to use algorithms to offer multiple treatment options with a list of preferences. This is definitely a paradigm shift to the current approach of trial-and-error method and long duration of treatment to determine response to a particular treatment.

  Conclusions Top

Precision or prediction psychiatry in the beginning phases, Dr. Nasser Ghaemi in a letter said that “no branch of medicine has undergone a transformation once every 50 years like the way psychiatry did.”[17] It is true that psychiatry still awaits a breakthrough in neurosciences to be able to make etiological diagnoses and more targeted and personalized treatment approaches. However, there is hope. Biomarkers are that hope.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Gray AJ. Stigma in psychiatry. J R Soc Med 2002;95:72-6.  Back to cited text no. 1
García-Gutiérrez MS, Navarrete F, Sala F, Gasparyan A, Austrich-Olivares A, Manzanares J. Biomarkers in psychiatry: Concept, definition, types and relevance to the clinical reality. Front Psychiatry 2020;11:432.  Back to cited text no. 2
Trofimova I, Netter P. In search of biomarkers for biobehavioural and psychiatric taxonomies. Neuropsychobiology 2021;80:79-83.  Back to cited text no. 3
McClure I. Bad medicine: Doctors doing harm since Hippocrates. Br Med J 2006;333:606.  Back to cited text no. 4
Mukherjee S. The emperor of all maladies. Can Fam Physician. 2011 Apr;57(4):460.  Back to cited text no. 5
Reduced Brd1 Expression Leads to Reversible Depression-Like Behaviors and Gene-Expression Changes in Female Mice | Translational Psychiatry. Available from: https://www.nature.com/articles/s41398-020-00914-2. [Last acessed on 2022 Feb 22].  Back to cited text no. 6
Aronson JK, Ferner RE. Biomarkers – A general review. Curr Protoc Pharmacol 2017;76:9.23.1-17.  Back to cited text no. 7
Soderstrom H, Blennow K, Sjodin AK, Forsman A. New evidence for an association between the CSF HVA: 5-HIAA ratio and psychopathic traits. J Neurol Neurosurg Psychiatry 2003;74:918-21.  Back to cited text no. 8
Coplan JD, Fulton SL, Reiner W, Jackowski A, Panthangi V, Perera TD, et al. Elevated cerebrospinal fluid 5-hydroxyindoleacetic acid in macaques following early life stress and inverse association with hippocampal volume: Preliminary implications for serotonin-related function in mood and anxiety disorders. Front Behav Neurosci 2014;8:440.  Back to cited text no. 9
Kułak-Bejda A, Waszkiewicz N, Bejda G, Zalewska A, Maciejczyk M. Diagnostic value of salivary markers in neuropsychiatric disorders. Dis Markers 2019;2019:4360612.  Back to cited text no. 10
Monteleone MC, Billi SC, Viale L, Catoira NP, Frasch AC, Brocco MA. Search of brain-enriched proteins in salivary extracellular vesicles for their use as mental disease biomarkers: A pilot study of the neuronal glycoprotein M6a. J Affect Disord Rep 2020;1:100003.  Back to cited text no. 11
Nguyen KP, Chin Fatt C, Treacher A, Mellema C, Cooper C, Jha MK, et al. Patterns of pretreatment reward task brain activation predict individual antidepressant response: Key results from the EMBARC randomized clinical trial. Biol Psychiatry 2022;91:550-60.  Back to cited text no. 12
Widge AS, Bilge MT, Montana R, Chang W, Rodriguez CI, Deckersbach T, et al. Electroencephalographic biomarkers for treatment response prediction in major depressive illness: A meta-analysis. Am J Psychiatry 2019;176:44-56.  Back to cited text no. 13
Hidalgo-Mazzei D, Young AH, Vieta E, Colom F. Behavioural biomarkers and mobile mental health: A new paradigm. Int J Bipolar Disord 2018;6:9.  Back to cited text no. 14
Clementz BA, Sweeney JA, Hamm JP, Ivleva EI, Ethridge LE, Pearlson GD, et al. Identification of distinct psychosis biotypes using brain-based biomarkers. Am J Psychiatry 2016;173:373-84.  Back to cited text no. 15
Insel T, Cuthbert B, Garvey M, Heinssen R, Pine DS, Quinn K, et al. Research domain criteria (RDoC): Toward a new classification framework for research on mental disorders. Am J Psychiatry 2010;167:748-51.  Back to cited text no. 16
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