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Biomarkers in Schizophrenia

2013; Future Medicine; Volume: 8; Issue: 1 Linguagem: Alemão

10.2217/bmm.13.138

1752-0371

Gabriel Vargas,

Mental Health and Psychiatry

Biomarkers in MedicineVol. 8, No. 1 Theme: Biomarkers in schizophrenia - ForewordFree AccessBiomarkers in schizophreniaGabriel VargasGabriel VargasMedical Sciences, Neuroscience Early Development, Amgen, One Amgen Center Drive, Thousand Oaks, CA 91320, USA. Published Online:11 Dec 2013https://doi.org/10.2217/bmm.13.138AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinkedInReddit Keywords: biomarkersschizophreniatranslationalThis May, the American Psychiatric Association (APA) published the latest edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM), which is commonly referred to as the bible of psychiatry [1]. Now in its fifth edition, DSM enables clinicians to diagnose psychiatric problems based on a list of symptoms that are considered to be the essential components of each disorder. This approach enables consistency in diagnosis across clinicians. However, DSM V, like its predecessors, is not based on pathophysiology and does little to incorporate biology into its diagnostic criteria.While there have been significant advances in our understanding of basic neuroscience over the last 60 years, this has not translated into psychiatric clinical practice. Indeed, psychiatry remains the only branch of medicine that does not routinely use diagnostic laboratory tests [2]. Much of this is due to the following factors: the underlying biology of psychiatric disorders is poorly understood; the preclinical models for psychiatric disorders are not very good; and the organ of interest is hard to access [3,4].This leads to a situation where, as a direct result of these issues, there is a lack of translational models and therefore the application of basic neuroscience to the clinical arena is more challenging than in other medical specialties.One way forward is to develop biomarkers to aid in prognosis, patient stratification and diagnosis. Once validated, these biomarkers can be used for the development of diagnostics, which can be used for improved clinical decision-making. The papers in this special thematic issue on biomarkers in schizophrenia discuss different approaches to the same common goal: the identification of biomarkers to enable better patient care.Sabine Bahn's group has a long track record in the identification of proteomic biomarkers to aid in the diagnosis of schizophrenia [5,6]. Their approach rests on the hypothesis that mental illness is a systemic disorder that will have perturbations across the whole body, including the composition of the blood. They review an extensive literature that has provided evidence of disturbances in inflammatory, hormonal and metabolic pathways [7]. The data generated through these proteomic approaches give credence to the idea that the periphery can be used to detect perturbation in mental illness and demonstrating this has been of immense importance.Identification of useful biomarkers for psychiatric disorders is very challenging without a concerted effort. Colin Dourish and Gerard Dawson describe some of the work being generated by an innovative collaboration orchestrated by the clinical research organization P1vital [8,9]. They have developed a framework in which a precompetitive consortium between industry and academia enables the development and validation of new biomarkers. This is accomplished through implementation of experimental medicine studies whereby potential biomarkers useful for psychiatric research are validated. This approach is exemplified by some of the imaging studies undertaken by this consortium that have used individuals categorized as high schizotypes, which is a personality disorder in the milder part of the schizophrenia spectrum. Research assessing spatial working memory in these individuals, who are in essence healthy but with some of the genetic load of schizophrenia, reveals that these high schizotypes have significant differences in their brain activation patterns, suggesting they have an inefficient encoding strategy. These findings suggest that these subjects may be useful surrogates for schizophrenic patients. This is important in that use of this subject population may make it easier to perform clinical studies in the schizophrenia field as these individuals are typically not on medications and are potentially easier to recruit for studies.Larry Ereshefsky and his colleagues outline some of the essential work that is needed in Phase I studies to detect early signs of efficacy in drug development [10]. Their manuscript covers a variety of biomarker platforms that aim to address what has been termed the three pillars of drug development demonstration of: exposure at the site of action, target binding and pharmacodynamic activity [11]. These methods include cognitive testing, imaging, EEG and specialized pharmacodynamic biomarkers. The selection of the appropriate approach depends on the particular attributes of the drug being tested and which system it will alter.The use of EEG biomarkers such as mismatch negativity (MMN), a preattentive auditory event-related potential, have been explored for their utility in schizophrenia. MMN is a translational biomarker that offers a unique window to some of the sensory processing deficits that are present in schizophrenia. As Perez and her colleagues write, this biomarker has shown a consistent and robust reduction in schizophrenia patients [12]. Interestingly, initial studies suggest that it may also be helpful in the prediction of conversion to psychosis in those subjects who are at high risk. These initial observations will need confirmation in longitudinal studies.Looking to other neurological conditions, current drug development strategies for Alzheimer's disease are moving to earlier stages of the disease with the idea that the most impact will be had prior to the development of full-blown disorder [13]. The Alzheimer's Disease Neuroimaging Initiative has been enormously successful in identifying biomarkers that can be used to predict conversion to disease from the prodromal stage [14]. Investigators studying prodromal schizophrenia have a similar goal in mind. Current research in this area is identifying subjects in the prodromal phase of schizophrenia to discover biomarkers that can be used to predict conversion [15]. Kristin Cadenhead and colleagues describe some of the efforts in identifying prognostic biomarkers [16]. These prognostic biomarkers may enable early intervention to improve outcomes, or even more excitingly, prevent the onset of schizophrenia. These biomarker platforms include neuroimaging, electrophysiology, and most robustly and consistently found in the prodrome, neurocognitive deficits. Interestingly, it appears that targeting specific cognitive deficits may be helpful in delaying or even preventing psychosis.All these efforts will ultimately move the field forward by identifying biomarkers that can then be developed for patient stratification, early diagnosis and prognosis, or to identify those subjects who are responders or nonresponders. These biomarkers can then form the core from which diagnostic products can be made to enable the goal of personalized medicine; that is, giving the right drug to the right patient at the right time. Improvement of psychiatric nosology will only come from a better understanding of the pathophysiology of these disorders. This can be achieved only through studying relatively homogenous patient populations that have some common biology. There is a catch-22 here, that to identify the biology one needs patient groups that are defined somewhat biologically. An alternative is to use particular phenotypic characteristics to define more homogenous groups and then explore the biology of this clustering. One example that used this method is the clinical data on the identification of CFHR1 protein as a response predictor biomarker for bitopertin [17]. These data suggest that baseline levels of CFHR1 may predict clinical response. One of the potential reasons a peripheral biomarker was identified in this example is that the patient population was comprised of negative symptom schizophrenic patients and was therefore more phenotypically homogenous than a take all comers schizophrenia trial.Ultimately, the use of phenotyping combined with biomarker discovery may enable the identification of subpopulations that will inform our diagnostic nosology such that we can expect future editions of the DSM to include the biological characteristics of these mental disorders.Financial & competing interests disclosureG Vargas is an Amgen employee and has stock in the company. Amgen develops neuroscience drugs; however, it does not currently have any marketed drugs or diagnostics in this therapeutic area. The author has no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.No writing assistance was utilized in the production of this manuscript.References1 American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (5th Edition). American Psychiatric Association, Washington, DC, USA (2013).Google Scholar2 Kapur S, Phillips AG, Insel TR. Why has it taken so long for biological psychiatry to develop clinical tests and what to do about it? Mol. Psychiatry17(12),1174–1179 (2012).Crossref, Medline, CAS, Google Scholar3 Nikolcheva T, Jäger S, Bush TA, Vargas G. Challenges in the development of companion diagnostics for neuropsychiatric disorders. Expert Rev. Mol. Diagn.11(8),829–837 (2011).Crossref, Medline, CAS, Google Scholar4 Dawson GR, Dourish CT, Goodwin GM. Special issue on CNS experimental medicine. J. Psychopharmacol.25(9),1145–1147 (2011). Crossref, Medline, Google Scholar5 Schwarz E, Izmailov R, Spain M et al. Validation of a blood-based laboratory test to aid in the confirmation of a diagnosis of schizophrenia. Biomark. Insights5,39–47 (2010).Crossref, Medline, Google Scholar6 Schwarz E, Guest PC, Rahmoune H et al. Identification of a biological signature for schizophrenia in serum. Mol. Psychiatry17,494–502 (2012).Crossref, Medline, CAS, Google Scholar7 Guest PC, Chan MK, Gottschalk MG, Bahn S. The use of proteomic biomarkers for improved diagnosis and stratification of schizophrenia patients. Biomarkers Med.8(1),15–27 (2014).Link, CAS, Google Scholar8 Dawson GR, Craig KJ, Dourish CT. Validation of experimental medicine methods in psychiatry: the P1vital approach and experience. Biochem. Pharmacol.81(12),1435–1441 (2011). Crossref, Medline, CAS, Google Scholar9 Dourish CT, Dawson GR. Precompetitive consortium approach to validation of the next generation of biomarkers in schizophrenia. Biomarkers Med.8(1),5–8 (2014).Link, CAS, Google Scholar10 English BA, Thomas K, Johnstone J, Bazih A, Gertsik L, Ereshefsky L. Use of translational pharmacodynamic biomarkers in early-phase clinical studies for schizophrenia. Biomarkers Med.8(1),29–49 (2014).Link, CAS, Google Scholar11 Morgan P, Van Der Graaf PH, Arrowsmith J et al. Can the flow of medicines be improved? Fundamental pharmacokinetic and pharmacological principles toward improving Phase II survival. Drug Discov. Today117(9–10),419–424 (2012). Crossref, Google Scholar12 Perez VB, Swerdlow NR, Braff DL, Näätänen R, Light GA. Using biomarkers to inform diagnosis, guide treatments and track response to interventions in psychotic illnesses. Biomarkers Med.8(1),9–14 (2014).Link, CAS, Google Scholar13 Hampel H. Current insights into the pathophysiology of Alzheimer's disease: selecting targets for early therapeutic intervention. Int. Psychogeriatr.24(Suppl. 1),S10–S17 (2012).Crossref, Medline, Google Scholar14 Cummings JL. Integrating ADNI results into Alzheimer's disease drug development programs. Neurobiol. Aging31(8),1481–1492 (2010).Crossref, Medline, Google Scholar15 Correll CU, Hauser M, Auther AM, Cornblatt BA. Research in people with psychosis risk syndrome: a review of the current evidence and future directions. J. Child Psychol. Psychiatry51(4),390–431 (2010). Crossref, Medline, Google Scholar16 Mirzakhanian H, Singh F, Cadenhead KS. Biomarkers in psychosis: an approach to early identification and individualized treatment. Biomarkers Med.8(1),51–57 (2014).Link, CAS, Google Scholar17 Santarelli L. An audience with…Luca Santarelli. Interview by Alexandra Flemming. Nat. Rev. Drug Discov.12(1),14–15 (2013).Crossref, Medline, Google ScholarFiguresReferencesRelatedDetailsCited ByOxytocin levels in individuals with schizophrenia are high in cerebrospinal fluid but low in serum: A systematic review and meta-analysis8 September 2021 | Metabolic Brain Disease, Vol. 36, No. 8MiRNAs of peripheral blood as the biomarker of schizophrenia29 August 2017 | Hereditas, Vol. 155, No. 1Signal processing approach to probe chemical space for discriminating redox signaturesBiosensors and Bioelectronics, Vol. 112Bridging Autism Spectrum Disorders and Schizophrenia through inflammation and biomarkers - pre-clinical and clinical investigations4 September 2017 | Journal of Neuroinflammation, Vol. 14, No. 1A possible serologic biomarker for maternal immune activation-associated neurodevelopmental disorders found in the rat modelsNeuroscience Research, Vol. 113The proteome of schizophrenia4 March 2015 | npj Schizophrenia, Vol. 1, No. 1MicroRNAs in Schizophrenia: Implications for Synaptic Plasticity and Dopamine–Glutamate Interaction at the Postsynaptic Density. New Avenues for Antipsychotic Treatment Under a Theranostic Perspective14 November 2014 | Molecular Neurobiology, Vol. 52, No. 3 Vol. 8, No. 1 Follow us on social media for the latest updates Metrics History Published online 11 December 2013 Published in print January 2014 Information© Future Medicine LtdKeywordsbiomarkersschizophreniatranslationalFinancial & competing interests disclosureG Vargas is an Amgen employee and has stock in the company. Amgen develops neuroscience drugs; however, it does not currently have any marketed drugs or diagnostics in this therapeutic area. The author has no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.No writing assistance was utilized in the production of this manuscript.PDF download