The Challenges and Promise of Neuroimaging in Psychiatry
2012; Cell Press; Volume: 73; Issue: 1 Linguagem: Inglês
10.1016/j.neuron.2011.12.014
ISSN1097-4199
Autores Tópico(s)Neurology and Historical Studies
ResumoNeuroimaging is central to the quest for a biological foundation of psychiatric diagnosis but so far has not yielded clinically relevant biomarkers for mental disorders. This review addresses potential reasons for this limitation and discusses refinements of paradigms and analytic techniques that may yield improved diagnostic and prognostic accuracy. Neuroimaging can also be used to probe genetically defined biological pathways underlying mental disorders, for example through the genetic imaging of variants discovered in genome-wide association studies. These approaches may ultimately reveal mechanisms through which genes contribute to psychiatric symptoms and how pharmacological and psychological interventions exert their effects. Neuroimaging is central to the quest for a biological foundation of psychiatric diagnosis but so far has not yielded clinically relevant biomarkers for mental disorders. This review addresses potential reasons for this limitation and discusses refinements of paradigms and analytic techniques that may yield improved diagnostic and prognostic accuracy. Neuroimaging can also be used to probe genetically defined biological pathways underlying mental disorders, for example through the genetic imaging of variants discovered in genome-wide association studies. These approaches may ultimately reveal mechanisms through which genes contribute to psychiatric symptoms and how pharmacological and psychological interventions exert their effects. The demonstration, in 1976, that patients with schizophrenia had enlarged cerebral ventricles (Johnstone et al., 1976Johnstone E.C. Crow T.J. Frith C.D. Husband J. Kreel L. Cerebral ventricular size and cognitive impairment in chronic schizophrenia.Lancet. 1976; 2: 924-926Abstract PubMed Scopus (20) Google Scholar), seemed to usher psychiatry into a new era where neuroimaging would help identify mental disorders and ultimately clarify their mechanisms. In the cultural climate of the 1970s, such claims of tangible biological signs may have perturbed those who believed that mental disorders were the product of early life experience and other biographical influences. In the past 35 years, modern psychiatry has largely overcome such dualisms, and there is now general agreement that environmental influences can manifest themselves in observable brain changes as well as genetic factors. Perhaps the most remarkable result of this rapprochement between psychological and biological approaches to mental illness is the emergence of research programs mapping out neural correlates and predictors of psychotherapy successfully with functional neuroimaging (Beutel et al., 2003Beutel M.E. Stern E. Silbersweig D.A. The emerging dialogue between psychoanalysis and neuroscience: neuroimaging perspectives.J. Am. Psychoanal. Assoc. 2003; 51: 773-801Crossref PubMed Google Scholar, DeRubeis et al., 2008DeRubeis R.J. Siegle G.J. Hollon S.D. Cognitive therapy versus medication for depression: treatment outcomes and neural mechanisms.Nat. Rev. Neurosci. 2008; 9: 788-796Crossref PubMed Scopus (141) Google Scholar, Kandel, 1999Kandel E.R. Biology and the future of psychoanalysis: a new intellectual framework for psychiatry revisited.Am. J. Psychiatry. 1999; 156: 505-524PubMed Google Scholar, Linden, 2006Linden D.E. How psychotherapy changes the brain—the contribution of functional neuroimaging.Mol. Psychiatry. 2006; 11: 528-538Crossref PubMed Scopus (149) Google Scholar, Linden, 2008Linden D.E. Brain imaging and psychotherapy: methodological considerations and practical implications.Eur. Arch. Psychiatry Clin. Neurosci. 2008; 258: 71-75Crossref PubMed Scopus (22) Google Scholar, Roffman et al., 2005Roffman J.L. Marci C.D. Glick D.M. Dougherty D.D. Rauch S.L. Neuroimaging and the functional neuroanatomy of psychotherapy.Psychol. Med. 2005; 35: 1385-1398Crossref PubMed Scopus (103) Google Scholar). Another important development has come out of the growing dissatisfaction with current diagnostic systems in psychiatry. Although the authors of the Diagnostic and Statistical Manual of Mental Disorders (DSM) (American Psychiatric Association, 2000American Psychiatric AssociationDiagnostic and Statistical Manual of Mental Disorders: DSM-IV-TR.Fourth Edition. American Psychiatric Association, Washington, DC2000Google Scholar) and the International Classification of Disease (World Health Organisation, 1992World Health OrganisationThe ICD-10 Classification of Mental and Behavioural Disorders: Clinical Descriptions and Diagnostic Guidelines. WHO, Geneva1992Google Scholar) were guided by the aim to make the diagnostic criteria more reliable, these criteria are still largely based on clinicians' assessments. Thus, patients whose symptoms are caused by very different biological processes may be subsumed under the same category, and some of them may receive inappropriate treatment as a consequence. In order to improve this situation, it has been suggested that the new DSM-5 incorporate etiological criteria. Yet reliable etiological models and biomarkers are currently not available for most psychiatric disorders, and even further clinical subtyping has not made the association with biological markers more stringent. Psychiatric diagnosis will thus continue to be based on descriptive criteria for the foreseeable future (First, 2010First M.B. Paradigm shifts and the development of the diagnostic and statistical manual of mental disorders: past experiences and future aspirations.Can. J. Psychiatry. 2010; 55: 692-700PubMed Google Scholar). Neuroimaging in its various guises is likely to play a major role in the quest for a biological foundation of psychiatric diagnoses, if only because it is the only array of techniques that routinely provides direct access to the living human brain (Table 1). Imaging can complement clinical trials in phases 0/I/II to determine in vivo effects of drugs and appropriate dosages, and in phases III/IV for treatment monitoring and stratification of patient samples and flexible dose adjustment over time.Table 1Comparison of Noninvasive Neuroimaging Modalities in Biomarker ResearchTechniqueSpatial ResolutionTemporal ResolutionSensitivity to Specific MoleculesRetest-ReliabilitySuitability for Multicenter StudiesReferencesStructural magnetic resonance imaging (MRI)Millimeter, in some cases (ultra-high field) submillimeterCan be used to track longitudinal changesNone, but can study effects of pharmacological intervention or genesGood within scanners, moderate across scanners of the same type, poor across magnet field strengthsYes if magnet of same field strength and rigorous protocol design / calibration / quality controlReliability: Kruggel et al., 2010Kruggel F. Turner J. Muftuler L.T. Alzheimer's Disease Neuroimaging InitiativeImpact of scanner hardware and imaging protocol on image quality and compartment volume precision in the ADNI cohort.Neuroimage. 2010; 49: 2123-2133Crossref PubMed Scopus (28) Google ScholarFunctional MRI (fMRI)MillimeterSecondsSee under structural MRIBlood oxygen level-dependent signal (BOLD) activation studies: needs to be determined for each paradigm; published reports go up to 0.8; perfusion studies: highUnder development; requires scanners of same field strength and well standardized paradigmsReliability: Blokland et al., 2011Blokland G.A. McMahon K.L. Thompson P.M. Martin N.G. de Zubicaray G.I. Wright M.J. Heritability of working memory brain activation.J. Neurosci. 2011; 31: 10882-10890Crossref PubMed Scopus (13) Google Scholar, Xu et al., 2010Xu G. Rowley H.A. Wu G. Alsop D.C. Shankaranarayanan A. Dowling M. Christian B.T. Oakes T.R. Johnson S.C. Reliability and precision of pseudo-continuous arterial spin labeling perfusion MRI on 3.0 T and comparison with 15O-water PET in elderly subjects at risk for Alzheimer's disease.NMR Biomed. 2010; 23: 286-293Crossref PubMed Scopus (4) Google Scholar. Multicenter: Barch and Mathalon, 2011Barch D.M. Mathalon D.H. Using brain imaging measures in studies of procognitive pharmacologic agents in schizophrenia: psychometric and quality assurance considerations.Biol. Psychiatry. 2011; 70: 13-18Abstract Full Text Full Text PDF PubMed Scopus (12) Google ScholarMagnetic resonance spectroscopy (MRS)CentimeterMinutesMillimolarReported as good for some brain regions and metabolites, optimized procedures for neurotransmitters (GABA, Glutamate/Glutamine) under developmentUnder development; for example, guidelines have been proposed for multiple sclerosisReliability: Geramita et al., 2011Geramita M. van der Veen J.W. Barnett A.S. Savostyanova A.A. Shen J. Weinberger D.R. Marenco S. Reproducibility of prefrontal γ-aminobutyric acid measurements with J-edited spectroscopy.NMR Biomed. 2011; 24: 1089-1098Crossref PubMed Scopus (12) Google Scholar. Multicenter: De Stefano et al., 2007De Stefano N. Filippi M. Miller D. Pouwels P.J. Rovira A. Gass A. Enzinger C. Matthews P.M. Arnold D.L. Guidelines for using proton MR spectroscopy in multicenter clinical MS studies.Neurology. 2007; 69: 1942-1952Crossref PubMed Scopus (52) Google ScholarPositron emission tomography (PET)/ single photon emission computed tomography (SPECT)Centimeter (SPECT) to millimeter (PET)MinutesPicomolarNeeds to be determined for each ligand and region; for example reports for raclopride range from moderate to goodStandardization procedures have been developed, for example for FDG-PET in clinical trials of ADReliability: Alakurtti et al., 2011Alakurtti K. Aalto S. Johansson J.J. Någren K. Tuokkola T. Oikonen V. Laine M. Rinne J.O. Reproducibility of striatal and thalamic dopamine D2 receptor binding using [11C]raclopride with high-resolution positron emission tomography.J. Cereb. Blood Flow Metab. 2011; 31: 155-165Crossref PubMed Scopus (6) Google Scholar, Yoder et al., 2011Yoder K.K. Albrecht D.S. Kareken D.A. Federici L.M. Perry K.M. Patton E.A. Zheng Q.H. Mock B.H. O'Connor S. Herring C.M. Test-retest variability of [11C]raclopride-binding potential in nontreatment-seeking alcoholics.Synapse. 2011; 65: 553-561Crossref PubMed Scopus (8) Google Scholar. Multicenter: Jagust et al., 2010Jagust W.J. Bandy D. Chen K. Foster N.L. Landau S.M. Mathis C.A. Price J.C. Reiman E.M. Skovronsky D. Koeppe R.A. Alzheimer's Disease Neuroimaging InitiativeThe Alzheimer's Disease Neuroimaging Initiative positron emission tomography core.Alzheimers Dement. 2010; 6: 221-229Abstract Full Text Full Text PDF PubMed Scopus (103) Google ScholarMagnetoencephalography (MEG)CentimeterMillisecondsSee under structural MRINeeds to be determined for each paradigm and parameter; for example, high for visual gamma activityUnder developmentReliability: Muthukumaraswamy et al., 2010Muthukumaraswamy S.D. Singh K.D. Swettenham J.B. Jones D.K. Visual gamma oscillations and evoked responses: variability, repeatability and structural MRI correlates.Neuroimage. 2010; 49: 3349-3357Crossref PubMed Scopus (31) Google Scholar. Multicenter: Gaetz et al., 2011Gaetz W. Roberts T.P. Singh K.D. Muthukumaraswamy S.D. Functional and structural correlates of the aging brain: Relating visual cortex (V1) gamma band responses to age-related structural change.Hum. Brain Mapp. 2011; (in press. Published online July 18, 2011)Google ScholarElectroencephalography (EEG) / event-related potentials (ERP)CentimeterMillisecondsSee under structural MRIDepends on paradigm, high for P300 ERP in oddball studiesQuality assurance and standardization procedures under developmentReliability and multicenter: Luck et al., 2011Luck S.J. Mathalon D.H. O'Donnell B.F. Hämäläinen M.S. Spencer K.M. Javitt D.C. Uhlhaas P.J. A roadmap for the development and validation of event-related potential biomarkers in schizophrenia research.Biol. Psychiatry. 2011; 70: 28-34Abstract Full Text Full Text PDF PubMed Scopus (30) Google Scholar Open table in a new tab A biomarker has been defined as a "characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention" (Biomarkers Definitions Working Group, 2001Biomarkers Definitions Working GroupBiomarkers and surrogate endpoints: preferred definitions and conceptual framework.Clin. Pharmacol. Ther. 2001; 69: 89-95Crossref PubMed Scopus (1448) Google Scholar). Biomarkers that indicate the presence of a disease can be used for diagnostic purposes, classification, or staging of disease or for the prediction of the course of the illness. Such prognostic biomarkers may be particularly useful if they predict the future occurrence of an illness in preclinical cases. In the context of clinical trials, biomarkers can be used for "proof of concept" where they indicate that an intervention affects disease-relevant pathological processes (Soares, 2010Soares H.D. The use of mechanistic biomarkers for evaluating investigational CNS compounds in early drug development.Curr. Opin. Investig. Drugs. 2010; 11: 795-801PubMed Google Scholar). Another use of biomarkers is for "proof of mechanism" where it is demonstrated that an intervention affects the desired biological process. A major application is to show that a drug engages with a target in vivo in the way expected from in vitro studies. Where the effects of a therapeutic intervention on the biomarker predict the desired clinical outcome, the biomarker could even be taken forward as a potential surrogate marker. A validated surrogate marker, which has to undergo approval according to strict criteria (Cummings, 2010Cummings J.L. Integrating ADNI results into Alzheimer's disease drug development programs.Neurobiol. Aging. 2010; 31: 1481-1492Abstract Full Text Full Text PDF PubMed Scopus (24) Google Scholar), could permit a reduction of the participant numbers and duration needed to demonstrate clinically relevant effects (Hampel et al., 2011Hampel H. Wilcock G. Andrieu S. Aisen P. Blennow K. Broich K. Carrillo M. Fox N.C. Frisoni G.B. Isaac M. et al.for the Oxford Task Force GroupBiomarkers for Alzheimer's disease therapeutic trials.Prog. Neurobiol. 2011; 95: 579-593Crossref PubMed Scopus (44) Google Scholar, Jagust et al., 2010Jagust W.J. Bandy D. Chen K. Foster N.L. Landau S.M. Mathis C.A. Price J.C. Reiman E.M. Skovronsky D. Koeppe R.A. Alzheimer's Disease Neuroimaging InitiativeThe Alzheimer's Disease Neuroimaging Initiative positron emission tomography core.Alzheimers Dement. 2010; 6: 221-229Abstract Full Text Full Text PDF PubMed Scopus (103) Google Scholar). Imaging biomarkers have been relatively successful in the field of neurodegenerative disorders. PET with 18F-fluorodeoxyglucose (FDG) distinguishes Alzheimer's disease (AD) from other dementias (frontotemporal dementia and dementia with Lewy bodies) with high classification accuracy (Mosconi et al., 2010Mosconi L. Berti V. Glodzik L. Pupi A. De Santi S. de Leon M.J. Pre-clinical detection of Alzheimer's disease using FDG-PET, with or without amyloid imaging.J. Alzheimers Dis. 2010; 20: 843-854PubMed Google Scholar). FDG-PET has also shown promise in predicting future AD in people with mild cognitive impairment (MCI) and even in cognitively normal individuals (Mosconi et al., 2010Mosconi L. Berti V. Glodzik L. Pupi A. De Santi S. de Leon M.J. Pre-clinical detection of Alzheimer's disease using FDG-PET, with or without amyloid imaging.J. Alzheimers Dis. 2010; 20: 843-854PubMed Google Scholar). Imaging biomarkers have also been used for proof-of-concept in the evaluation of new interventions for dementia. For example, FDG-PET has been used to demonstrate partial reversal of deficits in glucose metabolism in AD in a phase I trial of deep-brain stimulation (Laxton et al., 2010Laxton A.W. Tang-Wai D.F. McAndrews M.P. Zumsteg D. Wennberg R. Keren R. Wherrett J. Naglie G. Hamani C. Smith G.S. Lozano A.M. A phase I trial of deep brain stimulation of memory circuits in Alzheimer's disease.Ann. Neurol. 2010; 68: 521-534Crossref PubMed Scopus (143) Google Scholar). Amyloid imaging with PET can be used for the proof-of-concept and -mechanism of interventions that modify amyloid pathology through blockade of amyloidogenic enzymes or immunization (Scheinin et al., 2011Scheinin N.M. Scheinin M. Rinne J.O. Amyloid imaging as a surrogate marker in clinical trials in Alzheimer's disease.Q. J. Nucl. Med. Mol. Imaging. 2011; 55: 265-279PubMed Google Scholar). Although neither neuroimaging nor neurochemical biomarkers have thus far attained the status of approved surrogate end points for clinical trials in AD or MCI (Hampel et al., 2010Hampel H. Frank R. Broich K. Teipel S.J. Katz R.G. Hardy J. Herholz K. Bokde A.L. Jessen F. Hoessler Y.C. et al.Biomarkers for Alzheimer's disease: academic, industry and regulatory perspectives.Nat. Rev. Drug Discov. 2010; 9: 560-574Crossref PubMed Scopus (207) Google Scholar), their predictive value may give them a place in clinical trials of MCI where they can enrich the trial population with individuals affected by the AD-related pathological process (Cummings, 2010Cummings J.L. Integrating ADNI results into Alzheimer's disease drug development programs.Neurobiol. Aging. 2010; 31: 1481-1492Abstract Full Text Full Text PDF PubMed Scopus (24) Google Scholar). Compared to the wide spectrum of neuroimaging biomarker applications in dementia research, biomarker use in psychotic or affective disorders has been largely confined to the proof of mechanism of new drugs. Radioligands for the targets of the drug (commonly neurotransmitter receptors or transporters) can be used to measure target occupancy and help determine what doses are needed for a desired level of occupancy. This approach has been particularly widely used in the investigation of dopamine receptor occupancy of antipsychotic drugs (Nord and Farde, 2011Nord M. Farde L. Antipsychotic occupancy of dopamine receptors in schizophrenia.CNS Neurosci. Ther. 2011; 17: 97-103Crossref PubMed Scopus (38) Google Scholar) and of serotonin transporter blockade of antidepressants (Meyer, 2007Meyer J.H. Imaging the serotonin transporter during major depressive disorder and antidepressant treatment.J. Psychiatry Neurosci. 2007; 32: 86-102PubMed Google Scholar). Recent work has demonstrated a correlation between dopamine D2 receptor occupancy and clinical improvement after treatment with the antipsychotics aripiprazole (Kegeles et al., 2008Kegeles L.S. Slifstein M. Frankle W.G. Xu X. Hackett E. Bae S.A. Gonzales R. Kim J.H. Alvarez B. Gil R. et al.Dose-occupancy study of striatal and extrastriatal dopamine D2 receptors by aripiprazole in schizophrenia with PET and [18F]fallypride.Neuropsychopharmacology. 2008; 33: 3111-3125Crossref PubMed Scopus (55) Google Scholar) and quetiapine (Nikisch et al., 2010Nikisch G. Baumann P. Kiessling B. Reinert M. Wiedemann G. Kehr J. Mathé A.A. Piel M. Roesch F. Weisser H. et al.Relationship between dopamine D2 receptor occupancy, clinical response, and drug and monoamine metabolites levels in plasma and cerebrospinal fluid. A pilot study in patients suffering from first-episode schizophrenia treated with quetiapine.J. Psychiatr. Res. 2010; 44: 754-759Abstract Full Text PDF PubMed Scopus (10) Google Scholar), but patient numbers, as in most PET studies, were small. Radioligands are also available for other potential targets of new antipsychotics, for example cannabinoid, tachykinin, glutamate, and nicotinic acetylcholine receptors (Takano, 2010Takano A. The application of PET technique for the development and evaluation of novel antipsychotics.Curr. Pharm. Des. 2010; 16: 371-377Crossref PubMed Scopus (10) Google Scholar) (Table 2). Such proof-of-mechanism studies can be useful both for the identification and rejection of new drugs (Wong et al., 2009Wong D.F. Tauscher J. Gründer G. The role of imaging in proof of concept for CNS drug discovery and development.Neuropsychopharmacology. 2009; 34: 187-203Crossref PubMed Scopus (58) Google Scholar). However, only a limited number of receptor subtypes or binding sites can be targeted, and often they do not include those that are of greatest current clinical interest (for example, the glycine and D-serine binding sites on the NMDA [N-methyl-D-aspartate]-type glutamate receptor; Takano, 2010Takano A. The application of PET technique for the development and evaluation of novel antipsychotics.Curr. Pharm. Des. 2010; 16: 371-377Crossref PubMed Scopus (10) Google Scholar). Moreover, almost all current targets are membrane proteins (see Table 2) and the postsynaptic signaling cascades, which are presumed to be of crucial relevance to the neural mechanisms of psychosis, depression, and addiction, for example (Kleppisch and Feil, 2009Kleppisch T. Feil R. cGMP signalling in the mammalian brain: role in synaptic plasticity and behaviour.Handb Exp Pharmacol. 2009; 191: 549-579Crossref PubMed Scopus (62) Google Scholar, Nestler et al., 2009Nestler E.J. Hyman S.E. Malenka R.C. Molecular Neuropharmacology: A Foundation for Clinical Neuroscience.Second Edition. McGraw-Hill Medical, New York2009Google Scholar, Wolf and Linden, 2011Wolf C. Linden D.E. Biological pathways to adaptability - interactions between genome, epigenome, nervous system and environment for adaptive behavior.Genes Brain Behav. 2011; (in press. Published online November 3, 1011)https://doi.org/10.1111/j.1601-183X.2011.00752.xCrossref PubMed Scopus (8) Google Scholar), are largely inaccessible to in vivo molecular imaging. Nevertheless, neuroimaging with radioligands and MRI techniques, particularly MRS, have a place in the evaluation of the pharmacokinetics and pharmacodynamics of new psychotropic drugs (Wong et al., 2009Wong D.F. Tauscher J. Gründer G. The role of imaging in proof of concept for CNS drug discovery and development.Neuropsychopharmacology. 2009; 34: 187-203Crossref PubMed Scopus (58) Google Scholar).Table 2Important Molecular Targets of Noninvasive Imaging in the Human BrainBiological System and Imaging TechniquesSpecific Subsystem TargetedSpecific Target MoleculesNT Receptors (PET/ SPECT)dopamineD1,2,3 receptorsserotonin5-HT1A, 1B, 2A receptorsglutamateMetabotropic glutamate receptor 5; NMDA receptorhistamineH1, H3 receptorstachykininsNeurokinin 1 receptoradenosineA1, A2A receptorsacetylcholineAlpha4beta2 and Alpha7 subunits of nicotinic receptor; muscarinic receptoropioidsMu, kappa, delta receptorscannabinoidsCB1 receptorGABA (gamma-aminobutyric acid)GABA-A receptor (benzodiazepine binding site and Alpha5 subunit)Sigma receptorNT Transporter (PET/ SPECT)monoaminesDopamine transporter; Vesicular monoamine transporter 2; serotonin transporter; norepinephrine transporterNT Synthesis (PET/ SPECT, MRS)monoaminesAromatic amino acid decarboxylaseGABAglutamate / glutamineNT Metabolism (PET/ SPECT)monoaminesMonoamine oxidaseacetylcholineAcetylcholine esteraseButyrylcholine esteraseGeneral metabolism (PET)glucose uptakeoxygen metabolism, blood flowInflammation (PET)microgliaTranslocator protein (18kDa)Neurodegeneration (PET)extracellular changesAmyloid plaquesintracellular changesNeurofibrillary tanglesPostsynaptic signaling and neuronal metabolism (MRS)N-acetyl aspartate, myo-inositolDrug metabolism (PET)blood brain barrier / efflux transportersP-glycoproteinSources: Molecular Imaging and Contrast Agent Database (MICAD), accessed on 27 November 2011 at http://www.ncbi.nlm.nih.gov/books/NBK5330/, and Nikolaus et al., 2009Nikolaus S. Antke C. Müller H.W. In vivo imaging of synaptic function in the central nervous system: II. Mental and affective disorders.Behav. Brain Res. 2009; 204: 32-66Crossref PubMed Scopus (52) Google Scholar, Takano, 2010Takano A. The application of PET technique for the development and evaluation of novel antipsychotics.Curr. Pharm. Des. 2010; 16: 371-377Crossref PubMed Scopus (10) Google Scholar, Wong et al., 2009Wong D.F. Tauscher J. Gründer G. The role of imaging in proof of concept for CNS drug discovery and development.Neuropsychopharmacology. 2009; 34: 187-203Crossref PubMed Scopus (58) Google Scholar. Open table in a new tab Sources: Molecular Imaging and Contrast Agent Database (MICAD), accessed on 27 November 2011 at http://www.ncbi.nlm.nih.gov/books/NBK5330/, and Nikolaus et al., 2009Nikolaus S. Antke C. Müller H.W. In vivo imaging of synaptic function in the central nervous system: II. Mental and affective disorders.Behav. Brain Res. 2009; 204: 32-66Crossref PubMed Scopus (52) Google Scholar, Takano, 2010Takano A. The application of PET technique for the development and evaluation of novel antipsychotics.Curr. Pharm. Des. 2010; 16: 371-377Crossref PubMed Scopus (10) Google Scholar, Wong et al., 2009Wong D.F. Tauscher J. Gründer G. The role of imaging in proof of concept for CNS drug discovery and development.Neuropsychopharmacology. 2009; 34: 187-203Crossref PubMed Scopus (58) Google Scholar. The progress with diagnostic or prognostic imaging biomarkers of mental disorders has been comparatively disappointing. For example, a recent study confirmed the specificity of ventricular enlargement for schizophrenia compared to affective psychosis. However, this study suggested that relatives of patients with familial schizophrenia (that is, with at least two known cases in the family) may also show this sign (McDonald et al., 2006McDonald C. Marshall N. Sham P.C. Bullmore E.T. Schulze K. Chapple B. Bramon E. Filbey F. Quraishi S. Walshe M. Murray R.M. Regional brain morphometry in patients with schizophrenia or bipolar disorder and their unaffected relatives.Am. J. Psychiatry. 2006; 163: 478-487Crossref PubMed Scopus (129) Google Scholar). Thus, ventricle enlargement may be associated with the genetic risk of schizophrenia rather than the actual manifestation of the disease. Furthermore, the general problem with structural imaging findings in schizophrenia is that even where significant group differences have been reliably documented, the overlap with the healthy population is too large to allow for a diagnostic use. Structural imaging studies of white matter using diffusion tensor imaging (DTI) consistently report changes (smaller volume, lower fractional anisotropy) in the corpus callosum (Rotarska-Jagiela et al., 2008Rotarska-Jagiela A. Schönmeyer R. Oertel V. Haenschel C. Vogeley K. Linden D.E. The corpus callosum in schizophrenia-volume and connectivity changes affect specific regions.Neuroimage. 2008; 39: 1522-1532Crossref PubMed Scopus (74) Google Scholar), even in untreated patients (Venkatasubramanian et al., 2010Venkatasubramanian G. Jayakumar P.N. Reddy V.V. Reddy U.S. Gangadhar B.N. Keshavan M.S. Corpus callosum deficits in antipsychotic-naïve schizophrenia: evidence for neurodevelopmental pathogenesis.Psychiatry Res. 2010; 182: 141-145Abstract Full Text Full Text PDF PubMed Scopus (9) Google Scholar), but again the overlap with the healthy population is considerable. The same is true for the neurophysiological signatures of altered perceptual and cognitive processing in schizophrenia (Haenschel and Linden, 2011Haenschel C. Linden D.E.J. Neurophysiology of Cognitive Dysfunction in Schizophrenia.in: Ritsner M.S. Handbook of Schizophrenia Spectrum Disorders. Springer, Heidelberg2011Google Scholar) or fMRI measures of connectivity of resting state networks (Greicius, 2008Greicius M. Resting-state functional connectivity in neuropsychiatric disorders.Curr. Opin. Neurol. 2008; 21: 424-430Crossref PubMed Google Scholar), none of which has attained biomarker status. One reason for the failure, so far, of structural and neurophysiological measures to produce biomarkers of mental disorders might be that they lack the neurochemical specificity that is needed to detect a disease characterized by altered neurotransmitter or receptor function. Based on this rationale, SPECT or PET should be more successful, particularly in schizophrenia, where the treatment effects of antidopaminergic drugs point to an important role of the dopamine system. However, these techniques have so far not produced imaging biomarkers of schizophrenia either (Nikolaus et al., 2009Nikolaus S. Antke C. Müller H.W. In vivo imaging of synaptic function in the central nervous system: II. Mental and affective disorders.Behav. Brain Res. 2009; 204: 32-66Crossref PubMed Scopus (52) Google Scholar). For example, the decrease of dopamine receptor occupancy after amphetamine challenge (interpreted as increased responsiveness of presynaptic dopamine release) (Abi-Dargham et al., 1998Abi-Dargham A. Gil R. Krystal J. Baldwin R.M. Seibyl J.P. Bowers M. van Dyck C.H. Charney D.S. Innis R.B. Laruelle M. Increased striatal dopamine transmission in schizophrenia: confirmation in a second cohort.Am. J. Psychiatry. 1998; 155: 761-767PubMed Google Scholar, Laruelle et al., 1996Laruelle M. Abi-Dargham A. van Dyck C.H. Gil R. D'Souza C.D. Erdos J. McCance E. Rosenblatt W. Fingado C. Zoghbi S.S. et al.Single photon emission computerized tomography imaging of amphetamine-induced dopamine release in drug-free schizophrenic subjects.Proc. Natl. Acad. Sci. USA. 1996; 93: 9235-9240Crossref PubMed Google Scholar) shows too much overlap with the healthy population to allow for use as biomarker. Furthermore, patients with schizotypal personality disorder have similar changes (Abi-Dargham et al., 2004Abi-Dargham A. Kegeles L.S. Zea-Ponce Y. Mawlawi O. Martinez D. Mitropoulou V. O'Flynn K. Koenigsberg H.W. Van Heertum R. Cooper T. et al.Striatal amphetamine-induced dopamine release in patients with schizotypal personality disorder studied with single photon emission computed tomography and [123I]iodobenzamide.Biol. Psychiatry. 2004; 55: 1001-1006Abstract Full Text Full Text PDF PubMed Scopus (54) Google Scholar). Another key measure is the striatal uptake of 18F-DOPA (dihydroxyphenylalanine), thought to reflect dopamine synthesis. The majority of studies in schizophrenia, particularly with patients in the ac
Referência(s)