A correction for sample overlap in genome-wide association studies in a polygenic pleiotropy-informed framework.

BACKGROUND: There is considerable evidence that many complex traits have a partially shared genetic basis, termed pleiotropy. It is therefore useful to consider integrating genome-wide association study (GWAS) data across several traits, usually at the summary statistic level. A major practical challenge arises when these GWAS have overlapping subjects. This is particularly an issue when estimating pleiotropy using methods that condition the significance of one trait on the signficance of a second, such as the covariate-modulated false discovery rate (cmfdr). RESULTS: We propose a method for correcting for sample overlap at the summary statistic level. We quantify the expected amount of spurious correlation between the summary statistics from two GWAS due to sample overlap, and use this estimated correlation in a simple linear correction that adjusts the joint distribution of test statistics from the two GWAS. The correction is appropriate for GWAS with case-control or quantitative outcomes. Our simulations and data example show that without correcting for sample overlap, the cmfdr is not properly controlled, leading to an excessive number of false discoveries and an excessive false discovery proportion. Our correction for sample overlap is effective in that it restores proper control of the false discovery rate, at very little loss in power. CONCLUSIONS: With our proposed correction, it is possible to integrate GWAS summary statistics with overlapping samples in a statistical framework that is dependent on the joint distribution of the two GWAS

Using brain cell-type-specific protein interactomes to interpret neurodevelopmental genetic signals in schizophrenia

Genetics have nominated many schizophrenia risk genes and identified convergent signals between schizophrenia and neurodevelopmental disorders. However, functional interpretation of the nominated genes in the relevant brain cell types is often lacking. We executed interaction proteomics for six schizophrenia risk genes that have also been implicated in neurodevelopment in human induced cortical neurons. The resulting protein network is enriched for common variant risk of schizophrenia in Europeans and East Asians, is down-regulated in layer 5/6 cortical neurons of individuals affected by schizophrenia, and can complement fine-mapping and eQTL data to prioritize additional genes in GWAS loci. A sub-network centered on HCN1 is enriched for common variant risk and contains proteins (HCN4 and AKAP11) enriched for rare protein-truncating mutations in individuals with schizophrenia and bipolar disorder. Our findings showcase brain cell-type-specific interactomes as an organizing framework to facilitate interpretation of genetic and transcriptomic data in schizophrenia and its related disorders

Mathematical models for immunology:current state of the art and future research directions

The advances in genetics and biochemistry that have taken place over the last 10 years led to significant advances in experimental and clinical immunology. In turn, this has led to the development of new mathematical models to investigate qualitatively and quantitatively various open questions in immunology. In this study we present a review of some research areas in mathematical immunology that evolved over the last 10 years. To this end, we take a step-by-step approach in discussing a range of models derived to study the dynamics of both the innate and immune responses at the molecular, cellular and tissue scales. To emphasise the use of mathematics in modelling in this area, we also review some of the mathematical tools used to investigate these models. Finally, we discuss some future trends in both experimental immunology and mathematical immunology for the upcoming years

Age at first birth in women is genetically associated with increased risk of schizophrenia

Previous studies have shown an increased risk for mental health problems in children born to both younger and older parents compared to children of average-aged parents. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age at first birth in women (AFB). Here, we use independent data from the UK Biobank (N = 38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, and to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value = 1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value = 3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is -0.16 (SE = 0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE = 0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia in the UK Biobank sample. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health

Biosynthesis, characterization, and antimicrobial applications of silver nanoparticles

Priyanka Singh,1 Yeon Ju Kim,2 Hina Singh,1 Chao Wang,2 Kyu Hyon Hwang,3 Mohamed El-Agamy Farh,1 Deok Chun Yang1,2 1Department of Oriental Medicinal Material and Processing, 2Graduate School of Biotechnology and Ginseng Bank, College of Life Sciences, Kyung Hee University, Yongin, 3Gyeonggi-Do Agricultural Research & Extension Services, Gyeonggi, Republic of Korea Abstract: In the present study, the strain Brevibacterium frigoritolerans DC2 was explored for the efficient and extracellular synthesis of silver nanoparticles. These biosynthesized silver nanoparticles were characterized by ultraviolet-visible spectrophotometry, which detected the formation of silver nanoparticles in the reaction mixture and showed a maximum absorbance at 420 nm. In addition, field emission transmission electron microscopy revealed the spherical shape of the nanoparticles. The dynamic light scattering results indicated the average particle size of the product was 97 nm with a 0.191 polydispersity index. Furthermore, the product was analyzed by energy dispersive X-ray spectroscopy, X-ray diffraction, and elemental mapping, which displayed the presence of elemental silver in the product. Moreover, on a medical platform, the product was checked against pathogenic microorganisms including Vibrio parahaemolyticus, Salmonella enterica, Bacillus anthracis, Bacillus cereus, Escherichia coli, and Candida albicans. The nanoparticles demonstrated antimicrobial activity against all of these pathogenic microorganisms. Additionally, the silver nanoparticles were evaluated for their combined effects with the commercial antibiotics lincomycin, oleandomycin, vancomycin, novobiocin, penicillin G, and rifampicin against these pathogenic microorganisms. These results indicated that the combination of antibiotics with biosynthesized silver nanoparticles enhanced the antimicrobial effects of antibiotics. Therefore, the current study is a demonstration of an efficient biological synthesis of silver nanoparticles by B. frigoritolerans DC2 and its effect on the enhancement of the antmicrobial efficacy of well-known commercial antibiotics. Keywords: Brevibacterium frigoritolerans, biosynthesis, silver nanoparticles, antimicrobial activity, synergistic effec

Inter-individual variability and genetic influences on cytokine responses to bacteria and fungi

Little is known about the inter-individual variation of cytokine responses to different pathogens in healthy individuals. To systematically describe cytokine responses elicited by distinct pathogens and to determine the effect of genetic variation on cytokine production, we profiled cytokines produced by peripheral blood mononuclear cells from 197 individuals of European origin from the 200 Functional Genomics (200FG) cohort in the Human Functional Genomics Project (http://www.humanfunctionalgenomics.org), obtained over three different years. We compared bacteria- and fungi-induced cytokine profiles and found that most cytokine responses were organized around a physiological response to specific pathogens, rather than around a particular immune pathway or cytokine. We then correlated genome-wide single-nucleotide polymorphism (SNP) genotypes with cytokine abundance and identified six cytokine quantitative trait loci (QTLs). Among them, a cytokine QTL at the NAA35-GOLM1 locus markedly modulated interleukin (IL)-6 production in response to multiple pathogens and was associated with susceptibility to candidemia. Furthermore, the cytokine QTLs that we identified were enriched among SNPs previously associated with infectious diseases and heart diseases. These data reveal and begin to explain the variability in cytokine production by human immune cells in response to pathogens