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Kaul I, Sawchak S, Walling DP, Tamminga CA, Breier A, Zhu H, Miller AC, Paul SM, Brannan SK. Efficacy and Safety of Xanomeline-Trospium Chloride in Schizophrenia: A Randomized Clinical Trial. JAMA Psychiatry 2024:2818047. [PMID: 38691387 PMCID: PMC11063924 DOI: 10.1001/jamapsychiatry.2024.0785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 02/22/2024] [Indexed: 05/03/2024]
Abstract
Importance A significant need exists for new antipsychotic medications with different mechanisms of action, greater efficacy, and better tolerability than existing agents. Xanomeline is a dual M1/M4 preferring muscarinic receptor agonist with no direct D2 dopamine receptor blocking activity. KarXT combines xanomeline with the peripheral muscarinic receptor antagonist trospium chloride with the goal of reducing adverse events due to xanomeline-related peripheral muscarinic receptor activation. In prior trials, xanomeline-trospium chloride was effective in reducing symptoms of psychosis and generally well tolerated in people with schizophrenia. Objective To evaluate the efficacy and safety of xanomeline-trospium vs placebo in adults with schizophrenia. Design, Setting, and Participants EMERGENT-3 (NCT04738123) was a phase 3, multicenter, randomized, double-blind, placebo-controlled, 5-week trial of xanomeline-trospium in people with schizophrenia experiencing acute psychosis, conducted between April 1, 2021, and December 7, 2022, at 30 inpatient sites in the US and Ukraine. Data were analyzed from February to June 2023. Interventions Participants were randomized 1:1 to receive xanomeline-trospium chloride (maximum dose xanomeline 125 mg/trospium 30 mg) or placebo for 5 weeks. Main Outcomes and Measures The prespecified primary end point was change from baseline to week 5 in Positive and Negative Syndrome Scale (PANSS) total score. Secondary outcome measures were change from baseline to week 5 in PANSS positive subscale score, PANSS negative subscale score, PANSS Marder negative factor score, Clinical Global Impression-Severity score, and proportion of participants with at least a 30% reduction in PANSS total score. Safety and tolerability were also evaluated. Results A total of 256 participants (mean [SD] age, 43.1 [11.8] years; 191 men [74.6%]; 156 of 256 participants [60.9%] were Black or African American, 98 [38.3%] were White, and 1 [0.4%] was Asian) were randomized (125 in xanomeline-trospium group and 131 in placebo group). At week 5, xanomeline-trospium significantly reduced PANSS total score compared with placebo (xanomeline-trospium , -20.6; placebo, -12.2; least squares mean difference, -8.4; 95% CI, -12.4 to -4.3; P < .001; Cohen d effect size, 0.60). Discontinuation rates due to treatment-emergent adverse events (TEAEs) were similar between the xanomeline-trospium (8 participants [6.4%]) and placebo (7 participants [5.5%]) groups. The most common TEAEs in the xanomeline-trospium vs placebo group were nausea (24 participants [19.2%] vs 2 participants [1.6%]), dyspepsia (20 participants [16.0%] vs 2 participants [1.6%]), vomiting (20 participants [16.0%] vs 1 participant [0.8%]), and constipation (16 participants [12.8%] vs 5 participants [3.9%]). Measures of extrapyramidal symptoms, weight gain, and somnolence were similar between treatment groups. Conclusions and Relevance Xanomeline-trospium was efficacious and well tolerated in people with schizophrenia experiencing acute psychosis. These findings, together with the previously reported and consistent results from the EMERGENT-1 and EMERGENT-2 trials, support the potential of xanomeline-trospium to be the first in a putative new class of antipsychotic medications without D2 dopamine receptor blocking activity. Trial Registration ClinicalTrials.gov Identifier: NCT04738123.
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Affiliation(s)
- Inder Kaul
- Karuna Therapeutics, Boston, Massachusetts
| | | | | | - Carol A. Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical School, Dallas
| | - Alan Breier
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis
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Peña JE, Corbett BF, Tamminga CA, Bhatnagar S, Hitti FL. Investigating resistance to antidepressants in animal models. Neuroscience 2024:S0306-4522(24)00172-6. [PMID: 38697464 DOI: 10.1016/j.neuroscience.2024.04.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 04/12/2024] [Accepted: 04/25/2024] [Indexed: 05/05/2024]
Abstract
Major depressive disorder is one of the most prevalent psychiatric diseases, and up to 30-40% of patients remain symptomatic despite treatment. Novel therapies are sorely needed, and animal models may be used to elucidate fundamental neurobiological processes that contribute to human disease states. We conducted a systematic review of current preclinical approaches to investigating treatment resistance with the goal of describing a path forward for improving our understanding of treatment resistant depression. We conducted a broad literature search to identify studies relevant to the preclinical investigation of treatment resistant depression. We followed PRISMA (Preferred Reporting Items for Systemic Reviews and Meta-Analyses) guidelines and included all relevant studies. We identified 467 studies in our initial search. Of these studies, we included 69 in our systematic review after applying our inclusion/exclusion criteria. We identified 10 broad strategies for investigating treatment resistance in animal models. Stress hormone administration was the most commonly used model, and the most common behavioral test was the forced swim test. We systematically identified and reviewed current approaches for gaining insight into the neurobiology underlying treatment resistant depression using animal models. Each approach has its advantages and disadvantages, but all require careful consideration of their potential limitations regarding therapeutic translation. An enhanced understanding of treatment resistant depression is sorely needed given the burden of disease and lack of effective therapies.
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Affiliation(s)
- Julianna E Peña
- Department of Neurosurgery, University of Texas Southwestern Medical Center, Dallas, TX; Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX
| | | | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX
| | - Seema Bhatnagar
- Department of Anesthesiology and Critical Care, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA
| | - Frederick L Hitti
- Department of Neurosurgery, University of Texas Southwestern Medical Center, Dallas, TX; Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX.
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Guimond S, Alftieh A, Devenyi GA, Mike L, Chakravarty MM, Shah JL, Parker DA, Sweeney JA, Pearlson G, Clementz BA, Tamminga CA, Keshavan M. Enlarged pituitary gland volume: a possible state rather than trait marker of psychotic disorders. Psychol Med 2024:1-9. [PMID: 38357733 DOI: 10.1017/s003329172300380x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/16/2024]
Abstract
BACKGROUND Enlarged pituitary gland volume could be a marker of psychotic disorders. However, previous studies report conflicting results. To better understand the role of the pituitary gland in psychosis, we examined a large transdiagnostic sample of individuals with psychotic disorders. METHODS The study included 751 participants (174 with schizophrenia, 114 with schizoaffective disorder, 167 with psychotic bipolar disorder, and 296 healthy controls) across six sites in the Bipolar-Schizophrenia Network on Intermediate Phenotypes consortium. Structural magnetic resonance images were obtained, and pituitary gland volumes were measured using the MAGeT brain algorithm. Linear mixed models examined between-group differences with controls and among patient subgroups based on diagnosis, as well as how pituitary volumes were associated with symptom severity, cognitive function, antipsychotic dose, and illness duration. RESULTS Mean pituitary gland volume did not significantly differ between patients and controls. No significant effect of diagnosis was observed. Larger pituitary gland volume was associated with greater symptom severity (F = 13.61, p = 0.0002), lower cognitive function (F = 4.76, p = 0.03), and higher antipsychotic dose (F = 5.20, p = 0.02). Illness duration was not significantly associated with pituitary gland volume. When all variables were considered, only symptom severity significantly predicted pituitary gland volume (F = 7.54, p = 0.006). CONCLUSIONS Although pituitary volumes were not increased in psychotic disorders, larger size may be a marker associated with more severe symptoms in the progression of psychosis. This finding helps clarify previous inconsistent reports and highlights the need for further research into pituitary gland-related factors in individuals with psychosis.
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Affiliation(s)
- Synthia Guimond
- Department of Psychiatry, The Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
- Department of Psychoeducation and Psychology, Université du Québec en Outaouais, Gatineau, QC, Canada
- Department of Psychiatry, Massachusetts Mental Health Center and Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Ahmad Alftieh
- Department of Psychiatry, The Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
| | - Gabriel A Devenyi
- Department of Psychiatry, McGill University, Montréal, QC, Canada
- Douglas Mental Health University Institute, Verdun, QC, Canada
| | - Luke Mike
- Department of Psychiatry, Massachusetts Mental Health Center and Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - M Mallar Chakravarty
- Department of Psychiatry, McGill University, Montréal, QC, Canada
- Douglas Mental Health University Institute, Verdun, QC, Canada
- Department of Biomedical Engineering, McGill University Montréal, QC, Canada
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
| | - Jai L Shah
- Department of Psychiatry, McGill University, Montréal, QC, Canada
- Douglas Mental Health University Institute, Verdun, QC, Canada
| | - David A Parker
- Department of Psychology, BioImaging Research Center, University of Georgia, Athens, GA, USA
- Department of and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - John A Sweeney
- Department of Psychiatry, University of Cincinnati, Cincinnati, OH, USA
| | - Godfrey Pearlson
- Department of Psychiatry, Yale University, New Haven, CT, USA
- Department of Neuroscience, Yale University, New Haven, CT, USA
| | - Brett A Clementz
- Department of Psychology, BioImaging Research Center, University of Georgia, Athens, GA, USA
- Department of and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
| | - Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - Matcheri Keshavan
- Department of Psychiatry, Massachusetts Mental Health Center and Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
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LaCroix MS, Artikis E, Hitt BD, Beaver JD, Estill-Terpack SJ, Gleason K, Tamminga CA, Evers BM, White CL, Caughey B, Diamond MI. Tau seeding without tauopathy. J Biol Chem 2024; 300:105545. [PMID: 38072056 PMCID: PMC10797195 DOI: 10.1016/j.jbc.2023.105545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 11/28/2023] [Accepted: 11/29/2023] [Indexed: 01/04/2024] Open
Abstract
Neurodegenerative tauopathies such as Alzheimer's disease (AD) are caused by brain accumulation of tau assemblies. Evidence suggests tau functions as a prion, and cells and animals can efficiently propagate unique, transmissible tau pathologies. This suggests a dedicated cellular replication machinery, potentially reflecting a normal physiologic function for tau seeds. Consequently, we hypothesized that healthy control brains would contain seeding activity. We have recently developed a novel monoclonal antibody (MD3.1) specific for tau seeds. We used this antibody to immunopurify tau from the parietal and cerebellar cortices of 19 healthy subjects without any neuropathology, ranging 19 to 65 years. We detected seeding in lysates from the parietal cortex, but not in the cerebellum. We also detected no seeding in brain homogenates from wildtype or human tau knockin mice, suggesting that cellular/genetic context dictates development of seed-competent tau. Seeding did not correlate with subject age or brain tau levels. We confirmed our essential findings using an orthogonal assay, real-time quaking-induced conversion, which amplifies tau seeds in vitro. Dot blot analyses revealed no AT8 immunoreactivity above background levels in parietal and cerebellar extracts and ∼1/100 of that present in AD. Based on binding to a panel of antibodies, the conformational characteristics of control seeds differed from AD, suggesting a unique underlying assembly, or structural ensemble. Tau's ability to adopt self-replicating conformations under nonpathogenic conditions may reflect a normal function that goes awry in disease states.
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Affiliation(s)
- Michael S LaCroix
- Center for Alzheimer's and Neurodegenerative Diseases, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | | | - Brian D Hitt
- Center for Alzheimer's and Neurodegenerative Diseases, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, Texas, USA; Department of Neurology, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Joshua D Beaver
- Center for Alzheimer's and Neurodegenerative Diseases, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Sandi-Jo Estill-Terpack
- Center for Alzheimer's and Neurodegenerative Diseases, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Kelly Gleason
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Bret M Evers
- Department of Pathology, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Charles L White
- Department of Pathology, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Byron Caughey
- NIH/NIAID, Rocky Mountain Laboratories, Hamilton, Montana, USA
| | - Marc I Diamond
- Center for Alzheimer's and Neurodegenerative Diseases, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, Texas, USA; Department of Neurology, UT Southwestern Medical Center, Dallas, Texas, USA.
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Huang LY, Parker DA, Ethridge LE, Hamm JP, Keedy SS, Tamminga CA, Pearlson GD, Keshavan MS, Hill SK, Sweeney JA, McDowell JE, Clementz BA. Double dissociation between P300 components and task switch error type in healthy but not psychosis participants. Schizophr Res 2023; 261:161-169. [PMID: 37776647 PMCID: PMC11015813 DOI: 10.1016/j.schres.2023.09.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 06/02/2023] [Accepted: 09/13/2023] [Indexed: 10/02/2023]
Abstract
Event-related potentials (ERPs) during oddball tasks and the behavioral performance on the Penn Conditional Exclusion Task (PCET) measure context-appropriate responding: P300 ERPs to oddball targets reflect detection of input changes and context updating in working memory, and PCET performance indexes detection, adherence, and maintenance of mental set changes. More specifically, PCET variables quantify cognitive functions including inductive reasoning (set 1 completion), mental flexibility (perseverative errors), and working memory maintenance (regressive errors). Past research showed that both P300 ERPs and PCET performance are disrupted in psychosis. This study probed the possible neural correlates of 3 PCET abnormalities that occur in participants with psychosis via the overlapping cognitive demands of the two study paradigms. In a two-tiered analysis, psychosis (n = 492) and healthy participants (n = 244) were first divided based on completion of set 1 - which measures subjects' ability to use inductive reasoning to arrive at the correct set. Results showed that participants who failed set 1 produced lower parietal P300, independent of clinical status. In the second tier of analysis, a double dissociation was found among healthy set 1 completers: frontal P300 amplitudes were negatively associated with perseverative errors, and parietal P300 was negatively associated with regressive errors. In contrast, psychosis participants showed global P300 reductions regardless of PCET performance. From this we conclude that in psychosis, overall activations evoked by the oddball task are reduced while the cognitive functions required by PCET are still somewhat supported, showing some level of independence or compensatory physiology in psychosis between neural activities underlying the two tasks.
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Affiliation(s)
- Ling-Yu Huang
- Departments of Psychology & Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA, USA
| | - David A Parker
- Departments of Psychology & Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA, USA
| | - Lauren E Ethridge
- Department of Psychology and Pediatrics, University of Oklahoma, Norman, OK, USA
| | - Jordan P Hamm
- Department of Neuroscience, Georgia State University, Atlanta, GA, USA
| | - Sarah S Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, IL, USA
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | | | | | - S Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago, IL, USA
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Jennifer E McDowell
- Departments of Psychology & Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA, USA
| | - Brett A Clementz
- Departments of Psychology & Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA, USA.
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Lizano P, Kiely C, Mijalkov M, Meda SA, Keedy SK, Hoang D, Zeng V, Lutz O, Pereira JB, Ivleva EI, Volpe G, Xu Y, Lee AM, Rubin LH, Kristian Hill S, Clementz BA, Tamminga CA, Pearlson GD, Sweeney JA, Gershon ES, Keshavan MS, Bishop JR. Peripheral inflammatory subgroup differences in anterior Default Mode network and multiplex functional network topology are associated with cognition in psychosis. Brain Behav Immun 2023; 114:3-15. [PMID: 37506949 PMCID: PMC10592140 DOI: 10.1016/j.bbi.2023.07.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 07/17/2023] [Accepted: 07/22/2023] [Indexed: 07/30/2023] Open
Abstract
INTRODUCTION High-inflammation subgroups of patients with psychosis demonstrate cognitive deficits and neuroanatomical alterations. Systemic inflammation assessed using IL-6 and C-reactive protein may alter functional connectivity within and between resting-state networks, but the cognitive and clinical implications of these alterations remain unknown. We aim to determine the relationships of elevated peripheral inflammation subgroups with resting-state functional networks and cognition in psychosis spectrum disorders. METHODS Serum and resting-state fMRI were collected from psychosis probands (schizophrenia, schizoaffective, psychotic bipolar disorder) and healthy controls (HC) from the B-SNIP1 (Chicago site) study who were stratified into inflammatory subgroups based on factor and cluster analyses of 13 cytokines (HC Low n = 32, Proband Low n = 65, Proband High n = 29). Nine resting-state networks derived from independent component analysis were used to assess functional and multilayer connectivity. Inter-network connectivity was measured using Fisher z-transformation of correlation coefficients. Network organization was assessed by investigating networks of positive and negative connections separately, as well as investigating multilayer networks using both positive and negative connections. Cognition was assessed using the Brief Assessment of Cognition in Schizophrenia. Linear regressions, Spearman correlations, permutations tests and multiple comparison corrections were used for analyses in R. RESULTS Anterior default mode network (DMNa) connectivity was significantly reduced in the Proband High compared to Proband Low (Cohen's d = -0.74, p = 0.002) and HC Low (d = -0.85, p = 0.0008) groups. Inter-network connectivity between the DMNa and the right-frontoparietal networks was lower in Proband High compared to Proband Low (d = -0.66, p = 0.004) group. Compared to Proband Low, the Proband High group had lower negative (d = 0.54, p = 0.021) and positive network (d = 0.49, p = 0.042) clustering coefficient, and lower multiplex network participation coefficient (d = -0.57, p = 0.014). Network findings in high inflammation subgroups correlate with worse verbal fluency, verbal memory, symbol coding, and overall cognition. CONCLUSION These results expand on our understanding of the potential effects of peripheral inflammatory signatures and/or subgroups on network dysfunction in psychosis and how they relate to worse cognitive performance. Additionally, the novel multiplex approach taken in this study demonstrated how inflammation may disrupt the brain's ability to maintain healthy co-activation patterns between the resting-state networks while inhibiting certain connections between them.
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Affiliation(s)
- Paulo Lizano
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA; Division of Translational Neuroscience, Beth Israel Deaconess Medical Center, Boston, MA, USA.
| | - Chelsea Kiely
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Mite Mijalkov
- Neuro Division, Department of Clinical Neurosciences, Karolinska Institutet, Stockholm, Sweden
| | - Shashwath A Meda
- Department of Psychiatry, Yale University, New Haven, Connecticut, USA
| | - Sarah K Keedy
- Department of Psychiatry and Behavioral Neurosciences, University of Chicago, Chicago, IL, USA
| | - Dung Hoang
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Victor Zeng
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Olivia Lutz
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Joana B Pereira
- Neuro Division, Department of Clinical Neurosciences, Karolinska Institutet, Stockholm, Sweden; Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Sweden
| | - Elena I Ivleva
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX
| | - Giovanni Volpe
- Physics Department, University of Gothenburg, Gothenburg, Sweden
| | - Yanxun Xu
- Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA
| | - Adam M Lee
- Department of Experimental and Clinical Pharmacology and Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Leah H Rubin
- Department of Neurology, Psychiatry and Behavioral Sciences, Molecular and Comparative Pathobiology, and Epidemiology, Johns Hopkins University, Baltimore, MD, USA
| | - S Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL, USA
| | - Brett A Clementz
- Department of Psychology, University of Georgia, Athens, Georgia
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX
| | | | - John A Sweeney
- Department of Psychiatry, University of Cincinnati Medical Center, Cincinnati, OH, USA
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neurosciences, University of Chicago, Chicago, IL, USA
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Jeffrey R Bishop
- Department of Experimental and Clinical Pharmacology and Psychiatry, University of Minnesota, Minneapolis, MN, USA
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Mansouri S, Pessoni AM, Marroquín-Rivera A, Parise EM, Tamminga CA, Turecki G, Nestler EJ, Chen TH, Labonté B. Transcriptional dissection of symptomatic profiles across the brain of men and women with depression. Nat Commun 2023; 14:6835. [PMID: 37884562 PMCID: PMC10603117 DOI: 10.1038/s41467-023-42686-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Accepted: 10/18/2023] [Indexed: 10/28/2023] Open
Abstract
Major depressive disorder (MDD) is one of the most important causes of disability worldwide. While recent work provides insights into the molecular alterations in the brain of patients with MDD, whether these molecular signatures can be associated with the expression of specific symptom domains remains unclear. Here, we identified sex-specific gene modules associated with the expression of MDD, combining differential gene expression and co-expression network analyses in six cortical and subcortical brain regions. Our results show varying levels of network homology between males and females across brain regions, although the associations between these structures and the expression of MDD remain highly sex specific. We refined these associations to several symptom domains and identified transcriptional signatures associated with distinct functional pathways, including GABAergic and glutamatergic neurotransmission, metabolic processes and intracellular signal transduction, across brain regions associated with distinct symptomatic profiles in a sex-specific fashion. In most cases, these associations were specific to males or to females with MDD, although a subset of gene modules associated with common symptomatic features in both sexes were also identified. Together, our findings suggest that the expression of distinct MDD symptom domains associates with sex-specific transcriptional structures across brain regions.
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Affiliation(s)
- Samaneh Mansouri
- CERVO Brain Research Centre, Quebec, QC, Canada
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Québec, QC, Canada
| | - André M Pessoni
- CERVO Brain Research Centre, Quebec, QC, Canada
- Department of Psychiatry and Neurosciences, Faculty of Medicine, Université Laval, Quebec, QC, Canada
| | - Arturo Marroquín-Rivera
- CERVO Brain Research Centre, Quebec, QC, Canada
- Department of Psychiatry and Neurosciences, Faculty of Medicine, Université Laval, Quebec, QC, Canada
| | - Eric M Parise
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Carol A Tamminga
- Department of Psychiatry, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Gustavo Turecki
- McGill Group for Suicide Studies, Douglas Mental Health University Institute, Montreal, Canada
- Department of Psychiatry, McGill University, Montreal, Canada
| | - Eric J Nestler
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Ting-Huei Chen
- CERVO Brain Research Centre, Quebec, QC, Canada
- Department of Mathematics and Statistics, Laval University, Québec, QC, Canada
| | - Benoit Labonté
- CERVO Brain Research Centre, Quebec, QC, Canada.
- Department of Psychiatry and Neurosciences, Faculty of Medicine, Université Laval, Quebec, QC, Canada.
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Clementz BA, Chattopadhyay I, Trotti RL, Parker DA, Gershon ES, Hill SK, Ivleva EI, Keedy SK, Keshavan MS, McDowell JE, Pearlson GD, Tamminga CA, Gibbons RD. Clinical characterization and differentiation of B-SNIP psychosis Biotypes: Algorithmic Diagnostics for Efficient Prescription of Treatments (ADEPT)-1. Schizophr Res 2023; 260:143-151. [PMID: 37657281 PMCID: PMC10712427 DOI: 10.1016/j.schres.2023.08.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 08/08/2023] [Accepted: 08/09/2023] [Indexed: 09/03/2023]
Abstract
Clinically defined psychosis diagnoses are neurobiologically heterogeneous. The B-SNIP consortium identified and validated more neurobiologically homogeneous psychosis Biotypes using an extensive battery of neurocognitive and psychophysiological laboratory measures. However, typically the first step in any diagnostic evaluation is the clinical interview. In this project, we evaluated if psychosis Biotypes have clinical characteristics that can support their differentiation in addition to obtaining laboratory testing. Clinical interview data from 1907 individuals with a psychosis Biotype were used to create a diagnostic algorithm. The features were 58 ratings from standard clinical scales. Extremely randomized tree algorithms were used to evaluate sensitivity, specificity, and overall classification success. Biotype classification accuracy peaked at 91 % with the use of 57 items on average. A reduced feature set of 28 items, though, also showed 81 % classification accuracy. Using this reduced item set, we found that only 10-11 items achieved a one-vs-all (Biotype-1 or not, Biotype-2 or not, Biotype-3 or not) area under the sensitivity-specificity curve of .78 to .81. The top clinical characteristics for differentiating psychosis Biotypes, in order of importance, were (i) difficulty in abstract thinking, (ii) multiple indicators of social functioning, (iii) conceptual disorganization, (iv) severity of hallucinations, (v) stereotyped thinking, (vi) suspiciousness, (vii) unusual thought content, (viii) lack of spontaneous speech, and (ix) severity of delusions. These features were remarkably different from those that differentiated DSM psychosis diagnoses. This low-burden adaptive algorithm achieved reasonable classification accuracy and will support Biotype-specific etiological and treatment investigations even in under-resourced clinical and research environments.
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Affiliation(s)
- Brett A Clementz
- Department of Psychology, BioImaging Research Center, University of Georgia, Athens, GA 30602, United States of America.
| | - Ishanu Chattopadhyay
- Department of Medicine, Section of Hospital Medicine, University of Chicago, Chicago, IL, United States of America
| | - Rebekah L Trotti
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States of America
| | - David A Parker
- Department of Human Genetics, Emory University School of Medicine, Atlanta VA Medical Center, Atlanta, GA, United States of America
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States of America
| | - S Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL, United States of America
| | - Elena I Ivleva
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, United States of America
| | - Sarah K Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States of America
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States of America
| | - Jennifer E McDowell
- Department of Psychology, Owens Institute for Behavioral Research, University of Georgia, Athens, GA 30602, United States of America
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neuroscience, Yale University, School of Medicine, New Haven, CT, United States of America; Olin NeuroPsychiatry Research Center, Institute of Living, Hartford, CT, United States of America
| | - Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, United States of America
| | - Robert D Gibbons
- Center for Health Statistics, Departments of Medicine and Public Health Sciences, University of Chicago, Chicago, IL, United States of America
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9
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Zhu X, Zhou B, Pattni R, Gleason K, Tan C, Kalinowski A, Sloan S, Fiston-Lavier AS, Mariani J, Petrov D, Barres BA, Duncan L, Abyzov A, Vogel H, Moran JV, Vaccarino FM, Tamminga CA, Levinson DF, Urban AE. Author Correction: Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia. Nat Neurosci 2023; 26:1833. [PMID: 37648813 DOI: 10.1038/s41593-023-01438-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Affiliation(s)
- Xiaowei Zhu
- Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA, USA
- Department of Genetics, Stanford University, Palo Alto, CA, USA
| | - Bo Zhou
- Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA, USA
- Department of Genetics, Stanford University, Palo Alto, CA, USA
| | - Reenal Pattni
- Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA, USA
- Department of Genetics, Stanford University, Palo Alto, CA, USA
| | - Kelly Gleason
- Division of Translational Research in Schizophrenia, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Chunfeng Tan
- Division of Translational Research in Schizophrenia, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Agnieszka Kalinowski
- Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA, USA
| | - Steven Sloan
- Department of Human Genetics, Emory University, Atlanta, GA, USA
| | - Anna-Sophie Fiston-Lavier
- Institut des Sciences de l'Evolution de Montpellier (UMR 5554, CNRS-UM-IRD-EPHE), Université de Montpellier, Montpellier, France
| | | | - Dmitri Petrov
- Department of Biology, Stanford University, Palo Alto, CA, USA
| | - Ben A Barres
- Department of Neurobiology, Stanford University, Palo Alto, CA, USA
| | - Laramie Duncan
- Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA, USA
| | - Alexej Abyzov
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Hannes Vogel
- Department of Pathology, Stanford University, Palo Alto, CA, USA
| | - John V Moran
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Flora M Vaccarino
- Child Study Center, Yale University, New Haven, CT, USA
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Carol A Tamminga
- Division of Translational Research in Schizophrenia, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Douglas F Levinson
- Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA, USA
| | - Alexander E Urban
- Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA, USA.
- Department of Genetics, Stanford University, Palo Alto, CA, USA.
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10
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Al-Kachak A, Fulton SL, Di Salvo G, Chan JC, Farrelly LA, Lepack AE, Bastle RM, Kong L, Cathomas F, Newman EL, Menard C, Ramakrishnan A, Safovich P, Lyu Y, Covington HE, Shen L, Gleason K, Tamminga CA, Russo SJ, Maze I. Histone H3 serotonylation dynamics in dorsal raphe nucleus contribute to stress- and antidepressant-mediated gene expression and behavior. bioRxiv 2023:2023.05.04.539464. [PMID: 37205414 PMCID: PMC10187276 DOI: 10.1101/2023.05.04.539464] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Background Major depressive disorder (MDD), along with related mood disorders, is a debilitating illness that affects millions of individuals worldwide. While chronic stress increases incidence levels of mood disorders, stress-mediated disruptions in brain function that precipitate these illnesses remain elusive. Serotonin-associated antidepressants (ADs) remain the first line of therapy for many with depressive symptoms, yet low remission rates and delays between treatment and symptomatic alleviation have prompted skepticism regarding precise roles for serotonin in the precipitation of mood disorders. Our group recently demonstrated that serotonin epigenetically modifies histone proteins (H3K4me3Q5ser) to regulate transcriptional permissiveness in brain. However, this phenomenon has not yet been explored following stress and/or AD exposures. Methods We employed a combination of genome-wide and biochemical analyses in dorsal raphe nucleus (DRN) of male and female mice exposed to chronic social defeat stress to examine the impact of stress exposures on H3K4me3Q5ser dynamics, as well as associations between the mark and stress-induced gene expression. We additionally assessed stress-induced regulation of H3K4me3Q5ser following AD exposures, and employed viral-mediated gene therapy to reduce H3K4me3Q5ser levels in DRN and examine the impact on stress-associated gene expression and behavior. Results We found that H3K4me3Q5ser plays important roles in stress-mediated transcriptional plasticity. Chronically stressed mice displayed dysregulated H3K4me3Q5ser dynamics in DRN, with both AD- and viral-mediated disruption of these dynamics proving sufficient to rescue stress-mediated gene expression and behavior. Conclusions These findings establish a neurotransmission-independent role for serotonin in stress-/AD-associated transcriptional and behavioral plasticity in DRN.
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Affiliation(s)
- Amni Al-Kachak
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Sasha L. Fulton
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Giuseppina Di Salvo
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Jennifer C Chan
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Lorna A. Farrelly
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Ashley E. Lepack
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Ryan M. Bastle
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Lingchun Kong
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Flurin Cathomas
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Emily L. Newman
- Department of Psychiatry, McLean Hospital and Harvard Medical School, Belmont, MA 02478, USA
| | - Caroline Menard
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Aarthi Ramakrishnan
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Polina Safovich
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Yang Lyu
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Herbert E. Covington
- Department of Psychology, Empire State College, State University of New York, Saratoga Springs, NY 12866
| | - Li Shen
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Kelly Gleason
- Department of Psychiatry, University of Texas Southwestern Medical School, Dallas, TX, 75390, USA
| | - Carol A. Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical School, Dallas, TX, 75390, USA
| | - Scott J. Russo
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Ian Maze
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
- Howard Hughes Medical Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
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11
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Koen JD, Lewis L, Rugg MD, Clementz BA, Keshavan MS, Pearlson GD, Sweeney JA, Tamminga CA, Ivleva EI. Supervised machine learning classification of psychosis biotypes based on brain structure: findings from the Bipolar-Schizophrenia network for intermediate phenotypes (B-SNIP). Sci Rep 2023; 13:12980. [PMID: 37563219 PMCID: PMC10415369 DOI: 10.1038/s41598-023-38101-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 07/03/2023] [Indexed: 08/12/2023] Open
Abstract
Traditional diagnostic formulations of psychotic disorders have low correspondence with underlying disease neurobiology. This has led to a growing interest in using brain-based biomarkers to capture biologically-informed psychosis constructs. Building upon our prior work on the B-SNIP Psychosis Biotypes, we aimed to examine whether structural MRI (an independent biomarker not used in the Biotype development) can effectively classify the Biotypes. Whole brain voxel-wise grey matter density (GMD) maps from T1-weighted images were used to train and test (using repeated randomized train/test splits) binary L2-penalized logistic regression models to discriminate psychosis cases (n = 557) from healthy controls (CON, n = 251). A total of six models were evaluated across two psychosis categorization schemes: (i) three Biotypes (B1, B2, B3) and (ii) three DSM diagnoses (schizophrenia (SZ), schizoaffective (SAD) and bipolar (BD) disorders). Above-chance classification accuracies were observed in all Biotype (B1 = 0.70, B2 = 0.65, and B3 = 0.56) and diagnosis (SZ = 0.64, SAD = 0.64, and BD = 0.59) models. However, the only model that showed evidence of specificity was B1, i.e., the model was able to discriminate B1 vs. CON and did not misclassify other psychosis cases (B2 or B3) as B1 at rates above nominal chance. The GMD-based classifier evidence for B1 showed a negative association with an estimate of premorbid general intellectual ability, regardless of group membership, i.e. psychosis or CON. Our findings indicate that, complimentary to clinical diagnoses, the B-SNIP Psychosis Biotypes may offer a promising approach to capture specific aspects of psychosis neurobiology.
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Affiliation(s)
- Joshua D Koen
- Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA.
- Department of Psychology, University of Notre Dame, Notre Dame, IN, 46556, USA.
| | - Leslie Lewis
- Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA
| | - Michael D Rugg
- Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA
- UT Southwestern Medical Center, Dallas, TX, USA
- University of East Anglia, Norwich, UK
| | | | | | - Godfrey D Pearlson
- Institute of Living, Hartford Hospital, Hartford, CT, USA
- Yale School of Medicine, New Haven, CT, USA
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12
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Tamminga CA. Discovering informative biomarkers in psychiatry. World Psychiatry 2023; 22:270-271. [PMID: 37159346 PMCID: PMC10168152 DOI: 10.1002/wps.21084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/08/2023] [Indexed: 05/11/2023] Open
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13
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Fulton SL, Bendl J, Gameiro-Ros I, Fullard JF, Al-Kachak A, Lepack AE, Stewart AF, Singh S, Poller WC, Bastle RM, Hauberg ME, Fakira AK, Chen M, Cuttoli RDD, Cathomas F, Ramakrishnan A, Gleason K, Shen L, Tamminga CA, Milosevic A, Russo SJ, Swirski F, Blitzer RD, Slesinger PA, Roussos P, Maze I. ZBTB7A regulates MDD-specific chromatin signatures and astrocyte-mediated stress vulnerability in orbitofrontal cortex. bioRxiv 2023:2023.05.04.539425. [PMID: 37205394 PMCID: PMC10187272 DOI: 10.1101/2023.05.04.539425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Hyperexcitability in the orbitofrontal cortex (OFC) is a key clinical feature of anhedonic domains of Major Depressive Disorder (MDD). However, the cellular and molecular substrates underlying this dysfunction remain unknown. Here, cell-population-specific chromatin accessibility profiling in human OFC unexpectedly mapped genetic risk for MDD exclusively to non-neuronal cells, and transcriptomic analyses revealed significant glial dysregulation in this region. Characterization of MDD-specific cis-regulatory elements identified ZBTB7A - a transcriptional regulator of astrocyte reactivity - as an important mediator of MDD-specific chromatin accessibility and gene expression. Genetic manipulations in mouse OFC demonstrated that astrocytic Zbtb7a is both necessary and sufficient to promote behavioral deficits, cell-type-specific transcriptional and chromatin profiles, and OFC neuronal hyperexcitability induced by chronic stress - a major risk factor for MDD. These data thus highlight a critical role for OFC astrocytes in stress vulnerability and pinpoint ZBTB7A as a key dysregulated factor in MDD that mediates maladaptive astrocytic functions driving OFC hyperexcitability.
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Affiliation(s)
- Sasha L. Fulton
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jaroslav Bendl
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
| | - Isabel Gameiro-Ros
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John F. Fullard
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
| | - Amni Al-Kachak
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ashley E. Lepack
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Andrew F. Stewart
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sumnima Singh
- Department of Cardiology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- The Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
| | - Wolfram C. Poller
- Department of Cardiology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- The Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
| | - Ryan M. Bastle
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mads E. Hauberg
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
| | - Amanda K. Fakira
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Min Chen
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Romain Durand-de Cuttoli
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Flurin Cathomas
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Aarthi Ramakrishnan
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kelly Gleason
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - Li Shen
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Carol A. Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - Ana Milosevic
- Laboratory of Molecular and Cellular Neuroscience, Rockefeller University, New York, New York, USA
| | - Scott J. Russo
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Filip Swirski
- Department of Cardiology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- The Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
| | - Robert D. Blitzer
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
| | - Paul A. Slesinger
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Panos Roussos
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Center for Dementia Research, Nathan Kline Institute for Psychiatric Research, Orangeburg, New York, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, USA
| | - Ian Maze
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Howard Hughes Medical Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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14
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Cetin-Karayumak S, Lyall AE, Di Biase MA, Seitz-Holland J, Zhang F, Kelly S, Elad D, Pearlson G, Tamminga CA, Sweeney JA, Clementz BA, Schretlen D, Stegmayer K, Walther S, Lee J, Crow T, James A, Voineskos A, Buchanan RW, Szeszko PR, Malhotra AK, Keshavan M, Shenton ME, Rathi Y, Pasternak O, Kubicki M. Characterization of the extracellular free water signal in schizophrenia using multi-site diffusion MRI harmonization. Mol Psychiatry 2023; 28:2030-2038. [PMID: 37095352 DOI: 10.1038/s41380-023-02068-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 03/06/2023] [Accepted: 04/05/2023] [Indexed: 04/26/2023]
Abstract
Studies applying Free Water Imaging have consistently reported significant global increases in extracellular free water (FW) in populations of individuals with early psychosis. However, these published studies focused on homogenous clinical participant groups (e.g., only first episode or chronic), thereby limiting our understanding of the time course of free water elevations across illness stages. Moreover, the relationship between FW and duration of illness has yet to be directly tested. Leveraging our multi-site diffusion magnetic resonance imaging(dMRI) harmonization approach, we analyzed dMRI scans collected by 12 international sites from 441 healthy controls and 434 individuals diagnosed with schizophrenia-spectrum disorders at different illness stages and ages (15-58 years). We characterized the pattern of age-related FW changes by assessing whole brain white matter in individuals with schizophrenia and healthy controls. In individuals with schizophrenia, average whole brain FW was higher than in controls across all ages, with the greatest FW values observed from 15 to 23 years (effect size range = [0.70-0.87]). Following this peak, FW exhibited a monotonic decrease until reaching a minima at the age of 39 years. After 39 years, an attenuated monotonic increase in FW was observed, but with markedly smaller effect sizes when compared to younger patients (effect size range = [0.32-0.43]). Importantly, FW was found to be negatively associated with duration of illness in schizophrenia (p = 0.006), independent of the effects of other clinical and demographic data. In summary, our study finds in a large, age-diverse sample that participants with schizophrenia with a shorter duration of illness showed higher FW values compared to participants with more prolonged illness. Our findings provide further evidence that elevations in the FW are present in individuals with schizophrenia, with the greatest differences in the FW being observed in those at the early stages of the disorder, which might suggest acute extracellular processes.
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Affiliation(s)
- Suheyla Cetin-Karayumak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Amanda E Lyall
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Maria A Di Biase
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Johanna Seitz-Holland
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Fan Zhang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sinead Kelly
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA
| | - Doron Elad
- Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
| | | | - Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Brett A Clementz
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA, USA
| | - David Schretlen
- Department of Psychiatry and Behavioral Sciences, Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institutions, Baltimore, MD, USA
| | - Katharina Stegmayer
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Sebastian Walther
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Jungsun Lee
- Department of Psychiatry, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Tim Crow
- Department of Psychiatry, SANE POWIC, Warneford Hospital, University of Oxford, Oxford, UK
| | - Anthony James
- Department of Psychiatry, SANE POWIC, Warneford Hospital, University of Oxford, Oxford, UK
| | | | - Robert W Buchanan
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Philip R Szeszko
- Departments of Psychiatry and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research, Education, and Clinical Center, James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
| | - Anil K Malhotra
- The Feinstein Institutes for Medical Research and Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - Matcheri Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA
| | - Martha E Shenton
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Yogesh Rathi
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Marek Kubicki
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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15
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Zhang L, Lizano P, Xu Y, Rubin LH, Lee AM, Lencer R, Reilly JL, Keefe RSE, Keedy SK, Pearlson GD, Clementz BA, Keshavan MS, Gershon ES, Tamminga CA, Sweeney JA, Hill SK, Bishop JR. Peripheral inflammation is associated with impairments of inhibitory behavioral control and visual sensorimotor function in psychotic disorders. Schizophr Res 2023; 255:69-78. [PMID: 36965362 PMCID: PMC10175233 DOI: 10.1016/j.schres.2023.03.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 02/08/2023] [Accepted: 03/13/2023] [Indexed: 03/27/2023]
Abstract
Elevated markers of peripheral inflammation are common in psychosis spectrum disorders and have been associated with brain anatomy, pathology, and physiology as well as clinical outcomes. Preliminary evidence suggests a link between inflammatory cytokines and C-reactive protein (CRP) with generalized cognitive impairments in a subgroup of individuals with psychosis. Whether these patients with elevated peripheral inflammation demonstrate deficits in specific cognitive domains remains unclear. To examine this, seventeen neuropsychological and sensorimotor tasks and thirteen peripheral inflammatory and microvascular markers were quantified in a subset of B-SNIP consortium participants (129 psychosis, 55 healthy controls). Principal component analysis was conducted across the inflammatory markers, resulting in five inflammation factors. Three discrete latent cognitive domains (Visual Sensorimotor, General Cognitive Ability, and Inhibitory Behavioral Control) were characterized based on the neurobehavioral battery and examined in association with inflammation factors. Hierarchical clustering analysis identified cognition-sensitive high/low inflammation subgroups. Among persons with psychotic disorders but not healthy controls, higher inflammation scores had significant associations with impairments of Inhibitory Control (R2 = 0.100, p-value = 2.69e-4, q-value = 0.004) and suggestive associations with Visual Sensorimotor function (R2 = 0.039, p-value = 0.024, q-value = 0.180), but not with General Cognitive Ability (R2 = 0.015, p-value = 0.162). Greater deficits in Inhibitory Control were observed in the high inflammation patient subgroup, which represented 30.2 % of persons with psychotic disorders, as compared to the low inflammation psychosis subgroup. These findings indicate that inflammation dysregulation may differentially impact specific neurobehavioral domains across psychotic disorders, particularly performance on tasks requiring ongoing behavioral monitoring and control.
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Affiliation(s)
- Lusi Zhang
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, United States
| | - Paulo Lizano
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, United States; Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Division of Translational Neuroscience, Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - Yanxun Xu
- Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, United States
| | - Leah H Rubin
- Department of Neurology, Psychiatry, and Epidemiology, Johns Hopkins University, Baltimore, MD, United States
| | - Adam M Lee
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, United States
| | - Rebekka Lencer
- Institute for Translational Psychiatry, University of Münster, Münster, Germany; Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
| | - James L Reilly
- Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL, United States
| | - Richard S E Keefe
- Departments of Psychiatry, Neuroscience, and Psychology, Duke University, Durham, NC, United States
| | - Sarah K Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neurobiology, School of Medicine, Yale University, New Haven, CT, United States
| | - Brett A Clementz
- Department of Psychology and Neuroscience, University of Georgia, Athens, GA, United States
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, United States; Department of Psychiatry, Harvard Medical School, Boston, MA, United States
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center Dallas, TX, United States
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, United States
| | - S Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL, United States
| | - Jeffrey R Bishop
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, United States; Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, United States.
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16
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Trotti RL, Parker DA, Sabatinelli D, Keshavan MS, Keedy SK, Gershon ES, Pearlson GD, Hill SK, Tamminga CA, McDowell JE, Clementz BA. Emotional scene processing in biotypes of psychosis. Psychiatry Res 2023; 324:115227. [PMID: 37121219 PMCID: PMC10175237 DOI: 10.1016/j.psychres.2023.115227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 04/14/2023] [Accepted: 04/23/2023] [Indexed: 05/02/2023]
Abstract
Social-emotional deficits in psychosis may be indexed by deviations in emotional scene processing, but event-related potential (ERP) studies indicate such deviations may not map cleanly to diagnostic categories. Neurobiologically defined psychosis subgroups offer an alternative that may better capture neurophysiological correlates of social-emotional deficits. The current study investigates emotional scene-elicited ERPs in Biotypes of psychosis in a large (N = 622), well-characterized sample. Electroencephalography was recorded in healthy persons (N = 129), Biotype-1 (N = 195), Biotype-2 (N = 131), and Biotype-3 (N = 167) psychosis cases. ERPs were measured from posterior and centroparietal scalp locations. Neural responses to emotional scenes were compared between healthy and psychosis groups. Multivariate group discrimination analyses resulted in two composite variates that differentiated groups. The first variate displayed large differences between low-cognition (Biotype-1, Biotype-2) and intact-cognition groups (Biotype-3, healthy persons). The second indicated a small-to-moderate distinction of Biotypes-2 and -3 from Biotype-1 and healthy persons. Two multivariate correlations were identified indicating associations between 1) self-reported emotional experience and generalized cognition and 2) socio-occupational functioning and late-stage emotional processing. Psychosis Biotypes displayed emotional processing deficits not apparent in DSM psychosis subgroups. Future translational research may benefit from exploring emotional scene processing in such neurobiologically-defined psychosis groups.
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Affiliation(s)
- R L Trotti
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA.
| | - D A Parker
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - D Sabatinelli
- Department of Psychology, University of Georgia, Athens, GA, USA
| | - M S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - S K Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - E S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - G D Pearlson
- Institute of Living, Hartford Hospital, Hartford, CT, USA
| | - S K Hill
- Department of Psychology, Rosalind Franklin University, North Chicago, IL, USA
| | - C A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - J E McDowell
- Department of Psychology, University of Georgia, Athens, GA, USA
| | - B A Clementz
- Department of Psychology, University of Georgia, Athens, GA, USA
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17
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Mansouri S, Pessoni AM, Rivera AM, Tamminga CA, Parise E, Turecki G, Nestler EJ, Chen TH, Labonté B. Transcriptional dissection of symptomatic profiles across the brain of men and women with depression. bioRxiv 2023:2023.04.21.537733. [PMID: 37131585 PMCID: PMC10153251 DOI: 10.1101/2023.04.21.537733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Major depressive disorder (MDD) is one of the most important causes of disability worldwide. While recent work provides insights into the molecular alterations in the brain of patients with MDD, whether these molecular signatures can be associated with the expression of specific symptom domains in males and females remains unclear. Here, we identified sex-specific gene modules associated with the expression of MDD, combining differential gene expression and co-expression network analyses in six cortical and subcortical brain regions. Our results show varying levels of network homology between males and females across brain regions, although the association between these structures and the expression of MDD remains highly sex-specific. We refined these associations to several symptom domains and identified transcriptional signatures associated with distinct functional pathways, including GABAergic and glutamatergic neurotransmission, metabolic processes, and intracellular signal transduction, across brain regions associated with distinct symptomatic profiles in a sex-specific fashion. In most cases, these associations were specific to males or to females with MDD, although a subset of gene modules associated with common symptomatic features in both sexes was also identified. Together, our findings suggest that the expression of distinct MDD symptom domains is associated with sex-specific transcriptional structures across brain regions.
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18
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Issler O, van der Zee YY, Ramakrishnan A, Xia S, Zinsmaier AK, Tan C, Li W, Browne CJ, Walker DM, Salery M, Torres-Berrío A, Futamura R, Duffy JE, Labonte B, Girgenti MJ, Tamminga CA, Dupree JL, Dong Y, Murrough JW, Shen L, Nestler EJ. The long noncoding RNA FEDORA is a cell type- and sex-specific regulator of depression. Sci Adv 2022; 8:eabn9494. [PMID: 36449610 PMCID: PMC9710883 DOI: 10.1126/sciadv.abn9494] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 10/12/2022] [Indexed: 05/31/2023]
Abstract
Women suffer from depression at twice the rate of men, but the underlying molecular mechanisms are poorly understood. Here, we identify marked baseline sex differences in the expression of long noncoding RNAs (lncRNAs), a class of regulatory transcripts, in human postmortem brain tissue that are profoundly lost in depression. One such human lncRNA, RP11-298D21.1 (which we termed FEDORA), is enriched in oligodendrocytes and neurons and up-regulated in the prefrontal cortex (PFC) of depressed females only. We found that virally expressing FEDORA selectively either in neurons or in oligodendrocytes of PFC promoted depression-like behavioral abnormalities in female mice only, changes associated with cell type-specific regulation of synaptic properties, myelin thickness, and gene expression. We also found that blood FEDORA levels have diagnostic implications for depressed women and are associated with clinical response to ketamine. These findings demonstrate the important role played by lncRNAs, and FEDORA in particular, in shaping the sex-specific landscape of the brain and contributing to sex differences in depression.
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Affiliation(s)
- Orna Issler
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yentl Y. van der Zee
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Aarthi Ramakrishnan
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sunhui Xia
- Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Chunfeng Tan
- Department of Psychiatry, UT Southwestern, Dallas, TX, USA
| | - Wei Li
- Department of Psychiatry, UT Southwestern, Dallas, TX, USA
| | - Caleb J. Browne
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Deena M. Walker
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marine Salery
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Angélica Torres-Berrío
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rita Futamura
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Julia E. Duffy
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Benoit Labonte
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Matthew J. Girgenti
- Department of Anatomy and Neurobiology, Virginia Commonwealth University, Richmond, VA, USA
| | | | - Jeffrey L. Dupree
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Yan Dong
- Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA
| | - James W. Murrough
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Li Shen
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Eric J. Nestler
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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19
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Rootes-Murdy K, Edmond JT, Jiang W, Rahaman MA, Chen J, Perrone-Bizzozero NI, Calhoun VD, van Erp TGM, Ehrlich S, Agartz I, Jönsson EG, Andreassen OA, Westlye LT, Wang L, Pearlson GD, Glahn DC, Hong E, Buchanan RW, Kochunov P, Voineskos A, Malhotra A, Tamminga CA, Liu J, Turner JA. Clinical and cortical similarities identified between bipolar disorder I and schizophrenia: A multivariate approach. Front Hum Neurosci 2022; 16:1001692. [PMID: 36438633 PMCID: PMC9684186 DOI: 10.3389/fnhum.2022.1001692] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Accepted: 10/17/2022] [Indexed: 01/06/2024] Open
Abstract
BACKGROUND Structural neuroimaging studies have identified similarities in the brains of individuals diagnosed with schizophrenia (SZ) and bipolar I disorder (BP), with overlap in regions of gray matter (GM) deficits between the two disorders. Recent studies have also shown that the symptom phenotypes associated with SZ and BP may allow for a more precise categorization than the current diagnostic criteria. In this study, we sought to identify GM alterations that were unique to each disorder and whether those alterations were also related to unique symptom profiles. MATERIALS AND METHODS We analyzed the GM patterns and clinical symptom presentations using independent component analysis (ICA), hierarchical clustering, and n-way biclustering in a large (N ∼ 3,000), merged dataset of neuroimaging data from healthy volunteers (HV), and individuals with either SZ or BP. RESULTS Component A showed a SZ and BP < HV GM pattern in the bilateral insula and cingulate gyrus. Component B showed a SZ and BP < HV GM pattern in the cerebellum and vermis. There were no significant differences between diagnostic groups in these components. Component C showed a SZ < HV and BP GM pattern bilaterally in the temporal poles. Hierarchical clustering of the PANSS scores and the ICA components did not yield new subgroups. N-way biclustering identified three unique subgroups of individuals within the sample that mapped onto different combinations of ICA components and symptom profiles categorized by the PANSS but no distinct diagnostic group differences. CONCLUSION These multivariate results show that diagnostic boundaries are not clearly related to structural differences or distinct symptom profiles. Our findings add support that (1) BP tend to have less severe symptom profiles when compared to SZ on the PANSS without a clear distinction, and (2) all the gray matter alterations follow the pattern of SZ < BP < HV without a clear distinction between SZ and BP.
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Affiliation(s)
- Kelly Rootes-Murdy
- Department of Psychology, Georgia State University, Atlanta, GA, United States
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | - Jesse T. Edmond
- Department of Psychology, Georgia State University, Atlanta, GA, United States
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | - Wenhao Jiang
- Department of Psychosomatics and Psychiatry, Medical School, Zhongda Hospital, Institute of Psychosomatics, Southeast University, Nanjing, China
| | - Md A. Rahaman
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | - Jiayu Chen
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | | | - Vince D. Calhoun
- Department of Psychology, Georgia State University, Atlanta, GA, United States
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | - Theo G. M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, United States
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, United States
| | - Stefan Ehrlich
- Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Ingrid Agartz
- Division of Mental Health and Addiction, Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo, Norway
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institute and Stockholm Health Care Services, Stockholm, Sweden
- K. G. Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Erik G. Jönsson
- Division of Mental Health and Addiction, Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo, Norway
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institute and Stockholm Health Care Services, Stockholm, Sweden
| | - Ole A. Andreassen
- Division of Mental Health and Addiction, Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo, Norway
- K. G. Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Lars T. Westlye
- Division of Mental Health and Addiction, Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo, Norway
- K. G. Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Lei Wang
- Psychiatry and Behavioral Health, Ohio State Wexner Medical Center, Columbus, OH, United States
| | - Godfrey D. Pearlson
- Department of Psychiatry, Yale University, New Haven, CT, United States
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, Hartford, CT, United States
| | - David C. Glahn
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, Hartford, CT, United States
- Boston Children’s Hospital and Harvard Medical School, Boston, MA, United States
| | - Elliot Hong
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Robert W. Buchanan
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Peter Kochunov
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Aristotle Voineskos
- Department of Psychiatry, Centre for Addiction and Mental Health, University of Toronto, Toronto, ON, Canada
| | - Anil Malhotra
- Division of Psychiatry Research, Zucker Hillside Hospital, Queens, NY, United States
| | - Carol A. Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical School, Dallas, TX, United States
| | - Jingyu Liu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | - Jessica A. Turner
- Psychiatry and Behavioral Health, Ohio State Wexner Medical Center, Columbus, OH, United States
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20
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Zhao Q, Cao H, Zhang W, Li S, Xiao Y, Tamminga CA, Keshavan MS, Pearlson GD, Clementz BA, Gershon ES, Hill SK, Keedy SK, Ivleva EI, Lencer R, Sweeney JA, Gong Q, Lui S. A subtype of institutionalized patients with schizophrenia characterized by pronounced subcortical and cognitive deficits. Neuropsychopharmacology 2022; 47:2024-2032. [PMID: 35260788 PMCID: PMC9556672 DOI: 10.1038/s41386-022-01300-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 01/28/2022] [Accepted: 02/19/2022] [Indexed: 02/05/2023]
Abstract
Some patients with schizophrenia have severe cognitive impairment and functional deficits that require long-term institutional care. The patterns of brain-behavior alterations in these individuals, and their differences from patients living successfully in the community, remain poorly understood. Previous cognition-based studies for stratifying schizophrenia patients highlight the importance of subcortical structures in the context of illness heterogeneity. In the present study, subcortical volumes from 96 institutionalized patients with long-term schizophrenia were evaluated using cluster analysis to test for heterogeneity. These data were compared to those from two groups of community-dwelling individuals with schizophrenia for comparison purposes, including 68 long-term ill and 126 first-episode individuals. A total of 290 demographically matched healthy participants were included as normative references at a 1:1 ratio for each patient sample. A subtype of institutionalized patients was identified based on their pattern of subcortical alterations. Using a machine learning algorithm developed to discriminate the two groups of institutionalized patients, all three patient samples were found to have similar rates of patients assigned to the two subtypes (approximately 50% each). In institutionalized patients, only the subtype with the identified pattern of subcortical alterations had greater neocortical and cognitive abnormalities than those in the similarity classified community-dwelling patients with long-term illness. Thus, for the subtype of patients with a distinctive pattern of subcortical alterations, when the distinct pattern of subcortical alterations is present and particularly severe, it is associated with cognitive impairments that may contribute to persistent disability and institutionalization.
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Affiliation(s)
- Qiannan Zhao
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Hengyi Cao
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - Wenjing Zhang
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Siyi Li
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Yuan Xiao
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neurobiology, Yale University and Olin Neuropsychiatric Research Center, Hartford, CT, USA
| | - Brett A Clementz
- Department of Psychology, University of Georgia, Athens, GA, USA
| | - Elliot S Gershon
- Department of Psychiatry, University of Chicago, Chicago, IL, USA
| | - Scot Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago, IL, USA
| | - Sarah K Keedy
- Department of Psychiatry, University of Chicago, Chicago, IL, USA
| | - Elena I Ivleva
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Rebekka Lencer
- Department of Psychiatry and Psychotherapy, University of Münster, Münster, Germany
| | - John A Sweeney
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China.
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China.
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China.
| | - Su Lui
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China.
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China.
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China.
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21
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Huang LY, Jackson BS, Rodrigue AL, Tamminga CA, Gershon ES, Pearlson GD, Keshavan MS, Keedy SS, Hill SK, Sweeney JA, Clementz BA, McDowell JE. Antisaccade error rates and gap effects in psychosis syndromes from bipolar-schizophrenia network for intermediate phenotypes 2 (B-SNIP2). Psychol Med 2022; 52:2692-2701. [PMID: 33622437 DOI: 10.1017/s003329172000478x] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
BACKGROUND Antisaccade tasks can be used to index cognitive control processes, e.g. attention, behavioral inhibition, working memory, and goal maintenance in people with brain disorders. Though diagnoses of schizophrenia (SZ), schizoaffective (SAD), and bipolar I with psychosis (BDP) are typically considered to be distinct entities, previous work shows patterns of cognitive deficits differing in degree, rather than in kind, across these syndromes. METHODS Large samples of individuals with psychotic disorders were recruited through the Bipolar-Schizophrenia Network on Intermediate Phenotypes 2 (B-SNIP2) study. Anti- and pro-saccade task performances were evaluated in 189 people with SZ, 185 people with SAD, 96 people with BDP, and 279 healthy comparison participants. Logistic functions were fitted to each group's antisaccade speed-performance tradeoff patterns. RESULTS Psychosis groups had higher antisaccade error rates than the healthy group, with SZ and SAD participants committing 2 times as many errors, and BDP participants committing 1.5 times as many errors. Latencies on correctly performed antisaccade trials in SZ and SAD were longer than in healthy participants, although error trial latencies were preserved. Parameters of speed-performance tradeoff functions indicated that compared to the healthy group, SZ and SAD groups had optimal performance characterized by more errors, as well as less benefit from prolonged response latencies. Prosaccade metrics did not differ between groups. CONCLUSIONS With basic prosaccade mechanisms intact, the higher speed-performance tradeoff cost for antisaccade performance in psychosis cases indicates a deficit that is specific to the higher-order cognitive aspects of saccade generation.
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Affiliation(s)
- Ling-Yu Huang
- Departments of Psychology & Neuroscience, University of Georgia, Athens, GA, USA
| | - Brooke S Jackson
- Departments of Psychology & Neuroscience, University of Georgia, Athens, GA, USA
| | - Amanda L Rodrigue
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | | | | | - Sarah S Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - S Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago, IL, USA
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Brett A Clementz
- Departments of Psychology & Neuroscience, University of Georgia, Athens, GA, USA
| | - Jennifer E McDowell
- Departments of Psychology & Neuroscience, University of Georgia, Athens, GA, USA
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22
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Karpouzian-Rogers T, Sweeney JA, Rubin LH, McDowell J, Clementz BA, Gershon E, Keshavan MS, Pearlson GD, Tamminga CA, Reilly JL. Reduced task-evoked pupillary response in preparation for an executive cognitive control response among individuals across the psychosis spectrum. Schizophr Res 2022; 248:79-88. [PMID: 35963057 DOI: 10.1016/j.schres.2022.07.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Revised: 04/29/2022] [Accepted: 07/25/2022] [Indexed: 11/19/2022]
Abstract
Task-evoked pupillary response (TEPR) is a measure of physiological arousal modulated by cognitive demand. Healthy individuals demonstrate greater TEPR prior to correct versus error antisaccade trials and correct antisaccade versus visually guided saccade (VGS) trials. The relationship between TEPR and antisaccade performance in individuals with psychotic disorders and their relatives has not been investigated. Probands with schizophrenia, schizoaffective disorder, psychotic bipolar disorder, their first-degree relatives, and controls from the B-SNIP study completed antisaccade and VGS tasks. TEPR prior to execution of responses on these tasks was evaluated among controls compared to probands and relatives according to diagnostic groups and neurobiologically defined subgroups (biotypes). Controls demonstrated greater TEPR on antisaccade correct versus error versus VGS trials. TEPR was not differentiated between antisaccade correct versus error trials in bipolar or schizophrenia probands, though was greater on antisaccade compared to prosaccade trials. There was no modulation of TEPR in schizoaffective probands. Relatives of schizophrenia and schizoaffective probands and those with elevated psychosis spectrum traits failed to demonstrate differential TEPR on antisaccade correct versus error trials. No proband or relative biotypes demonstrated differential TEPR on antisaccade correct versus error trials, and only proband biotype 3 and relative biotypes 3 and 2 demonstrated greater TEPR on antisaccade versus VGS trials. Our findings suggest that aberrant modulation of preparatory activity prior to saccade execution contributes to impaired executive cognitive control across the psychosis spectrum, including nonpsychotic relatives with elevated clinical risk. Reduced pupillary modulation under cognitive challenge may thus be a biomarker for the psychosis phenotype.
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Affiliation(s)
- Tatiana Karpouzian-Rogers
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, United States of America
| | - John A Sweeney
- Department of Psychiatry, University of Cincinnati College of Medicine, Cincinnati, OH, United States of America
| | - Leah H Rubin
- Departments of Neurology and Psychiatry, Johns Hopkins School of Medicine, Baltimore, MD, United States of America; Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, United States of America
| | - Jennifer McDowell
- Department of Psychology, University of Georgia, Athens, GA, United States of America
| | - Brett A Clementz
- Department of Psychology, University of Georgia, Athens, GA, United States of America
| | - Elliot Gershon
- Psychiatry, University of Chicago, Chicago, IL, United States of America
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States of America
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neurobiology, Yale University and Olin Neuropsychiatric Research Center, Hartford, CT, United States of America
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, United States of America
| | - James L Reilly
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, United States of America.
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23
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Pietrzykowski MO, Waters AB, Gansler DA, Jerram M, Pearlson GD, Tamminga CA, Clementz BA, Keshavan MS, Gershon ES. A-173 Grey Matter Volume, Psychotic Disorders, And Heredity of Alcohol Use Disorder: Reconceptualization by B-SNIP Biotypes. Arch Clin Neuropsychol 2022. [DOI: 10.1093/arclin/acac060.173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Objective: Bipolar and Schizophrenia Network for Intermediate Phenotypes (B-SNIP) researchers have proposed three Biotypes that show advantages of a dimensional approach to classification, revealing different levels of dysfunction severity through EEG and various forms of cognitive testing. Although preliminary work has been done showing neuroanatomical differences among the biotypes and patterns of heredity, more research is required to investigate the contribution of significant co-morbid factors such as alcohol misuse. Objective. Neuroanatomical data were used to further understand the biomarker of grey matter volume (GMV) in relation to the B-SNIP Biotypes and the interacting influence of family history of alcohol use disorder (FH-AUD).
Method. Biotype, FH-AUD, and demographic variables (age, sex, education, and ethnicity) were used in hierarchical regression analyses for prediction of total volume and two key regions (superior parietal cortex and posterior cingulate cortex) in stable probands (n = 347) and their healthy first-degree relatives (n = 346) separately. Prediction was also analyzed in the context of conventional diagnosis of psychotic disorders (schizophrenia, schizoaffective disorder, and bipolar disorder with psychotic features). Structural data were analyzed using FreeSurfer.
Results. Biotype was shown to be a more robust predictor of GMV than diagnosis both generally and specifically in relevant regions (p < .05). A pattern of GMV reduction based on severity was observed both in probands and relatives. Effects of FH-AUD and its interaction with Biotype were occasionally observed.
Conclusions. This study contributes to the efforts of psychobiological research to establish a more valid conceptualization of psychological disorders through biological mechanisms.
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24
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Zhang L, Lizano P, Guo B, Xu Y, Rubin LH, Hill SK, Alliey-Rodriguez N, Lee AM, Wu B, Keedy SK, Tamminga CA, Pearlson GD, Clementz BA, Keshavan MS, Gershon ES, Sweeney JA, Bishop JR. Inflammation subtypes in psychosis and their relationships with genetic risk for psychiatric and cardiometabolic disorders. Brain Behav Immun Health 2022; 22:100459. [PMID: 35496776 PMCID: PMC9046804 DOI: 10.1016/j.bbih.2022.100459] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Accepted: 03/31/2022] [Indexed: 02/07/2023] Open
Abstract
Cardiometabolic disorders have known inflammatory implications, and peripheral measures of inflammation and cardiometabolic disorders are common in persons with psychotic disorders. Inflammatory signatures are also related to neurobiological and behavioral changes in psychosis. Relationships between systemic inflammation and cardiometabolic genetic risk in persons with psychosis have not been examined. Thirteen peripheral inflammatory markers and genome-wide genotyping were assessed in 122 participants (n = 86 psychosis, n = 36 healthy controls) of European ancestry. Cluster analyses of inflammatory markers classified higher and lower inflammation subgroups. Single-trait genetic risk scores (GRS) were constructed for each participant using previously reported GWAS summary statistics for the following traits: schizophrenia, bipolar disorder, major depressive disorder, coronary artery disease, type-2 diabetes, low-density lipoprotein, high-density lipoprotein, triglycerides, and waist-to-hip ratio. Genetic correlations across traits were quantified. Principal component (PC) analysis of the cardiometabolic GRSs generated six PC loadings used in regression models to examine associations with inflammation markers. Functional module discovery explored biological mechanisms of the inflammation association of cardiometabolic GRS genes. A subgroup of 38% persons with psychotic disorders was characterized with higher inflammation status. These higher inflammation individuals had lower BACS scores (p = 0.038) compared to those with lower inflammation. The first PC of the cardiometabolic GRS matrix was related to higher inflammation status in persons with psychotic disorders (OR = 2.037, p = 0.001). Two of eight modules within the functional interaction network of cardiometabolic GRS genes were enriched for immune processes. Cardiometabolic genetic risk may predispose some individuals with psychosis to elevated inflammation which adversely impacts cognition associated with illness.
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Affiliation(s)
- Lusi Zhang
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, USA
| | - Paulo Lizano
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Bin Guo
- Division of Biostatistics, School of Public Health, University of Minnesota, MN, USA
| | - Yanxun Xu
- Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA
| | - Leah H. Rubin
- Department of Neurology, Psychiatry, and Epidemiology, Johns Hopkins University, Baltimore, MD, USA
| | - S. Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL, USA
| | - Ney Alliey-Rodriguez
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Adam M. Lee
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, USA
| | - Baolin Wu
- Division of Biostatistics, School of Public Health, University of Minnesota, MN, USA
| | - Sarah K. Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Carol A. Tamminga
- Department of Psychiatry, Southwestern Medical Center, University of Texas, Dallas, TX, USA
| | - Godfrey D. Pearlson
- Department of Psychiatry, School of Medicine, Yale University, New Haven, CT, USA
- Department of Neurobiology, School of Medicine, Yale University, New Haven, CT, USA
| | - Brett A. Clementz
- Department of Psychology and Neuroscience, University of Georgia, Athens, GA, USA
| | - Matcheri S. Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Elliot S. Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - John A. Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Jeffrey R. Bishop
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, USA
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, USA
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25
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Farrelly LA, Zheng S, Schrode N, Topol A, Bhanu NV, Bastle RM, Ramakrishnan A, Chan JC, Cetin B, Flaherty E, Shen L, Gleason K, Tamminga CA, Garcia BA, Li H, Brennand KJ, Maze I. Chromatin profiling in human neurons reveals aberrant roles for histone acetylation and BET family proteins in schizophrenia. Nat Commun 2022; 13:2195. [PMID: 35459277 PMCID: PMC9033776 DOI: 10.1038/s41467-022-29922-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Accepted: 03/01/2022] [Indexed: 12/19/2022] Open
Abstract
Schizophrenia (SZ) is a psychiatric disorder with complex genetic risk dictated by interactions between hundreds of risk variants. Epigenetic factors, such as histone posttranslational modifications (PTMs), have been shown to play critical roles in many neurodevelopmental processes, and when perturbed may also contribute to the precipitation of disease. Here, we apply an unbiased proteomics approach to evaluate combinatorial histone PTMs in human induced pluripotent stem cell (hiPSC)-derived forebrain neurons from individuals with SZ. We observe hyperacetylation of H2A.Z and H4 in neurons derived from SZ cases, results that were confirmed in postmortem human brain. We demonstrate that the bromodomain and extraterminal (BET) protein, BRD4, is a bona fide 'reader' of H2A.Z acetylation, and further provide evidence that BET family protein inhibition ameliorates transcriptional abnormalities in patient-derived neurons. Thus, treatments aimed at alleviating BET protein interactions with hyperacetylated histones may aid in the prevention or treatment of SZ.
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Affiliation(s)
- Lorna A Farrelly
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Shuangping Zheng
- Beijing Advanced Innovation Center for Structural Biology, MOE Key Laboratory of Protein Sciences, Department of Basic Medical Sciences, School of Medicine, Tsinghua University, 100084, Beijing, China
| | - Nadine Schrode
- Department of Genetics and Genomic Sciences, Pamela Sklar Division of Psychiatric Genomics, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Aaron Topol
- Graduate School of Biomedical Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Natarajan V Bhanu
- Epigenetics Institute, Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Ryan M Bastle
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Aarthi Ramakrishnan
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Jennifer C Chan
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Bulent Cetin
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Erin Flaherty
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Sciences, Pamela Sklar Division of Psychiatric Genomics, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Li Shen
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Kelly Gleason
- Department of Psychiatry, University of Texas Southwestern Medical School, Dallas, TX, 75390, USA
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical School, Dallas, TX, 75390, USA
| | - Benjamin A Garcia
- Epigenetics Institute, Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Haitao Li
- Beijing Advanced Innovation Center for Structural Biology, MOE Key Laboratory of Protein Sciences, Department of Basic Medical Sciences, School of Medicine, Tsinghua University, 100084, Beijing, China.
| | - Kristen J Brennand
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Department of Genetics and Genomic Sciences, Pamela Sklar Division of Psychiatric Genomics, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Departments of Psychiatry and Genetics, Wu Tsai Institute, Yale School of Medicine, New Haven, CT, 065109, USA.
| | - Ian Maze
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Howard Hughes Medical Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
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26
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Tamminga CA, Pearlson G, Gershon E, Keedy S, Hudgens-Haney ME, Ivleva EI, Parker DA, McDowell JE, Clementz B. Using psychosis biotypes and the Framingham model for parsing psychosis biology. Schizophr Res 2022; 242:132-134. [PMID: 35123865 DOI: 10.1016/j.schres.2022.01.018] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 01/11/2022] [Indexed: 12/28/2022]
Abstract
The Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) has invested in the collection and use of multiple biomarkers in individuals with psychosis. We expect psychosis biology and its distinctive types to be reflected in the biomarkers, as they are the 'behaviors' of the brain. Like infectious diseases, we expect the etiologies of these biomarker-driven entities to be multiple and complex. Biomarkers have not yet been annotated with disease characteristics and need to be. As a model, we seek to adopt aspects of the Framingham Heart Study (FHS) to guide and organize these observations.
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Affiliation(s)
| | | | - Elliot Gershon
- University of Chicago, Chicago, IL, United States of America
| | - Sarah Keedy
- University of Chicago, Chicago, IL, United States of America
| | | | | | - David A Parker
- University of Georgia, Athens, GA, United States of America
| | | | - Brett Clementz
- University of Georgia, Athens, GA, United States of America
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27
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Girdhar K, Hoffman GE, Bendl J, Rahman S, Dong P, Liao W, Hauberg ME, Sloofman L, Brown L, Devillers O, Kassim BS, Wiseman JR, Park R, Zharovsky E, Jacobov R, Flatow E, Kozlenkov A, Gilgenast T, Johnson JS, Couto L, Peters MA, Phillips-Cremins JE, Hahn CG, Gur RE, Tamminga CA, Lewis DA, Haroutunian V, Dracheva S, Lipska BK, Marenco S, Kundakovic M, Fullard JF, Jiang Y, Roussos P, Akbarian S. Chromatin domain alterations linked to 3D genome organization in a large cohort of schizophrenia and bipolar disorder brains. Nat Neurosci 2022; 25:474-483. [PMID: 35332326 PMCID: PMC8989650 DOI: 10.1038/s41593-022-01032-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 02/09/2022] [Indexed: 12/19/2022]
Abstract
Chromosomal organization, scaling from the 147 base pair nucleosome to
megabase-ranging domains encompassing multiple transcriptional units including
heritability loci for psychiatric traits, remains largely unexplored in the
human brain. Here, we construct promoter and enhancer enriched nucleosomal
histone modification landscapes for adult prefrontal cortex (PFC) from H3-lysine
27 acetylation and H3-lysine 4 trimethylation profiles, generated from (n=739)
388 controls and 351 subjects diagnosed with schizophrenia (SCZ) or bipolar
disorder (BD). We mapped thousands of cis-regulatory domains (CRDs), revealing
fine-grained, 104-106 bp chromosomal organization, firmly
integrated into Hi-C topologically associating domain (TAD) stratification by
open/repressive chromosomal environments and nuclear topography. Large clusters
of hyperacetylated CRDs were enriched for SCZ heritability, with prominent
representation of regulatory sequences governing fetal development and
glutamatergic neuron signaling. Therefore, SCZ and BD brains show coordinated
dysregulation of risk-associated regulatory sequences assembled into kilo- to
megabase-scaling chromosomal domains.
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Affiliation(s)
- Kiran Girdhar
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Gabriel E Hoffman
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jaroslav Bendl
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Samir Rahman
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Pengfei Dong
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Will Liao
- New York Genome Center, New York, NY, USA
| | - Mads E Hauberg
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Laura Sloofman
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Leanne Brown
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Olivia Devillers
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bibi S Kassim
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jennifer R Wiseman
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Royce Park
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Elizabeth Zharovsky
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rivky Jacobov
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Elie Flatow
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alexey Kozlenkov
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Thomas Gilgenast
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Jessica S Johnson
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lizette Couto
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Jennifer E Phillips-Cremins
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Chang-Gyu Hahn
- Department of Psychiatry, Vickie and Jack Farber Institute for Neuroscience, Jefferson University, Philadelphia, PA, USA
| | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Carol A Tamminga
- Department of Psychiatry, The University of Texas Southwestern Medical School, Dallas, TX, USA
| | - David A Lewis
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Vahram Haroutunian
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, NY, USA
| | | | - Stella Dracheva
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, NY, USA
| | - Barbara K Lipska
- Human Brain Collection Core, National Institute of Mental Health-Intramural Research Program, Bethesda, MD, USA
| | - Stefano Marenco
- Human Brain Collection Core, National Institute of Mental Health-Intramural Research Program, Bethesda, MD, USA
| | - Marija Kundakovic
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Biological Sciences, Fordham University, Bronx, NY, USA
| | - John F Fullard
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yan Jiang
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Institutes of Brain Science, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Panos Roussos
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, NY, USA. .,Center for Dementia Research, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
| | - Schahram Akbarian
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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28
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Zhang L, Hill SK, Guo B, Wu B, Alliey-Rodriguez N, Eum S, Lizano P, Ivleva EI, Reilly JL, Keefe RSE, Keedy SK, Tamminga CA, Pearlson GD, Clementz BA, Keshavan MS, Gershon ES, Sweeney JA, Bishop JR. Impact of polygenic risk for coronary artery disease and cardiovascular medication burden on cognitive impairment in psychotic disorders. Prog Neuropsychopharmacol Biol Psychiatry 2022; 113:110464. [PMID: 34756932 PMCID: PMC8932335 DOI: 10.1016/j.pnpbp.2021.110464] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 10/13/2021] [Accepted: 10/25/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND Cognitive impairment is a core deficit across psychotic disorders, the causes and therapeutics of which remain unclear. Epidemiological observations have suggested associations between cognitive dysfunction in psychotic disorders and cardiovascular risk factors, but an underlying etiology has not been established. METHODS Neuropsychological performance using the Brief Assessment of Cognition in Schizophrenia (BACS) was assessed in 616 individuals of European ancestry (403 psychosis, 213 controls). Polygenic risk scores for coronary artery disease (PRSCAD) were quantified for each participant across 13 p-value thresholds (PT 0.5-5e-8). Cardiovascular and psychotropic medications were categorized for association analyses. Each PRSCAD was examined in relation to the BACS and the optimized PT was confirmed with five-fold cross-validation and independent validation. Functional enrichment analyses were used to identify biological mechanisms linked to PRSCAD-cognition associations. Multiple regression analyses examined PRSCAD under the optimal PT and medication burden in relation to the BACS composite and subtest scores. RESULTS Higher PRSCAD was associated with lower BACS composite scores (p = 0.001) in the psychosis group, primarily driven by the Verbal Memory subtest (p < 0.001). Genes linked to multiple nervous system related processes and pathways were significantly enriched in PRSCAD. After controlling for PRSCAD, a greater number of cardiovascular medications was also correlated with worse BACS performance in patients with psychotic disorders (p = 0.029). CONCLUSIONS Higher PRSCAD and taking more cardiovascular medications were both significantly associated with cognitive impairment in psychosis. These findings indicate that cardiovascular factors may increase the risk for cognitive dysfunction and related functional outcomes among individuals with psychotic disorders.
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Affiliation(s)
- Lusi Zhang
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, United States of America
| | - Scot Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL, United States of America
| | - Bin Guo
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, United States of America
| | - Baolin Wu
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, United States of America
| | - Ney Alliey-Rodriguez
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States of America
| | - Seenae Eum
- Department of Pharmacogenomics, School of Pharmacy, Shenandoah University, Fairfax, VA, United States of America
| | - Paulo Lizano
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States of America
| | - Elena I Ivleva
- Department of Psychiatry, Southwestern Medical Center, University of Texas, Dallas, TX, United States of America
| | - James L Reilly
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States of America
| | - Richard S E Keefe
- Departments of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, United States of America
| | - Sarah K Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States of America
| | - Carol A Tamminga
- Department of Psychiatry, Southwestern Medical Center, University of Texas, Dallas, TX, United States of America
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neurobiology, School of Medicine, Yale University, New Haven, CT, United States of America
| | - Brett A Clementz
- Department of Psychology and Neuroscience, University of Georgia, Athens, GA, United States of America
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States of America
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States of America
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, United States of America
| | - Jeffrey R Bishop
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, United States of America; Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, United States of America.
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29
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Raymond N, Lizano P, Kelly S, Hegde R, Keedy S, Pearlson GD, Gershon ES, Clementz BA, Tamminga CA, Keshavan M. What can clozapine’s effect on neural oscillations tell us about its therapeutic effects? A scoping review and synthesis. Biomark Neuropsychiatry 2022. [DOI: 10.1016/j.bionps.2022.100048] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
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30
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Clementz BA, Parker DA, Trotti RL, McDowell JE, Keedy SK, Keshavan MS, Pearlson GD, Gershon ES, Ivleva EI, Huang LY, Hill SK, Sweeney JA, Thomas O, Hudgens-Haney M, Gibbons RD, Tamminga CA. Psychosis Biotypes: Replication and Validation from the B-SNIP Consortium. Schizophr Bull 2022; 48:56-68. [PMID: 34409449 PMCID: PMC8781330 DOI: 10.1093/schbul/sbab090] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Current clinical phenomenological diagnosis in psychiatry neither captures biologically homologous disease entities nor allows for individualized treatment prescriptions based on neurobiology. In this report, we studied two large samples of cases with schizophrenia, schizoaffective, and bipolar I disorder with psychosis, presentations with clinical features of hallucinations, delusions, thought disorder, affective, or negative symptoms. A biomarker approach to subtyping psychosis cases (called psychosis Biotypes) captured neurobiological homology that was missed by conventional clinical diagnoses. Two samples (called "B-SNIP1" with 711 psychosis and 274 healthy persons, and the "replication sample" with 717 psychosis and 198 healthy persons) showed that 44 individual biomarkers, drawn from general cognition (BACS), motor inhibitory (stop signal), saccadic system (pro- and anti-saccades), and auditory EEG/ERP (paired-stimuli and oddball) tasks of psychosis-relevant brain functions were replicable (r's from .96-.99) and temporally stable (r's from .76-.95). Using numerical taxonomy (k-means clustering) with nine groups of integrated biomarker characteristics (called bio-factors) yielded three Biotypes that were virtually identical between the two samples and showed highly similar case assignments to subgroups based on cross-validations (88.5%-89%). Biotypes-1 and -2 shared poor cognition. Biotype-1 was further characterized by low neural response magnitudes, while Biotype-2 was further characterized by overactive neural responses and poor sensory motor inhibition. Biotype-3 was nearly normal on all bio-factors. Construct validation of Biotype EEG/ERP neurophysiology using measures of intrinsic neural activity and auditory steady state stimulation highlighted the robustness of these outcomes. Psychosis Biotypes may yield meaningful neurobiological targets for treatments and etiological investigations.
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Affiliation(s)
- Brett A Clementz
- Departments of Psychology and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
| | - David A Parker
- Departments of Psychology and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
| | - Rebekah L Trotti
- Departments of Psychology and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
| | - Jennifer E McDowell
- Departments of Psychology and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
| | - Sarah K Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neuroscience, Yale University School of Medicine, New Haven, CT, USA
- Institute of Living, Hartford Healthcare Corp, Hartford, CT, USA
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Elena I Ivleva
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - Ling-Yu Huang
- Departments of Psychology and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
| | - S Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago, IL, USA
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Olivia Thomas
- Departments of Psychology and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
| | | | - Robert D Gibbons
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
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31
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Affiliation(s)
- Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas.
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32
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Citrome L, Abi-Dargham A, Bilder RM, Duffy RA, Dunlop BW, Harvey PD, Pizzagalli DA, Tamminga CA, McIntyre RS, Kane JM. Making Sense of the Matrix: A Qualitative Assessment and Commentary on Connecting Psychiatric Symptom Scale Items to the Research Domain Criteria (RDoC). Innov Clin Neurosci 2022; 19:26-32. [PMID: 35382070 PMCID: PMC8970242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The Research Domain Criteria (RDoC) initiative aims to organize research according to domains of brain function. Dysfunction within these domains leads to psychopathology that is classically measured with rating scales. Examining the correspondence between the specific measures assessed within rating scales and RDoC domains is necessary to assess the needs for new RDoC-focused scales. Such RDoC-focused scales have the potential of allowing translation of this work into the clinical domain of measuring psychopathology and designing treatment. Here, we describe an initial qualitative assessment by a group of 10 clinician-scientists of the alignment between RDoC domains and the items within five commonly used rating scales. In this commentary, we report limited correspondence and make recommendations for future work needed to address these limitations.
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Affiliation(s)
- Leslie Citrome
- Dr. Citrome is with New York Medical College in Valhalla, New York
- Dr. Abi-Dargham is with Stony Brook University in Stony Brook, New York
- Dr. Bilder is with the University of California in Los Angeles, California
- Dr. Duffy is with Otsuka Pharmaceutical Development and Commercialization in Princeton, New Jersey
- Dr. Dunlop is with Emory University in Atlanta, Georgia
- Dr. Harvey is with the Miller School of Medicine, University of Miami in Miami, Florida
- Dr. Pizzagalli is with Harvard Medical School in Boston, Massachusetts
- Dr. Tamminga is with the University of Texas Southwestern in Dallas, Texas
- Dr. McIntyre is with the University of Toronto in Toronto, Canada
- Dr. Kane is with the Zucker School of Medicine at Hofstra/Northwell in Hempstead, New York
| | - Anissa Abi-Dargham
- Dr. Citrome is with New York Medical College in Valhalla, New York
- Dr. Abi-Dargham is with Stony Brook University in Stony Brook, New York
- Dr. Bilder is with the University of California in Los Angeles, California
- Dr. Duffy is with Otsuka Pharmaceutical Development and Commercialization in Princeton, New Jersey
- Dr. Dunlop is with Emory University in Atlanta, Georgia
- Dr. Harvey is with the Miller School of Medicine, University of Miami in Miami, Florida
- Dr. Pizzagalli is with Harvard Medical School in Boston, Massachusetts
- Dr. Tamminga is with the University of Texas Southwestern in Dallas, Texas
- Dr. McIntyre is with the University of Toronto in Toronto, Canada
- Dr. Kane is with the Zucker School of Medicine at Hofstra/Northwell in Hempstead, New York
| | - Robert M Bilder
- Dr. Citrome is with New York Medical College in Valhalla, New York
- Dr. Abi-Dargham is with Stony Brook University in Stony Brook, New York
- Dr. Bilder is with the University of California in Los Angeles, California
- Dr. Duffy is with Otsuka Pharmaceutical Development and Commercialization in Princeton, New Jersey
- Dr. Dunlop is with Emory University in Atlanta, Georgia
- Dr. Harvey is with the Miller School of Medicine, University of Miami in Miami, Florida
- Dr. Pizzagalli is with Harvard Medical School in Boston, Massachusetts
- Dr. Tamminga is with the University of Texas Southwestern in Dallas, Texas
- Dr. McIntyre is with the University of Toronto in Toronto, Canada
- Dr. Kane is with the Zucker School of Medicine at Hofstra/Northwell in Hempstead, New York
| | - Ruth A Duffy
- Dr. Citrome is with New York Medical College in Valhalla, New York
- Dr. Abi-Dargham is with Stony Brook University in Stony Brook, New York
- Dr. Bilder is with the University of California in Los Angeles, California
- Dr. Duffy is with Otsuka Pharmaceutical Development and Commercialization in Princeton, New Jersey
- Dr. Dunlop is with Emory University in Atlanta, Georgia
- Dr. Harvey is with the Miller School of Medicine, University of Miami in Miami, Florida
- Dr. Pizzagalli is with Harvard Medical School in Boston, Massachusetts
- Dr. Tamminga is with the University of Texas Southwestern in Dallas, Texas
- Dr. McIntyre is with the University of Toronto in Toronto, Canada
- Dr. Kane is with the Zucker School of Medicine at Hofstra/Northwell in Hempstead, New York
| | - Boadie W Dunlop
- Dr. Citrome is with New York Medical College in Valhalla, New York
- Dr. Abi-Dargham is with Stony Brook University in Stony Brook, New York
- Dr. Bilder is with the University of California in Los Angeles, California
- Dr. Duffy is with Otsuka Pharmaceutical Development and Commercialization in Princeton, New Jersey
- Dr. Dunlop is with Emory University in Atlanta, Georgia
- Dr. Harvey is with the Miller School of Medicine, University of Miami in Miami, Florida
- Dr. Pizzagalli is with Harvard Medical School in Boston, Massachusetts
- Dr. Tamminga is with the University of Texas Southwestern in Dallas, Texas
- Dr. McIntyre is with the University of Toronto in Toronto, Canada
- Dr. Kane is with the Zucker School of Medicine at Hofstra/Northwell in Hempstead, New York
| | - Philip D Harvey
- Dr. Citrome is with New York Medical College in Valhalla, New York
- Dr. Abi-Dargham is with Stony Brook University in Stony Brook, New York
- Dr. Bilder is with the University of California in Los Angeles, California
- Dr. Duffy is with Otsuka Pharmaceutical Development and Commercialization in Princeton, New Jersey
- Dr. Dunlop is with Emory University in Atlanta, Georgia
- Dr. Harvey is with the Miller School of Medicine, University of Miami in Miami, Florida
- Dr. Pizzagalli is with Harvard Medical School in Boston, Massachusetts
- Dr. Tamminga is with the University of Texas Southwestern in Dallas, Texas
- Dr. McIntyre is with the University of Toronto in Toronto, Canada
- Dr. Kane is with the Zucker School of Medicine at Hofstra/Northwell in Hempstead, New York
| | - Diego A Pizzagalli
- Dr. Citrome is with New York Medical College in Valhalla, New York
- Dr. Abi-Dargham is with Stony Brook University in Stony Brook, New York
- Dr. Bilder is with the University of California in Los Angeles, California
- Dr. Duffy is with Otsuka Pharmaceutical Development and Commercialization in Princeton, New Jersey
- Dr. Dunlop is with Emory University in Atlanta, Georgia
- Dr. Harvey is with the Miller School of Medicine, University of Miami in Miami, Florida
- Dr. Pizzagalli is with Harvard Medical School in Boston, Massachusetts
- Dr. Tamminga is with the University of Texas Southwestern in Dallas, Texas
- Dr. McIntyre is with the University of Toronto in Toronto, Canada
- Dr. Kane is with the Zucker School of Medicine at Hofstra/Northwell in Hempstead, New York
| | - Carol A Tamminga
- Dr. Citrome is with New York Medical College in Valhalla, New York
- Dr. Abi-Dargham is with Stony Brook University in Stony Brook, New York
- Dr. Bilder is with the University of California in Los Angeles, California
- Dr. Duffy is with Otsuka Pharmaceutical Development and Commercialization in Princeton, New Jersey
- Dr. Dunlop is with Emory University in Atlanta, Georgia
- Dr. Harvey is with the Miller School of Medicine, University of Miami in Miami, Florida
- Dr. Pizzagalli is with Harvard Medical School in Boston, Massachusetts
- Dr. Tamminga is with the University of Texas Southwestern in Dallas, Texas
- Dr. McIntyre is with the University of Toronto in Toronto, Canada
- Dr. Kane is with the Zucker School of Medicine at Hofstra/Northwell in Hempstead, New York
| | - Roger S McIntyre
- Dr. Citrome is with New York Medical College in Valhalla, New York
- Dr. Abi-Dargham is with Stony Brook University in Stony Brook, New York
- Dr. Bilder is with the University of California in Los Angeles, California
- Dr. Duffy is with Otsuka Pharmaceutical Development and Commercialization in Princeton, New Jersey
- Dr. Dunlop is with Emory University in Atlanta, Georgia
- Dr. Harvey is with the Miller School of Medicine, University of Miami in Miami, Florida
- Dr. Pizzagalli is with Harvard Medical School in Boston, Massachusetts
- Dr. Tamminga is with the University of Texas Southwestern in Dallas, Texas
- Dr. McIntyre is with the University of Toronto in Toronto, Canada
- Dr. Kane is with the Zucker School of Medicine at Hofstra/Northwell in Hempstead, New York
| | - John M Kane
- Dr. Citrome is with New York Medical College in Valhalla, New York
- Dr. Abi-Dargham is with Stony Brook University in Stony Brook, New York
- Dr. Bilder is with the University of California in Los Angeles, California
- Dr. Duffy is with Otsuka Pharmaceutical Development and Commercialization in Princeton, New Jersey
- Dr. Dunlop is with Emory University in Atlanta, Georgia
- Dr. Harvey is with the Miller School of Medicine, University of Miami in Miami, Florida
- Dr. Pizzagalli is with Harvard Medical School in Boston, Massachusetts
- Dr. Tamminga is with the University of Texas Southwestern in Dallas, Texas
- Dr. McIntyre is with the University of Toronto in Toronto, Canada
- Dr. Kane is with the Zucker School of Medicine at Hofstra/Northwell in Hempstead, New York
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Brown JA, Jackson BS, Burton CR, Hoy JE, Sweeney JA, Pearlson GD, Keshavan MS, Keedy SS, Gershon ES, Tamminga CA, Clementz BA, McDowell JE. Reduced white matter microstructure in bipolar disorder with and without psychosis. Bipolar Disord 2021; 23:801-809. [PMID: 33550654 PMCID: PMC8514149 DOI: 10.1111/bdi.13055] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
OBJECTIVES Affective and psychotic features overlap considerably in bipolar I disorder, complicating efforts to determine its etiology and develop targeted treatments. In order to clarify whether mechanisms are similar or divergent for bipolar disorder with psychosis (BDP) and bipolar disorder with no psychosis (BDNP), neurobiological profiles for both the groups must first be established. This study examines white matter structure in the BDP and BDNP groups, in an effort to identify portions of white matter that may differ between the bipolar and healthy groups or between the bipolar subgroups themselves. METHODS Diffusion-weighted imaging data were acquired from participants with BDP (n = 45), BDNP (n = 40), and healthy comparisons (HC) (n = 66). Fractional anisotropy (FA), radial diffusivity (RD), and spin distribution function (SDF) values indexing white matter diffusivity or spin density were calculated and compared between the groups. RESULTS In comparisons between both the bipolar groups and HC, FA (FDR < 0.00001) and RD (FDR = 0.0037) differed minimally, in localized portions of the left cingulum and corpus callosum, while reductions in SDF (FDR = 0.0002) were more widespread. The bipolar subgroups did not differ from each other on FA, RD, or SDF metrics. CONCLUSIONS Together, these results demonstrate a novel profile of white matter differences in bipolar disorder and suggest that this white matter pathology is associated with the affective disturbance common to those with bipolar disorder rather than the psychotic features unique to some. The white matter alterations identified in this study may provide substrates for future studies examining specific mechanisms that target affective domains of illness.
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Affiliation(s)
- Jennifer A Brown
- Departments of Psychology and Neuroscience, University of Georgia, Athens, GA, USA
| | - Brooke S Jackson
- Departments of Psychology and Neuroscience, University of Georgia, Athens, GA, USA
| | - Courtney R Burton
- Departments of Psychology and Neuroscience, University of Georgia, Athens, GA, USA
| | - Jennifer E Hoy
- Departments of Psychology and Neuroscience, University of Georgia, Athens, GA, USA
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Godfrey D Pearlson
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.,Institute of Living/Hartford Hospital, Hartford, CT, USA
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Hospital, Harvard Medical School, Boston, MA, USA
| | - Sarah S Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical School, Dallas, TX, USA
| | - Brett A Clementz
- Departments of Psychology and Neuroscience, University of Georgia, Athens, GA, USA
| | - Jennifer E McDowell
- Departments of Psychology and Neuroscience, University of Georgia, Athens, GA, USA
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34
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Parker DA, Trotti RL, McDowell JE, Keedy SK, Hill SK, Gershon ES, Ivleva EI, Pearlson GD, Keshavan MS, Tamminga CA, Clementz BA. Auditory Oddball Responses Across the Schizophrenia-Bipolar Spectrum and Their Relationship to Cognitive and Clinical Features. Am J Psychiatry 2021; 178:952-964. [PMID: 34407624 DOI: 10.1176/appi.ajp.2021.20071043] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE Neural activations during auditory oddball tasks may be endophenotypes for psychosis and bipolar disorder. The authors investigated oddball neural deviations that discriminate multiple diagnostic groups across the schizophrenia-bipolar spectrum (schizophrenia, schizoaffective disorder, psychotic bipolar disorder, and nonpsychotic bipolar disorder) and clarified their relationship to clinical and cognitive features. METHODS Auditory oddball responses to standard and target tones from 64 sensor EEG recordings were compared across patients with psychosis (total N=597; schizophrenia, N=225; schizoaffective disorder, N=201; bipolar disorder with psychosis, N=171), patients with bipolar disorder without psychosis (N=66), and healthy comparison subjects (N=415) from the second iteration of the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP2) study. EEG activity was analyzed in voltage and in the time-frequency domain (low, beta, and gamma bands). Event-related potentials (ERPs) were compared with those from an independent sample collected during the first iteration of B-SNIP (B-SNIP1; healthy subjects, N=211; psychosis group, N=526) to establish the repeatability of complex oddball ERPs across multiple psychosis syndromes (r values >0.94 between B-SNIP1 and B-SNIP2). RESULTS Twenty-six EEG features differentiated the groups; they were used in discriminant and correlational analyses. EEG variables from the N100, P300, and low-frequency ranges separated the groups along a diagnostic continuum from healthy to bipolar disorder with psychosis/bipolar disorder without psychosis to schizoaffective disorder/schizophrenia and were strongly related to general cognitive function (r=0.91). P50 responses to standard trials and early beta/gamma frequency responses separated the bipolar disorder without psychosis group from the bipolar disorder with psychosis group. P200, N200, and late beta/gamma frequency responses separated the two bipolar disorder groups from the other groups. CONCLUSIONS Neural deviations during auditory processing are related to psychosis history and bipolar disorder. There is a powerful transdiagnostic relationship between severity of these neural deviations and general cognitive performance. These results have implications for understanding the neurobiology of clinical syndromes across the schizophrenia-bipolar spectrum that may have an impact on future biomarker research.
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Affiliation(s)
- David A Parker
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Rebekah L Trotti
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Jennifer E McDowell
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Sarah K Keedy
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - S Kristian Hill
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Elliot S Gershon
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Elena I Ivleva
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Godfrey D Pearlson
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Matcheri S Keshavan
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Carol A Tamminga
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Brett A Clementz
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
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35
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Elad D, Cetin‐Karayumak S, Zhang F, Cho KIK, Lyall AE, Seitz‐Holland J, Ben‐Ari R, Pearlson GD, Tamminga CA, Sweeney JA, Clementz BA, Schretlen DJ, Viher PV, Stegmayer K, Walther S, Lee J, Crow TJ, James A, Voineskos AN, Buchanan RW, Szeszko PR, Malhotra AK, Keshavan MS, Shenton ME, Rathi Y, Bouix S, Sochen N, Kubicki MR, Pasternak O. Improving the predictive potential of diffusion MRI in schizophrenia using normative models-Towards subject-level classification. Hum Brain Mapp 2021; 42:4658-4670. [PMID: 34322947 PMCID: PMC8410550 DOI: 10.1002/hbm.25574] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2020] [Revised: 05/04/2021] [Accepted: 05/27/2021] [Indexed: 12/11/2022] Open
Abstract
Diffusion MRI studies consistently report group differences in white matter between individuals diagnosed with schizophrenia and healthy controls. Nevertheless, the abnormalities found at the group-level are often not observed at the individual level. Among the different approaches aiming to study white matter abnormalities at the subject level, normative modeling analysis takes a step towards subject-level predictions by identifying affected brain locations in individual subjects based on extreme deviations from a normative range. Here, we leveraged a large harmonized diffusion MRI dataset from 512 healthy controls and 601 individuals diagnosed with schizophrenia, to study whether normative modeling can improve subject-level predictions from a binary classifier. To this aim, individual deviations from a normative model of standard (fractional anisotropy) and advanced (free-water) dMRI measures, were calculated by means of age and sex-adjusted z-scores relative to control data, in 18 white matter regions. Even though larger effect sizes are found when testing for group differences in z-scores than are found with raw values (p < .001), predictions based on summary z-score measures achieved low predictive power (AUC < 0.63). Instead, we find that combining information from the different white matter tracts, while using multiple imaging measures simultaneously, improves prediction performance (the best predictor achieved AUC = 0.726). Our findings suggest that extreme deviations from a normative model are not optimal features for prediction. However, including the complete distribution of deviations across multiple imaging measures improves prediction, and could aid in subject-level classification.
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Affiliation(s)
- Doron Elad
- Department of MathematicsTel‐Aviv UniversityTel‐AvivIsrael
| | - Suheyla Cetin‐Karayumak
- Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Fan Zhang
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Kang Ik K. Cho
- Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Amanda E. Lyall
- Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Departments of Psychiatry and NeuroscienceMassachusetts General Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| | - Johanna Seitz‐Holland
- Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of PsychiatryUniversity Hospital, Ludwig Maximilian University of MunichMunichGermany
| | | | | | - Carol A. Tamminga
- Department of PsychiatryUT Southwestern Medical CenterDallasTexasUSA
| | - John A. Sweeney
- Department of Psychiatry and Behavioral NeuroscienceUniversity of CincinnatiCincinnatiOhioUSA
| | - Brett A. Clementz
- Departments of Psychology and NeuroscienceBio‐Imaging Research Center, University of GeorgiaAthensGeorgiaUSA
| | - David J. Schretlen
- Department of Psychiatry and Behavioral Sciences, Morgan Department of Radiology and Radiological ScienceJohns Hopkins Medical InstitutionsBaltimoreMarylandUSA
| | - Petra Verena Viher
- Translational Research CenterUniversity Hospital of Psychiatry, University of BernBernSwitzerland
| | - Katharina Stegmayer
- Translational Research CenterUniversity Hospital of Psychiatry, University of BernBernSwitzerland
| | - Sebastian Walther
- Translational Research CenterUniversity Hospital of Psychiatry, University of BernBernSwitzerland
| | - Jungsun Lee
- Department of PsychiatryUniversity of Ulsan College of Medicine, Asan Medical CenterSeoulSouth Korea
| | - Tim J. Crow
- Department of Psychiatry, SANE POWICWarneford Hospital, University of OxfordOxfordUK
| | - Anthony James
- Department of Psychiatry, SANE POWICWarneford Hospital, University of OxfordOxfordUK
| | - Aristotle N. Voineskos
- Centre for Addiction and Mental Health, Department of PsychiatryUniversity of TorontoTorontoCanada
| | - Robert W. Buchanan
- Maryland Psychiatric Research Center, Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Philip R. Szeszko
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Mental Illness Research, Education and Clinical CenterJames J. Peters VA Medical CenterNew YorkNew YorkUSA
| | - Anil K. Malhotra
- The Feinstein Institute for Medical Research and Zucker Hillside HospitalManhassetNew YorkUSA
| | - Matcheri S. Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical CentreHarvard Medical SchoolBostonMassachusettsUSA
| | - Martha E. Shenton
- Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Departments of Psychiatry and NeuroscienceMassachusetts General Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| | - Yogesh Rathi
- Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Sylvain Bouix
- Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Nir Sochen
- Department of MathematicsTel‐Aviv UniversityTel‐AvivIsrael
| | - Marek R. Kubicki
- Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Departments of Psychiatry and NeuroscienceMassachusetts General Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| | - Ofer Pasternak
- Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
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36
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Eskridge CLM, Hochberger WC, Kaseda ET, Lencer R, Reilly JL, Keedy SK, Keefe RSE, Pearlson GD, Keshavan MS, Tamminga CA, Sweeney JA, Hill SK. Deficits in generalized cognitive ability, visual sensorimotor function, and inhibitory control represent discrete domains of neurobehavioral deficit in psychotic disorders. Schizophr Res 2021; 236:54-60. [PMID: 34392106 PMCID: PMC8464494 DOI: 10.1016/j.schres.2021.07.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 05/06/2021] [Accepted: 07/26/2021] [Indexed: 10/20/2022]
Abstract
Psychotic disorders are characterized by impaired cognition, yet some reports indicate specific deficits extend beyond reduced general cognitive ability. This study utilized exploratory and confirmatory factor analytic methods to evaluate the latent structure of a broad neurocognitive battery used in the Bipolar-Schizophrenia Network of Intermediate Phenotypes (B-SNIP) study, which included neuropsychological and neurophysiological measures in psychotic disorder probands and their unaffected first-degree relatives. Findings indicate that the factor structure of data from this set of assessments is more complex than the unitary factor of global cognitive ability underlying the Brief Assessment of Cognition in Schizophrenia (BACS). In addition to assessing generalized cognitive ability, two other factors were identified: visual sensorimotor function and inhibitory behavioral control. This complex cognitive architecture, derived in controls, generalized to patients across the psychosis spectrum and to their unaffected relatives. These findings highlight the need for a more differentiated assessment of neurobehavioral functions in studies designed to test for diagnostically specific biomarkers, endophenotypes for gene discovery and beneficial effects of therapeutics on cognitive function.
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Affiliation(s)
- Courtney L M Eskridge
- Rosalind Franklin University of Medicine and Science, Department of Psychology, North Chicago, IL, United States.
| | - William C Hochberger
- Advanced Neurobehavioral Health of Southern California, San Diego, CA, United States
| | - Erin T Kaseda
- Rosalind Franklin University of Medicine and Science, Department of Psychology, North Chicago, IL, United States
| | - Rebekka Lencer
- University of Muenster, Department of Psychiatry and Psychotherapy, Munster, Germany
| | - James L Reilly
- Northwestern University, Department of Psychiatry and Behavioral Sciences, Chicago, IL, United States
| | - Sarah K Keedy
- University of Chicago, Department of Psychiatry, Chicago, IL, United States
| | - Richard S E Keefe
- Duke University, Departments of Psychiatry, Neuroscience, and Psychology, Durham, NC, United States
| | - Godfrey D Pearlson
- Yale University School of Medicine, Departments of Psychiatry and Neurobiology, New Haven, CT, United States
| | - Matcheri S Keshavan
- Beth Israel Deaconess Medical Center and Harvard Medical School, Department of Psychiatry, Boston, MA, United States
| | - Carol A Tamminga
- University of Texas-Southwestern University Hospital, Department of Psychiatry, Dallas, TX, United States
| | - John A Sweeney
- University of Cincinnati, Department of Psychiatry and Behavioral Neuroscience, Cincinnati, OH, United States
| | - S Kristian Hill
- Rosalind Franklin University of Medicine and Science, Department of Psychology, North Chicago, IL, United States
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37
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Xiao Y, Liao W, Long Z, Tao B, Zhao Q, Luo C, Tamminga CA, Keshavan MS, Pearlson GD, Clementz BA, Gershon ES, Ivleva EI, Keedy SK, Biswal BB, Mechelli A, Lencer R, Sweeney JA, Lui S, Gong Q. Subtyping Schizophrenia Patients Based on Patterns of Structural Brain Alterations. Schizophr Bull 2021; 48:241-250. [PMID: 34508358 PMCID: PMC8781382 DOI: 10.1093/schbul/sbab110] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Schizophrenia is a complex and heterogeneous syndrome. Whether quantitative imaging biomarkers can identify discrete subgroups of patients as might be used to foster personalized medicine approaches for patient care remains unclear. Cross-sectional structural MR images of 163 never-treated first-episode schizophrenia patients (FES) and 133 chronically ill patients with midcourse schizophrenia from the Bipolar and Schizophrenia Network for Intermediate Phenotypes (B-SNIP) consortium and a total of 403 healthy controls were recruited. Morphometric measures (cortical thickness, surface area, and subcortical structures) were extracted for each subject and then the optimized subtyping results were obtained with nonsupervised cluster analysis. Three subgroups of patients defined by distinct patterns of regional cortical and subcortical morphometric features were identified in FES. A similar three subgroup pattern was identified in the independent dataset of patients from the multi-site B-SNIP consortium. Similarities of classification patterns across these two patient cohorts suggest that the 3-group typology is relatively stable over the course of illness. Cognitive functions were worse in subgroup 1 with midcourse schizophrenia than those in subgroup 3. These findings provide novel insight into distinct subgroups of patients with schizophrenia based on structural brain features. Findings of different cognitive functions among the subgroups support clinical differences in the MRI-defined illness subtypes. Regardless of clinical presentation and stage of illness, anatomic MR subgrouping biomarkers can separate neurobiologically distinct subgroups of schizophrenia patients, which represent an important and meaningful step forward in differentiating subtypes of patients for studies of illness neurobiology and potentially for clinical trials.
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Affiliation(s)
- Yuan Xiao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China,Department of Psychiatry, University of Münster, Münster, Germany
| | - Wei Liao
- Center for Information in BioMedicine, School of Life Science and Technology, University of Electronic Science and Technology, Chengdu, Sichuan, China
| | - Zhiliang Long
- Center for Information in BioMedicine, School of Life Science and Technology, University of Electronic Science and Technology, Chengdu, Sichuan, China
| | - Bo Tao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Qiannan Zhao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Chunyan Luo
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neurobiology, Yale University and Olin Neuropsychiatric Research Center, Hartford, CT, USA
| | - Brett A Clementz
- Department of Psychology, University of Georgia, Athens, GA, USA
| | - Elliot S Gershon
- Department of Psychiatry, University of Chicago, Chicago, IL, USA
| | - Elena I Ivleva
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Sarah K Keedy
- Department of Psychiatry, University of Chicago, Chicago, IL, USA
| | - Bharat B Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
| | - Andrea Mechelli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Rebekka Lencer
- Department of Psychiatry, University of Münster, Münster, Germany
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China,To whom correspondence should be addressed; #37 GuoXue Xiang, Chengdu 610041, China; Tel: 86-28-85423960, Fax: 86-28-85423503; e-mail:
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
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38
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Eum S, Hill SK, Alliey-Rodriguez N, Stevenson JM, Rubin LH, Lee AM, Mills LJ, Reilly JL, Lencer R, Keedy SK, Ivleva E, Keefe RSE, Pearlson GD, Clementz BA, Tamminga CA, Keshavan MS, Gershon ES, Sweeney JA, Bishop JR. Genome-wide association study accounting for anticholinergic burden to examine cognitive dysfunction in psychotic disorders. Neuropsychopharmacology 2021; 46:1802-1810. [PMID: 34145405 PMCID: PMC8358015 DOI: 10.1038/s41386-021-01057-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 05/17/2021] [Accepted: 06/03/2021] [Indexed: 12/13/2022]
Abstract
Identifying genetic contributors to cognitive impairments in psychosis-spectrum disorders can advance understanding of disease pathophysiology. Although CNS medications are known to affect cognitive performance, they are often not accounted for in genetic association studies. In this study, we performed a genome-wide association study (GWAS) of global cognitive performance, measured as composite z-scores from the Brief Assessment of Cognition in Schizophrenia (BACS), in persons with psychotic disorders and controls (N = 817; 682 cases and 135 controls) from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) study. Analyses accounting for anticholinergic exposures from both psychiatric and non-psychiatric medications revealed five significantly associated variants located at the chromosome 3p21.1 locus, with the top SNP rs1076425 in the inter-alpha-trypsin inhibitor heavy chain 1 (ITIH1) gene (P = 3.25×E-9). The inclusion of anticholinergic burden improved association models (P < 0.001) and the number of significant SNPs identified. The effect sizes and direction of effect of the top variants remained consistent when investigating findings within individuals receiving specific antipsychotic drugs and after accounting for antipsychotic dose. These associations were replicated in a separate study sample of untreated first-episode psychosis. The chromosome 3p21.1 locus was previously reported to have association with the risk for psychotic disorders and cognitive performance in healthy individuals. Our findings suggest that this region may be a psychosis risk locus that is associated with cognitive mechanisms. Our data highlight the general point that the inclusion of medication exposure information may improve the detection of gene-cognition associations in psychiatric genetic research.
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Affiliation(s)
- Seenae Eum
- grid.412555.20000 0001 0511 4494Department of Pharmacogenomics, Shenandoah University, Fairfax, VA USA
| | - S. Kristian Hill
- grid.262641.50000 0004 0388 7807Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL USA
| | - Ney Alliey-Rodriguez
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL USA
| | - James M. Stevenson
- grid.21107.350000 0001 2171 9311Division of Clinical Pharmacology, Department of Medicine, Johns Hopkins University, Baltimore, MD USA
| | - Leah H. Rubin
- grid.21107.350000 0001 2171 9311Departments of Neurology, Psychiatry, and Epidemiology, Johns Hopkins University, Baltimore, MD USA
| | - Adam M. Lee
- grid.17635.360000000419368657Department of Experimental and Clinical Pharmacology, University of Minnesota, Minneapolis, MN USA
| | - Lauren J. Mills
- grid.17635.360000000419368657Masonic Cancer Center and Department of Pediatrics, University of Minnesota, Minneapolis, MN USA
| | - James L. Reilly
- grid.16753.360000 0001 2299 3507Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL USA
| | - Rebekka Lencer
- grid.5949.10000 0001 2172 9288Institute of Translational Psychiatry and Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Muenster, Muenster, Germany ,grid.4562.50000 0001 0057 2672Department of Psychiatry and Psychotherapy, University of Luebeck, Luebeck, Germany
| | - Sarah K. Keedy
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL USA
| | - Elena Ivleva
- grid.267313.20000 0000 9482 7121Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX USA
| | - Richard S. E. Keefe
- grid.26009.3d0000 0004 1936 7961Department of Psychiatry, Duke University School of Medicine, Durham, NC USA
| | - Godfrey D. Pearlson
- grid.277313.30000 0001 0626 2712Departments of Psychiatry and Neuroscience, Yale School of Medicine, Olin Center, Institute of Living, Hartford Healthcare, Hartford, CT USA
| | - Brett A. Clementz
- grid.213876.90000 0004 1936 738XDepartment of Psychology, University of Georgia, Athens, GA USA
| | - Carol A. Tamminga
- grid.267313.20000 0000 9482 7121Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX USA
| | - Matcheri S. Keshavan
- grid.239395.70000 0000 9011 8547Beth Israel Deaconess Medical Center, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Psychiatry, Harvard Medical School, Boston, MA USA
| | - Elliot S. Gershon
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL USA
| | - John A. Sweeney
- grid.413561.40000 0000 9881 9161Department of Psychiatry, University of Cincinnati Medical Center, Cincinnati, OH USA
| | - Jeffrey R. Bishop
- grid.17635.360000000419368657Department of Experimental and Clinical Pharmacology, University of Minnesota, Minneapolis, MN USA ,grid.17635.360000000419368657Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN USA
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39
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Seitz-Holland J, Cetin-Karayumak S, Wojcik JD, Lyall A, Levitt J, Shenton ME, Pasternak O, Westin CF, Baxi M, Kelly S, Mesholam-Gately R, Vangel M, Pearlson G, Tamminga CA, Sweeney JA, Clementz BA, Schretlen D, Viher PV, Stegmayer K, Walther S, Lee J, Crow T, James A, Voineskos A, Buchanan RW, Szeszko PR, Malhotra AK, Rathi Y, Keshavan M, Kubicki M. Elucidating the relationship between white matter structure, demographic, and clinical variables in schizophrenia-a multicenter harmonized diffusion tensor imaging study. Mol Psychiatry 2021; 26:5357-5370. [PMID: 33483689 PMCID: PMC8329919 DOI: 10.1038/s41380-021-01018-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 11/24/2020] [Accepted: 01/05/2021] [Indexed: 01/30/2023]
Abstract
White matter (WM) abnormalities are repeatedly demonstrated across the schizophrenia time-course. However, our understanding of how demographic and clinical variables interact, influence, or are dependent on WM pathologies is limited. The most well-known barriers to progress are heterogeneous findings due to small sample sizes and the confounding influence of age on WM. The present study leverages access to the harmonized diffusion magnetic-resonance-imaging data and standardized clinical data from 13 international sites (597 schizophrenia patients (SCZ)). Fractional anisotropy (FA) values for all major WM structures in patients were predicted based on FA models estimated from a healthy population (n = 492). We utilized the deviations between predicted and real FA values to answer three essential questions. (1) "Which clinical variables explain WM abnormalities?". (2) "Does the degree of WM abnormalities predict symptom severity?". (3) "Does sex influence any of those relationships?". Regression and mediator analyses revealed that a longer duration-of-illness is associated with more severe WM abnormalities in several tracts. In addition, they demonstrated that a higher antipsychotic medication dose is related to more severe corpus callosum abnormalities. A structural equation model revealed that patients with more WM abnormalities display higher symptom severity. Last, the results exhibited sex-specificity. Males showed a stronger association between duration-of-illness and WM abnormalities. Females presented a stronger association between WM abnormalities and symptom severity, with IQ impacting this relationship. Our findings provide clear evidence for the interaction of demographic, clinical, and behavioral variables with WM pathology in SCZ. Our results also point to the need for longitudinal studies, directly investigating the casualty and sex-specificity of these relationships, as well as the impact of cognitive resiliency on structure-function relationships.
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Affiliation(s)
- Johanna Seitz-Holland
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Suheyla Cetin-Karayumak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Joanne D Wojcik
- Department of Psychiatry, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA
| | - Amanda Lyall
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - James Levitt
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Brockton, MA, USA
| | - Martha E Shenton
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Brockton, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Carl-Fredrik Westin
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Madhura Baxi
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Graduate Program of Neuroscience, Boston University, Boston, MA, USA
| | - Sinead Kelly
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA
| | - Raquelle Mesholam-Gately
- Department of Psychiatry, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA
| | - Mark Vangel
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Brett A Clementz
- Department of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA, USA
| | - David Schretlen
- Department of Psychiatry and Behavioral Sciences, Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institutions, Baltimore, MD, USA
| | - Petra Verena Viher
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Katharina Stegmayer
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Sebastian Walther
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Jungsun Lee
- Department of Psychiatry, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Tim Crow
- Department of Psychiatry, SANE POWIC, Warneford Hospital, University of Oxford, Oxford, UK
| | - Anthony James
- Department of Psychiatry, SANE POWIC, Warneford Hospital, University of Oxford, Oxford, UK
| | - Aristotle Voineskos
- Center for Addiction and Mental Health, Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Robert W Buchanan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Philip R Szeszko
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research, Education and Clinical Center, James J. Peters VA Medical Center, Bronx, New York, NY, USA
| | - Anil K Malhotra
- The Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Yogesh Rathi
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Matcheri Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA
| | - Marek Kubicki
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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40
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Trotti RL, Abdelmageed S, Parker DA, Sabatinelli D, Tamminga CA, Gershon ES, Keedy SK, Keshavan MS, Pearlson GD, Sweeney JA, McDowell JE, Clementz BA. Neural Processing of Repeated Emotional Scenes in Schizophrenia, Schizoaffective Disorder, and Bipolar Disorder. Schizophr Bull 2021; 47:1473-1481. [PMID: 33693875 PMCID: PMC8379546 DOI: 10.1093/schbul/sbab018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Impaired emotional processing and cognitive functioning are common in schizophrenia, schizoaffective disorder, and bipolar disorders, causing significant socioemotional disability. While a large body of research demonstrates abnormal cognition/emotion interactions in these disorders, previous studies investigating abnormalities in the emotional scene response using event-related potentials (ERPs) have yielded mixed findings, and few studies compare findings across psychiatric diagnoses. The current study investigates the effects of emotion and repetition on ERPs in a large, well-characterized sample of participants with schizophrenia-bipolar syndromes. Two ERP components that are modulated by emotional content and scene repetition, the early posterior negativity (EPN) and late positive potential (LPP), were recorded in healthy controls and participants with schizophrenia, schizoaffective disorder, bipolar disorder with psychosis, and bipolar disorder without psychosis. Effects of emotion and repetition were compared across groups. Results displayed significant but small effects in schizophrenia and schizoaffective disorder, with diminished EPN amplitudes to neutral and novel scenes, reduced LPP amplitudes to emotional scenes, and attenuated effects of scene repetition. Despite significant findings, small effect sizes indicate that emotional scene processing is predominantly intact in these disorders. Multivariate analyses indicate that these mild ERP abnormalities are related to cognition, psychosocial functioning, and psychosis severity. This relationship suggests that impaired cognition, rather than diagnosis or mood disturbance, may underlie disrupted neural scene processing in schizophrenia-bipolar syndromes.
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Affiliation(s)
- Rebekah L Trotti
- Department of Psychology, University of Georgia, 613 Psychology Building, 125 Baldwin St., Athens, GA 30602, USA
| | - Sunny Abdelmageed
- Department of Psychology, University of Georgia, 613 Psychology Building, 125 Baldwin St., Athens, GA 30602, USA
| | - David A Parker
- Department of Psychology, University of Georgia, 613 Psychology Building, 125 Baldwin St., Athens, GA 30602, USA
| | - Dean Sabatinelli
- Department of Psychology, University of Georgia, 613 Psychology Building, 125 Baldwin St., Athens, GA 30602, USA
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Sarah K Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | | | | | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Jennifer E McDowell
- Department of Psychology, University of Georgia, 613 Psychology Building, 125 Baldwin St., Athens, GA 30602, USA
| | - Brett A Clementz
- Department of Psychology, University of Georgia, 613 Psychology Building, 125 Baldwin St., Athens, GA 30602, USA
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41
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Türközer HB, Ivleva EI, Palka J, Clementz BA, Shafee R, Pearlson GD, Sweeney JA, Keshavan MS, Gershon ES, Tamminga CA. Biomarker Profiles in Psychosis Risk Groups Within Unaffected Relatives Based on Familiality and Age. Schizophr Bull 2021; 47:1058-1067. [PMID: 33693883 PMCID: PMC8266584 DOI: 10.1093/schbul/sbab013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Investigating biomarkers in unaffected relatives (UR) of individuals with psychotic disorders has already proven productive in research on psychosis neurobiology. However, there is considerable heterogeneity among UR based on features linked to psychosis vulnerability. Here, using the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) dataset, we examined cognitive and neurophysiologic biomarkers in first-degree UR of psychosis probands, stratified by 2 widely used risk factors: familiality status of the respective proband (the presence or absence of a first- or second-degree relative with a history of psychotic disorder) and age (within or older than the common age range for developing psychosis). We investigated biomarkers that best differentiate the above specific risk subgroups. Additionally, we examined the relationship of biomarkers with Polygenic Risk Scores for Schizophrenia (PRSSCZ) in a subsample of Caucasian probands and healthy controls (HC). Our results demonstrate that the Brief Assessment of Cognition in Schizophrenia (BACS) score, antisaccade error (ASE) factor, and stop-signal task (SST) factor best differentiate UR (n = 169) from HC (n = 137) (P = .013). Biomarker profiles of UR of familial (n = 82) and non-familial (n = 83) probands were not significantly different. Furthermore, ASE and SST factors best differentiated younger UR (age ≤ 30) (n = 59) from older UR (n = 110) and HC from both age groups (age ≤ 30 years, n=49; age > 30 years, n = 88) (P < .001). In addition, BACS (r = -0.175, P = .006) and ASE factor (r = 0.188, P = .006) showed associations with PRSSCZ. Taken together, our findings indicate that cognitive biomarkers-"top-down inhibition" impairments in particular-may be of critical importance as indicators of psychosis vulnerability.
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Affiliation(s)
- Halide Bilge Türközer
- Department of Psychiatry, the University of Texas Southwestern Medical Center, Dallas, TX
| | - Elena I Ivleva
- Department of Psychiatry, the University of Texas Southwestern Medical Center, Dallas, TX
| | - Jayme Palka
- Department of Psychiatry, the University of Texas Southwestern Medical Center, Dallas, TX
| | - Brett A Clementz
- Department of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA
| | - Rebecca Shafee
- Department of Genetics, Harvard Medical School, Boston, MA
| | - Godfrey D Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT
- Departments of Psychiatry and Neuroscience, Yale University, New Haven, CT
| | - John A Sweeney
- Department of Psychiatry, the University of Texas Southwestern Medical Center, Dallas, TX
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH
| | - Matcheri S Keshavan
- Department of Psychiatry and Cognitive Neurology, Beth Israel Deaconess Medical Center, Boston, MA
- Harvard Medical School, Boston, MA
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL
| | - Carol A Tamminga
- Department of Psychiatry, the University of Texas Southwestern Medical Center, Dallas, TX
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42
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Lizano P, Lutz O, Xu Y, Rubin LH, Paskowitz L, Lee AM, Eum S, Keedy SK, Hill SK, Reilly JL, Wu B, Tamminga CA, Clementz BA, Pearlson GD, Gershon ES, Keshavan MS, Sweeney JA, Bishop JR. Multivariate relationships between peripheral inflammatory marker subtypes and cognitive and brain structural measures in psychosis. Mol Psychiatry 2021; 26:3430-3443. [PMID: 33060818 PMCID: PMC8046847 DOI: 10.1038/s41380-020-00914-0] [Citation(s) in RCA: 69] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 10/02/2020] [Indexed: 12/19/2022]
Abstract
Elevations in peripheral inflammatory markers have been reported in patients with psychosis. Whether this represents an inflammatory process defined by individual or subgroups of markers is unclear. Further, relationships between peripheral inflammatory marker elevations and brain structure, cognition, and clinical features of psychosis remain unclear. We hypothesized that a pattern of plasma inflammatory markers, and an inflammatory subtype established from this pattern, would be elevated across the psychosis spectrum and associated with cognition and brain structural alterations. Clinically stable psychosis probands (Schizophrenia spectrum, n = 79; Psychotic Bipolar disorder, n = 61) and matched healthy controls (HC, n = 60) were assessed for 15 peripheral inflammatory markers, cortical thickness, subcortical volume, cognition, and symptoms. A combination of unsupervised exploratory factor analysis and hierarchical clustering was used to identify inflammation subtypes. Levels of IL6, TNFα, VEGF, and CRP were significantly higher in psychosis probands compared to HCs, and there were marker-specific differences when comparing diagnostic groups. Individual and/or inflammatory marker patterns were associated with neuroimaging, cognition, and symptom measures. A higher inflammation subgroup was defined by elevations in a group of 7 markers in 36% of Probands and 20% of HCs. Probands in the elevated inflammatory marker group performed significantly worse on cognitive measures of visuo-spatial working memory and response inhibition, displayed elevated hippocampal, amygdala, putamen and thalamus volumes, and evidence of gray matter thickening compared to the proband group with low inflammatory marker levels. These findings specify the nature of peripheral inflammatory marker alterations in psychotic disorders and establish clinical, neurocognitive and neuroanatomic associations with increased inflammatory activation in psychosis. The identification of a specific subgroup of patients with inflammatory alteration provides a potential means for targeting treatment with anti-inflammatory medications.
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Affiliation(s)
- Paulo Lizano
- Beth Israel Deaconess Medical Center, Boston, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
| | - Olivia Lutz
- Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Yanxun Xu
- Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA
| | - Leah H Rubin
- Department of Neurology, Psychiatry, and Epidemiology, Johns Hopkins University, Baltimore, MD, USA
| | - Lyle Paskowitz
- Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA
| | - Adam M Lee
- Department of Experimental and Clinical Pharmacology and Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Seenae Eum
- School of Pharmacy, Shenandoah University, Winchester, Virginia, USA
| | - Sarah K Keedy
- Department of Psychiatry and Behavioral Neurosciences, University of Chicago, Chicago, IL, USA
| | - S Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL, USA
| | - James L Reilly
- Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL, USA
| | - Baolin Wu
- Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA
| | - Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - Brett A Clementz
- Department of Psychology, University of Georgia, Athens, GA, USA
| | | | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neurosciences, University of Chicago, Chicago, IL, USA
| | - Matcheri S Keshavan
- Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - John A Sweeney
- Deptartment of Psychiatry, University of Cincinnati Medical Center, Cincinnati, OH, USA
| | - Jeffrey R Bishop
- Department of Experimental and Clinical Pharmacology and Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA.
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43
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Asif H, Alliey-Rodriguez N, Keedy S, Tamminga CA, Sweeney JA, Pearlson G, Clementz BA, Keshavan MS, Buckley P, Liu C, Neale B, Gershon ES. GWAS significance thresholds for deep phenotyping studies can depend upon minor allele frequencies and sample size. Mol Psychiatry 2021; 26:2048-2055. [PMID: 32066829 PMCID: PMC7429341 DOI: 10.1038/s41380-020-0670-3] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Revised: 01/28/2020] [Accepted: 01/29/2020] [Indexed: 02/01/2023]
Abstract
An important issue affecting genome-wide association studies with deep phenotyping (multiple correlated phenotypes) is determining the suitable family-wise significance threshold. Straightforward family-wise correction (Bonferroni) of p < 0.05 for 4.3 million genotypes and 335 phenotypes would give a threshold of p < 3.46E-11. This would be too conservative because it assumes all tests are independent. The effective number of tests, both phenotypic and genotypic, must be adjusted for the correlations between them. Spectral decomposition of the phenotype matrix and LD-based correction of the number of tested SNPs are currently used to determine an effective number of tests. In this paper, we compare these calculated estimates with permutation-determined family-wise significance thresholds. Permutations are performed by shuffling individual IDs of the genotype vector for this dataset, to preserve correlation of phenotypes. Our results demonstrate that the permutation threshold is influenced by minor allele frequency (MAF) of the SNPs, and by the number of individuals tested. For the more common SNPs (MAF > 0.1), the permutation family-wise threshold was in close agreement with spectral decomposition methods. However, for less common SNPs (0.05 < MAF ≤ 0.1), the permutation threshold calculated over all SNPs was off by orders of magnitude. This applies to the number of individuals studied (here 777) but not to very much larger numbers. Based on these findings, we propose that the threshold to find a particular level of family-wise significance may need to be established using separate permutations of the actual data for several MAF bins.
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Affiliation(s)
- Huma Asif
- Department of Psychiatry and Behavioral Neurosciences, University of Chicago, 924 East 57th Street Room. R016, Chicago, IL, 60637, USA.
| | - Ney Alliey-Rodriguez
- Department of Psychiatry and Behavioral Neurosciences, University of Chicago, 924 East 57th Street Room. R016, Chicago, IL, 60637, USA
| | - Sarah Keedy
- Department of Psychiatry and Behavioral Neurosciences, University of Chicago, 924 East 57th Street Room. R016, Chicago, IL, 60637, USA
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - John A Sweeney
- Department of Psychiatry, University of Cincinnati, Cincinnati, OH, USA
| | - Godfrey Pearlson
- Departments of Psychiatry & Neuroscience, Yale University, New Haven, CT, USA
| | - Brett A Clementz
- Department of Psychology, University of Georgia, Athens, GA, USA
| | | | | | - Chunyu Liu
- Department of Psychiatry, SUNY Upstate Medical University, Binghamton, NY, USA
| | | | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neurosciences, University of Chicago, 924 East 57th Street Room. R016, Chicago, IL, 60637, USA. .,Department of Human Genetics, University of Chicago, 924 East 57th Street Room. R016, Chicago, IL, 60637, USA.
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44
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Anderson MP, Quinton R, Kelly K, Falzon A, Halladay A, Schumann CM, Hof PR, Tamminga CA, Hare CK, Amaral DG. Autism BrainNet: A Collaboration Between Medical Examiners, Pathologists, Researchers, and Families to Advance the Understanding and Treatment of Autism Spectrum Disorder. Arch Pathol Lab Med 2021; 145:494-501. [PMID: 32960953 DOI: 10.5858/arpa.2020-0164-ra] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/18/2020] [Indexed: 11/06/2022]
Abstract
CONTEXT.— Autism spectrum disorder is a neurodevelopmental condition that affects over 1% of the population worldwide. Developing effective preventions and treatments for autism will depend on understanding the neuropathology of the disorder. While evidence from magnetic resonance imaging indicates altered development of the autistic brain, it lacks the resolution needed to identify the cellular and molecular underpinnings of the disorder. Postmortem studies of human brain tissue currently represent the only viable option to pursuing these critical studies. Historically, the availability of autism brain tissue has been extremely limited. OBJECTIVE.— To overcome this limitation, Autism BrainNet, funded by the Simons Foundation, was formed as a network of brain collection sites that work in a coordinated fashion to develop a library of human postmortem brain tissues for distribution to researchers worldwide. Autism BrainNet has collection sites (or Nodes) in California, Texas, and Massachusetts; affiliated, international Nodes are located in Oxford, England and Montreal, Quebec, Canada. DATA SOURCES.— Pubmed, Autism BrainNet. CONCLUSIONS.— Because the death of autistic individuals is often because of an accident, drowning, suicide, or sudden unexpected death in epilepsy, they often are seen in a medical examiner's or coroner's office. Yet, autism is rarely considered when evaluating the cause of death. Advances in our understanding of chronic traumatic encephalopathy have occurred because medical examiners and neuropathologists questioned whether a pathologic change might exist in individuals who played contact sports and later developed severe behavioral problems. This article highlights the potential for equally significant breakthroughs in autism arising from the proactive efforts of medical examiners, pathologists, and coroners in partnership with Autism BrainNet.
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Affiliation(s)
- Matthew P Anderson
- From the Departments of Neurology and Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts (Anderson)
| | - Reade Quinton
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota (Quinton)
| | - Karen Kelly
- Department of Pathology and Laboratory Medicine, Brody School of Medicine at East Carolina University Greenville, North Carolina (Kelly)
| | - Andrew Falzon
- Office of the Chief State Medical Examiner, Trenton, New Jersey (Falzon)
| | - Alycia Halladay
- Autism Science Foundation, New York, New York (Halladay).,Department of Pharmacology and Toxicology, Rutgers University, Piscataway, New Jersey (Halladay)
| | - Cynthia M Schumann
- The MIND Institute, University of California at Davis, Sacramento (Schumann and Amaral)
| | - Patrick R Hof
- Nash Family Department of Neuroscience, Friedman Brain Institute, and Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, New York (Hof)
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas (Tamminga)
| | | | - David G Amaral
- The MIND Institute, University of California at Davis, Sacramento (Schumann and Amaral)
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45
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Kelly S, Guimond S, Pasternak O, Lutz O, Lizano P, Cetin-Karayumak S, Sweeney JA, Pearlson G, Clementz BA, McDowell JE, Tamminga CA, Shenton ME, Keshavan MS. White matter microstructure across brain-based biotypes for psychosis - findings from the bipolar-schizophrenia network for intermediate phenotypes. Psychiatry Res Neuroimaging 2021; 308:111234. [PMID: 33385763 DOI: 10.1016/j.pscychresns.2020.111234] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 10/22/2020] [Accepted: 12/01/2020] [Indexed: 12/14/2022]
Abstract
The B-SNIP consortium identified three brain-based Biotypes across the psychosis spectrum, independent of clinical phenomenology. To externally validate the Biotype model, we used free-water fractional volume (FW) and free-water corrected fractional anisotropy (FAT) to compare white matter differences across Biotypes and clinical diagnoses. Diffusion tensor imaging data from 167 individuals were included: 41 healthy controls, 55 schizophrenia probands, 47 schizoaffective disorder probands, and 24 probands with psychotic bipolar disorder. Compared to healthy controls, FAt reductions were observed in the body of corpus callosum (BCC) for schizoaffective disorder (d = 0.91) and schizophrenia (d = 0.64). Grouping by Biotype, Biotype 1 showed FAt reductions in the CC and fornix, with largest effect in the BCC (d = 0.87). Biotype 2 showed significant FAt reductions in the BCC (d = 0.90). Schizoaffective disorder individuals had elevated FW in the CC, fornix and anterior corona radiata (ACR), with largest effect in the BCC (d = 0.79). Biotype 2 showed elevated FW in the CC, fornix and ACR, with largest effect in the BCC (d = 0.94). While significant diagnosis comparisons were observed, overall greater discrimination from healthy controls was observed for lower FAt in Biotype 1 and elevated FW in Biotype 2. However, between-group differences were modest, with one region (cerebral peduncle) showing a between-Biotype effect. No between-group effects were observed for diagnosis groupings.
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Affiliation(s)
- Sinead Kelly
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, United States; Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, United States.
| | - Synthia Guimond
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, United States; Department of Psychiatry, The Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON K1Z 7K4, Canada
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - Olivia Lutz
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, United States
| | - Paulo Lizano
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, United States
| | - Suheyla Cetin-Karayumak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - John A Sweeney
- Department of Psychiatry, University of Cincinnati, Cincinnati, OH 45221, United States
| | - Godfrey Pearlson
- Department of Psychiatry, Yale University, New Haven, CT 06520, United States
| | - Brett A Clementz
- Department of Psychology, University of Georgia, Athens, GA 30602, United States
| | - Jennifer E McDowell
- Department of Psychology, University of Georgia, Athens, GA 30602, United States
| | - Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX 75390, United States
| | - Martha E Shenton
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, United States; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, United States
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46
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Frässle S, Harrison SJ, Heinzle J, Clementz BA, Tamminga CA, Sweeney JA, Gershon ES, Keshavan MS, Pearlson GD, Powers A, Stephan KE. Regression dynamic causal modeling for resting-state fMRI. Hum Brain Mapp 2021; 42:2159-2180. [PMID: 33539625 PMCID: PMC8046067 DOI: 10.1002/hbm.25357] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 01/05/2021] [Accepted: 01/20/2021] [Indexed: 02/03/2023] Open
Abstract
“Resting‐state” functional magnetic resonance imaging (rs‐fMRI) is widely used to study brain connectivity. So far, researchers have been restricted to measures of functional connectivity that are computationally efficient but undirected, or to effective connectivity estimates that are directed but limited to small networks. Here, we show that a method recently developed for task‐fMRI—regression dynamic causal modeling (rDCM)—extends to rs‐fMRI and offers both directional estimates and scalability to whole‐brain networks. First, simulations demonstrate that rDCM faithfully recovers parameter values over a wide range of signal‐to‐noise ratios and repetition times. Second, we test construct validity of rDCM in relation to an established model of effective connectivity, spectral DCM. Using rs‐fMRI data from nearly 200 healthy participants, rDCM produces biologically plausible results consistent with estimates by spectral DCM. Importantly, rDCM is computationally highly efficient, reconstructing whole‐brain networks (>200 areas) within minutes on standard hardware. This opens promising new avenues for connectomics.
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Affiliation(s)
- Stefan Frässle
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Zurich, Switzerland
| | - Samuel J Harrison
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Zurich, Switzerland
| | - Jakob Heinzle
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Zurich, Switzerland
| | - Brett A Clementz
- Department of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, Georgia, USA
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - John A Sweeney
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Elliot S Gershon
- Department of Psychiatry, University of Chicago, Chicago, Illinois, USA.,Department of Human Genetics, University of Chicago, Chicago, Illinois, USA
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Godfrey D Pearlson
- Olin Neuropsychiatry Research Center, Hartford Hospital, Institute of Living, Hartford, Connecticut, USA.,Department of Psychiatry & Neuroscience, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Albert Powers
- Department of Psychiatry & Neuroscience, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Klaas E Stephan
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Zurich, Switzerland.,Max Planck Institute for Metabolism Research, Cologne, Germany
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47
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Zhu X, Zhou B, Pattni R, Gleason K, Tan C, Kalinowski A, Sloan S, Fiston-Lavier AS, Mariani J, Petrov D, Barres BA, Duncan L, Abyzov A, Vogel H, Moran JV, Vaccarino FM, Tamminga CA, Levinson DF, Urban AE. Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia. Nat Neurosci 2021; 24:186-196. [PMID: 33432196 PMCID: PMC8806165 DOI: 10.1038/s41593-020-00767-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Accepted: 11/21/2020] [Indexed: 02/06/2023]
Abstract
Retrotransposons can cause somatic genome variation in the human nervous system, which is hypothesized to have relevance to brain development and neuropsychiatric disease. However, the detection of individual somatic mobile element insertions presents a difficult signal-to-noise problem. Using a machine-learning method (RetroSom) and deep whole-genome sequencing, we analyzed L1 and Alu retrotransposition in sorted neurons and glia from human brains. We characterized two brain-specific L1 insertions in neurons and glia from a donor with schizophrenia. There was anatomical distribution of the L1 insertions in neurons and glia across both hemispheres, indicating retrotransposition occurred during early embryogenesis. Both insertions were within the introns of genes (CNNM2 and FRMD4A) inside genomic loci associated with neuropsychiatric disorders. Proof-of-principle experiments revealed these L1 insertions significantly reduced gene expression. These results demonstrate that RetroSom has broad applications for studies of brain development and may provide insight into the possible pathological effects of somatic retrotransposition.
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Affiliation(s)
- Xiaowei Zhu
- Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA, USA
- Department of Genetics, Stanford University, Palo Alto, CA, USA
| | - Bo Zhou
- Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA, USA
- Department of Genetics, Stanford University, Palo Alto, CA, USA
| | - Reenal Pattni
- Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA, USA
- Department of Genetics, Stanford University, Palo Alto, CA, USA
| | - Kelly Gleason
- Division of Translational Research in Schizophrenia, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Chunfeng Tan
- Division of Translational Research in Schizophrenia, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Agnieszka Kalinowski
- Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA, USA
| | - Steven Sloan
- Department of Human Genetics, Emory University, Atlanta, GA, USA
| | - Anna-Sophie Fiston-Lavier
- Institut des Sciences de l'Evolution de Montpellier (UMR 5554, CNRS-UM-IRD-EPHE), Université de Montpellier, Montpellier, France
| | | | - Dmitri Petrov
- Department of Biology, Stanford University, Palo Alto, CA, USA
| | - Ben A Barres
- Department of Neurobiology, Stanford University, Palo Alto, CA, USA
| | - Laramie Duncan
- Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA, USA
| | - Alexej Abyzov
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Hannes Vogel
- Department of Pathology, Stanford University, Palo Alto, CA, USA
| | - John V Moran
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Flora M Vaccarino
- Child Study Center, Yale University, New Haven, CT, USA
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Carol A Tamminga
- Division of Translational Research in Schizophrenia, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Douglas F Levinson
- Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA, USA
| | - Alexander E Urban
- Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA, USA.
- Department of Genetics, Stanford University, Palo Alto, CA, USA.
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48
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Martin-Cook K, Palmer L, Thornton L, Rush AJ, Tamminga CA, Ibrahim HM. Setting Measurement-Based Care in Motion: Practical Lessons in the Implementation and Integration of Measurement-Based Care in Psychiatry Clinical Practice. Neuropsychiatr Dis Treat 2021; 17:1621-1631. [PMID: 34079260 PMCID: PMC8164712 DOI: 10.2147/ndt.s308615] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 04/13/2021] [Indexed: 01/18/2023] Open
Abstract
Measurement-based care (MBC) involves the systematic use of standardized measurements to inform treatment decisions. MBC can enhance clinical decision-making and quality of care by prompting personalized changes in treatment based on measured patient outcomes. MBC can also promote more precise communications between patients and clinicians around individual patient care. While commonly employed in psychiatric clinical research, the use of MBC in everyday practice can be complicated by clinic operations and variability across patients. We implemented MBC in the UT Southwestern Psychiatry Multispecialty Outpatient Clinic during the expansion of our general psychiatry clinic and subspecialty targeted programs. This article describes the top 10 lessons we learned as we confronted practical obstacles around implementing the ideals of MBC into a pre-existing, busy psychiatric clinical practice and how doing so impacts care, provider engagement, patient engagement, and research opportunity.
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Affiliation(s)
- Kristin Martin-Cook
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Lucy Palmer
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Larry Thornton
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - A John Rush
- National University of Singapore, Singapore; Department of Psychiatry, Duke University School of Medicine, Durham, NC, USA; Department of Psychiatry, Texas Tech Health Sciences Center, Midland, TX, USA
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Hicham M Ibrahim
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
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Tamminga CA, Clementz BA, Pearlson G, Keshavan M, Gershon ES, Ivleva EI, McDowell J, Meda SA, Keedy S, Calhoun VD, Lizano P, Bishop JR, Hudgens-Haney M, Alliey-Rodriguez N, Asif H, Gibbons R. Biotyping in psychosis: using multiple computational approaches with one data set. Neuropsychopharmacology 2021; 46:143-155. [PMID: 32979849 PMCID: PMC7689458 DOI: 10.1038/s41386-020-00849-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 08/24/2020] [Accepted: 08/26/2020] [Indexed: 12/15/2022]
Abstract
Focusing on biomarker identification and using biomarkers individually or in clusters to define biological subgroups in psychiatry requires a re-orientation from behavioral phenomenology to quantifying brain features, requiring big data approaches for data integration. Much still needs to be accomplished, not only to refine but also to build support for the application and customization of such an analytical phenotypic approach. In this review, we present some of what Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) has learned so far to guide future applications of multivariate phenotyping and their analyses to understanding psychosis. This paper describes several B-SNIP projects that use phenotype data and big data computations to generate novel outcomes and glimpse what phenotypes contribute to disease understanding and, with aspiration, to treatment. The source of the phenotypes varies from genetic data, structural neuroanatomic localization, immune markers, brain physiology, and cognition. We aim to see guiding principles emerge and areas of commonality revealed. And, we will need to demonstrate not only data stability but also the usefulness of biomarker information for subgroup identification enhancing target identification and treatment development.
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Affiliation(s)
- Carol A. Tamminga
- grid.267313.20000 0000 9482 7121Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX 75390 USA
| | - Brett A. Clementz
- grid.213876.90000 0004 1936 738XDepartments of Psychology, Neuroscience, and BioImaging Research Center, University of Georgia, Athens, GA 30602 USA
| | - Godfrey Pearlson
- grid.277313.30000 0001 0626 2712Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT USA ,grid.47100.320000000419368710Departments of Psychiatry & Neuroscience, Yale University, New Haven, CT USA
| | - Macheri Keshavan
- grid.239395.70000 0000 9011 8547Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, United States
| | - Elliot S. Gershon
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL 60637 USA
| | - Elena I. Ivleva
- grid.267313.20000 0000 9482 7121Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX 75390 USA
| | - Jennifer McDowell
- grid.213876.90000 0004 1936 738XDepartments of Psychology, Neuroscience, and BioImaging Research Center, University of Georgia, Athens, GA 30602 USA
| | - Shashwath A. Meda
- grid.277313.30000 0001 0626 2712Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT USA ,grid.47100.320000000419368710Departments of Psychiatry & Neuroscience, Yale University, New Haven, CT USA
| | - Sarah Keedy
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL 60637 USA
| | - Vince D. Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia USA
| | - Paulo Lizano
- grid.239395.70000 0000 9011 8547Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, United States
| | - Jeffrey R. Bishop
- grid.17635.360000000419368657Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, United States ,grid.17635.360000000419368657Department of Psychiatry, University of Minnesota Medical School, Minneapolis, MN 55455 USA
| | - Matthew Hudgens-Haney
- grid.267313.20000 0000 9482 7121Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX 75390 USA
| | - Ney Alliey-Rodriguez
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL 60637 USA
| | - Huma Asif
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL 60637 USA
| | - Robert Gibbons
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL 60637 USA ,grid.170205.10000 0004 1936 7822Departments of Medicine and Public Health Sciences, University of Chicago, Chicago, Ill USA
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50
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Parker DA, Trotti RL, McDowell JE, Keedy SK, Gershon ES, Ivleva EI, Pearlson GD, Keshavan MS, Tamminga CA, Sweeney JA, Clementz BA. Auditory paired-stimuli responses across the psychosis and bipolar spectrum and their relationship to clinical features. Biomark Neuropsychiatry 2020; 3:100014. [PMID: 36644018 PMCID: PMC9837793 DOI: 10.1016/j.bionps.2020.100014] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
Background EEG responses during auditory paired-stimuli paradigms are putative biomarkers of psychosis syndromes. The initial iteration of the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP1) showed unique and common patterns of abnormalities across schizophrenia (SZ), schizoaffective disorder (SAD), and bipolar disorder with psychosis (BDP). This study replicates those findings in new and large samples of psychosis cases and extends them to an important comparison group, bipolar disorder without psychosis (BDNP). Methods Paired stimuli responses from 64-sensor EEG recording were compared across psychosis (n = 597; SZ = 225, SAD = 201, BDP = 171), BDNP (n = 66), and healthy (n = 415) subjects from the second iteration of B-SNIP. EEG activity was analyzed in voltage and in the time-frequency domain. Principal component analysis (PCA) over sensors (sPCA) was used to efficiently capture EEG voltage responses to the paired stimuli. Evoked power was calculated via a Morlet wavelet procedure. A frequency PCA divided evoked power data into three frequency bands: Low (4-17 Hz), Beta (18-32 Hz), and Gamma (33-55 Hz). Each time-course (ERP Voltage, Low, Beta, and Gamma) were then segmented into 20 ms bins and analyzed for group differences. To efficiently summarize the multiple EEG components that best captured group differences we used multivariate discriminant and correlational analyses. This approach yields a reduced set of measures that may be useful in subsequent biomarker investigations. Results Group ANOVAs identified 17 time-ranges that showed significant group differences (p < .05 after FDR correction), constructively replicating B-SNIP1 findings. Multivariate linear discriminant analysis parsimoniously selected variables that best accounted for group differences: The P50 response to S1 and S2 uniquely separated BDNP from healthy and psychosis subjects (BDNP > all other groups); the S1 N100 response separated groups along an axis of psychopathology severity (HC > BDNP > BDP > SAD > SZ); the S1 P200 response indexed psychosis psychopathology (HC/BDNP > SAD/SZ/BDP); and the preparatory period to the S2 stimulus separated SZ from other groups (SZ > SAD/BDP>HC/BDNP).Canonical correlation identified an association between the neural responses during the S1 N100, S1 N200 and S2 preparatory period and PANSS positive symptoms and social functioning. The neural responses during the S1 P50 and S1 N100 were associated with PANSS Negative/General, MADRS and Young Mania symptoms. Conclusions This study constructively replicated prior B-SNIP1 research on auditory deviations observed during the paired stimuli task in SZ, SAD and BDP. Inclusion of a group of BDNP allows for the identification of biomarkers more closely related to affective versus nonaffective clinical phenotypes and neural distinctions between BDP and BDNP. Findings have implications for nosology and future translational work given that some biomarkers are shared across all psychosis and some are unique to affective syndromes.
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Affiliation(s)
| | | | - Jennifer E. McDowell
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Georgia
| | - Sarah K. Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, United States of America
| | - Elliot S. Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, United States of America
| | - Elena I. Ivleva
- Department of Psychiatry, UT Southwestern Medical Center, United States of America
| | - Godfrey D. Pearlson
- Neuroscience, Yale School of Medicine, Institute of Living, Hartford Hospital, United States of America
| | - Matcheri S. Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, United States of America
| | - Carol A. Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, United States of America
| | - John A. Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, United States of America
| | - Brett A. Clementz
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Georgia, Corresponding author at: Psychology Department, 125 Jackson Street, Athens GA, 30601, Greece. (B.A. Clementz)
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