Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. - Evangelou, Evangelos; Warren, Helen R; Mosen-Ansorena, David; Mifsud, Borbala; Pazoki, Raha; Gao, He; Ntritsos, Georgios; Dimou, Niki; Cabrera, Claudia P; Karaman, Ibrahim; Ng, Fu Liang; Evangelou, Marina; et al. (Nat Genet, 2018)
High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.

Genome-wide association meta-analysis highlights light-induced signaling as a driver for refractive error. - Tedja, Milly S; Wojciechowski, Robert; Hysi, Pirro G; Eriksson, Nicholas; Furlotte, Nicholas A; Verhoeven, Virginie J M; Iglesias, Adriana I; Meester-Smoor, Magda A; Tompson, Stuart W; Fan, Qiao; Khawaja, Anthony P; Cheng, Ching-Yu; et al. (Nat Genet, 2018)
Refractive errors, including myopia, are the most frequent eye disorders worldwide and an increasingly common cause of blindness. This genome-wide association meta-analysis in 160,420 participants and replication in 95,505 participants increased the number of established independent signals from 37 to 161 and showed high genetic correlation between Europeans and Asians (>0.78). Expression experiments and comprehensive in silico analyses identified retinal cell physiology and light processing as prominent mechanisms, and also identified functional contributions to refractive-error development in all cell types of the neurosensory retina, retinal pigment epithelium, vascular endothelium and extracellular matrix. Newly identified genes implicate novel mechanisms such as rod-and-cone bipolar synaptic neurotransmission, anterior-segment morphology and angiogenesis. Thirty-one loci resided in or near regions transcribing small RNAs, thus suggesting a role for post-transcriptional regulation. Our results support the notion that refractive errors are caused by a light-dependent retina-to-sclera signaling cascade and delineate potential pathobiological molecular drivers.

Genome-wide association study identifies 74 loci associated with educational attainment. - Okbay, Aysu; Beauchamp, Jonathan P; Fontana, Mark Alan; Lee, James J; Pers, Tune H; Rietveld, Cornelius A; Turley, Patrick; Chen, Guo-Bo; Emilsson, Valur; Meddens, S Fleur W; Oskarsson, Sven; Pickrell, Joseph K; et al. (Nature, 2016)
Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.
Keywords: Alzheimer Disease; Bipolar Disorder; Brain; Cognition; Computational Biology; Educational Status; Fetus; Gene Expression Regulation; Gene-Environment Interaction; Genome-Wide Association Study; Great Britain; Humans; Molecular Sequence Annotation; Polymorphism, Single Nucleotide; Schizophrenia

A general approach for haplotype phasing across the full spectrum of relatedness. - O'Connell, Jared; Gurdasani, Deepti; Delaneau, Olivier; Pirastu, Nicola; Ulivi, Sheila; Cocca, Massimiliano; Traglia, Michela; Huang, Jie; Huffman, Jennifer E; Rudan, Igor; McQuillan, Ruth; Fraser, Ross M; et al. (PLoS Genet, 2014)
Many existing cohorts contain a range of relatedness between genotyped individuals, either by design or by chance. Haplotype estimation in such cohorts is a central step in many downstream analyses. Using genotypes from six cohorts from isolated populations and two cohorts from non-isolated populations, we have investigated the performance of different phasing methods designed for nominally 'unrelated' individuals. We find that SHAPEIT2 produces much lower switch error rates in all cohorts compared to other methods, including those designed specifically for isolated populations. In particular, when large amounts of IBD sharing is present, SHAPEIT2 infers close to perfect haplotypes. Based on these results we have developed a general strategy for phasing cohorts with any level of implicit or explicit relatedness between individuals. First SHAPEIT2 is run ignoring all explicit family information. We then apply a novel HMM method (duoHMM) to combine the SHAPEIT2 haplotypes with any family information to infer the inheritance pattern of each meiosis at all sites across each chromosome. This allows the correction of switch errors, detection of recombination events and genotyping errors. We show that the method detects numbers of recombination events that align very well with expectations based on genetic maps, and that it infers far fewer spurious recombination events than Merlin. The method can also detect genotyping errors and infer recombination events in otherwise uninformative families, such as trios and duos. The detected recombination events can be used in association scans for recombination phenotypes. The method provides a simple and unified approach to haplotype estimation, that will be of interest to researchers in the fields of human, animal and plant genetics.
Keywords: Chromosome Mapping; Cohort Effect; Family; Genotype; Haplotypes; Humans; Models, Genetic; Pedigree; Phenotype; Recombination, Genetic