Cited by 768Schizophrenia research and treatmentMental Health and PsychiatryBipolar Disorder and Treatment

The DOI matches its Crossref record; 50 of the 50 references it cites were found in a registry or an index.

Identification of Distinct Psychosis Biotypes Using Brain-Based Biomarkers

Open access

Clementz, Brett A., Sweeney, John A., Hamm, Jordan P., Ivleva, Elena I., Ethridge, Lauren E., Pearlson, Godfrey D., Keshavan, Matcheri S., Tamminga, Carol A.·2016·American Journal of Psychiatry

DOI 10.1176/appi.ajp.2015.14091200PMC PMC5314432

Open this paper in CoChat — free account

Abstract

OBJECTIVE: Clinical phenomenology remains the primary means for classifying psychoses despite considerable evidence that this method incompletely captures biologically meaningful differentiations. Rather than relying on clinical diagnoses as the gold standard, this project drew on neurobiological heterogeneity among psychosis cases to delineate subgroups independent of their phenomenological manifestations. METHOD: A large biomarker panel (neuropsychological, stop signal, saccadic control, and auditory stimulation paradigms) characterizing diverse aspects of brain function was collected on individuals with schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis (N=711), their first-degree relatives (N=883), and demographically comparable healthy subjects (N=278). Biomarker variance across paradigms was exploited to create nine integrated variables that were used to capture neurobiological variance among the psychosis cases. Data on external validating measures (social functioning, structural magnetic resonance imaging, family biomarkers, and clinical information) were collected. RESULTS: Multivariate taxometric analyses identified three neurobiologically distinct psychosis biotypes that did not respect clinical diagnosis boundaries. The same analysis procedure using clinical DSM diagnoses as the criteria was best described by a single severity continuum (schizophrenia worse than schizoaffective disorder worse than bipolar psychosis); this was not the case for biotypes. The external validating measures supported the distinctiveness of these subgroups compared with clinical diagnosis, highlighting a possible advantage of neurobiological versus clinical categorization schemes for differentiating psychotic disorders. CONCLUSIONS: These data illustrate how multiple pathways may lead to clinically similar psychosis manifestations, and they provide explanations for the marked heterogeneity observed across laboratories on the same biomarker variables when DSM diagnoses are used as the gold standard.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1176/appi.ajp.2015.14091200

Cites

50 of 50 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Diagnostic and Statistical Manual of Mental Disorders
American Psychiatric Association (2013) · doi:10.1176/appi.books.9780890425596 · Cited by 116,369
Data clustering: 50 years beyond K-means
Jain, A. K. (2009) · Pattern Recognition Letters · doi:10.1016/j.patrec.2009.09.011 · Cited by 10,021
Research domain criteria (RDoC): toward a new classification framework for research on mental disorders
Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D. S., Quinn, K., Sanislow, C., & Wang, P. (2010) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2010.09091379 · Cited by 7,067
Estimating the Number of Clusters in a Data Set Via the Gap Statistic
Tibshirani, R., Walther, G., & Hastie, T. (2001) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00293 · Cited by 6,205
The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups
METABRIC Group, Curtis, C., Shah, S. P., Chin, S.-F., Turashvili, G., Rueda, O. M., Dunning, M. J., Speed, D., Lynch, A. G., Samarajiwa, S., et al. (2012) · Nature · doi:10.1038/nature10983 · Cited by 6,097
Comparative efficacy and tolerability of 15 antipsychotic drugs in schizophrenia: a multiple-treatments meta-analysis
Leucht, S., Cipriani, A., Spineli, L., Mavridis, D., Örey, D., Richter, F., Samara, M., Barbui, C., Engel, R. R., Geddes, J. R., et al. (2013) · The Lancet · doi:10.1016/s0140-6736(13)60733-3 · Cited by 2,561
Preterm labor: One syndrome, many causes
Romero, R., Dey, S. K., & Fisher, S. J. (2014) · Science · doi:10.1126/science.1251816 · Cited by 1,984
The Family History Method Using Diagnostic Criteria
Andreasen, N. C. (1977) · Archives of General Psychiatry · doi:10.1001/archpsyc.1977.01770220111013 · Cited by 1,903
The Brief Assessment of Cognition in Schizophrenia: reliability, sensitivity, and comparison with a standard neurocognitive battery
Keefe, R. (2004) · Schizophrenia Research · doi:10.1016/j.schres.2003.09.011 · Cited by 1,573
K -means clustering via principal component analysis
Ding, C. H. Q., & He, X. (2004) · doi:10.1145/1015330.1015408 · Cited by 1,412

Show all 50 references

Research works printed but not linked: 7

Bethune G, 2010, J Thorac Dis, 2, 48
National Research Council (US), 2011, Committee on a Framework for Developing a New Taxonomy of Disease: Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease
Hyman SE, Cerebrum
Zanarini MC, 1996, Diagnostic Interview for DSM-IV Personality Disorders (DIPD-IV)
Iacono WG, 1993, Prog Exp Pers Psychopathol Res, 16, 11
Friston KJ, 1995, Clin Neurosci, 3, 89
Rosenberg RN, 2014, Rosenberg’s Molecular and Genetic Basis of Neurological and Psychiatric Diseases

Sorted by citations

Items 401–500 of 767

The golden age of computational psychiatry is within sight
Vinogradov, S. (2017) · Nature Human Behaviour · doi:10.1038/s41562-017-0047 · Cited by 10
Advances in Psychiatric Diagnosis: Past, Present, and Future
North, C. S., & Surís, A. (2017) · Behavioral Sciences · doi:10.3390/bs7020027 · Cited by 11
Biotypes: promise and pitfalls
Barch, D. M. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.04.012 · Cited by 9
NMDAR dysfunction and the regulation of dopaminergic transmission in schizophrenia
Dwyer, G. E., Johnsen, E., & Hugdahl, K. (2024) · Schizophrenia Research · doi:10.1016/j.schres.2024.07.025 · Cited by 9
Quantitative analysis of literature on diagnostic biomarkers of Schizophrenia: revealing research hotspots and future prospects
Jin, L., Wu, L., Zhang, J., Jia, W., Zhou, H., Jiang, S., Jiang, P., Li, Y., & Li, Y. (2025) · BMC Psychiatry · doi:10.1186/s12888-025-06644-3 · Cited by 9
From synapse to system: mechanistic pathways of neural signaling dysfunction in psychiatric disorders
Gupta, R., Jha, N. K., Kumar, N., Nagraik, R., & Ravi, K. (2026) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2026.1762930 · Cited by 14
Biomarker Profiles in Psychosis Risk Groups Within Unaffected Relatives Based on Familiality and Age
Türközer, H. B., Ivleva, E. I., Palka, J. M., Clementz, B. A., Shafee, R., Pearlson, G. D., Sweeney, J. A., Keshavan, M. S., Gershon, E. S., & Tamminga, C. A. (2021) · Schizophrenia Bulletin · doi:10.1093/schbul/sbab013 · Cited by 9
Self-citation
Re-Inventing the Dsm as A Transdiagnostic Model: Psychiatric Disorders Are Extensively Interconnected
Nasrallah, H. A. (2021) · Annals of Clinical Psychiatry · doi:10.12788/acp.0037 · Cited by 9
Etiopathogenic Models of Psychosis Spectrum Illnesses Must Resolve Four Key Features
Vinogradov, S., Hamid, A., & Redish, A. D. (2022) · Biological Psychiatry · doi:10.1016/j.biopsych.2022.06.024 · Cited by 9
From psychiatric kinds to harmful symptoms
Gauld, C. (2022) · Synthese · doi:10.1007/s11229-022-03922-5 · Cited by 9
NEUROCOGNITIVE PROFILES OF PATIENTS WITH THE FIRST EPISODE OF PSYCHOSIS AND SCHIZOPHRENIA DO NOT DIFFER QUALITATIVELY: A NESTED CROSS-SECTIONAL STUDY
Kuharić, D. B., Makarić, P., Kekin, I., Bajić, Ž., Živković, M., Savić, A., Jukić, V., & Kuzman, M. R. (2019) · Psychiatria Danubina · doi:10.24869/psyd.2019.43 · Cited by 9
Application of Near-Infrared Spectroscopy for Understanding Spontaneous Brain Activity During Resting State in Schizophrenia: A Mini Review
Yanagi, M., & Shirakawa, O. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.704506 · Cited by 9
The scheduling of adolescence with Netrin-1 and UNC5C
Hoops, D., Kyne, R., Salameh, S., MacGowan, D., Avramescu, R. G., Ewing, E., He, A. T., Orsini, T., Durand, A., Popescu, C., et al. (2024) · eLife · doi:10.7554/elife.88261 · Cited by 8
Identifying psychosis subtypes use individualized covariance structural differential networks and multi-site clustering
Ji, Y., Pearlson, G. D., Bustillo, J., Kochunov, P. V., Turner, J. A., Jiang, R., Shao, W., Zhang, X., Fu, Z., Li, K., et al. (2023) · Schizophrenia Research · doi:10.1016/j.schres.2023.12.013 · Cited by 8
Self-citation
The status of MRI databases across the world focused on psychiatric and neurological disorders
Tanaka, S., Kasai, K., Okamoto, Y., Koike, S., Hayashi, T., Yamashita, A., Yamashita, O., Johnstone, T., Pestilli, F., Doya, K., et al. (2024) · Psychiatry and Clinical Neurosciences · doi:10.1111/pcn.13717 · Cited by 8
RDoC Framework Through the Lens of Predictive Processing: Focusing on Cognitive Systems Domain
Banaraki, A. K., Toghi, A., & Mohammadzadeh, A. (2024) · Computational Psychiatry · doi:10.5334/cpsy.119 · Cited by 11
Identifying neurobiological heterogeneity in clinical high-risk psychosis: a data-driven biotyping approach using resting-state functional connectivity
Tang, X., Wei, Y., Pang, J., Xu, L., Cui, H., Liu, X., Hu, Y., Ju, M., Tang, Y., Long, B., et al. (2025) · Schizophrenia · doi:10.1038/s41537-025-00565-6 · Cited by 8
Empirically supported interventions in psychology: contributions of Research Domain Criteria
Pasion, R., Martins, E. C., & Barbosa, F. (2019) · Psicologia Reflexão e Crítica · doi:10.1186/s41155-019-0128-1 · Cited by 10
Applications of hypergraph-based methods in classifying and subtyping psychiatric disorders: a survey
Ju, N., & Du, Y. (2023) · Radiology Science · doi:10.15212/radsci-2023-0008 · Cited by 8
Changing the Diagnostic Concept of Schizophrenia: The NIMH Research Domain Criteria Initiative
Morris, S. E., Vaidyanathan, U., & Cuthbert, B. N. (2016) · Nebraska Symposium on Motivation/The Nebraska symposium on motivation · doi:10.1007/978-3-319-30596-7_8 · Cited by 8
Polygenic pleiotropy and potential causal relationships between educational attainment, neurobiological profile, and positive psychotic symptoms
Lin, K., Chen, C., Öngür, D., Betensky, R. A., Smoller, J. W., Blacker, D., & Hall, M. (2018) · Translational Psychiatry · doi:10.1038/s41398-018-0144-4 · Cited by 9
Cluster analysis with MOODS‐SR illustrates a potential bipolar disorder risk phenotype in young adults with remitted major depressive disorder
Kling, L. R., Bessette, K. L., DelDonno, S. R., Ryan, K. A., Drevets, W. C., McInnis, M. G., Phillips, M. L., & Langenecker, S. A. (2018) · Bipolar Disorders · doi:10.1111/bdi.12693 · Cited by 9
Natural kinds of mental disorder
Werkhoven, S. (2021) · Synthese · doi:10.1007/s11229-021-03239-9 · Cited by 8
Deficits in generalized cognitive ability, visual sensorimotor function, and inhibitory control represent discrete domains of neurobehavioral deficit in psychotic disorders
Eskridge, C. L. M., Hochberger, W. C., Kaseda, E. T., Lencer, R., Reilly, J. L., Keedy, S., Keefe, R. S. E., Pearlson, G. D., Keshavan, M. S., Tamminga, C. A., et al. (2021) · Schizophrenia Research · doi:10.1016/j.schres.2021.07.036 · Cited by 8
Self-citation
Investigating Trauma as a Risk Factor for Psychosis
Freedman, R. (2016) · Schizophrenia Bulletin · doi:10.1093/schbul/sbw153 · Cited by 8
Characterizing the distinct imaging phenotypes, clinical behavior, and genetic vulnerability of brain maturational subtypes in mood disorders
Zheng, J., Zong, X., Tang, L., Guo, H., Zhao, P., Womer, F. Y., Zhang, X., Tang, Y., & Wang, F. (2024) · Psychological Medicine · doi:10.1017/s0033291724000886 · Cited by 7
Neuroscience in Pictures: 3. Schizophrenia
Keshavan, M. S., & Song, S. H. (2024) · Asian Journal of Psychiatry · doi:10.1016/j.ajp.2024.104278 · Cited by 7
Self-citation
Cognitive performance and differentiation of B-SNIP psychosis Biotypes: Algorithmic Diagnostics for Efficient Prescription of Treatments (ADEPT) - 2
Clementz, B. A., Chattopadhyay, I., Hill, S. K., McDowell, J. E., Keedy, S., Parker, D., Trotti, R. L., Ivleva, E. I., Keshavan, M. S., Gershon, E. S., et al. (2024) · Biomarkers in Neuropsychiatry · doi:10.1016/j.bionps.2024.100117 · Cited by 7
Self-citation
Neurofilament Light Protein as a Biomarker in Severe Mental Disorders: A Systematic Review
Squitti, R., Fiorenza, A., Martinelli, A., Brembati, V., Crescenti, D., Rongioletti, M. C. A., & Ghidoni, R. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms26010061 · Cited by 7
Clinical and cortical similarities identified between bipolar disorder I and schizophrenia: A multivariate approach
Rootes-Murdy, K., Edmond, J. T., Jiang, W., Rahaman, M. A., Chen, J., Perrone‐Bizzozero, N. I., Calhoun, V. D., van Erp, T. G. M., Ehrlich, S., Agartz, I., et al. (2022) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2022.1001692 · Cited by 7
Self-citation
Brain network characteristics separating individuals at clinical high risk for psychosis into normality or psychosis
Choi, S., Kyeong, S.-H., Cho, K. I. K., Yun, J., Lee, T. Y., Park, H. Y., Kim, S. N., & Kwon, J. S. (2017) · Schizophrenia Research · doi:10.1016/j.schres.2017.03.028 · Cited by 7
Cognitive Enhancement in Schizophrenia and Related Disorders
Keshavan, M. S., & Eack, S. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108163682 · Cited by 7
Self-citation
Do neurobiological differences exist between paranoid and non-paranoid schizophrenia? Findings from the bipolar schizophrenia network on intermediate phenotypes study
Lutz, O., Lizano, P. L., Mothi, S. S., Zeng, V., Hegde, R. R., Hoang, D. T., Henson, P., Brady, R. O., Tamminga, C. A., Pearlson, G. D., et al. (2020) · Schizophrenia Research · doi:10.1016/j.schres.2020.02.011 · Cited by 7
Self-citation
Testing the Stability and Validity of an Executive Dysfunction Classification Using Task-Based Assessment in Children and Adolescents
Manfro, A. G., Pine, D. S., Polanczyk, G. V., Santoro, M. L., Smoller, J. W., Koenen, K. C., Mari, J. D. J., Pan, P. M., Zugman, A., Schäfer, J., et al. (2020) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2020.11.016 · Cited by 7
[Retracted] Optimization of Multidimensional Clinical Information System for Schizophrenia
Jiang, Y. Y., Yu, H., & Jiang, J. (2021) · Complexity · doi:10.1155/2021/1744155 · Cited by 7
Retracted
Common Brain Networks Between Major Depressive-Disorder Diagnosis and Symptoms of Depression That Are Validated for Independent Cohorts
Yamashita, A., Sakai, Y., Yamada, T., Yahata, N., Kunimatsu, A., Okada, N., Itahashi, T., Hashimoto, R., Mizuta, H., Ichikawa, N., et al. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.667881 · Cited by 7
Evaluating delay of gamma oscillations in patients with schizophrenia using evoked response audiometry system
Yanagi, M., Tsuchiya, A., Hosomi, F., Terada, T., Ozaki, S., Shirakawa, O., & Hashimoto, M. (2022) · Scientific Reports · doi:10.1038/s41598-022-15311-6 · Cited by 7
Evaluation of boundaries between mood and psychosis disorder using dynamic functional network connectivity ( dFNC ) via deep learning classification
Rokham, H., Falakshahi, H., Fu, Z., Pearlson, G. D., & Calhoun, V. D. (2023) · Human Brain Mapping · doi:10.1002/hbm.26273 · Cited by 6
Self-citation
Reward anticipation-related neural activation following cued reinforcement in adults with psychotic psychopathology and biological relatives
Demro, C., Lahud, E., Burton, P. C., Purcell, J. R., Simon, J. J., & Sponheim, S. R. (2024) · Psychological Medicine · doi:10.1017/s0033291723003343 · Cited by 10
Cognitive and Functional Assessment of Psychosis Stratification Study (CoFAPSS): Rationale, Design, and Characteristics
Clark, S. R., Schubert, K. O., Olagunju, A. T., Lyrtzis, E., & Baune, B. T. (2018) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2018.00662 · Cited by 6
Computational phenotyping and longitudinal dynamics to inform clinical decision-making in psychiatry
Ferrante, M., & Gordon, J. A. (2020) · Neuropsychopharmacology · doi:10.1038/s41386-020-00852-z · Cited by 7
Phenoscreening: a developmental approach to research domain criteria‐motivated sampling
Doyle, C., Lasch, C., Vollman, E. P., Desjardins, C. D., Helwig, N. E., Jacob, S., Wolff, J. J., & Elison, J. T. (2020) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13341 · Cited by 9
Calcium Imaging in Drug Discovery for Psychiatric Disorders
Seshadri, S., Hoeppner, D. J., & Tajinda, K. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.00713 · Cited by 7
First episode psychosis longitudinal cohort studies: The CIBERSAM FEP cohort
Fraguas, D., & Díaz‐Caneja, C. M. (2021) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2021.06.011 · Cited by 7
Neuropsychiatric drug development: Perspectives on the current landscape, opportunities and potential future directions
Loïodice, S., D’Acquisto, F., Drinkenburg, P., Suojanen, C., Llorca, P., & Manji, H. K. (2024) · Drug Discovery Today · doi:10.1016/j.drudis.2024.104255 · Cited by 7
Brain network dynamics reflect psychiatric illness status and transdiagnostic symptom profiles across health and disease
Cocuzza, C. V., Chopra, S., Segal, A., Labache, L., Chin, R., Joss, K., & Holmes, A. J. (2026) · Nature Communications · doi:10.1038/s41467-026-75585-6 · Cited by 9
A virtual reality-based multimodal framework for adolescent depression screening using machine learning
Wu, Y.-Z., Qiao, Y., Wu, L.-C., Gao, M., Wong, T.-Y., Li, J.-Y., Wang, Z., Zhao, X., Zhao, H., & Fan, X.-W. (2025) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2025.1655554 · Cited by 5
The Era of Precision Psychiatry: Toward a New Paradigm in Diagnosis and Care
CASALE, A. D., Bronzatti, L., Arena, J. F., Gentile, G., Lai, C., Girardi, P., Simmaco, M., & Borro, M. (2025) · Psychiatry International · doi:10.3390/psychiatryint6040146 · Cited by 6
Subtyping schizophrenia based on symptomatology and cognition using a data driven approach
Castro-de-Araujo, L. F. S., Machado, D. B., Barreto, M. L., & Kanaan, R. (2020) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2020.111136 · Cited by 6
Genetic analysis of psychosis Biotypes: shared Ancestry-adjusted polygenic risk and unique genomic associations
Xia, C., Alliey‐Rodriguez, N., Tamminga, C. A., Keshavan, M. S., Pearlson, G. D., Keedy, S., Clementz, B. A., McDowell, J. E., Parker, D., Lencer, R., et al. (2024) · Molecular Psychiatry · doi:10.1038/s41380-024-02876-z · Cited by 9
Self-citation
Dissecting Schizophrenia Biology Using Pleiotropy With Cognitive Genomics
Bhattacharyya, U., John, J., Lencz, T., & Lam, M. (2025) · Biological Psychiatry · doi:10.1016/j.biopsych.2025.02.890 · Cited by 7
Eye movement as a biomarker of impaired organizational strategies during visual memory encoding in obsessive–compulsive disorder
Kim, M., Shin, W., Lee, T. H., Kim, T., Hwang, W. J., & Kwon, J. S. (2021) · Scientific Reports · doi:10.1038/s41598-021-97885-1 · Cited by 6
Exploring negative symptoms heterogeneity in patients diagnosed with schizophrenia and schizoaffective disorder using cluster analysis
Fekih‐Romdhane, F., Hajje, R., Haddad, C., Hallit, S. R., & Azar, J. (2023) · BMC Psychiatry · doi:10.1186/s12888-023-05101-3 · Cited by 6
Pre-onset risk characteristics for mania among young people at clinical high risk for psychosis
Ratheesh, A., Cotton, S., Davey, C. G., Lin, A. P., Wood, S. J., Yuen, H. P., Bechdolf, A., McGorry, P. D., Yung, A. R., Berk, M., et al. (2017) · Schizophrenia Research · doi:10.1016/j.schres.2017.04.036 · Cited by 6
Distinct structural brain circuits indicate mood and apathy profiles in bipolar disorder
Jiang, W., Andreassen, O. A., Agartz, I., Lagerberg, T. V., Westlye, L. T., Calhoun, V. D., & Turner, J. A. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101989 · Cited by 7
Biological fingerprints for psychosis
Tamminga, C. A., & Clementz, B. A. (2019) · Neuropsychopharmacology · doi:10.1038/s41386-019-0505-6 · Cited by 6
Self-citation
Dissimilar social cognition signatures in remitted schizophrenia and bipolar disorder
Mehta, U. M., Punith, M., Kumar, C. N., Kumar, J. K., Reddy, Y. C. J., & Thirthalli, J. (2021) · Asian Journal of Psychiatry · doi:10.1016/j.ajp.2021.102593 · Cited by 7
Zwölf Jahre Research Domain Criteria in der psychiatrischen Forschung und Praxis: Anspruch und Wirklichkeit
Hirjak, D., Schwarz, E., & Meyer‐Lindenberg, A. (2021) · Der Nervenarzt · doi:10.1007/s00115-021-01174-1 · Cited by 6
Impact of polygenic risk for coronary artery disease and cardiovascular medication burden on cognitive impairment in psychotic disorders
Zhang, L.-S., Hill, S., Guo, B., Wu, B., Alliey-Rodriguez, N., Eum, S., Lizano, P., Ivleva, E., Reilly, J., Keefe, R., et al. (2021) · Progress in Neuro-psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2021.110464 · Cited by 4
Self-citation
Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA studyPreprint
Georgiadis, F., Larivière, S., Glahn, D. C., Hong, L. E., Kochunov, P. V., Mowry, B. J., Loughland, C. M., Pantelis, C., Henskens, F. A., Green, M. J., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.02.12.527904 · Cited by 6
The BAsic NeuroCognitive Continuum ( BANCC ): Delineation of dimensional and categorical features for etiological and treatment investigations of idiopathic psychosis
Warren, H. C., Parker, D. A., Trotti, R. L., Zeng, V., Meda, S. A., Lencer, R., Sprenger, A., Hill, S. K., Brown, J. A., Doss, I., et al. (2025) · Psychiatry and Clinical Neurosciences · doi:10.1111/pcn.13887 · Cited by 5
Self-citation
Neuroimaging Data Informed Mood and Psychosis Diagnosis Using an Ensemble Deep Multimodal Framework
Rokham, H., Falakshahi, H., Pearlson, G. D., & Calhoun, V. D. (2025) · Human Brain Mapping · doi:10.1002/hbm.70347 · Cited by 5
Self-citation
Vision and Psychosis: A Clinical Translational Perspective
Türközer, H. B., Lizano, P. L., Tamminga, C. A., & Silverstein, S. M. (2025) · Biological Psychiatry · doi:10.1016/j.biopsych.2025.11.005 · Cited by 6
Self-citation
Lesioned hemisphere‐specific phenotypes of post‐stroke fatigue emerge from motor and mood characteristics in chronic stroke
Doncker, W. D., & Kuppuswamy, A. (2023) · European Journal of Neurology · doi:10.1111/ene.16170 · Cited by 5
A telescopic independent component analysis on functional magnetic resonance imaging dataset
Mirzaeian, S., Faghiri, A., Calhoun, V. D., & Iraji, A. (2024) · Network Neuroscience · doi:10.1162/netn_a_00421 · Cited by 5
Evaluating the Exposome Score for Schizophrenia in a Transdiagnostic Psychosis Cohort: Associations With Psychosis Risk, Symptom Severity, and Personality Traits
Kromenacker, B., Yassin, W., Keshavan, M. S., Parker, D., Thakkar, V. J., Pearlson, G. D., Keedy, S., McDowell, J., Gershon, E. S., Ivleva, E. I., et al. (2025) · Schizophrenia Bulletin · doi:10.1093/schbul/sbae219 · Cited by 5
Self-citation
Towards clinical subtypes in schizophrenia: integrating cognitive, functional, and digital phenotyping assessments
Byun, A. J. S., Lane, E., Langholm, C., Flathers, M., Hall, M., & Torous, J. B. (2025) · Molecular Psychiatry · doi:10.1038/s41380-025-03054-5 · Cited by 5
An opportunity for primary prevention research in psychotic disorders
Gershon, E. S., Lee, S., Zhou, X., Sweeney, J. A., Tamminga, C. A., Pearlson, G. D., Clementz, B. A., Keshavan, M. S., Alliey‐Rodriguez, N., Hudgens‐Haney, M. E., et al. (2021) · Schizophrenia Research · doi:10.1016/j.schres.2021.07.001 · Cited by 5
Self-citation
Application of evoked response audiometry for specifying aberrant gamma oscillations in schizophrenia
Yanagi, M., Tsuchiya, A., Hosomi, F., Ozaki, S., & Shirakawa, O. (2022) · Scientific Reports · doi:10.1038/s41598-021-04278-5 · Cited by 5
Interactive effects of polygenic risk and cognitive subtype on brain morphology in schizophrenia spectrum and bipolar disorders
Quidé, Y., Watkeys, O. J., Girshkin, L., Kaur, M., Carr, V. J., Cairns, M. J., & Green, M. J. (2022) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-022-01450-4 · Cited by 4
Utility of Computational Approaches for Precision Psychiatry: Applications to Substance Use Disorders
Vassileva, J., Lee, J.-H., Psederska, E., & Ahn, W. (2023) · Neuromethods · doi:10.1007/978-1-0716-3230-7_14 · Cited by 5
Not one thing at a time: When concomitant multiple stressors produce a transdiagnostic clinical picture
Ferber, S. G., Shoval, G., Weller, A., & Zalsman, G. (2023) · World Journal of Psychiatry · doi:10.5498/wjp.v13.i7.402 · Cited by 5
Neurobiology-based cognitive biotypes using multi-scale intrinsic connectivity networks in psychotic disorders
Andrés-Camazón, P., Díaz‐Caneja, C. M., Ballem, R., Chen, J., Calhoun, V. D., & Iraji, A. (2025) · Schizophrenia · doi:10.1038/s41537-025-00593-2 · Cited by 6
Biological Subtypes Bridge Diagnoses and Biomarkers: A Novel Research Track for Mental Disorders
Song, M., Yang, Z., Jing Sui （Beijing Normal University）， my correct affiliation is beijing normal university, N. Q. U. O. S. A. T., & Jiang, T. (2017) · Neuroscience Bulletin · doi:10.1007/s12264-017-0108-3 · Cited by 5
Seven short reflections on the notion of schizophrenia
McGrath, J. J., & Wray, N. R. (2021) · Schizophrenia Research · doi:10.1016/j.schres.2021.09.026 · Cited by 5
Neural Processing of Repeated Emotional Scenes in Schizophrenia, Schizoaffective Disorder, and Bipolar Disorder
Trotti, R. L., Abdelmageed, S., Parker, D., Sabatinelli, D., Tamminga, C. A., Gershon, E. S., Keedy, S., Keshavan, M. S., Pearlson, G. D., Sweeney, J. A., et al. (2021) · Schizophrenia Bulletin · doi:10.1093/schbul/sbab018 · Cited by 5
Self-citation
Introduction to Psychiatry
King, D. R., & Brenner, A. M. (2023) · Springer eBooks · doi:10.1007/978-3-031-15401-0_1 · Cited by 5
The Core Deficit of “Classical” Schizophrenia Cuts Across the Psychosis Spectrum
Keshavan, M. S., Kelly, S., & Hall, M. (2020) · The Canadian Journal of Psychiatry · doi:10.1177/0706743719898911 · Cited by 5
Self-citation
Neurodiversity-informed inclusive understanding of neurological differences
Larrauri, C. A., Stein, M. A., Wickramasinghe, A., Ntolkeras, G., & Yassin, W. (2025) · Nature Mental Health · doi:10.1038/s44220-025-00398-3 · Cited by 5
Aberrant cortical–subcortical-cerebellar connectivity in resting-state fMRI as an imaging marker of schizophrenia and psychosis: a systematic review of data-driven whole-brain functional connectivity analyses
Jensen, K. M., King, T. Z., Andrés-Camazón, P., Calhoun, V. D., & Iraji, A. (2025) · Frontiers in Neuroimaging · doi:10.3389/fnimg.2025.1650987 · Cited by 7
Salience network segregation and symptom profiles in psychosis risk subgroups among youth and early adults
Iyer, A., Stanford, W., Dayan, E., & Xavier, R. M. (2025) · Schizophrenia · doi:10.1038/s41537-025-00687-x · Cited by 5
Mediodorsal and pulvinar thalamus reductions across the psychosis spectrum
Zeng, V., Hoang, D., Song, S. H., Trotti, R. L., Parker, D., Raymond, N., Iska, N., del Re, E. C., Coxon, E., Rychagov, N., et al. (2026) · Schizophrenia Research · doi:10.1016/j.schres.2026.02.002 · Cited by 4
Self-citation
Schizophrenia: advances in pathophysiology, management, and precision medicine
Sawa, A., Chiappelli, J., Hamrah, O., & Cascella, N. G. (2026) · BMJ · doi:10.1136/bmj-2026-635470 · Cited by 4
EEG alpha reactivity on eyes opening discriminates patients with schizophrenia and schizoaffective disorder
Валерьевна, Г. Ж., Larionova, E. V., Shmukler, A. B., Horáček, J., & Zaytseva, Y. (2024) · Clinical Neurophysiology · doi:10.1016/j.clinph.2024.03.003 · Cited by 4
White Matter, Cognition, and Electrophysiological Variables in Bipolar Disorder: Using Multimodal Integration of Biomarker Variables Associated With Bipolar Disorder to Elucidate Deficits
Berardi, A., Brown, J. A., Jackson, B. S., Huang, L., Trotti, R. L., Parker, D. A., Hill, S. K., Ivleva, E. I., Pearlson, G. D., Tamminga, C. A., et al. (2025) · Bipolar Disorders · doi:10.1111/bdi.70010 · Cited by 4
Self-citation
Neuroanatomical subtyping for schizophrenia with machine learning
Sungur, I., Selek, S., Keskin, K., Hinc, A. C., Yazici, F., Aktaş, E. Ö., Erdoğan, Y., & Gönül, A. S. (2025) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2025.112058 · Cited by 4
A 5-min paradigm to evoke robust emotional reactivity in neuroimaging studies
Sabatinelli, D., Winker, C., Farkas, A. H., Rehbein, M. A., & Junghoefer, M. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1102213 · Cited by 4
Global reward processing deficits predict negative symptoms transdiagnostically and transphasically in a severe mental illness-spectrum sample
Luther, L., Jarvis, S. A., Spilka, M. J., & Strauss, G. P. (2023) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-023-01714-7 · Cited by 6
Cognitive subtypes in youth at clinical high risk for psychosis
Yassin, W., Green, J. B., Keshavan, M. S., del Re, E. C., Addington, J., Bearden, C. E., Cadenhead, K. S., Cannon, T. D., Cornblatt, B. A., Mathalon, D. H., et al. (2025) · Psychiatry and Clinical Neurosciences · doi:10.1111/pcn.13861 · Cited by 4
Self-citation
Double-Dissociation Studies in Psychiatric Research: A Scoping Review
Kilçiksiz, C. M., & Öngür, D. (2019) · Harvard Review of Psychiatry · doi:10.1097/hrp.0000000000000233 · Cited by 4
Psychiatric Drug Discovery and Development
Shahid, M., Neill, J. C., & Hutchison, J. B. (2020) · Cambridge University Press eBooks · doi:10.1017/9781911623465.004 · Cited by 5
A Century of Behavioral Genetics at the University of Minnesota
Willoughby, E. A., Giannelis, A., Iacono, W. G., McGue, M. K., & Vrieze, S. I. (2022) · Twin Research and Human Genetics · doi:10.1017/thg.2023.1 · Cited by 5
The Research Domain Criteria Project: Integrative Translation for Psychopathology
Cuthbert, B. N., Miller, G. A., Sanislow, C. A., & Vaidyanathan, U. (2023) · Oxford University Press eBooks · doi:10.1093/med-psych/9780197542521.003.0004 · Cited by 4
Protocol for a systematic review and meta-analysis of coordinate-based network mapping of brain structure in bipolar disorder across the lifespan
Jones, B. D. M., Zhukovsky, P., Hawco, C. S., Ortiz, A., Cipriani, A., Voineskos, A. N., Mulsant, B. H., & Husain, M. I. (2023) · BJPsych Open · doi:10.1192/bjo.2023.569 · Cited by 4
Using Connectivity to Explain Neuropsychiatric Conditions: The Example of Autism
Adamek, J. H., Luo, Y., & Ewen, J. B. (2022) · Handbook of Neuroengineering · doi:10.1007/978-981-15-2848-4_90-1 · Cited by 4
Kraepelin’s Crumbling Twin Pillars: Using Biology to Reconstruct Psychiatric Nosology From the Bottom Up
Aquino, J. P. D., & Ross, D. A. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.09.008 · Cited by 4
Selected risk factors for schizophrenia: between the diversity of aetiological models and personalised psychiatry
Śmierciak, N., Krzyściak, W., Szwajca, M., Kazek, G., Urbanek, K., Bryll, A., & Pilecki, M. W. (2018) · Psychiatria i Psychologia Kliniczna · doi:10.15557/pipk.2018.0046 · Cited by 3
The National Institute of Mental Health Research Domain Criteria
Sanislow, C. A., Morris, S. E., Pacheco, J., & Cuthbert, B. N. (2020) · doi:10.1093/med/9780198713005.003.0008 · Cited by 5
Computational modelling of EEG and fMRI paradigms reveals a consistent loss of pyramidal cell synaptic gain in schizophreniaPreprint
Adams, R. A., Pinotsis, D. A., Tsirlis, K., Unruh, L., Mahajan, A., Horas, A. M., Convertino, L., Summerfelt, A. T., Sampath, H., Du, X. M., et al. (2021) · medRxiv · doi:10.1101/2021.01.07.21249389 · Cited by 4
Increased whole-brain functional heterogeneity in psychosis during rest and task
Keane, B. P., Abrham, Y. T., Hearne, L. J., Bi, H., & Hu, B. (2024) · NeuroImage Clinical · doi:10.1016/j.nicl.2024.103630 · Cited by 3

Authors: Clementz, B. A., Sweeney, J. A., Hamm, J. P., Ivleva, E. I., Ethridge, L. E., Pearlson, G. D., Keshavan, M. S., & Tamminga, C. A.
Affiliations: Hartford Hospital (US)
ORCID: Clementz, Brett A.
Sweeney, John A.
Hamm, Jordan P.
Ivleva, Elena I.
Ethridge, Lauren E.
Pearlson, Godfrey D.
Keshavan, Matcheri S.
Tamminga, Carol A.
Venue: American Journal of Psychiatry
Publisher: American Psychiatric Association Publishing
Published: 2016-04-01
Volume: 173
Issue: 4
Pages: 373-384
ISSN: 0002-953X (ISSN-L)
1535-7228
DOI: 10.1176/appi.ajp.2015.14091200
PMC: PMC5314432
OpenAlex: W2190536949
Cited by: 768
References: 50
Citations by year: 2026: 64 · 2025: 59 · 2024: 58 · 2023: 61 · 2022: 70 · 2021: 78 · 2020: 72 · 2019: 122 · 2018: 68 · 2017: 75 · 2016: 40
FWCI: 49.56
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Locations: American Journal of Psychiatry (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Funders: National Institute of Mental Health (R01MH077852, MH‐077945, MH 077852, R01MH077851, MH-078113, MH077851, R01MH096913, MH‐077862, R01MH078113, R01MH077862, R01MH077945)
Topics: Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
Social Sciences › Arts and Humanities › Philosophy › Mental Health and Psychiatry
Health Sciences › Medicine › Psychiatry and Mental health › Bipolar Disorder and Treatment
Keywords: schizophrenia, schizoaffective disorder, taxometric analysis, neuropsychological assessment, stop-signal task, auditory stimulation, first-degree relatives, social functioning, structural MRI
MeSH terms: Acoustic Stimulation, Adult, Bipolar Disorder, Brain, Electroencephalography, Evoked Potentials, Auditory, Family, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Neuropsychological Tests, Phenotype, Psychotic Disorders, Saccades, Schizophrenia, Schizophrenic Psychology, Case-Control Studies, Young Adult

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Identification of Distinct Psychosis Biotypes Using Brain-Based Biomarkers

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks