Distinct and shared contributions of diagnosis and symptom domains to cognitive performance in severe mental illness in the Paisa population: a case-control study

ABSTRACT: Background: Severe mental illness diagnoses have overlapping symptomatology and shared genetic risk, motivating cross-diagnostic investigations of disease-relevant quantitative measures. We analysed relationships between neurocognitive performance, symptom domains, and diagnoses in a large sample of people with severe mental illness not ascertained for a specific diagnosis (cases), and people without mental illness (controls) from a single, homogeneous population. Methods: In this case-control study, cases with severe mental illness were ascertained through electronic medical records at Clínica San Juan de Dios de Manizales (Manizales, Caldas, Colombia) and the Hospital Universitario San Vicente Fundación (Medellín, Antioquía, Colombia). Participants were assessed for speed and accuracy using the Penn Computerized Neurocognitive Battery (CNB). Cases had structured interview-based diagnoses of schizophrenia, bipolar 1, bipolar 2, or major depressive disorder. Linear mixed models, using CNB tests as repeated measures, modelled neurocognition as a function of diagnosis, sex, and all interactions. Follow-up analyses in cases included symptom factor scores obtained from exploratory factor analysis of symptom data as main effects. Findings: Between Oct 1, 2017, and Nov 1, 2019, 2406 participants (1689 cases [schizophrenia n=160; bipolar 1 disorder n=519; bipolar 2 disorder n=204; and major depressive disorder n=806] and 717 controls; mean age 39 years (SD 14); and 1533 female) were assessed. Participants with bipolar 1 disorder and schizophrenia had similar impairments in accuracy and speed across cognitive domains. Participants with bipolar 2 disorder and major depressive disorder performed similarly to controls, with subtle deficits in executive and social cognition. A three-factor model (psychosis, mania, and depression) best represented symptom data. Controlling for diagnosis, premorbid IQ, and disease severity, high lifetime psychosis scores were associated with reduced accuracy and speed across cognitive domains, whereas high depression scores were associated with increased social cognition accuracy. Interpretation: Cross-diagnostic investigations showed that neurocognitive function in severe mental illness is characterised by two distinct profiles (bipolar 1 disorder and schizophrenia, and bipolar 2 disorder and major depressive disorder), and is associated with specific symptom domains. These results suggest the utility of this design for elucidating severe mental illness causes and trajectories.

• Autores: López Jaramillo, Carlos Alberto; Vargas Upegui, Cristian David; Agudelo Arango, Luis Guillermo; Díaz Zuluaga, Ana María; Melo Espejo, Juanita; López Tobón, María Cecilia; Palacio Ortiz, Juan David; Ruiz Sánchez, Sergio; Valencia Echeverry, Johanna; Castaño Ramírez, Oscar Mauricio; Service, Susan K .; Port, Allison M.; Moore, Tyler M.; Munoz Umanes, Marfred; Teshiba, Terri M.; Espinoza, Alesandra; Loohuis, Loes Olde; De la Hoz Gomez, Juan; Brodey, Benjamin B.; Sabatti, Chiara; Escobar, Javier I.; Reus, Victor I.; Gur, Ruben C.; Bearden, Carrie E.; Freimer, Nelson B.
• Tipo de recurso: Article of investigation
• Fecha de publicación: 2020
• Institución: Universidad de Antioquia
• Repositorio: Repositorio UdeA
• Idioma: eng
• OAI Identifier: oai:bibliotecadigital.udea.edu.co:10495/45429
• Acceso en línea: https://hdl.handle.net/10495/45429
• Palabra clave: Bipolar Disorder; Trastorno Bipolar; Case-Control Studies; Estudios de Casos y Controles; Cognition Disorders; Trastornos del Conocimiento; Depressive Disorder, Major; Trastorno Depresivo Mayor; Linear Models; Modelos Lineales; Schizophrenic Psychology; Psicología del Esquizofrénico; https://id.nlm.nih.gov/mesh/D001714; https://id.nlm.nih.gov/mesh/D016022; https://id.nlm.nih.gov/mesh/D003072; https://id.nlm.nih.gov/mesh/D003865; https://id.nlm.nih.gov/mesh/D016014; https://id.nlm.nih.gov/mesh/D012565
• Rights: openAccess
• License: https://creativecommons.org/licenses/by-nc-nd/4.0/