The major psychoses (SZ, SAD, BDP), when defined by clinical phenomenology alone, overlap extensively on neurobiological, biomarker, co-morbid, symptomatic, and genetic characteristics. Our field may benefit from transformational re-conceptualizations of disease seen in other areas of medicine when biological variables are considered in disease definitions and identification. This approach in psychiatry will depend on: (i) use of well- defined disease domains, (ii) large samples that capture clinical heterogeneity and support statistical approaches, and (iii) ability to acquire quantifiable laboratory measures t inform re-conceptualization of disease characteristics. The 5-site B-SNIP focus is psychosis, an ideal clinical phenotype for this purpose. B- SNIP1 recruited over 2500 volunteers and performed dense phenotyping across multiple levels of analysis (cognitive, psychophysiological, brain imaging, social and clinical). The overall data described a continuum of phenotypic alterations across the DSM psychosis diagnoses (BDP, SAD, SZ) with little evidence of diagnostic specificity. In an attempt to use these dense phenotypic characteristics to define biologically based subgroups, we re-grouped probands using biomarkers and a multistage multivariate analysis procedure. We identified 3 psychosis Biotypes based on core phenotypic features. Biotypes showed unique differences across external validators that were not used in the initial construction of the categories. B-SNIP2 will replicate and extend B- SNIP1 using enhanced proband number, biomarker panel, and sophistication of multivariate statistical approaches. We will accomplish our goals within the context of two specific aims. SA(1) Construct a 'Psychosis Biomarker Database' (PBD): Recruit 3000 new psychosis probands and 600 healthy volunteers and collect data including clinical, psychosocial, electrophysiological, ocular motor, imaging and blood biomarkers. Core biomarkers (used for Biotype definition) and external validators (used for verifying neurobiological distinctiveness of Biotypes) will be collected as specified. Genetic characteristics of the participants will be obtained in collaboratin with the Broad Institute. SA(2) Contrast and test taxometric approaches to categorizing psychosis: Evaluate the ability of different taxonomic structures to define psychosis subgroups, based on data in the PBD: (i) DSM, (ii) B-SNIP2 biotypes based on clinical variables, (iii) B-SNIP1 Biotypes, (iv) B-SNIP2-generated biotypes based on biomarkers, and (v) B-SNIP2 biotypes based on both clinical variables and biomarkers. Beginning with traditional DSM diagnostic criteria as the taxonomy and testing (i)-(v) we will use linear, quadratic and nonparametric discriminant function analysis applied to external biomarker validators to examine the association between the traditional diagnostic system and the biologically- derived classification (imaging, psychosocial and genetic external validators). We will be able to determine the strongest taxonomic approach based on biological characteristics. We seek a rational classification of psychotic disorders that will be successful in identifying novel disease targets and treatments approaches.
The DSM major psychosis diagnoses (schizophrenia, schizoaffective disorder, bipolar disorder with psychosis) overlap extensively on neurobiology and genetics. Our collaborative group (called B-SNIP) developed a psychosis classification scheme (which we called Biotypes) using biological measures that are superior to DSM diagnoses for capturing neurobiological similarities and differences. In this project, we will broaden and extend this work to refine the neurobiological Biotype definitions, characterize unique molecular and genetic features of Biotypes, and test various classifications using multivariate approaches, which will be an important step toward personalized medicine for psychiatry.
|Abush, Hila; Ghose, Subroto; Van Enkevort, Erin A et al. (2018) Associations between adolescent cannabis use and brain structure in psychosis. Psychiatry Res Neuroimaging 276:53-64|
|Rodrigue, Amanda L; McDowell, Jennifer E; Tandon, Neeraj et al. (2018) Multivariate Relationships Between Cognition and Brain Anatomy Across the Psychosis Spectrum. Biol Psychiatry Cogn Neurosci Neuroimaging 3:992-1002|
|Rubin, Leah H; Li, Siyi; Yao, Li et al. (2018) Peripheral oxytocin and vasopressin modulates regional brain activity differently in men and women with schizophrenia. Schizophr Res 202:173-179|
|Gershon, Elliot S; Pearlson, Godfrey; Keshavan, Matcheri S et al. (2018) Genetic analysis of deep phenotyping projects in common disorders. Schizophr Res 195:51-57|
|Hochberger, W C; Combs, T; Reilly, J L et al. (2018) Deviation from expected cognitive ability across psychotic disorders. Schizophr Res 192:300-307|
|Ivleva, Elena I; Clementz, Brett A; Dutcher, Anthony M et al. (2017) Brain Structure Biomarkers in the Psychosis Biotypes: Findings From the Bipolar-Schizophrenia Network for Intermediate Phenotypes. Biol Psychiatry 82:26-39|
|Reilly, James L; Hill, S Kristian; Gold, James M et al. (2017) Impaired Context Processing is Attributable to Global Neuropsychological Impairment in Schizophrenia and Psychotic Bipolar Disorder. Schizophr Bull 43:397-406|
|Eum, Seenae; Hill, S Kristian; Rubin, Leah H et al. (2017) Cognitive burden of anticholinergic medications in psychotic disorders. Schizophr Res 190:129-135|
|Tandon, Neeraj; Nanda, Pranav; Padmanabhan, Jaya L et al. (2017) Novel gene-brain structure relationships in psychotic disorder revealed using parallel independent component analyses. Schizophr Res 182:74-83|
|Lencer, R; Mills, L J; Alliey-Rodriguez, N et al. (2017) Genome-wide association studies of smooth pursuit and antisaccade eye movements in psychotic disorders: findings from the B-SNIP study. Transl Psychiatry 7:e1249|
Showing the most recent 10 out of 87 publications