Cross-tissue eQTL enrichment of associations in schizophrenia.

The genome-wide association study of the Psychiatric Genomics Consortium identified over one hundred schizophrenia susceptibility loci. The number of non-coding variants discovered suggests that gene regulation could mediate the effect of these variants on disease. Expression quantitative trait loci (eQTLs) contribute to variation in levels of mRNA. Given the co-occurrence of schizophrenia and several traits not involving the central nervous system (CNS), we investigated the enrichment of schizophrenia associations among eQTLs for four non-CNS tissues: adipose tissue, epidermal tissue, lymphoblastoid cells and blood. Significant enrichment was seen in eQTLs of all tissues: adipose (β = 0.18, p = 8.8 × 10−06), epidermal (β = 0.12, p = 3.1 × 10−04), lymphoblastoid (β = 0.19, p = 6.2 × 10−08) and blood (β = 0.19, p = 6.4 × 10−06). For comparison, we looked for enrichment of association with traits of known relevance to one or more of these tissues (body mass index, height, rheumatoid arthritis, systolic blood pressure and type-II diabetes) and found that schizophrenia enrichment was of similar scale to that observed when studying diseases in the context of a more likely causal tissue. To further investigate tissue specificity, we looked for differential enrichment of eQTLs with relevant Roadmap affiliation (enhancers and promoters) and varying distance from the transcription start site. Neither factor significantly contributed to the enrichment, suggesting that this is equally distributed in tissue-specific and cross-tissue regulatory elements. Our analyses suggest that functional correlates of schizophrenia risk are prevalent in non-CNS tissues. This could be because of pleiotropy or the effectiveness of variants affecting expression in different contexts. This suggests the utility of large, single-tissue eQTL experiments to increase eQTL discovery power in the study of schizophrenia, in addition to smaller, multiple-tissue approaches. Our results conform to the notion that schizophrenia is a systemic disorder involving many tissues

Draft Genome Sequence of the Marine Streptomyces sp. Strain PP-C42, Isolated from the Baltic Sea

Streptomyces, a branch of aerobic Gram-positive bacteria represents the largest genus of actinobacteria. The streptomycetes are characterized by a complex secondary metabolism and produce over two-thirds of the clinically used natural antibiotics today. Here we report the draft genome sequence of a Streptomyces strain PP-C42 isolated from the marine environment. A subset of unique genes and gene clusters for diverse secondary metabolites as well as antimicrobial peptides (AMPs) could be identified from the genome, showing great promise as a source for novel bioactive compound

Draft Genome Sequence of the Marine Streptomyces sp. Strain PP-C42, Isolated from the Baltic Sea

Streptomyces, a branch of aerobic Gram-positive bacteria represents the largest genus of actinobacteria. The streptomycetes are characterized by a complex secondary metabolism and produce over two-thirds of the clinically used natural antibiotics today. Here we report the draft genome sequence of a Streptomyces strain PP-C42 isolated from the marine environment. A subset of unique genes and gene clusters for diverse secondary metabolites as well as antimicrobial peptides (AMPs) could be identified from the genome, showing great promise as a source for novel bioactive compound

Estimating effect sizes and expected replication probabilities from GWAS summary statistics

Genome-wide Association Studies (GWAS) result in millions of summary statistics (“z-scores”) for single nucleotide polymorphism (SNP) associations with phenotypes. These rich datasets afford deep insights into the nature and extent of genetic contributions to complex phenotypes such as psychiatric disorders, which are understood to have substantial genetic components that arise from very large numbers of SNPs. The complexity of the datasets, however, poses a significant challenge to maximizing their utility. This is reflected in a need for better understanding the landscape of z-scores, as such knowledge would enhance causal SNP and gene discovery, help elucidate mechanistic pathways, and inform future study design. Here we present a parsimonious methodology for modeling effect sizes and replication probabilities, relying only on summary statistics from GWAS substudies, and a scheme allowing for direct empirical validation. We show that modeling z-scores as a mixture of Gaussians is conceptually appropriate, in particular taking into account ubiquitous non-null effects that are likely in the datasets due to weak linkage disequilibrium with causal SNPs. The four-parameter model allows for estimating the degree of polygenicity of the phenotype and predicting the proportion of chip heritability explainable by genome-wide significant SNPs in future studies with larger sample sizes. We apply the model to recent GWAS of schizophrenia (N = 82,315) and putamen volume (N = 12,596), with approximately 9.3 million SNP z-scores in both cases. We show that, over a broad range of z-scores and sample sizes, the model accurately predicts expectation estimates of true effect sizes and replication probabilities in multistage GWAS designs. We assess the degree to which effect sizes are over-estimated when based on linear-regression association coefficients. We estimate the polygenicity of schizophrenia to be 0.037 and the putamen to be 0.001, while the respective sample sizes required to approach fully explaining the chip heritability are 106 and 105. The model can be extended to incorporate prior knowledge such as pleiotropy and SNP annotation. The current findings suggest that the model is applicable to a broad array of complex phenotypes and will enhance understanding of their genetic architectures

Identification of shared genetic variants between schizophrenia and lung cancer.

Epidemiology studies suggest associations between schizophrenia and cancer. However, the underlying genetic mechanisms are not well understood, and difficult to identify from epidemiological data. We investigated if there is a shared genetic architecture between schizophrenia and cancer, with the aim to identify specific overlapping genetic loci. First, we performed genome-wide enrichment analysis and second, we analyzed specific loci jointly associated with schizophrenia and cancer by the conjunction false discovery rate. We analyzed the largest genome-wide association studies of schizophrenia and lung, breast, prostate, ovary, and colon-rectum cancer including more than 220,000 subjects, and included genetic association with smoking behavior. Polygenic enrichment of associations with lung cancer was observed in schizophrenia, and weak enrichment for the remaining cancer sites. After excluding the major histocompatibility complex region, we identified three independent loci jointly associated with schizophrenia and lung cancer. The strongest association included nicotinic acetylcholine receptors and is an established pleiotropic locus shared between lung cancer and smoking. The two other loci were independent of genetic association with smoking. Functional analysis identified downstream pleiotropic effects on epigenetics and gene-expression in lung and brain tissue. These findings suggest that genetic factors may explain partly the observed epidemiological association of lung cancer and schizophrenia

Nucleation of a sodium droplet on C60

We investigate theoretically the progressive coating of C60 by several sodium atoms. Density functional calculations using a nonlocal functional are performed for NaC60 and Na2C60 in various configurations. These data are used to construct an empirical atomistic model in order to treat larger sizes in a statistical and dynamical context. Fluctuating charges are incorporated to account for charge transfer between sodium and carbon atoms. By performing systematic global optimization in the size range 1<=n<=30, we find that Na_nC60 is homogeneously coated at small sizes, and that a growing droplet is formed above n=>8. The separate effects of single ionization and thermalization are also considered, as well as the changes due to a strong external electric field. The present results are discussed in the light of various experimental data.Comment: 17 pages, 10 figure

Leveraging genomic annotations and pleiotropic enrichment for improved replication rates in schizophrenia GWAS

Most of the genetic architecture of schizophrenia (SCZ) has not yet been identified. Here, we apply a novel statistical algorithm called Covariate-Modulated Mixture Modeling (CM3), which incorporates auxiliary information (heterozygosity, total linkage disequilibrium, genomic annotations, pleiotropy) for each single nucleotide polymorphism (SNP) to enable more accurate estimation of replication probabilities, conditional on the observed test statistic (“z-score”) of the SNP. We use a multiple logistic regression on z-scores to combine information from auxiliary information to derive a “relative enrichment score” for each SNP. For each stratum of these relative enrichment scores, we obtain nonparametric estimates of posterior expected test statistics and replication probabilities as a function of discovery z-scores, using a resampling-based approach that repeatedly and randomly partitions meta-analysis sub-studies into training and replication samples. We fit a scale mixture of two Gaussians model to each stratum, obtaining parameter estimates that minimize the sum of squared differences of the scale-mixture model with the stratified nonparametric estimates. We apply this approach to the recent genome-wide association study (GWAS) of SCZ (n = 82,315), obtaining a good fit between the model-based and observed effect sizes and replication probabilities. We observed that SNPs with low enrichment scores replicate with a lower probability than SNPs with high enrichment scores even when both they are genome-wide significant (p < 5x10-8). There were 693 and 219 independent loci with model-based replication rates ≥80% and ≥90%, respectively. Compared to analyses not incorporating relative enrichment scores, CM3 increased out-of-sample yield for SNPs that replicate at a given rate. This demonstrates that replication probabilities can be more accurately estimated using prior enrichment information with CM3

Impact of children's migration on health and health care-seeking behavior of elderly left behind

<p>Abstract</p> <p>Background</p> <p>Many countries are facing the burden of accelerated population aging and a lack of institutional support to meet the needs of older individuals. In developing countries, adult children are primarily responsible for the care of their elderly parents. However, out-migration of adult children is common in these countries. This study aims to explore the impact of migration on the health of the elderly left behind and their health care-seeking behavior.</p> <p>Methods</p> <p>This paper uses data from a national survey of older persons in Thailand conducted in 2007. The analysis is confined to those who were aged 60 years or above and who had at least one child (biological or step/adopted) (n = 28,677). Logistic regression was used to assess the net effect of migration of adult children on the health of the elderly left behind and their health care-seeking behavior, after controlling for other socio-demographic and economic variables.</p> <p>Results</p> <p>More than two-thirds of the elderly (67%) had at least one migrant child. About three-fifths (58%) reported that they had at least one symptom of poor mental health. Almost three in five elderly (56%) rated their health as poor, and 44% had experienced at least one chronic disease. About two-thirds of the elderly (65%) got sick during the 5 years preceding the survey. An overwhelming majority of elderly (88%) who got sick during the five years preceding the survey had sought treatment for their last illness.</p> <p>After controlling for socio-demographic and economic variables, our study found that those elderly who had a migrant child were more likely (OR = 1.10; 95% CI 1.05-1.17) to have symptoms of poor mental health than those whose children had not migrated. However, no significant association was observed among physical health, such as experience of chronic disease, perceived poor health, and illness of the elderly left behind. Interestingly, however, out-migration of adult children was independently associated with higher utilization of health services. The elderly who had migrant children were more likely (odds ratio = 1.22, CI 1.11-1.33) than those whose children had not migrated to seek treatment for their most recent illness, after controlling for socio-demographic and economic variables.</p> <p>Conclusion</p> <p>Our study provides novel evidence on an issue of special importance to countries affected by heavy out-migration of adult children, an issue that has received little attention. Out-migration of adult children was highly associated with poor mental health but it was not associated with the physical health of the elderly left behind. Out-migration of children was also highly associated with higher utilization of health facilities by the elderly. Thus, in order to decrease morbidity among the elderly as well as to maintain and enhance the well-being of families, programs should focus on alleviating the symptoms of poor mental health among the elderly left behind and aim to reduce the differences in utilization of health care-seeking behavior among elderly with children present in the community and elderly left behind.</p

Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score

Background Identifying individuals at risk for developing Alzheimer disease (AD) is of utmost importance. Although genetic studies have identified AD-associated SNPs in APOE and other genes, genetic information has not been integrated into an epidemiological framework for risk prediction. Methods and findings Using genotype data from 17,008 AD cases and 37,154 controls from the International Genomics of Alzheimer’s Project (IGAP Stage 1), we identified AD-associated SNPs (at p < 10−5 ). We then integrated these AD-associated SNPs into a Cox proportional hazard model using genotype data from a subset of 6,409 AD patients and 9,386 older controls from Phase 1 of the Alzheimer’s Disease Genetics Consortium (ADGC), providing a polygenic hazard score (PHS) for each participant. By combining population-based incidence rates and the genotype-derived PHS for each individual, we derived estimates of instantaneous risk for developing AD, based on genotype and age, and tested replication in multiple independent cohorts (ADGC Phase 2, National Institute on Aging Alzheimer’s Disease Center [NIA ADC], and Alzheimer’s Disease Neuroimaging Initiative [ADNI], total n = 20,680). Within the ADGC Phase 1 cohort, individuals in the highest PHS quartile developed AD at a considerably lower age and had the highest yearly AD incidence rate. Among APOE ε3/3 individuals, the PHS modified expected age of AD onset by more than 10 y between the lowest and highest deciles (hazard ratio 3.34, 95% CI 2.62–4.24, p = 1.0 × 10−22). In independent cohorts, the PHS strongly predicted empirical age of AD onset (ADGC Phase 2, r = 0.90, p = 1.1 × 10−26) and longitudinal progression from normal aging to AD (NIA ADC, Cochran–Armitage trend test, p = 1.5 × 10−10), and was associated with neuropathology (NIA ADC, Braak stage of neurofibrillary tangles, p = 3.9 × 10−6 , and Consortium to Establish a Registry for Alzheimer’s Disease score for neuritic plaques, p = 6.8 × 10−6 ) and in vivo markers of AD neurodegeneration (ADNI, volume loss within the entorhinal cortex, p = 6.3 × 10−6 , and hippocampus, p = 7.9 × 10−5 ). Additional prospective validation of these results in non-US, non-white, and prospective community-based cohorts is necessary before clinical use. Conclusions We have developed a PHS for quantifying individual differences in age-specific genetic risk for AD. Within the cohorts studied here, polygenic architecture plays an important role in modifying AD risk beyond APOE. With thorough validation, quantification of inherited genetic variation may prove useful for stratifying AD risk and as an enrichment strategy in therapeutic trials

The Kolumbo submarine volcano of Santorini island is a large pool of bacterial strains with antimicrobial activity

Microbes in hydrothermal vents with their unique secondary metabolism may represent an untapped potential source of new natural products. In this study, samples were collected from the hydrothermal field of Kolumbo submarine volcano in the Aegean Sea, in order to isolate bacteria with antimicrobial activity. Eight hundred and thirty-two aerobic heterotrophic bacteria were isolated and then differentiated through BOX-PCR analysis at the strain level into 230 genomic fingerprints, which were screened against 13 different type strains (pathogenic and nonpathogenic) of Gram-positive, Gram-negative bacteria and fungi. Forty-two out of 176 bioactive-producing genotypes (76 %) exhibited antimicrobial activity against at least four different type strains and were selected for 16S rDNA sequencing and screening for nonribosomal peptide (NRPS) and polyketide (PKS) synthases genes. The isolates were assigned to genus Bacillus and Proteobacteria, and 20 strains harbored either NRPS, PKS type I or both genes. This is the first report on the diversity of culturable mesophilic bacteria associated with antimicrobial activity from Kolumbo area; the extremely high proportion of antimicrobial-producing strains suggested that this unique environment may represent a potential reservoir of novel bioactive compounds