Social cognition in people with schizophrenia: a cluster-analytic approach

Rocca, Paola; Galderisi, Silvana; Rossi, Alessandro; Bertolino, Alessandro; Rucci, Paola; Gibertoni, Dino; Montemagni, Cristiana; Sigaudo, Monica; Mucci, Armida; Bucci, Paola; Acciavatti, T.; Aguglia, Eugenio; Amore, Mario; Bellomo, Antonello; Ronchi, Diana De; Dell’Osso, Liliana; Fabio, Fabio Di; Girardi, Paolo; Goracci, Arianna; Marchesi, Carlo; Monteleone, Palmiero; Niolu, Cinzia; Pinna, Federica; Roncone, Rita; Sacchetti, Emilio; Santonastaso, Paolo; Zeppegno, Patrizia; Maj, Mario

doi:10.1017/s0033291716001100

Cited by 71 publications

(73 citation statements)

References 58 publications

(108 reference statements)

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“…Although our findings provide a rationale for broadening the discussion of EOS differences beyond age alone (≤12 or ≥13), other investigators would need to replicate and validate these findings before they could be considered consistently identifiable “subtypes” of EOS. Cluster analysis has been previously used by numerous investigators searching for ways to harness the heterogeneity of individuals diagnosed with schizophrenia‐spectrum disorders across the life span to provide a useful platform for more effective treatment strategies: cognitive subgroups based on differential brain volumetric reductions and cognitive decline (Weinberg et al, ); interaction of multiple gene variants and their effects on schizophrenia phenotypes (Cheah et al, ); social cognition subgroups (Rocca, Galderisi, Rossi, et al, ); functional outcomes across subgroups of adults (Rocca et al, ); and cognitive profiles of subgroups based on neuropsychological measures (Reser, Allott, Killackey, Farhall, & Cotton, ) among many others over the past two decades.…”

Section: Discussionmentioning

confidence: 99%

Diagnostic clusters associated with an early onset schizophrenia diagnosis among children and adolescents

Jerrell

McIntyre

Deroche

2017

Hum. Psychopharmacol Clin Exp

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Section: Discussionmentioning

confidence: 99%

Diagnostic clusters associated with an early onset schizophrenia diagnosis among children and adolescents

Jerrell

McIntyre

Deroche

2017

Hum. Psychopharmacol Clin Exp

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“…The total sample size per study ranged from 62 to 8231 individuals irrespective of participants' diagnostic status. The reported clustering methods were Kmeans or non-hierarchical clustering analysis 21,53,55,[69][70][71][72][73][74][75][76] , Ward's method or hierarchical analysis [77][78][79][80][81][82][83] , K-means clustering and Ward's method 18,38,54,[84][85][86][87][88][89] , latent class or profile analysis 15,90,91 and two-step cluster analysis [92][93][94] . One study 95 identified clusters using a combination of clinical/empirical and statistical clustering methods.…”

Section: Cross-sectional Studiesmentioning

confidence: 99%

A systematic review and narrative synthesis of data-driven studies in schizophrenia symptoms and cognitive deficits

et al. 2020

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To tackle the phenotypic heterogeneity of schizophrenia, data-driven methods are often applied to identify subtypes of its symptoms and cognitive deficits. However, a systematic review on this topic is lacking. The objective of this review was to summarize the evidence obtained from longitudinal and cross-sectional data-driven studies in positive and negative symptoms and cognitive deficits in patients with schizophrenia spectrum disorders, their unaffected siblings and healthy controls or individuals from general population. Additionally, we aimed to highlight methodological gaps across studies and point out future directions to optimize the translatability of evidence from data-driven studies. A systematic review was performed through searching PsycINFO, PubMed, PsycTESTS, PsycARTICLES, SCOPUS, EMBASE and Web of Science electronic databases. Both longitudinal and cross-sectional studies published from 2008 to 2019, which reported at least two statistically derived clusters or trajectories were included. Two reviewers independently screened and extracted the data. In this review, 53 studies (19 longitudinal and 34 cross-sectional) that conducted among 17,822 patients, 8729 unaffected siblings and 5520 controls or general population were included. Most longitudinal studies found four trajectories that characterized by stability, progressive deterioration, relapsing and progressive amelioration of symptoms and cognitive function. Cross-sectional studies commonly identified three clusters with low, intermediate (mixed) and high psychotic symptoms and cognitive profiles. Moreover, identified subgroups were predicted by numerous genetic, sociodemographic and clinical factors. Our findings indicate that schizophrenia symptoms and cognitive deficits are heterogeneous, although methodological limitations across studies are observed. Identified clusters and trajectories along with their predictors may be used to base the implementation of personalized treatment and develop a risk prediction model for high-risk individuals with prodromal symptoms.

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“…Nonetheless, it is useful to consider this construct as a whole and link it with patients' clinical outcome. For instance, the Italian Network for Research on Psychoses (Rocca et al, ) identified clusters of patients according to their social cognition performances, the cluster consisting of the most impaired being the individuals with the worst symptomatic pattern in neurocognition, disorganization, and positive symptoms. The same group (Galderisi et al, ) lately confirmed via a network analysis that social cognition is nearer to the core of schizophrenia, than positive, negative, and disorganization symptoms are.…”

Section: Relevance Of Social Cognition In Schizophreniamentioning

confidence: 99%

Genetic and clinical features of social cognition in 22q11.2 deletion syndrome

Lattanzi

Buzzanca

Frascarelli

et al. 2018

J of Neuroscience Research

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22q11.2 deletion syndrome (22q11.2 DS) is widely known as one of the most compelling genetic models of schizophrenia so far, being almost 40% of the carriers affected by psychotic symptoms. Moreover, most of these subjects also show impairment in social cognition, which is a comprehensive array of function that guides social interaction with the others, leading as well to the acquisition of new cognitive and social skills. In the last decade researchers have argued whether social cognition dysfunctions could be underlined by specific genetic alterations, and whether these are linked to specific clinical features. Some valid candidate genes are RTN4R, that encodes a protein which inhibits axonal sprouting, DGCR8, crucial in mRNA processing, or catechol-O-methyltransferase (COMT) and proline oxydase 1 (PRODH), involved in catecholamine metabolism in frontal cortex. This is the first article to address the topic of social cognition in 22q11.2 DS from a wide perspective, with a highlight on its genetic characteristics. We will provide a narrative review of the most recent findings and we will point out new directions on this research path, in order to achieve an effective characterization of the neurobiological system underlying social behavior.

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Social cognition in people with schizophrenia: a cluster-analytic approach

Abstract: If replicated, the identification of such subtypes in clinical practice may help in tailoring rehabilitation efforts to the person's strengths to gain more benefit to the person.

Cited by 71 publications

References 58 publications

Diagnostic clusters associated with an early onset schizophrenia diagnosis among children and adolescents

Diagnostic clusters associated with an early onset schizophrenia diagnosis among children and adolescents

A systematic review and narrative synthesis of data-driven studies in schizophrenia symptoms and cognitive deficits

Genetic and clinical features of social cognition in 22q11.2 deletion syndrome

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