Bright quasars, powered by accretion onto billion-solar-mass black holes, already existed at the epoch of reionization, when the Universe was 0.5-1 billion years old(1). How these black holes... Show moreBright quasars, powered by accretion onto billion-solar-mass black holes, already existed at the epoch of reionization, when the Universe was 0.5-1 billion years old(1). How these black holes formed in such a short time isthe subject of debate, particularly asthey lie above the correlation between black-hole mass and galaxy dynamical mass(2,3) in the local Universe. What slowed down black-hole growth, leading towards the symbioticgrowth observed in the local Universe, and when this process started, has hitherto not been known, although black-hole feedback is a likely driver(4). Here we report optical and near-infrared observations of a sample of quasars at redshifts 5.8 less than or similar to z less than or similar to 6.6. About half ofthe quasar spectra reveal broad, blueshifted absorption line troughs, tracing black-hole-driven winds with extreme outflowvelocities, up to 17% of the speed of light. The fraction of quasars with such outflow winds at z greater than or similar to 5.8 approximate to 2.4 is times higher than at z approximate to 2-4. We infer that outflows at z greater than or similar to 5.8 inject large amounts of energy into the interstellar medium and suppress nuclear gas accretion, slowing down black-hole growth. The outflow phase may then mark the beginning of substantial black-hole feedback. The red optical colours of outflow quasars at z greater than or similar to 5.8 indeed suggest that these systems are dusty and may be caught during an initial quenching phase of obscured accretion(5). Show less
Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could... Show morePolygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs. Show less
