TY - JOUR
T1 - Testing Psychosis Phenotypes From Bipolar–Schizophrenia Network for Intermediate Phenotypes for Clinical Application
T2 - Biotype Characteristics and Targets
AU - Clementz, Brett A.
AU - Trotti, Rebekah L.
AU - Pearlson, Godfrey D.
AU - Keshavan, Matcheri S.
AU - Gershon, Elliot S.
AU - Keedy, Sarah K.
AU - Ivleva, Elena I.
AU - McDowell, Jennifer E.
AU - Tamminga, Carol A.
N1 - Funding Information:
This work was supported by the National Institute of Mental Health (NIMH) through its support of the Bipolar–Schizophrenia Network for Intermediate Phenotypes (Grant Nos. MH077851 [to CAT], MH078113 [to MSK], MH077945 [to GDP], MH096942 [to BAC], and MH096957 [to ESG]). GDP is also supported by research grants from the NIMH , National Institute on Alcohol Abuse and Alcoholism , National Institute on Drug Abuse , National Highway Traffic Safety Administration , and National Institute of Diabetes and Digestive and Kidney Diseases . MSK is supported by research grants from the NIMH and the Bear and Natalia Foundations. EII is supported by a research grant from the NIMH (Grant No. 1K23 MH102656 ). JEM is supported by a research grant from the National Institutes of Health (Grant No. HL143440 ). CAT is supported by additional grants from the NIMH (Grant Nos. T32MHo76690 and P50MH096890 ).
Funding Information:
This work was supported by the National Institute of Mental Health (NIMH) through its support of the Bipolar?Schizophrenia Network for Intermediate Phenotypes (Grant Nos. MH077851 [to CAT], MH078113 [to MSK], MH077945 [to GDP], MH096942 [to BAC], and MH096957 [to ESG]). GDP is also supported by research grants from the NIMH, National Institute on Alcohol Abuse and Alcoholism, National Institute on Drug Abuse, National Highway Traffic Safety Administration, and National Institute of Diabetes and Digestive and Kidney Diseases. MSK is supported by research grants from the NIMH and the Bear and Natalia Foundations. EII is supported by a research grant from the NIMH (Grant No. 1K23 MH102656). JEM is supported by a research grant from the National Institutes of Health (Grant No. HL143440). CAT is supported by additional grants from the NIMH (Grant Nos. T32MHo76690 and P50MH096890). BAC reports ad hoc consultancies with Astellas. GDP reports a small honorarium as deputy editor of the journal Schizophrenia Research. MSK reports an honorarium from the journal Schizophrenia Research as editor and consulting fees from the Alkermes Foundation. ESG reports consulting fees from Guidepoint and GLG consulting firms. CAT reports ad hoc consultancies with Sunovion, Astellas, and Acadia as well as scientific board memberships with Karuna and Kynexis. The other authors report no biomedical financial interests or potential conflicts of interest.
Publisher Copyright:
© 2020
PY - 2020/8
Y1 - 2020/8
N2 - Background: Psychiatry aspires to the molecular understanding of its disorders and, with that knowledge, to precision medicine. Research supporting such goals in the dimension of psychosis has been compromised, in part, by using phenomenology alone to estimate disease entities. To this end, we are proponents of a deep phenotyping approach in psychosis, using computational strategies to discover the most informative phenotypic fingerprint as a promising strategy to uncover mechanisms in psychosis. Methods: Doing this, the Bipolar–Schizophrenia Network for Intermediate Phenotypes (B-SNIP) has used biomarkers to identify distinct subtypes of psychosis with replicable biomarker characteristics. While we have presented these entities as relevant, their potential utility in clinical practice has not yet been demonstrated. Results: Here we carried out an analysis of clinical features that characterize biotypes. We found that biotypes have unique and defining clinical characteristics that could be used as initial screens in the clinical and research settings. Differences in these clinical features appear to be consistent with biotype biomarker profiles, indicating a link between biological features and clinical presentation. Clinical features associated with biotypes differ from those associated with DSM diagnoses, indicating that biotypes and DSM syndromes are not redundant and are likely to yield different treatment predictions. We highlight 3 predictions based on biotype that are derived from individual biomarker features and cannot be obtained from DSM psychosis syndromes. Conclusions: In the future, biotypes may prove to be useful for targeting distinct molecular, circuit, cognitive, and psychosocial therapies for improved functional outcomes.
AB - Background: Psychiatry aspires to the molecular understanding of its disorders and, with that knowledge, to precision medicine. Research supporting such goals in the dimension of psychosis has been compromised, in part, by using phenomenology alone to estimate disease entities. To this end, we are proponents of a deep phenotyping approach in psychosis, using computational strategies to discover the most informative phenotypic fingerprint as a promising strategy to uncover mechanisms in psychosis. Methods: Doing this, the Bipolar–Schizophrenia Network for Intermediate Phenotypes (B-SNIP) has used biomarkers to identify distinct subtypes of psychosis with replicable biomarker characteristics. While we have presented these entities as relevant, their potential utility in clinical practice has not yet been demonstrated. Results: Here we carried out an analysis of clinical features that characterize biotypes. We found that biotypes have unique and defining clinical characteristics that could be used as initial screens in the clinical and research settings. Differences in these clinical features appear to be consistent with biotype biomarker profiles, indicating a link between biological features and clinical presentation. Clinical features associated with biotypes differ from those associated with DSM diagnoses, indicating that biotypes and DSM syndromes are not redundant and are likely to yield different treatment predictions. We highlight 3 predictions based on biotype that are derived from individual biomarker features and cannot be obtained from DSM psychosis syndromes. Conclusions: In the future, biotypes may prove to be useful for targeting distinct molecular, circuit, cognitive, and psychosocial therapies for improved functional outcomes.
KW - Biomarkers
KW - Computational neuroscience
KW - Neurobiological
KW - Precision medicine
KW - Psychopathology
KW - Transdiagnostic
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U2 - 10.1016/j.bpsc.2020.03.011
DO - 10.1016/j.bpsc.2020.03.011
M3 - Article
C2 - 32600898
AN - SCOPUS:85087012976
SN - 2451-9022
VL - 5
SP - 808
EP - 818
JO - Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
JF - Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
IS - 8
ER -