Neurobiological underpinnings of cognitive subtypes in psychoses: A cross-diagnostic cluster analysis

Fernández-Linsenbarth, Inés; Planchuelo‐Gómez, Álvaro; Díez, Álvaro; Arjona, Antonio; Luis, Rodrigo de; Martín-Santiago, Óscar; Benito-Sánchez, José Antonio; Pérez-Laureano, Ángela; González-Parra, David; Montes-Gonzalo, Carmen; Melero-Lerma, Raquel; Morante, Sonia Fernández; Sanz-Fuentenebro, Javier; Gómez‐Pilar, Javier; Núñez, Pablo; Molina, Vicente

doi:10.1016/j.schres.2020.11.013

Cited by 14 publications

(25 citation statements)

References 47 publications

(70 reference statements)

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“…With shared polygenic risk for SSD and BD now well-established [ 24 , 28 – 30 ], it is plausible that any association between PRS-SZ and brain-based phenotypes may extend to cases with BD who show more severe cognitive deficits. Regardless of the number of subgroups delineated in these analyses, there is some consensus in reporting a subgroup with severe cognitive deficits that show reduced fronto-temporal grey matter volume and cortical thickness relative to various reference groups showing various degrees of relatively spared cognition [ 15 , 31 , 32 ]. Recent studies have begun to examine cognitive- and brain-based phenotypes in relation to polygenic risk for schizophrenia (PRS-SZ), with increasing PRS-SZ being associated with more pronounced cognitive deficits [ 33 , 34 ].…”

Section: Introductionmentioning

confidence: 99%

Interactive effects of polygenic risk and cognitive subtype on brain morphology in schizophrenia spectrum and bipolar disorders

Quidé

Watkeys

Girshkin

et al. 2022

Eur Arch Psychiatry Clin Neurosci

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Grey matter volume (GMV) may be associated with polygenic risk for schizophrenia (PRS-SZ) and severe cognitive deficits in people with schizophrenia, schizoaffective disorder (collectively SSD), and bipolar disorder (BD). This study examined the interactive effects of PRS-SZ and cognitive subtypes of SSD and BD in relation to GMV. Two-step cluster analysis was performed on 146 clinical cases (69 SSD and 77 BD) assessed on eight cognitive domains (verbal and visual memory, executive function, processing speed, visual processing, language ability, working memory, and planning). Among them, 55 BD, 51 SSD, and 58 healthy controls (HC), contributed to focal analyses of the relationships between cognitive subtypes, PRS-SZ and their interaction on GMV. Two distinct cognitive subtypes were evident among the combined sample of cases: a ‘cognitive deficit’ group (CD; N = 31, 20SSD/11BD) showed severe impairment across all cognitive indices, and a ‘cognitively spared’ (CS; N = 75; 31SSD/44BD) group showed intermediate cognitive performance that was significantly worse than the HC group but better than the CD subgroup. A cognitive subgroup-by-PRS-SZ interaction was significantly associated with GMV in the left precentral gyrus. Moderation analyses revealed a significant negative relationship between PRS-SZ and GMV in the CD group only. At low and average (but not high) PRS-SZ, larger precentral GMV was evident in the CD group compared to both CS and HC groups, and in the CS group compared to HCs. This study provides evidence for a relationship between regional GMV changes and PRS-SZ in psychosis spectrum cases with cognitive deficits, but not in cases cognitively spared.

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Section: Introductionmentioning

confidence: 99%

Interactive effects of polygenic risk and cognitive subtype on brain morphology in schizophrenia spectrum and bipolar disorders

Quidé

Watkeys

Girshkin

et al. 2022

Eur Arch Psychiatry Clin Neurosci

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“…Cluster analysis allows the classification of individuals into subgroups based on their cognitive profiles, and such analyses have tended to identify 3 distinct subgroups: a relatively intact group, an intermediate group (a subgroup with the level of cognitive deficits sitting between normal performance and severe cognitive impairment), and a severely impaired group showing global deficits 16 , 17 . Although not all studies have identified a relatively intact cluster group 21 , a recent meta-analysis of relevant studies confirmed that a 3-cluster solution is the most supported outcome (17 of 22 studies reviewed) 22 . A very limited subset of such studies has included neuroimaging data alongside the cognitive assessments, to examine the relationships between group assignment and brain structure, and these have shown links to the underlying neurobiology.…”

Section: Introductionmentioning

confidence: 99%

Clustering of cognitive subtypes in schizophrenia patients and their siblings: relationship with regional brain volumes

Alkan

Evans

2022

Schizophr

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Schizophrenia patients (SZH) often show impaired cognition and reduced brain structural volumes; these deficits are also detectable in healthy relatives of SZH. However, there is considerable heterogeneity: a sizable percentage of SZH are relatively cognitively intact; clustering strategies have proved useful for categorising into cognitive subgroups. We used a clustering strategy to investigate relationships between subgroup assignment and brain volumes, in 102 SZH (N = 102) and 32 siblings of SZH (SZH-SIB), alongside 92 controls (CON) and 48 of their siblings. SZH had poorer performance in all cognitive domains, and smaller brain volumes within prefrontal and temporal regions compared to controls. We identified three distinct cognitive clusters (‘neuropsychologically normal’, ‘intermediate’, ‘cognitively impaired’) based on age- and gender-adjusted cognitive domain scores. The majority of SZH (60.8%) were assigned to the cognitively impaired cluster, while the majority of SZH-SIB (65.6%) were placed in the intermediate cluster. Greater right middle temporal volume distinguished the normal cluster from the more impaired clusters. Importantly, the observed brain volume differences between SZH and controls disappeared after adjustment for cluster assignment. This suggests an intimate link between cognitive performance levels and regional brain volume differences in SZH. This highlights the importance of accounting for heterogeneity in cognitive performance within SZH populations when attempting to characterise the brain structural abnormalities associated with the disease.

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“…In this context, neurocognition varies across the main domains affected in patients with schizophrenia, such as verbal and working memory, motor and performance speed, verbal fluency, social cognition and problem-solving [2]. Growing evidence has indicated that different cognitive subgroups may exist within the psychosis spectrum [1][2][3][4][5][6]. Preliminary evidence suggests that such cognitive subgroups may be associated with distinctive brain structure [1,7,8].…”

Section: Introductionmentioning

confidence: 99%

“…Growing evidence has indicated that different cognitive subgroups may exist within the psychosis spectrum [1][2][3][4][5][6]. Preliminary evidence suggests that such cognitive subgroups may be associated with distinctive brain structure [1,7,8].…”

Section: Introductionmentioning

confidence: 99%

Real-life outcomes in biotypes of psychotic disorders based on neurocognitive performance

Molina

Fernández-Linsenbarth

Queipo-de-Llano

et al. 2022

Eur Arch Psychiatry Clin Neurosci

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Aiming at discerning potential biotypes within the psychotic syndrome, we have recently reported the possible existence of two clusters or biotypes across schizophrenia and bipolar disorder characterized by their cognitive performance using the Brief Assessment of Cognition in Schizophrenia (BACS) instrument and validated with independent biological and clinical indexes (Fernández-Linsenbarth et al. in Schizophr Res 229:102–111, 2021). In this previous work, the group with larger cognitive deficits (N = 93, including 69 chronic schizophrenia, 17 first episodes (FE) of schizophrenia and 7 bipolar disorder patients) showed smaller thalamus and hippocampus volume and hyper-synchronic electroencephalogram than the group with milder deficits (N = 105, including 58 chronic schizophrenia, 25 FE and 22 bipolar disorder patients). We predicted that if these biotypes indeed corresponded to different cognitive and biological substrates, their adaptation to real life would be different. To this end, in the present work we have followed up the patients’ population included in that work at 1st and 3rd years after the date of inclusion in the 2021 study and we report on the statistical comparisons of each clinical and real-life outcomes between them. The first cluster, with larger cognitive deficits and more severe biological alterations, showed during that period a decreased capacity for job tenure (1st and 3rd years), more admissions to a psychiatric ward (1st year) and a higher likelihood for quitting psychiatric follow-up (3rd year). Patients in the second cluster, with moderate cognitive deficits, were less compliant with prescribed treatment at the 3rd year. The differences in real-life outcomes may give additional external validity to that yielded by biological measurements to the described biotypes based on neurocognition.

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Neurobiological underpinnings of cognitive subtypes in psychoses: A cross-diagnostic cluster analysis

Cited by 14 publications

References 47 publications

Interactive effects of polygenic risk and cognitive subtype on brain morphology in schizophrenia spectrum and bipolar disorders

Interactive effects of polygenic risk and cognitive subtype on brain morphology in schizophrenia spectrum and bipolar disorders

Clustering of cognitive subtypes in schizophrenia patients and their siblings: relationship with regional brain volumes

Real-life outcomes in biotypes of psychotic disorders based on neurocognitive performance

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