Correction: Leveraging correlations between variants in polygenic risk scores to detect heterogeneity in GWAS cohorts.

[This corrects the article DOI: 10.1371/journal.pgen.1009015.].

Leveraging correlations between variants in polygenic risk scores to detect heterogeneity in GWAS cohorts.

Evidence from both GWAS and clinical observation has suggested that certain psychiatric, metabolic, and autoimmune diseases are heterogeneous, comprising multiple subtypes with distinct genomic etiologies and Polygenic Risk Scores (PRS). However, the presence of subtypes within many phenotypes is frequently unknown. We present CLiP (Correlated Liability Predictors), a method to detect heterogeneity in single GWAS cohorts. CLiP calculates a weighted sum of correlations between SNPs contributing to a PRS on the case/control liability scale. We demonstrate mathematically and through simulation that among i.i.d. homogeneous cases generated by a liability threshold model, significant anti-correlations are expected between otherwise independent predictors due to ascertainment on the hidden liability score. In the presence of heterogeneity from distinct etiologies, confounding by covariates, or mislabeling, these correlation patterns are altered predictably. We further extend our method to two additional association study designs: CLiP-X for quantitative predictors in applications such as transcriptome-wide association, and CLiP-Y for quantitative phenotypes, where there is no clear distinction between cases and controls. Through simulations, we demonstrate that CLiP and its extensions reliably distinguish between homogeneous and heterogeneous cohorts when the PRS explains as low as 3% of variance on the liability scale and cohorts comprise 50, 000 - 100, 000 samples, an increasingly practical size for modern GWAS. We apply CLiP to heterogeneity detection in schizophrenia cohorts totaling > 50, 000 cases and controls collected by the Psychiatric Genomics Consortium. We observe significant heterogeneity in mega-analysis of the combined PGC data (p-value 8.54 × 0-4), as well as in individual cohorts meta-analyzed using Fisher's method (p-value 0.03), based on significantly associated variants. We also apply CLiP-Y to detect heterogeneity in neuroticism in over 10, 000 individuals from the UK Biobank and detect heterogeneity with a p-value of 1.68 × 10-9. Scores were not significantly reduced when partitioning by known subclusters ("Depression" and "Worry"), suggesting that these factors are not the primary source of observed heterogeneity.

Resilience of aggregated microbial communities subjected to drought--small-scale studies.

The response of microbial communities to disturbance is a major concern for microbial ecologists since potential modifications in their composition and functioning may affect ecosystems to a larger extent. Microbial ecosystems may be resistant (not affected) or may present engineering (return to initial state) or ecological resilience. In the latter case, when the disturbance is released, the ecosystem evolves towards a new equilibrium state. The aim of this study was to determine if variations in the magnitude of a disturbance could induce either engineering or ecological resilience. We used phototrophic biofilms grown in mesocosms as a model of microbial ecosystem and increasing drought duration (1-8 weeks) as a range of disturbances. Biofilm composition (algal and prokaryotic), photosynthetic activity (PhytoPAM), and potential functional diversity (Biolog) were determined at the end of dry phase and after a 2-week rewetting phase in individual aquaria. We only observed an ecological resilience of the biofilm, with a resistance of phototrophic component for the weakest disturbance. After rewetting, the biofilm could fulfill the same functions, but its species composition was highly modified. We observed a shift from cyanobacteria dominance towards diatom dominance. The disturbance caused a transition towards a new steady state of the biofilm. We also observed a positive effect of stress duration on biofilm productivity after resilience.

Silver nanoparticles impact phototrophic biofilm communities to a considerably higher degree than ionic silver.

Due to the significant increase in nanoparticle production and especially that of silver nanoparticles over the past decade, the toxicity of silver in both ionic (Ag(+)) and nanoparticulate (AgNPs) form must be studied in detail in order to understand their impact on natural ecosystems. A comparative study of the effect of AgNPs and ionic silver on two independent phototrophic biofilms was conducted in a rotating annular bioreactor (RAB) operating under constant conditions. The concentration of dissolved silver in the inlet solution was progressively increased every 4 days of exposure, from 0.1 to 100 µg L(-1). In the course of the 40-day experiment, biofilm samples were collected to determine the evolution of biomass, chlorophyll-a, as well as photosynthetic and heterotrophic enzymatic activities in response to silver addition. Analysis of both dissolved and particulate silver allowed quantification of the distribution coefficient and uptake rate constants. The presence of both AgNPs and Ag(+) produced significant changes in the biofilm structure, decreasing the relative percentage of Diatomophyceae and Cyanophyceae and increasing the relative percentage of Chlorophyceae. The accumulation capacity of the phototrophic biofilm with respect to ionic silver and the corresponding distribution coefficients were an order of magnitude higher than those of the phototrophic biofilm with respect to AgNPs. Higher levels of AgNPs decreased the biomass from 8.6 ± 0.2 mg cm(-2) for 0-10 µg L(-1) AgNPs to 6.0 ± 0.1 mg cm(-2) for 100 µg L(-1) added AgNPs, whereas ionic silver did not have any toxic effect on the biofilm growth up to 100 µg L(-1) of added Ag(+). At the same time, AgNPs did not significantly affect the photosynthetic activity of the biofilm surface communities compared to Ag(+). It can thus be hypothesized that negatively charged AgNPs may travel through the biofilm water channels, thereby affecting the whole biofilm structure. In contrast, positively charged Ag(+) is bound at the cell surfaces and EPS, thus blocking its further flux within the biofilm layers. On the whole, the phototrophic biofilm demonstrated significant capacities to accumulate silver within the surface layers. The main mechanism to avoid the toxic effects is metal complexation with exopolysaccharides and accumulation within cell walls, especially pronounced under Ag(+) stress. The significant AgNPs and Ag(+) uptake capacities of phototrophic biofilm make it a highly resistant ecosystem in silver-polluted river waters.