R. Walter Heinrichs

The Primacy of Cognition in Schizophrenia.

Cognitive tasks and concepts are used increasingly in schizophrenia science and treatment. Recent meta-analyses show that across a spectrum of research domains only cognitive measures distinguish a majority of schizophrenia patients from healthy people. Average effect sizes derived from common clinical tests of attention, memory, language, and reasoning are twice as large as those obtained in structural magnetic resonance imaging and positron emission tomography studies. Chronic stress, genes, brain disturbances, task structure, gender, and sociocultural background may all enhance the sensitivity of cognitive performance to schizophrenia. At the same time, disease heterogeneity and the presence of endophenotypes and subtypes within the patient population may place upper limits on the strength of any specific cognitive finding. Schizophrenia is a complex biobehavioral disorder that manifests itself primarily in cognition.

Neurological Soft Signs in Schizophrenia: A Meta-analysis

BACKGROUND Neurological soft signs (NSS) are hypothesized as candidate endophenotypes for schizophrenia, but their prevalence and relations with clinical and demographic data are unknown. The authors undertook a quantification (meta-analysis) of the published literature on NSS in patients with schizophrenia and healthy controls. A systematic search was conducted for published articles reporting NSS and related data using standard measures in schizophrenia and healthy comparison groups. METHOD A systematic search was conducted for published articles reporting data on the prevalence of NSS in schizophrenia using standard clinical rating scales and healthy comparison groups. Meta-analyses were performed using the Comprehensive Meta-analysis software package. Effect sizes (Cohen d) indexing the difference between schizophrenic patients and the healthy controls were calculated on the basis of reported statistics. Potential moderator variables evaluated included age of patient samples, level of education, sample sex proportions, medication doses, and negative and positive symptoms. RESULTS A total of 33 articles met inclusion criteria for the meta-analysis. A large and reliable group difference (Cohen d) indicated that, on average, a majority of patients (73%) perform outside the range of healthy subjects on aggregate NSS measures. Cognitive performance and positive and negative symptoms share 2%-10% of their variance with NSS. CONCLUSIONS NSS occur in a majority of the schizophrenia patient population and are largely distinct from symptomatic and cognitive features of the illness.

Neurocognitive subtypes of chronic schizophrenia

Performance on four key neurocognitive tasks was used to search for subtypes in 104 DSM-IIIR schizophrenic patients. The tasks were the Wisconsin Card Sorting Test to index executive prefrontal cerebral function, intrusion errors from the California Verbal Learning Test to tap hippocampal-diencephalic mnestic function, bilateral hand performance on the Purdue Pegboard to index fine motor-basal ganglial function, and a pro-rated IQ from the Wechsler Adult Intelligence Scale-Revised to measure general cognitive-cerebral function. Neurocognitive data were analyzed using hierarchical and disjoint clustering procedures with Euclidean distance. A five cluster solution was considered optimal. Cluster 1 (n = 24) comprised patients with selective executive-prefrontal dysfunction; cluster 2 (n = 16) suggested normative function; cluster 3 (n = 20) involved patients with executive-motor/cortico-basal ganglial deficit; cluster 4 (n = 25) suggested dementia/multi-focal disturbance; and cluster 5 (n = 19) consisted of patients with selective motor-basal ganglial deficit. The subtypes differed significantly in age, duration of illness, and extent of hospitalization. Suggestive trends in sex composition and anti-Parkinsonian medication patterns were noted. Neurocognitive tasks combined with cluster analysis have promise in reducing and clarifying the heterogeneity of schizophrenia.

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.

Depression in multiple sclerosis: a quantitative review of the evidence.

The published literature on depression in multiple sclerosis (MS) is reviewed quantitatively. The authors report mean effect sizes for 20 studies comparing depression scores of MS patients with those of healthy participants (d=1.07) and 21 studies comparing depression scores of MS patients with those of patients who have other chronic conditions (d=-0.14). The confidence interval for the mean overall MS-medical comparison included 0. However, subgroups of patients with chronic fatigue and spinal-neuromuscular conditions were more and less depressed than MS patients, respectively. Results indicate that a majority of MS patients with mild to moderate disability levels are distinguishable from healthy people in terms of depressive symptoms. However, the depression-disease link is complex and not specific to this form of demyelinating illness.

Schizophrenia and the frontal brain: a quantitative review.

Structural and physiological frontal brain system deficits in patients with schizophrenia are reviewed quantitatively. We report effect sizes from studies since 1980 that used structural (CT, MRI), and functional (PET) neuroimaging methods. We found both literatures to be distinguished by heterogeneity whereby most patients show normative frontal function and structure, a minority shows diminished values and some patients demonstrate augmented function and structure rather than deficit. The average magnitude of difference between patients and controls is generally too modest to support the idea that frontal brain dysfunction is a necessary component of schizophrenia. This modesty is most apparent in average effects obtained for frontal brain volume (M = -.36), left frontal brain volume (M = -.16), frontal resting metabolism, and blood flow (M = -.64). Effect sizes of this magnitude imply that schizophrenia and control distributions overlap by as much as 88% and no less than about 60% on frontal brain measures. It is only when behavioral measures are employed as activation tasks during frontal blood flow and metabolism studies, that average effect sizes rise in magnitude to indicate patient-control distribution overlaps that are less than 50%. Overall, the findings are hard to incorporate within single disease models that propose major involvement of the frontal system, at least at the degree of resolution obtained with current imaging technology.

Are schizophrenia and schizoaffective disorder neuropsychologically distinguishable

This study sought to objectify the distinction between schizophrenia and schizoaffective disorder in terms of standard tasks measuring verbal and non-verbal cognitive ability, auditory working memory, verbal declarative memory and visual processing speed. Research participants included 103 outpatients with a diagnosis of schizophrenia, 48 with schizoaffective disorder, and 72 non-patients from the community. Schizophrenia patients were impaired on all cognitive measures relative to schizoaffective patients and non-psychiatric participants. Regression-based prediction models revealed that cognitive measures classified schizophrenia patients accurately (91%), but not patients with schizoaffective disorder (35%). In addition, there was no statistical evidence for the unique predictive validity of any specific cognitive task. Patients with schizophrenia were significantly more symptomatic and had greater community support requirements than those with schizoaffective disorder. However, group differences in cognitive performance are insufficient to separate these syndromes of psychotic illness.

Schizophrenia and memory impairment: evidence for a neurocognitive subtype

Evidence is presented that verbal memory impairment distinguishes a subgroup of patients with schizophrenia who also differ in symptom profile and illness adjustment. On the basis of the California Verbal Learning Test (CVLT), a sample of patients was partitioned into memory-impaired (n=16) and memory-unimpaired groups (n=16). Groups were matched for age, sex, IQ, and anti-psychotic medication. These groups were then compared using the Brief Psychiatric Rating Scale (BPRS) and the Sickness Impact Profile (SIP). Results indicate that memory-impaired schizophrenia patients experience significantly more positive symptoms and a poorer quality of life than their memory-unimpaired counterparts. This finding supports the idea that neurocognitive measures are a valuable way of organizing the heterogeneous disease states of schizophrenia.

Neurological soft signs in non-psychotic first-degree relatives of patients with schizophrenia: A systematic review and meta-analysis

BACKGROUND Neurological soft signs (NSS) have been associated with the neuropsychopathology of schizophrenia, and have been proposed as candidate endophenotypes for this clinical group. However, the prevalence rate of NSS in non-psychotic first-degree relatives is not fully known. The authors systematically and quantitatively reviewed the literature to determine the magnitude of difference between: (1) first-degree non-psychotic relatives of schizophrenia patients and healthy controls, and (2) between schizophrenia patients and their non-psychotic relatives. METHODS An article search and meta-analysis was conducted using the Comprehensive Meta-Analysis software package to quantify group differences. Mean effect sizes (standardized group mean differences) and associated confidence intervals along with homogeneity and publication bias tests and statistics were calculated. RESULTS Search procedures identified 11 independent studies that met the inclusion criteria. Quantification of NSS differences yielded a mean effect size of 0.81 for schizophrenia patients and their non-psychotic relatives and 0.97 for non-psychotic relatives of schizophrenia patients and healthy controls. CONCLUSIONS The current findings show that there are large group differences in NSS prevalence between patients with schizophrenia, non-psychotic relatives, and healthy controls. These results are consistent with the argument that NSS are familial in nature, segregate with the illness and may be valid and useful endophenotypes.

Predictors of medication competence in schizophrenia patients

Competence in self-administration of a drug regimen is related to both treatment adherence and functional outcome. Previous research with middle-aged and older schizophrenia patients suggests a central role for cognitive performance in predicting this competence. We examined the relative and joint contributions of demographic, clinical and cognitive predictors of medication management ability in an age-representative group of patients. The study participants comprised 147 patients with schizophrenia or schizoaffective disorder ranging from 21 to 65 years of age. Measures included demographic variables, current symptoms, subjective treatment response and a battery of cognitive tests. Competence in medication management was indexed with the Medication Management Ability Assessment (MMAA). Multiple regression analyses revealed that cognitive variables accounted for a significant proportion of the variance in MMAA scores over and above the contribution of all other variables. Measures of word recognition and pronunciation, auditory working memory and verbal learning yielded unique contributions to prediction. Positive and negative symptoms and subject treatment evaluations did not independently predict medication competency. This study documents a considerable range in MMAA scores across a demographically broad schizophrenia sample and supports the unique contribution of specific cognitive factors in predicting medication competence.