Association of Toll-like receptor 4 (TLR4) with chronic plaque type psoriasis and psoriatic arthritis.

Family studies have provided overwhelming evidence for an underlying genetic component to psoriasis. Toll-like receptors (TLRs) are key transmembrane proteins in both the innate and adaptive immune responses which are known to be integral processes in psoriasis. Recent functional studies support this notion having suggested a role for TLR4 in the pathogenesis of psoriasis. Furthermore a missense polymorphism in the TLR4 gene has been associated with a number of autoimmune conditions, including Crohn diseases, making TLR4 a viable candidate gene for investigation. The aim of this study was to investigate polymorphisms across the TLR4 region with a high-density single nucleotide polymorphism (SNP) panel in a large cohort of patients with chronic plaque type psoriasis. Twenty SNPs were successfully genotyped using Sequenom iPLEX Gold platform in 2826 UK chronic plaque type psoriasis patients including subgroup data on presence of confirmed psoriatic arthritis (n = 1839) and early-onset psoriasis (n = 1466) was available. Allele frequencies for psoriasis patients were compared against imputed Wellcome Trust Case Control Consortium controls (n = 4861). Significant association was observed between a missense variant rs4986790 of TLR4 (Asp229Gly) and plaque type psoriasis (p = 2 × 10(-4)) which was also notable in those with psoriatic arthritis (p = 2 × 10(-4)) and early-onset psoriasis (p = 8 × 10(-4)). We present data suggestive of an association between a functional variant and an intronic variant of TLR4 and chronic plaque type psoriasis and psoriatic arthritis. However, validation of this association in independent cohorts will be necessary

Genome-wide association studies in oesophageal adenocarcinoma and Barrett's oesophagus: a large-scale meta-analysis.

BACKGROUND: Oesophageal adenocarcinoma represents one of the fastest rising cancers in high-income countries. Barrett's oesophagus is the premalignant precursor of oesophageal adenocarcinoma. However, only a few patients with Barrett's oesophagus develop adenocarcinoma, which complicates clinical management in the absence of valid predictors. Within an international consortium investigating the genetics of Barrett's oesophagus and oesophageal adenocarcinoma, we aimed to identify novel genetic risk variants for the development of Barrett's oesophagus and oesophageal adenocarcinoma. METHODS: We did a meta-analysis of all genome-wide association studies of Barrett's oesophagus and oesophageal adenocarcinoma available in PubMed up to Feb 29, 2016; all patients were of European ancestry and disease was confirmed histopathologically. All participants were from four separate studies within Europe, North America, and Australia and were genotyped on high-density single nucleotide polymorphism (SNP) arrays. Meta-analysis was done with a fixed-effects inverse variance-weighting approach and with a standard genome-wide significance threshold (p<5 × 10-8). We also did an association analysis after reweighting of loci with an approach that investigates annotation enrichment among genome-wide significant loci. Furthermore, the entire dataset was analysed with bioinformatics approaches-including functional annotation databases and gene-based and pathway-based methods-to identify pathophysiologically relevant cellular mechanisms. FINDINGS: Our sample comprised 6167 patients with Barrett's oesophagus and 4112 individuals with oesophageal adenocarcinoma, in addition to 17 159 representative controls from four genome-wide association studies in Europe, North America, and Australia. We identified eight new risk loci associated with either Barrett's oesophagus or oesophageal adenocarcinoma, within or near the genes CFTR (rs17451754; p=4·8 × 10-10), MSRA (rs17749155; p=5·2 × 10-10), LINC00208 and BLK (rs10108511; p=2·1 × 10-9), KHDRBS2 (rs62423175; p=3·0 × 10-9), TPPP and CEP72 (rs9918259; p=3·2 × 10-9), TMOD1 (rs7852462; p=1·5 × 10-8), SATB2 (rs139606545; p=2·0 × 10-8), and HTR3C and ABCC5 (rs9823696; p=1·6 × 10-8). The locus identified near HTR3C and ABCC5 (rs9823696) was associated specifically with oesophageal adenocarcinoma (p=1·6 × 10-8) and was independent of Barrett's oesophagus development (p=0·45). A ninth novel risk locus was identified within the gene LPA (rs12207195; posterior probability 0·925) after reweighting with significantly enriched annotations. The strongest disease pathways identified (p<10-6) belonged to muscle cell differentiation and to mesenchyme development and differentiation. INTERPRETATION: Our meta-analysis of genome-wide association studies doubled the number of known risk loci for Barrett's oesophagus and oesophageal adenocarcinoma and revealed new insights into causes of these diseases. Furthermore, the specific association between oesophageal adenocarcinoma and the locus near HTR3C and ABCC5 might constitute a novel genetic marker for prediction of the transition from Barrett's oesophagus to oesophageal adenocarcinoma. Fine-mapping and functional studies of new risk loci could lead to identification of key molecules in the development of Barrett's oesophagus and oesophageal adenocarcinoma, which might encourage development of advanced prevention and intervention strategies. FUNDING: US National Cancer Institute, US National Institutes of Health, National Health and Medical Research Council of Australia, Swedish Cancer Society, Medical Research Council UK, Cambridge NIHR Biomedical Research Centre, Cambridge Experimental Cancer Medicine Centre, Else Kröner Fresenius Stiftung, Wellcome Trust, Cancer Research UK, AstraZeneca UK, University Hospitals of Leicester, University of Oxford, Australian Research Council

Machine learning for genetic prediction of psychiatric disorders: a systematic review

Machine learning methods have been employed to make predictions in psychiatry from genotypes, with the potential to bring improved prediction of outcomes in psychiatric genetics; however, their current performance is unclear. We aim to systematically review machine learning methods for predicting psychiatric disorders from genetics alone and evaluate their discrimination, bias and implementation. Medline, PsycInfo, Web of Science and Scopus were searched for terms relating to genetics, psychiatric disorders and machine learning, including neural networks, random forests, support vector machines and boosting, on 10 September 2019. Following PRISMA guidelines, articles were screened for inclusion independently by two authors, extracted, and assessed for risk of bias. Overall, 63 full texts were assessed from a pool of 652 abstracts. Data were extracted for 77 models of schizophrenia, bipolar, autism or anorexia across 13 studies. Performance of machine learning methods was highly varied (0.48–0.95 AUC) and differed between schizophrenia (0.54–0.95 AUC), bipolar (0.48–0.65 AUC), autism (0.52–0.81 AUC) and anorexia (0.62–0.69 AUC). This is likely due to the high risk of bias identified in the study designs and analysis for reported results. Choices for predictor selection, hyperparameter search and validation methodology, and viewing of the test set during training were common causes of high risk of bias in analysis. Key steps in model development and validation were frequently not performed or unreported. Comparison of discrimination across studies was constrained by heterogeneity of predictors, outcome and measurement, in addition to sample overlap within and across studies. Given widespread high risk of bias and the small number of studies identified, it is important to ensure established analysis methods are adopted. We emphasise best practices in methodology and reporting for improving future studies

Sexual reproduction in populations of Austropuccinia psidii

Austropuccinia psidii is a rust fungus that has expanded its known geographic distribution and host range on Myrtaceae. Invasions by rust fungi are often caused by asexual urediniospores that give rise to populations with low genotypic diversity. Recently it was shown that basidiospores, the gametic spores of A. psidii, were able to infect species of Myrtaceae under controlled conditions. The present study tested the hypothesis that sexual reproduction occurs through infection of Myrtaceae by basidiospores of A. psidii in recently invasive populations from New Zealand and South Africa. We provided three lines of evidence to test this hypothesis: i) presence of a sexual stage, ii) high genotypic diversity within an invasive population, and iii) no genetic linkage between microsatellite markers in multilocus genotypes. Our results provide evidence that invasions of A. psidii are caused by both urediniospores that spread clonal genotypes, and teliospores that produce recombinant basidiospores, which infect Myrtaceae. We reject the hypothesis that field infections of A. psidii are only caused by asexual urediniospores, and support that sexual reproduction occurs in invasive populations and may accelerate adaptation to environmental change

Sexual reproduction in populations of Austropuccinia psidii

Austropuccinia psidii is a rust fungus that has expanded its known geographic distribution and host range on Myrtaceae. Invasions by rust fungi are often caused by asexual urediniospores that give rise to populations with low genotypic diversity. Recently it was shown that basidiospores, the gametic spores of A. psidii, were able to infect species of Myrtaceae under controlled conditions. The present study tested the hypothesis that sexual reproduction occurs through infection of Myrtaceae by basidiospores of A. psidii in recently invasive populations from New Zealand and South Africa. We provided three lines of evidence to test this hypothesis: i) presence of a sexual stage, ii) high genotypic diversity within an invasive population, and iii) no genetic linkage between microsatellite markers in multilocus genotypes. Our results provide evidence that invasions of A. psidii are caused by both urediniospores that spread clonal genotypes, and teliospores that produce recombinant basidiospores, which infect Myrtaceae. We reject the hypothesis that field infections of A. psidii are only caused by asexual urediniospores, and support that sexual reproduction occurs in invasive populations and may accelerate adaptation to environmental change

Using public control genotype data to increase power and decrease cost of case–control genetic association studies

Genome-wide association (GWA) studies are a powerful approach for identifying novel genetic risk factors associated with human disease. A GWA study typically requires the inclusion of thousands of samples to have sufficient statistical power to detect single nucleotide polymorphisms (SNPs) that are associated with only modest increases in risk of disease given the heavy burden of a multiple test correction that is necessary to maintain valid statistical tests. Low statistical power and the high financial cost of performing a GWA study remains prohibitive for many scientific investigators anxious to perform such a study using their own samples. A number of remedies have been suggested to increase statistical power and decrease cost, including the utilization of free publicly available genotype data and multi-stage genotyping designs. Herein, we compare the statistical power and relative costs of alternative association study designs that use cases and screened controls to study designs that are based only on, or additionally include, free public control genotype data. We describe a novel replication-based two-stage study design, which uses free public control genotype data in the first stage and follow-up genotype data on case-matched controls in the second stage, that preserves many of the advantages inherent when using only an epidemiologically matched set of controls. Specifically, we show that our proposed two-stage design can substantially increase statistical power and decrease cost of performing a GWA study while controlling the type I error rate that can be inflated when using public controls due to differences in ancestry and batch genotype effects