A retrospective study of premorbid ability and aging differences in cognitive clusters of schizophrenia

Examining the association of life course neurocognitive ability with real-world functioning in schizophrenia-spectrum disorders

There is considerable variability in neurocognitive functioning within schizophrenia-spectrum disorders, and neurocognitive performance ranges from severe global impairment to normative performance. Few investigations of neurocognitive clusters have considered the degree to which deterioration relative to premorbid neurocognitive abilities is related to key illness characteristics. Moreover, while neurocognition and community functioning are strongly related, understanding of the sources of variability in the association between these two domains is also limited; it is unknown what proportion of participants would over-perform or under-perform the level of functioning expected based on current neurocognitive performance vs. lifelong attainment. This study examined data from 954 outpatients with schizophrenia-spectrum disorders across three previous studies. Neurocognition, community functioning, and symptoms were assessed. Neurocognitive subgroups were created based on current neurocognition, estimated premorbid IQ, and degree of deterioration from premorbid using z-score cut-offs; functional subgroups were created with cluster analysis based on the Specific Level of Functioning Scale and current neurocognition. The sample was neurocognitively heterogeneous; 65% displayed current neurocognitive impairment and 84% experienced some level of deterioration. Thirty percent of our sample was relatively higher functioning despite significant neurocognitive impairment. Individuals with better community functioning, regardless of neurocognitive performance, had lower symptom severity compared to those with worse functioning. These results highlight the variability in neurocognition and its role in functioning. Understanding individual differences in neurocognitive and functional profiles and the interaction between prior and current cognitive functioning can guide individualized treatment and selection of participants for clinical treatment studies.

Lifespan evolution of neurocognitive impairment in schizophrenia - A narrative review

Cognitive impairment is a well-recognized key feature of schizophrenia. Here we review the evidence on (1) the onset and sensitive periods of change in cognitive impairment before and after the first psychotic episode, and (2) heterogeneity in neurocognitive presentations across cognitive domains between and within individuals. Overall, studies suggest that mild cognitive impairment in individuals who develop schizophrenia or related disorders is already present during early childhood. Cross-sectional studies further suggest increasing cognitive impairments from pre- to post-psychosis onset, with the greatest declines between adolescence, the prodrome, and the first psychotic episode and with some variability between domains. Longitudinal studies with more than 10 years of observation time are scarce but support mild cognitive declines after psychosis onset until late adulthood. Whether and how much this cognitive decline exceeds normal aging, proceeds further in older patients, and is specific to certain cognitive domains and subpopulations of patients remains to be investigated. Finally, studies show substantial heterogeneity in cognitive performance in schizophrenia and suggest a variety of impairment profiles.

This review highlights a clear need for long-term studies that include a control group and individuals from adolescence to old age to better understand critical windows of cognitive change and their predictors. The available evidence stresses the importance of interventions that aim to counter cognitive decline during the prodromal years, as well as careful assessment of cognition in order to determine who will profit most from which cognitive training.

Brain Structure in Neuropsychologically Defined Subgroups of Schizophrenia and Psychotic Bipolar Disorder

BACKGROUND

Neuropsychological impairment is heterogeneous in psychosis. The association of intracranial volume (ICV) and total brain volume (TBV) with cognition suggests brain structure abnormalities in psychosis will covary with the severity of cognitive impairment. We tested the following hypotheses: (1) brain structure abnormalities will be more extensive in neuropsychologically impaired psychosis patients; (2) psychosis patients with premorbid cognitive limitations will show evidence of hypoplasia (ie, smaller ICV); and (3) psychosis patients with evidence of cognitive decline will demonstrate atrophy (ie, smaller TBV, but normal ICV).

METHODS

One hundred thirty-one individuals with psychosis and 97 healthy subjects underwent structural magnetic resonance imaging and neuropsychological testing. Patients were divided into neuropsychologically normal and impaired groups. Impaired patients were further subdivided into deteriorated and compromised groups if estimated premorbid intellect was average or below average, respectively. ICV and TBV were compared across groups. Localized brain volumes were qualitatively examined using voxel-based morphometry.

RESULTS

Compared to healthy subjects, neuropsychologically impaired patients exhibited smaller TBV, reduced grey matter volume in frontal, temporal, and subcortical brain regions, and widespread white matter volume loss. Neuropsychologically compromised patients had smaller ICV relative to healthy subjects, and neuropsychologically normal and deteriorated patient groups, but relatively normal TBV. Deteriorated patients exhibited smaller TBV compared to healthy subjects, but relatively normal ICV. Unexpectedly, TBV, adjusted for ICV, was reduced in neuropsychologically normal patients.

CONCLUSIONS

Patients with long-standing cognitive limitations exhibit evidence of early cerebral hypoplasia, whereas neuropsychologically normal and deteriorated patients show evidence of brain tissue loss consistent with progression or later cerebral dysmaturation.

Exploring cognitive heterogeneity in first-episode psychosis: What cluster analysis can reveal

Variable outcomes in first-episode psychosis (FEP) are partly attributable to heterogeneity in cognitive functioning. To aid identification of those likely to have poorer or better outcomes, we examined whether purported cognitive profiles identified through use of cluster analysis in chronic schizophrenia were evident in FEP. We also aimed to assess whether there was a relationship between cognitive profile and factors independent of the solution, providing external validation that the cognitive profiles represented distinct subgroups. Ward's method hierarchical cluster analysis, verified by a k-means cluster solution, was performed using data obtained from a cognitive test battery administered to 128 participants aged 15-25 years. Four cognitive profiles were identified. A continuity element was evident; participants in cluster four were more cognitively impaired compared to participants in cluster three, who appeared more cognitively intact. Clusters one and two were distinguishable across measures of attention and working memory and visual recognition memory, most likely reflecting sample specific patterns of deficit. Participants in cluster four had significantly lower premorbid and current IQ and higher negative symptoms compared to participants in cluster three. The distinct levels and patterns of cognition found in chronic schizophrenia cohorts are also evident across diagnostic categories in FEP.

A cognitive-emotional biomarker for predicting remission with antidepressant medications: a report from the iSPOT-D trial

Depression involves impairments in a range of cognitive and emotional capacities. It is unknown whether these functions can inform medication choice when considered as a composite predictive biomarker. We tested whether behavioral tests, grounded in the neurobiology of cognitive and emotional functions, predict outcome with common antidepressants. Medication-free outpatients with nonpsychotic major depressive disorder (N=1008; 665 completers) were assessed before treatment using 13 computerized tests of psychomotor, executive, memory-attention, processing speed, inhibitory, and emotional functions. Matched healthy controls (N=336) provided a normative reference sample for test performance. Depressed participants were then randomized to escitalopram, sertraline, or venlafaxine-extended release, and were assessed using the 16-item Quick Inventory of Depressive Symptomatology (QIDS-SR16) and the 17-item Hamilton Rating Scale for Depression. Given the heterogeneity of depression, analyses were furthermore stratified by pretreatment performance. We then used pattern classification with cross-validation to determine individual patient-level composite predictive biomarkers of antidepressant outcome based on test performance. A subgroup of depressed participants (approximately one-quarter of patients) were found to be impaired across most cognitive tests relative to the healthy norm, from which they could be discriminated with 91% accuracy. These patients with generally impaired cognitive task performance had poorer treatment outcomes. For this impaired subgroup, task performance furthermore predicted remission on the QIDS-SR16 at 72% accuracy specifically following treatment with escitalopram but not the other medications. Therefore, tests of cognitive and emotional functions can form a clinically meaningful composite biomarker that may help drive general treatment outcome prediction for optimal treatment selection in depression, particularly for escitalopram.

Deconstructing negative symptoms of schizophrenia: avolition-apathy and diminished expression clusters predict clinical presentation and functional outcome

BACKGROUND

Previous studies indicate that negative symptoms reflect a separable domain of pathology from other symptoms of schizophrenia. However, it is currently unclear whether negative symptoms themselves are multi-faceted, and whether sub-groups of patients who display unique negative symptom profiles can be identified.

METHODS

A data-driven approach was used to examine the heterogeneity of negative symptom presentations in two samples: Study 1 included 199 individuals with schizophrenia assessed with a standard measure of negative symptoms and Study 2 included 169 individuals meeting criteria for deficit schizophrenia (i.e., primary and enduring negative symptoms) assessed with a specialized measure of deficit symptoms. Cluster analysis was used to determine whether different groups of patients with distinct negative symptoms profiles could be identified.

RESULTS

Across both studies, we found evidence for two distinctive negative symptom sub-groups: one group with predominantly Avolition-Apathy (AA) symptoms and another with a predominantly Diminished Expression (DE) profile. Follow-up discriminant function analyses confirmed the validity of these groups. AA and DE negative symptom sub-groups significantly differed on clinically relevant external validators, including measures of functional outcome, premorbid adjustment, clinical course, disorganized symptoms, social cognition, sex, and ethnicity.

CONCLUSIONS

These results suggest that distinct subgroups of patients with elevated AA or DE can be identified within the broader diagnosis of schizophrenia and that these subgroups show clinically meaningful differences in presentation. Additionally, AA tends to be associated with poorer outcomes than DE, suggesting that it may be a more severe aspect of psychopathology.

Cortical thickness in neuropsychologically near-normal schizophrenia

Schizophrenia is a severe psychiatric illness with widespread impairments of cognitive functioning; however, a certain percentage of subjects are known to perform in the normal range on neuropsychological measures. While the cognitive profiles of these individuals have been examined, there has been relatively little attention to the neuroanatomical characteristics of this important subgroup. The aims of this study were to statistically identify schizophrenia subjects with relatively normal cognition, examine their neuroanatomical characteristics relative to their more impaired counterparts using cortical thickness mapping, and to investigate relationships between these characteristics and demographic variables to better understand the nature of cognitive heterogeneity in schizophrenia. Clinical, neuropsychological, and MRI data were collected from schizophrenia (n = 79) and healthy subjects (n = 65). A series of clustering algorithms on neuropsychological scores was examined, and a 2-cluster solution that separated subjects into neuropsychologically near-normal (NPNN) and neuropsychologically impaired (NPI) groups was determined most appropriate. Surface-based cortical thickness mapping was utilized to examine differences in thinning among schizophrenia subtypes compared with the healthy participants. A widespread cortical thinning pattern characteristic of schizophrenia emerged in the NPI group, while NPNN subjects demonstrated very limited thinning relative to healthy comparison subjects. Analysis of illness duration indicated minimal effects on subtype classification and cortical thickness results. Findings suggest a strong link between cognitive impairment and cortical thinning in schizophrenia, where subjects with near-normal cognitive abilities also demonstrate near-normal cortical thickness patterns. While generally supportive of distinct etiological processes for cognitive subtypes, results provide direction for further examination of additional neuroanatomical differences.

Cognitive profiles in persons with chronic schizophrenia

Cognitive heterogeneity has been a key barrier to clarifying the neuropathologic underpinnings of schizophrenia. We used an idiographic method for cluster analysis of neuropsychological data from 144 middle-aged and older people with schizophrenia to characterize and group the patterns of relative (within-person) profiles of cognitive strength and weakness. Results indicated a 5-cluster solution as most appropriate, with relatively even distribution across the 5 clusters in terms of the proportion of patients in each cluster. Cognitive subtyping may be useful in imaging and genetic research on schizophrenia, as well as having practical utility in treatment planning and cognitive rehabilitation.

What do we know about neuropsychological aspects of schizophrenia?

Application of a neuropsychological perspective to the study of schizophrenia has established a number of important facts about this disorder. Some of the key findings from the existing literature are that, while neurocognitive impairment is present in most, if not all, persons with schizophrenia, there is both substantial interpatient heterogeneity and remarkable within-patient stability of cognitive function over the long-term course of the illness. Such findings have contributed to the firm establishment of neurobiologic models of schizophrenia, and thereby help to reduce the social stigma that was sometimes associated with purely psychogenic models popular during parts of the 20th century. Neuropsychological studies in recent decades have established the primacy of cognitive functions over psychopathologic symptoms as determinants of functional capacity and independence in everyday functioning. Although the cognitive benefits of both conventional and even second generation antipsychotic medications appear marginal at best, recognition of the primacy of cognitive deficits as determinants of functional disability in schizophrenia has catalyzed recent efforts to develop targeted treatments for the cognitive deficits of this disorder. Despite these accomplishments, however, some issues remain to be resolved. Efforts to firmly establish the specific neurocognitive/neuropathologic systems responsible for schizophrenia remain elusive, as do efforts to definitively demonstrate the specific cognitive deficits underlying specific forms of functional impairment. Further progress may be fostered by recent initiatives to integrate neuropsychological studies with experimental neuroscience, perhaps leading to measures of deficits in cognitive processes more clearly associated with specific, identifiable brain systems.

Analysis of cognitive performance in schizophrenia patients and healthy individuals with unsupervised clustering models

Currently, assignment of cognitive test results to particular cognitive domains is guided by theoretical considerations and expert judgments which may vary. More objective means of classification may advance understanding of the relationships between test performance and the cognitive functions probed. We examined whether "atheoretical" analyses of cognitive test data can help identify potential hidden structures in cognitive performance. Novel data-mining methods which "let the data talk" without a priori theoretically bound constraints were used to analyze neuropsychological test results of 75 schizophrenia patients and 57 healthy individuals. The analyses were performed on the combined sample to maximize the "atheoretical" approach and allow it to reveal different structures of cognition in patients and controls. Analyses used unsupervised clustering methods, including hierarchical clustering, self-organizing maps (SOM), k-means and supermagnetic clustering (SPC). The model revealed two major clusters containing accuracy and reaction time measures respectively. The sensitivity (75% versus 52%) and specificity (95% versus 77% ) of these clusters for diagnosing schizophrenia differed. Downstream branching was influenced by stimulus domain. Predictions arising from this "atheoretical" model are supported by evidence from published studies. This preliminary study suggests that appropriate application of data-mining methods may contribute to investigation of cognitive functions.

Cognitive heterogeneity in schizophrenia

PURPOSE

Further clarification of the nature of cognitive heterogeneity in schizophrenia is needed to aid the endophenotype approach to the understanding of the genetic basis of the disorder. This review summarizes recent neuropsychological studies of schizophrenia, aimed at establishing whether there are valid forms of cognitive impairment that can be defined with the use of neuropsychological measures in patients with schizophrenia, and studies that have attempted to relate specific neuropsychological findings to genetic polymorphisms.

RECENT FINDINGS

There is good evidence for significant cognitive heterogeneity in schizophrenia. It is not yet clear, however, whether this heterogeneity is better accounted for by a general loss of function, varying in degree between different patients, or by impairment in specific cognitive abilities, for example working memory. Molecular genetic studies have provided evidence for associations of single nucleotide polymorphisms with both specific and general impairments, with some additional support for a working memory deficit from neuroimaging studies.

SUMMARY

Larger, better controlled studies are needed before the genetic sources of cognitive heterogeneity in schizophrenia can be accurately characterized. This will be aided with the development and use of more specific neuropsychological tasks that can accurately discriminate between different cognitive domains.

Etiological Heterogeneity and Intelligence Test Scores in Patients with Schizophrenia

Previous research has indicated that patients with a family history of schizophrenia show a greater degree of cognitive and neuropsychological impairment than patients without a family history. We examined the neurocognitive performance, using the WAIS-R, of 51 patients with a family history (familial) and 103 patients without a family history (sporadic) to determine if differences exist that may help to explain the heterogeneous neuropsychological profile of the illness. The family history groups did not differ with respect to gender, diagnosis, ethnicity, age, age of onset, education or duration of illness. Multivariate analyses, covarying for age of onset and education, showed the sporadic group performed significantly better than the familial group on the digit symbol and object assembly subtests, with a trend level difference in overall performance IQ score. Additionally, we identified significant gender differences in favor of males for full scale and verbal IQ, the information, digit span, block design, and arithmetic subtests, and at a trend level, the picture assembly subtest. The family history group differences reflect relative dysfunction in visual attention and scanning, visuomotor control, and spatial processing and reasoning. Overall, the results suggest that sporadic patients have better perceptual-organizational skills and faster speed of processing.

Family-based clusters of cognitive test performance in familial schizophrenia

BACKGROUND

Cognitive traits derived from neuropsychological test data are considered to be potential endophenotypes of schizophrenia. Previously, these traits have been found to form a valid basis for clustering samples of schizophrenia patients into homogeneous subgroups. We set out to identify such clusters, but apart from previous studies, we included both schizophrenia patients and family members into the cluster analysis. The aim of the study was to detect family clusters with similar cognitive test performance.

METHODS

Test scores from 54 randomly selected families comprising at least two siblings with schizophrenia spectrum disorders, and at least two unaffected family members were included in a complete-linkage cluster analysis with interactive data visualization.

RESULTS

A well-performing, an impaired, and an intermediate family cluster emerged from the analysis. While the neuropsychological test scores differed significantly between the clusters, only minor differences were observed in the clinical variables.

CONCLUSIONS

The visually aided clustering algorithm was successful in identifying family clusters comprising both schizophrenia patients and their relatives. The present classification method may serve as a basis for selecting phenotypically more homogeneous groups of families in subsequent genetic analyses.

Meta-analysis and the science of schizophrenia: variant evidence or evidence of variants?

Quantification (meta-analysis) of the neuroscience evidence on schizophrenia shows very modest average differences between patient and control distributions across a great variety of measures and literatures. The strongest findings involve cognitive and psychophysiological measures. Several possible explanations for this situation are reviewed including technical immaturity, methodological variability, dimensional and multiple illness models and the nature of cognitive measurement. An argument is developed that biological subtypes and endophenotypes within the broad diagnostic category of schizophrenia underpin the meta-analytic evidence. Considerations in the use of this evidence to identify illness variants are described and four candidate subtypes are proposed. Schizophrenia is a disease that will resist biological definition until its variants are isolated and extracted from the generic patient population.