Similarities and differences between multivariate patterns of cognitive and socio-cognitive deficits in schizophrenia, bipolar disorder and related risk

Author:

Raio Alessandra,Pergola GiulioORCID,Rampino Antonio,Russo Marianna,D’Ambrosio EnricoORCID,Selvaggi Pierluigi,De Chiara Valerie,Altamura Mario,Brudaglio Flora,Saponaro Alessandro,Semisa Domenico,Bertolino Alessandro,Antonucci Linda A.,Blasi GiuseppeORCID,Manzari Anna,Carofiglio Angela,Barrasso Giuseppe,Bellomo Antonello,Leccisotti Ivana,Di Fino Melania,Andriola Ileana,Pennacchio Teresa Claudia,

Abstract

AbstractCognition and social cognition anomalies in patients with bipolar disorder (BD) and schizophrenia (SCZ) have been largely documented, but the degree of overlap between the two disorders remains unclear in this regard. We used machine learning to generate and combine two classifiers based on cognitive and socio-cognitive variables, thus delivering unimodal and multimodal signatures aimed at discriminating BD and SCZ from two independent groups of Healthy Controls (HC1 and HC2 respectively). Multimodal signatures discriminated well between patients and controls in both the HC1-BD and HC2-SCZ cohorts. Although specific disease-related deficits were characterized, the HC1 vs. BD signature successfully discriminated HC2 from SCZ, and vice-versa. Such combined signatures allowed to identify also individuals at First Episode of Psychosis (FEP), but not subjects at Clinical High Risk (CHR), which were classified neither as patients nor as HC. These findings suggest that both trans-diagnostic and disease-specific cognitive and socio-cognitive deficits characterize SCZ and BD. Anomalous patterns in these domains are also relevant to early stages of disease and offer novel insights for personalized rehabilitative programs.

Funder

Regione Puglia Funding "Early Identification of Psychosis Risk: a longitudinal study on endophenotypes involved in psychosis and bipolar disorder (PI: Prof. Alessandro Bertolino).

Publisher

Springer Science and Business Media LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3