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ObjectiveMany psychotropic medications used to treat schizophrenia have significant anticholinergic properties, which are linked to cognitive impairment and dementia risk in healthy subjects. Clarifying the impact of cognitive impairment attributable to anticholinergic medication burden may help optimize cognitive outcomes in schizophrenia. The aim of this study was to comprehensively characterize how this burden affects functioning across multiple cognitive domains in schizophrenia outpatients.MethodsCross-sectional data were analyzed using inferential statistics and exploratory structural equation modeling to determine the relationship between anticholinergic medication burden and cognition. Patients with a diagnosis of schizophrenia or schizoaffective disorder (N=1,120) were recruited from the community at five U.S. universities as part of the Consortium on the Genetics of Schizophrenia-2. For each participant, prescribed medications were rated and summed according to a modified Anticholinergic Cognitive Burden (ACB) scale. Cognitive functioning was assessed by performance on domains of the Penn Computerized Neurocognitive Battery (PCNB).ResultsACB score was significantly associated with cognitive performance, with higher ACB groups scoring worse than lower ACB groups on all domains tested on the PCNB. Similar effects were seen on other cognitive tests. Effects remained significant after controlling for demographic characteristics and potential proxies of illness severity, including clinical symptoms and chlorpromazine-equivalent antipsychotic dosage.ConclusionsAnticholinergic medication burden in schizophrenia is substantial, common, conferred by multiple medication classes, and associated with cognitive impairments across all cognitive domains. Anticholinergic medication burden from all medication classes-including psychotropics used in usual care-should be considered in treatment decisions and accounted for in studies of cognitive functioning in schizophrenia.

BackgroundLatency of the acoustic startle reflex is the time from presentation of the startling stimulus until the response, and provides an index of neural processing speed. Schizophrenia subjects exhibit slowed latency compared to healthy controls. One prior publication reported significant heritability of latency. The current study was undertaken to replicate and extend this solitary finding in a larger cohort.MethodsSchizophrenia probands, their relatives, and control subjects from the Consortium on the Genetics of Schizophrenia (COGS-1) were tested in a paradigm to ascertain magnitude, latency, and prepulse inhibition of startle. Trial types in the paradigm were: pulse-alone, and trials with 30, 60, or 120ms between the prepulse and pulse. Comparisons of subject groups were conducted with ANCOVAs to assess startle latency and magnitude. Heritability of startle magnitude and latency was analyzed with a variance component method implemented in SOLAR v.4.3.1.Results980 subjects had analyzable startle results: 199 schizophrenia probands, 456 of their relatives, and 325 controls. A mixed-design ANCOVA on startle latency in the four trial types was significant for subject group (F(2,973)=4.45, p=0.012) such that probands were slowest, relatives were intermediate and controls were fastest. Magnitude to pulse-alone trials differed significantly between groups by ANCOVA (F(2,974)=3.92, p=0.020) such that controls were lowest, probands highest, and relatives intermediate. Heritability was significant (p&nbsp

BackgroundA long-standing epidemiological puzzle is the reduced rate of rheumatoid arthritis (RA) in those with schizophrenia (SZ) and vice versa. Traditional epidemiological approaches to determine if this negative association is underpinned by genetic factors would test for reduced rates of one disorder in relatives of the other, but sufficiently powered data sets are difficult to achieve. The genomics era presents an alternative paradigm for investigating the genetic relationship between two uncommon disorders.MethodsWe use genome-wide common single nucleotide polymorphism (SNP) data from independently collected SZ and RA case-control cohorts to estimate the SNP correlation between the disorders. We test a genotype X environment (GxE) hypothesis for SZ with environment defined as winter- vs summer-born.ResultsWe estimate a small but significant negative SNP-genetic correlation between SZ and RA (-0.046, s.e. 0.026, P = 0.036). The negative correlation was stronger for the SNP set attributed to coding or regulatory regions (-0.174, s.e. 0.071, P = 0.0075). Our analyses led us to hypothesize a gene-environment interaction for SZ in the form of immune challenge. We used month of birth as a proxy for environmental immune challenge and estimated the genetic correlation between winter-born and non-winter born SZ to be significantly less than 1 for coding/regulatory region SNPs (0.56, s.e. 0.14, P = 0.00090).ConclusionsOur results are consistent with epidemiological observations of a negative relationship between SZ and RA reflecting, at least in part, genetic factors. Results of the month of birth analysis are consistent with pleiotropic effects of genetic variants dependent on environmental context.

Schizophrenia is an idiopathic mental disorder with a heritable component and a substantial public health impact. We conducted a multi-stage genome-wide association study (GWAS) for schizophrenia beginning with a Swedish national sample (5,001 cases and 6,243 controls) followed by meta-analysis with previous schizophrenia GWAS (8,832 cases and 12,067 controls) and finally by replication of SNPs in 168 genomic regions in independent samples (7,413 cases, 19,762 controls and 581 parent-offspring trios). We identified 22 loci associated at genome-wide significance; 13 of these are new, and 1 was previously implicated in bipolar disorder. Examination of candidate genes at these loci suggests the involvement of neuronal calcium signaling. We estimate that 8,300 independent, mostly common SNPs (95% credible interval of 6,300-10,200 SNPs) contribute to risk for schizophrenia and that these collectively account for at least 32% of the variance in liability. Common genetic variation has an important role in the etiology of schizophrenia, and larger studies will allow more detailed understanding of this disorder.

ObjectiveMultiple sources of evidence suggest that genetic factors influence variation in clinical features of schizophrenia. The authors present the first genome-wide association study (GWAS) of dimensional symptom scores among individuals with schizophrenia.MethodBased on the Lifetime Dimensions of Psychosis Scale ratings of 2,454 case subjects of European ancestry from the Molecular Genetics of Schizophrenia (MGS) sample, three symptom factors (positive, negative/disorganized, and mood) were identified with exploratory factor analysis. Quantitative scores for each factor from a confirmatory factor analysis were analyzed for association with 696,491 single-nucleotide polymorphisms (SNPs) using linear regression, with correction for age, sex, clinical site, and ancestry. Polygenic score analysis was carried out to determine whether case and comparison subjects in 16 Psychiatric GWAS Consortium (PGC) schizophrenia samples (excluding MGS samples) differed in scores computed by weighting their genotypes by MGS association test results for each symptom factor.ResultsNo genome-wide significant associations were observed between SNPs and factor scores. Most of the SNPs producing the strongest evidence for association were in or near genes involved in neurodevelopment, neuroprotection, or neurotransmission, including genes playing a role in Mendelian CNS diseases, but no statistically significant effect was observed for any defined gene pathway. Finally, polygenic scores based on MGS GWAS results for the negative/disorganized factor were significantly different between case and comparison subjects in the PGC data set; for MGS subjects, negative/disorganized factor scores were correlated with polygenic scores generated using case-control GWAS results from the other PGC samples.ConclusionsThe polygenic signal that has been observed in cross-sample analyses of schizophrenia GWAS data sets could be in part related to genetic effects on negative and disorganized symptoms (i.e., core features of chronic schizophrenia).