Emma Knowles

Processing Speed Deficits in Schizophrenia: Reexamining the Evidence

OBJECTIVE A recent meta-analysis identified processing speed inefficiency as the largest single cognitive impairment in schizophrenia. However, the effect of potential moderator variables, such as medication status and severity of illness, remained unclear. The authors present an extended meta-analysis of processing speed and other specific cognitive functions in schizophrenia and examine the role of potential moderator variables. METHOD In addition to the studies identified in the original analysis, subsequently published articles were identified via systematic searches of MEDLINE and PsycINFO for the period from May 2006 to January 2009. The authors extracted data for potential moderator variables, including publication year; severity of illness; chlorpromazine equivalent daily dose; and mean IQ, mean age, and sample size for each study. Effect sizes were calculated for all measures, and meta-influence and homogeneity analyses were conducted. RESULTS Eleven studies were added to the original analysis, increasing the schizophrenia sample size from 1,915 to 4,135. The largest effect size was for coding tasks (g=-1.50), followed by category fluency (g=-1.31). However, for coding tasks, variation in effect size magnitude attributable to heterogeneity was substantial. Metaregression analyses indicated that three moderator variables were related to coding task effect size: publication year, IQ difference from comparison subjects, and chlorpromazine equivalent daily dose. There was a difference of 0.8 effect size units between studies with low compared with high chlorpromazine equivalent daily dose. No significant relationships were found between any moderators and the other cognitive tasks included in the meta-analysis. CONCLUSIONS The processing speed impairment in schizophrenia is substantially affected by several moderating factors, in particular antipsychotic medication dosage.

Molecular genetic evidence for overlap between general cognitive ability and risk for schizophrenia: a report from the Cognitive Genomics consorTium (COGENT).

It has long been recognized that generalized deficits in cognitive ability represent a core component of schizophrenia (SCZ), evident before full illness onset and independent of medication. The possibility of genetic overlap between risk for SCZ and cognitive phenotypes has been suggested by the presence of cognitive deficits in first-degree relatives of patients with SCZ; however, until recently, molecular genetic approaches to test this overlap have been lacking. Within the last few years, large-scale genome-wide association studies (GWAS) of SCZ have demonstrated that a substantial proportion of the heritability of the disorder is explained by a polygenic component consisting of many common single-nucleotide polymorphisms (SNPs) of extremely small effect. Similar results have been reported in GWAS of general cognitive ability. The primary aim of the present study is to provide the first molecular genetic test of the classic endophenotype hypothesis, which states that alleles associated with reduced cognitive ability should also serve to increase risk for SCZ. We tested the endophenotype hypothesis by applying polygenic SNP scores derived from a large-scale cognitive GWAS meta-analysis (~5000 individuals from nine nonclinical cohorts comprising the Cognitive Genomics consorTium (COGENT)) to four SCZ case-control cohorts. As predicted, cases had significantly lower cognitive polygenic scores compared to controls. In parallel, polygenic risk scores for SCZ were associated with lower general cognitive ability. In addition, using our large cognitive meta-analytic data set, we identified nominally significant cognitive associations for several SNPs that have previously been robustly associated with SCZ susceptibility. Results provide molecular confirmation of the genetic overlap between SCZ and general cognitive ability, and may provide additional insight into pathophysiology of the disorder.

Arguments for the sake of endophenotypes: Examining common misconceptions about the use of endophenotypes in psychiatric genetics

Endophenotypes are measurable biomarkers that are correlated with an illness, at least in part, because of shared underlying genetic influences. Endophenotypes may improve our power to detect genes influencing risk of illness by being genetically simpler, closer to the level of gene action, and with larger genetic effect sizes or by providing added statistical power through their ability to quantitatively rank people within diagnostic categories. Furthermore, they also provide insight into the mechanisms underlying illness and will be valuable in developing biologically‐based nosologies, through efforts such as RDoC, that seek to explain both the heterogeneity within current diagnostic categories and the overlapping clinical features between them. While neuroimaging, electrophysiological, and cognitive measures are currently most used in psychiatric genetic studies, researchers currently are attempting to identify candidate endophenotypes that are less genetically complex and potentially closer to the level of gene action, such as transcriptomic and proteomic phenotypes. Sifting through tens of thousands of such measures requires automated, high‐throughput ways of assessing, and ranking potential endophenotypes, such as the Endophenotype Ranking Value. However, despite the potential utility of endophenotypes for gene characterization and discovery, there is considerable resistance to endophenotypic approaches in psychiatry. In this review, we address and clarify some of the common issues associated with the usage of endophenotypes in the psychiatric genetics community.

Molecular genetic evidence for overlap between general cognitive ability and risk for schizophrenia: a report from the Cognitive Genomics consorTium (COGENT)

It has long been recognized that generalized deficits in cognitive ability represent a core component of schizophrenia (SCZ), evident before full illness onset and independent of medication. The possibility of genetic overlap between risk for SCZ and cognitive phenotypes has been suggested by the presence of cognitive deficits in first-degree relatives of patients with SCZ; however, until recently, molecular genetic approaches to test this overlap have been lacking. Within the last few years, large-scale genome-wide association studies (GWAS) of SCZ have demonstrated that a substantial proportion of the heritability of the disorder is explained by a polygenic component consisting of many common single-nucleotide polymorphisms (SNPs) of extremely small effect. Similar results have been reported in GWAS of general cognitive ability. The primary aim of the present study is to provide the first molecular genetic test of the classic endophenotype hypothesis, which states that alleles associated with reduced cognitive ability should also serve to increase risk for SCZ. We tested the endophenotype hypothesis by applying polygenic SNP scores derived from a large-scale cognitive GWAS meta-analysis (~5000 individuals from nine nonclinical cohorts comprising the Cognitive Genomics consorTium (COGENT)) to four SCZ case-control cohorts. As predicted, cases had significantly lower cognitive polygenic scores compared to controls. In parallel, polygenic risk scores for SCZ were associated with lower general cognitive ability. In addition, using our large cognitive meta-analytic data set, we identified nominally significant cognitive associations for several SNPs that have previously been robustly associated with SCZ susceptibility. Results provide molecular confirmation of the genetic overlap between SCZ and general cognitive ability, and may provide additional insight into pathophysiology of the disorder.

Genetic basis of neurocognitive decline and reduced white-matter integrity in normal human brain aging

Significance Identification of genes associated with brain aging should improve our understanding of the biological processes that govern normal age-related decline. In randomly selected pedigrees, we documented profound aging effects from young adulthood to old age (18–83 years) on neurocognitive ability and diffusion-based white-matter measures. Despite significant phenotypic correlation between white-matter integrity and tests of processing speed, working memory, declarative memory, and intelligence, no evidence for shared genetic determination was observed. Applying a gene-by-environment interaction analysis where age is an environmental factor, we demonstrate a heritable basis for neurocognitive deterioration with age. In contrast, increasing white-matter incoherence with age appears to be nongenetic. Identifying brain-aging traits is a critical first step in delineating the biological mechanisms of successful aging. Identification of genes associated with brain aging should markedly improve our understanding of the biological processes that govern normal age-related decline. However, challenges to identifying genes that facilitate successful brain aging are considerable, including a lack of established phenotypes and difficulties in modeling the effects of aging per se, rather than genes that influence the underlying trait. In a large cohort of randomly selected pedigrees (n = 1,129 subjects), we documented profound aging effects from young adulthood to old age (18–83 y) on neurocognitive ability and diffusion-based white-matter measures. Despite significant phenotypic correlation between white-matter integrity and tests of processing speed, working memory, declarative memory, and intelligence, no evidence for pleiotropy between these classes of phenotypes was observed. Applying an advanced quantitative gene-by-environment interaction analysis where age is treated as an environmental factor, we demonstrate a heritable basis for neurocognitive deterioration as a function of age. Furthermore, by decomposing gene-by-aging (G × A) interactions, we infer that different genes influence some neurocognitive traits as a function of age, whereas other neurocognitive traits are influenced by the same genes, but to differential levels, from young adulthood to old age. In contrast, increasing white-matter incoherence with age appears to be nongenetic. These results clearly demonstrate that traits sensitive to the genetic influences on brain aging can be identified, a critical first step in delineating the biological mechanisms of successful aging.

GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium

The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms (SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (P<5 × 10−8). Gene-based analysis identified an additional three Bonferroni-corrected significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a conservatively estimated SNP heritability of 21.5% (s.e.=0.01%) for general cognitive function. Integration with prior GWAS of cognitive performance and educational attainment yielded several additional significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric disorders, birth length/weight and smoking behavior, as well as a novel genetic association to the personality trait of openness. These data provide new insight into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness.

Influence of age, sex and genetic factors on the human brain

We report effects of age, age2, sex and additive genetic factors on variability in gray matter thickness, surface area and white matter integrity in 1,010 subjects from the Genetics of Brain Structure and Function Study. Age was more strongly associated with gray matter thickness and fractional anisotropy of water diffusion in white matter tracts, while sex was more strongly associated with gray matter surface area. Widespread heritability of neuroanatomic traits was observed, suggesting that brain structure is under strong genetic control. Furthermore, our findings indicate that neuroimaging-based measurements of cerebral variability are sensitive to genetic mediation. Fundamental studies of genetic influence on the brain will help inform gene discovery initiatives in both clinical and normative samples.

Ventral Anterior Cingulate Connectivity Distinguished Nonpsychotic Bipolar Illness from Psychotic Bipolar Disorder and Schizophrenia

Bipolar illness is a debilitating neuropsychiatric disorder associated with alterations in the ventral anterior cingulate cortex (vACC), a brain region thought to regulate emotional behavior. Although recent data-driven functional connectivity studies provide evidence consistent with this possibility, the role of vACC in bipolar illness and its pattern of whole brain connectivity remain unknown. Furthermore, no study has established whether vACC exhibits differential whole brain connectivity in bipolar patients with and without co-occurring psychosis and whether this pattern resembles that found in schizophrenia. We conducted a human resting-state functional connectivity investigation focused on the vACC seed in 73 remitted bipolar I disorder patients (33 with psychosis history), 56 demographically matched healthy comparison subjects, and 73 demographically matched patients with chronic schizophrenia. Psychosis history within the bipolar disorder group corresponded with significant between-group connectivity alterations along the dorsal medial prefrontal surface when using the vACC seed. Patients with psychosis history showed reduced connectivity (Cohens d = -0.69), whereas those without psychosis history showed increased vACC coupling (Cohens d = 0.8) relative to controls. The vACC connectivity observed in chronic schizophrenia patients was not significantly different from that seen in bipolar patients with psychosis history but was significantly reduced compared with that in bipolar patients without psychosis history. These robust findings reveal complex vACC connectivity alterations in bipolar illness, which suggest differences depending on co-occurrence of lifetime psychosis. The similarities in vACC connectivity patterns in schizophrenia and psychotic bipolar disorder patients may suggest the existence of common mechanisms underlying psychotic symptoms in the two disorders.

Reduced White Matter Integrity in Sibling Pairs Discordant for Bipolar Disorder

OBJECTIVE Several lines of evidence indicate that white matter integrity is compromised in bipolar disorder, but the nature, extent, and biological causes remain elusive. To determine the extent to which white matter deficits in bipolar disorder are familial, the authors investigated white matter integrity in a large sample of bipolar patients, unaffected siblings, and healthy comparison subjects. METHOD The authors collected diffusion imaging data for 64 adult bipolar patients, 60 unaffected siblings (including 54 discordant sibling pairs), and 46 demographically matched comparison subjects. Fractional anisotropy was compared between the groups using voxel-wise tract-based spatial statistics and by extracting mean fractional anisotropy from 10 regions of interest. Additionally, intraclass correlation coefficients were calculated between the sibling pairs as an index of familiality. RESULTS Widespread fractional anisotropy reductions in bipolar patients (>40,000 voxels) and more subtle reductions in their siblings, mainly restricted to the corpus callosum, posterior thalamic radiations, and left superior longitudinal fasciculus (>2,000 voxels) were observed. Similarly, region-of-interest analysis revealed significant reductions in most white matter regions in patients. In siblings, fractional anisotropy in the posterior thalamic radiation and the forceps was nominally reduced. Significant between-sibling correlations were found for mean fractional anisotropy across the tract-based spatial statistic skeleton, within significant clusters, and within nearly all regions of interest. CONCLUSIONS These findings emphasize the relevance of white matter to neuropathology and familiality of bipolar disorder and encourage further use of white matter integrity markers as endophenotypes in genetic studies.

The Puzzle of Processing Speed, Memory, and Executive Function Impairments in Schizophrenia: Fitting the Pieces Together

BACKGROUND Substantial impairment in performance on the digit-symbol substitution task in patients with schizophrenia is well established, which has been widely interpreted as denoting a specific impairment in processing speed. However, other higher order cognitive functions might be more critical to performance on this task. To date, this idea has not been rigorously investigated in patients with schizophrenia. METHODS Neuropsychological measures of processing speed, memory, and executive functioning were completed by 125 patients with schizophrenia and 272 control subjects. We implemented a series of confirmatory factor and structural regression modeling to build an integrated model of processing speed, memory, and executive function with which to deconstruct the digit-symbol substitution task and characterize discrepancies between patients with schizophrenia and control subjects. RESULTS The overall structure of the processing speed, memory, and executive function model was the same across groups (χ(2) = 208.86, p > .05), but the contribution of the specific cognitive domains to coding task performance differed significantly. When completing the task, control subjects relied on executive function and, indirectly, on working memory ability, whereas patients with schizophrenia used an alternative set of cognitive operations whereby they relied on the same processes required to complete verbal fluency tasks. CONCLUSIONS Successful coding task performance relies predominantly on executive function, rather than processing speed or memory. Patients with schizophrenia perform poorly on this task because of an apparent lack of appropriate executive function input; they rely instead on an alternative cognitive pathway.