Neuroimaging as a potential biomarker to optimize psychiatric research and treatment (original) (raw)
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Psychiatric neuroimaging: Joining forces with epidemiology
European Psychiatry, 2008
Severe mental illnesses such as schizophrenia and mood disorders have a major impact on public health. Disease prevalence and phenotypic expression are the products of environment and gene interactions. However, our incomplete understanding of their aetiology and pathophysiology thwarts primary prevention and early diagnosis and limits the effective application of currently available treatments as well as the development of novel therapeutic approaches. Neuroimaging can provide detailed in vivo information about the biological mechanisms underpinning the relationship between genetic variation and clinical phenotypes or response to treatment. However, the biological complexity of severe mental illness results from unknown or unpredictable interactions between multiple genetic and environmental factors, many of which have only been partially identified. We propose that the use of epidemiological principles to neuroimaging research is a necessary next step in psychiatric research. Because of the complexity of mental disorders and the multiple risk factors involved only the use of large epidemiologically defined samples will allow us to study the broader spectrum of psychopathology, including sub-threshold presentation and explore pathophysiological processes and the functional impact of genetic and non-genetic factors on the onset and persistence of psychopathology.
Neuroimaging-Based Biomarkers in Psychiatry: Clinical Opportunities of a Paradigm Shift A
Neuroimaging research has substantiated the functional and structural abnormalities underlying psychiatric disorders but has, thus far, failed to have a significant impact on clinical practice. Recently, neuroimaging-based diagnoses and clinical predictions derived from machine learning analysis have shown significant potential for clinical translation. This review introduces the key concepts of this approach, including how the multivariate integration of patterns of brain abnormalities is a crucial component. We survey recent findings that have potential application for diagnosis, in particular early and differential diagnoses in Alzheimer disease and schizophrenia, and the prediction of clinical response to treatment in depression. We discuss the specific clinical opportunities and the challenges for developing biomarkers for psychiatry in the absence of a diagnostic gold standard. We propose that longitudinal outcomes, such as early diagnosis and prediction of treatment response, offer definite opportunities for progress. We propose that efforts should be directed toward clinically challenging predictions in which neuroimaging may have added value, compared with the existing standard assessment. We conclude that diagnostic and prognostic biomarkers will be developed through the joint application of expert psychiatric knowledge in addition to advanced methods of analysis.
Neuroimaging in psychiatric pharmacogenetics research: The promise and pitfalls
The integration of research on neuroimaging and pharmacogenetics holds promise for improving treatment for neuropsychiatric conditions. Neuroimaging may provide a more sensitive early measure of treatment response in genetically defined patient groups, and could facilitate development of novel therapies based on an improved understanding of pathogenic mechanisms underlying pharmacogenetic associations. This review summarizes progress in efforts to incorporate neuroimaging into genetics and treatment research on major psychiatric disorders such as schizophrenia, major depressive disorder, bipolar disorder, attention-deficit/hyperactivity disorder, and addiction. Methodological challenges include: performing genetic analyses in small study populations used in imaging studies; inclusion of patients with psychiatric comorbidities; and the extensive variability across studies in neuroimaging protocols, neurobehavioral task probes, and analytic strategies. Moreover, few studies use pharmacogenetic designs that permit testing of genotype x drug effects. As a result of these limitations, few findings have been fully replicated. Future studies that pre-screen participants for genetic variants selected a priori based on drug metabolism and targets have the greatest potential to advance the science and practice of psychiatric treatment.
F1000 - Post-publication peer review of the biomedical literature, 2013
The integration of research on neuroimaging and pharmacogenetics holds promise for improving treatment for neuropsychiatric conditions. Neuroimaging may provide a more sensitive early measure of treatment response in genetically defined patient groups, and could facilitate development of novel therapies based on an improved understanding of pathogenic mechanisms underlying pharmacogenetic associations. This review summarizes progress in efforts to incorporate neuroimaging into genetics and treatment research on major psychiatric disorders, such as schizophrenia, major depressive disorder, bipolar disorder, attention-deficit/hyperactivity disorder, and addiction. Methodological challenges include: performing genetic analyses in small study populations used in imaging studies; inclusion of patients with psychiatric comorbidities; and the extensive variability across studies in neuroimaging protocols, neurobehavioral task probes, and analytic strategies. Moreover, few studies use pharmacogenetic designs that permit testing of genotype  drug effects. As a result of these limitations, few findings have been fully replicated. Future studies that pre-screen participants for genetic variants selected a priori based on drug metabolism and targets have the greatest potential to advance the science and practice of psychiatric treatment.
Intermediate phenotypes in psychiatric disorders
Current Opinion in Genetics & Development, 2011
The small effect size of most individual risk factors for psychiatric disorders likely reflects biological heterogeneity and diagnostic imprecision, which has encouraged genetic studies of intermediate biological phenotypes that are closer to the molecular effects of risk genes than are the clinical symptoms. Neuroimaging-based intermediate phenotypes have emerged as particularly promising because they map risk associated gene effects onto physiological processes in brain that are altered in patients and in their healthy relatives. Recent evidence using this approach has elucidated discrete, dissociable biological mechanisms of risk genes at the level of neural circuitries, and their related cognitive functions. This approach may greatly contribute to our understanding of the genetics and pathophysiology of psychiatric disorders.
Genes, Brains, and Behavior: Imaging Genetics for Neuropsychiatric Disorders
J Neuropsychiatry Clin Neurosci., 2015
The majority of neuropsychiatric disorders show a strong degree of heritability, yet little is known about molecular factors involved in the pathophysiology of diseases like schizophrenia. After a brief historical introduction into the current understanding of neuropsychiatric disorders, the aim of this study is to discuss imaging genetics as a strategy to explore the pathophysiology of neuropsychiatric disorders. The candidate gene approach of imaging genetics is used for validation/ replication studies of genes, whereas the hypothesis-free, noncandidate gene approach appears to be a tool for gene discovery. Besides, integration of environmental factors into neuroimaging begins to converge on neuroimaging studies of genetic variation. In the light of data from other avenues such as animal experimentation, these developments show a model of interdisciplinary research, which may lead to identifying markers for neuropsychiatric disorders.
Neuroimaging genomics in psychiatry-a translational approach
Genome medicine, 2017
Neuroimaging genomics is a relatively new field focused on integrating genomic and imaging data in order to investigate the mechanisms underlying brain phenotypes and neuropsychiatric disorders. While early work in neuroimaging genomics focused on mapping the associations of candidate gene variants with neuroimaging measures in small cohorts, the lack of reproducible results inspired better-powered and unbiased large-scale approaches. Notably, genome-wide association studies (GWAS) of brain imaging in thousands of individuals around the world have led to a range of promising findings. Extensions of such approaches are now addressing epigenetics, gene-gene epistasis, and gene-environment interactions, not only in brain structure, but also in brain function. Complementary developments in systems biology might facilitate the translation of findings from basic neuroscience and neuroimaging genomics to clinical practice. Here, we review recent approaches in neuroimaging genomics-we highl...
Mapping the Schizophrenia Genes by Neuroimaging: The Opportunities and the Challenges
International Journal of Molecular Sciences, 2018
Schizophrenia (SZ) is a heritable brain disease originating from a complex interaction of genetic and environmental factors. The genes underpinning the neurobiology of SZ are largely unknown but recent data suggest strong evidence for genetic variations, such as single nucleotide polymorphisms, making the brain vulnerable to the risk of SZ. Structural and functional brain mapping of these genetic variations are essential for the development of agents and tools for better diagnosis, treatment and prevention of SZ. Addressing this, neuroimaging methods in combination with genetic analysis have been increasingly used for almost 20 years. So-called imaging genetics, the opportunities of this approach along with its limitations for SZ research will be outlined in this invited paper. While the problems such as reproducibility, genetic effect size, specificity and sensitivity exist, opportunities such as multivariate analysis, development of multisite consortia for large-scale data collection, emergence of non-candidate gene (hypothesis-free) approach of neuroimaging genetics are likely to contribute to a rapid progress for gene discovery besides to gene validation studies that are related to SZ.
Neuroimaging tests for clinical psychiatry: Are we there yet?
Journal of psychiatry & neuroscience : JPN, 2017
Biomarkers index normal and abnormal biological processes, sometimes identifying the response potential of particular treatments. Though widely used in much of medicine, none has proven sufficiently robust to enter clinical practice in psych iatry. 1,2 And yet, recent high-quality neuroimaging studies give confidence that this is not an unattainable goal. Here's why. Neural fingerprinting There is now replicated evidence of neural "fingerprints." These functional connectivity networks are unique to the individual and consistent across testing conditions. 3,4 In the largest of these studies, with nearly 800 participants tested between the ages of 8 and 22 years, networks stabilized earlier in female than in male participants and earlier in healthy adolescents than psychologically troubled ones. 4 Individual differences in these "fingerprints" show evidence of being shaped by early life experiences 5,6 and of corresponding to cognitive-affective traits. 6,7