Atrazine and cancer incidence among pesticide applicators in the agricultural health study (1994-2007).

Atrazine is a triazine herbicide used widely in the United States. Although it is an animal carcinogen, the mechanism in rodents does not appear to operate in humans. Few epidemiologic studies have provided evidence for an association

Respiratory Cancer and Inhaled Inorganic Arsenic in Copper Smelters Workers: A Linear Relationship with Cumulative Exposure that Increases with Concentration

BACKGROUND: Inhalation of high levels of airborne inorganic arsenic is a recognized cause of respiratory cancer. Although multiple epidemiologic studies have demonstrated this association, there have been few analyses of the mathematical relationship between cumulative arsenic exposure and risk of respiratory cancer, and no assessment as to whether and how arsenic concentration may modify this association. OBJECTIVES: The objective is an evaluation of the shape of the relationship between respiratory cancer mortality and cumulative inhaled arsenic exposure among copper smelter workers, and the modification of that relationship by arsenic concentration. METHODS: We used Poisson regression methods to analyze data from a cohort of arsenic-exposed copper smelter workers under a linear-exponential model for the excess relative risk. RESULTS: Within categories of arsenic concentration, the association between respiratory cancer and cumulative arsenic exposure was consistent with linearity. The slope of the linear relationship with cumulative exposure increased with increasing arsenic concentration category. CONCLUSIONS: Our results suggested a direct concentration effect from inhaled inorganic arsenic, whereby the excess relative risk for a fixed cumulative exposure was greater when delivered at a higher concentration and shorter duration than when delivered at a lower concentration and longer duration. KEY WORDS: arsenic, dose–response relationship, lung neoplasms, occupational diseases. Environ Health Perspect 116:1661–1665 (2008). doi:10.1289/ehp.11515 available vi

Safeguarding human–wildlife cooperation

Human–wildlife cooperation occurs when humans and free-living wild animals actively coordinate their behavior to achieve a mutually beneficial outcome. These interactions provide important benefits to both the human and wildlife communities involved, have wider impacts on the local ecosystem, and represent a unique intersection of human and animal cultures. The remaining active forms are human–honeyguide and human–dolphin cooperation, but these are at risk of joining several inactive forms (including human–wolf and human–orca cooperation). Human–wildlife cooperation faces a unique set of conservation challenges, as it requires multiple components—a motivated human and wildlife partner, a suitable environment, and compatible interspecies knowledge—which face threats from ecological and cultural changes. To safeguard human–wildlife cooperation, we recommend: (i) establishing ethically sound conservation strategies together with the participating human communities; (ii) conserving opportunities for human and wildlife participation; (iii) protecting suitable environments; (iv) facilitating cultural transmission of traditional knowledge; (v) accessibly archiving Indigenous and scientific knowledge; and (vi) conducting long-term empirical studies to better understand these interactions and identify threats. Tailored safeguarding plans are therefore necessary to protect these diverse and irreplaceable interactions. Broadly, our review highlights that efforts to conserve biological and cultural diversity should carefully consider interactions between human and animal cultures

Multiple Recurrent De Novo CNVs, Including Duplications of the 7q11.23 Williams Syndrome Region, Are Strongly Associated with Autism

SummaryWe have undertaken a genome-wide analysis of rare copy-number variation (CNV) in 1124 autism spectrum disorder (ASD) families, each comprised of a single proband, unaffected parents, and, in most kindreds, an unaffected sibling. We find significant association of ASD with de novo duplications of 7q11.23, where the reciprocal deletion causes Williams-Beuren syndrome, characterized by a highly social personality. We identify rare recurrent de novo CNVs at five additional regions, including 16p13.2 (encompassing genes USP7 and C16orf72) and Cadherin 13, and implement a rigorous approach to evaluating the statistical significance of these observations. Overall, large de novo CNVs, particularly those encompassing multiple genes, confer substantial risks (OR = 5.6; CI = 2.6–12.0, p = 2.4 × 10-7). We estimate there are 130–234 ASD-related CNV regions in the human genome and present compelling evidence, based on cumulative data, for association of rare de novo events at 7q11.23, 15q11.2-13.1, 16p11.2, and Neurexin 1

Variability in Working Memory Performance Explained by Epistasis vs Polygenic Scores in the ZNF804A Pathway

Importance: We investigated the variation in neuropsychological function explained by risk alleles at the psychosis susceptibility gene ZNF804A and its interacting partners using single nucleotide polymorphisms (SNPs), polygenic scores, and epistatic analyses. Of particular importance was the relative contribution of the polygenic score vs epistasis in variation explained. Objectives To (1) assess the association between SNPs in ZNF804A and the ZNF804A polygenic score with measures of cognition in cases with psychosis and (2) assess whether epistasis within the ZNF804A pathway could explain additional variation above and beyond that explained by the polygenic score. Design, Setting, and Participants: Patients with psychosis (n = 424) were assessed in areas of cognitive ability impaired in schizophrenia including IQ, memory, attention, and social cognition. We used the Psychiatric GWAS Consortium 1 schizophrenia genome-wide association study to calculate a polygenic score based on identified risk variants within this genetic pathway. Cognitive measures significantly associated with the polygenic score were tested for an epistatic component using a training set (n = 170), which was used to develop linear regression models containing the polygenic score and 2-SNP interactions. The best-fitting models were tested for replication in 2 independent test sets of cases: (1) 170 individuals with schizophrenia or schizoaffective disorder and (2) 84 patients with broad psychosis (including bipolar disorder, major depressive disorder, and other psychosis). Main Outcomes and Measures: Participants completed a neuropsychological assessment battery designed to target the cognitive deficits of schizophrenia including general cognitive function, episodic memory, working memory, attentional control, and social cognition. Results: Higher polygenic scores were associated with poorer performance among patients on IQ, memory, and social cognition, explaining 1% to 3% of variation on these scores (range, P = .01 to .03). Using a narrow psychosis training set and independent test sets of narrow phenotype psychosis (schizophrenia and schizoaffective disorder), broad psychosis, and control participants (n = 89), the addition of 2 interaction terms containing 2 SNPs each increased the R2 for spatial working memory strategy in the independent psychosis test sets from 1.2% using the polygenic score only to 4.8% (P = .11 and .001, respectively) but did not explain additional variation in control participants. Conclusions and Relevance: These data support a role for the ZNF804A pathway in IQ, memory, and social cognition in cases. Furthermore, we showed that epistasis increases the variation explained above the contribution of the polygenic score

A Systematic Review of the Prevalence of Schizophrenia

BACKGROUND: Understanding the prevalence of schizophrenia has important implications for both health service planning and risk factor epidemiology. The aims of this review are to systematically identify and collate studies describing the prevalence of schizophrenia, to summarize the findings of these studies, and to explore selected factors that may influence prevalence estimates. METHODS AND FINDINGS: Studies with original data related to the prevalence of schizophrenia (published 1965–2002) were identified via searching electronic databases, reviewing citations, and writing to authors. These studies were divided into “core” studies, “migrant” studies, and studies based on “other special groups.” Between- and within-study filters were applied in order to identify discrete prevalence estimates. Cumulative plots of prevalence estimates were made and the distributions described when the underlying estimates were sorted according to prevalence type (point, period, lifetime, and lifetime morbid risk). Based on combined prevalence estimates, the influence of selected key variables was examined (sex, urbanicity, migrant status, country economic index, and study quality). A total of 1,721 prevalence estimates from 188 studies were identified. These estimates were drawn from 46 countries, and were based on an estimated 154,140 potentially overlapping prevalent cases. We identified 132 core studies, 15 migrant studies, and 41 studies based on other special groups. The median values per 1,000 persons (10%–90% quantiles) for the distributions for point, period, lifetime, and lifetime morbid risk were 4.6 (1.9–10.0), 3.3 (1.3–8.2), 4.0 (1.6–12.1), and 7.2 (3.1–27.1), respectively. Based on combined prevalence estimates, we found no significant difference (a) between males and females, or (b) between urban, rural, and mixed sites. The prevalence of schizophrenia in migrants was higher compared to native-born individuals: the migrant-to-native-born ratio median (10%–90% quantile) was 1.8 (0.9–6.4). When sites were grouped by economic status, prevalence estimates from “least developed” countries were significantly lower than those from both “emerging” and “developed” sites (p = 0.04). Studies that scored higher on a quality score had significantly higher prevalence estimates (p = 0.02). CONCLUSIONS: There is a wealth of data about the prevalence of schizophrenia. These gradients, and the variability found in prevalence estimate distributions, can provide direction for future hypothesis-driven research