Genetic analysis of over half a million people characterises C-reactive protein loci

Data availability: The summary statistics of the CHARGE CRP GWAS used in this study is publicly available from the IEU open GWAS project accession code ieu-b-35 (Trait: C-Reactive protein level - IEU Open GWAS project (mrcieu.ac.uk)). The derived CRP GWAS meta-analysis summary statistics generated in this study has been deposited in the GWAS catalogue under accession code GCST00186 (https://www.ebi.ac.uk/gwas/). Human genome assembly GRCh37 (hg19) from Genome Reference Consortium https://www.sanger.ac.uk/data/genome-reference-consortium/).Copyright © The Author(s) 2022. Chronic low-grade inflammation is linked to a multitude of chronic diseases. We report the largest genome-wide association study (GWAS) on C-reactive protein (CRP), a marker of systemic inflammation, in UK Biobank participants (N = 427,367, European descent) and the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium (total N = 575,531 European descent). We identify 266 independent loci, of which 211 are not previously reported. Gene-set analysis highlighted 42 gene sets associated with CRP levels (p ≤ 3.2 ×10−6) and tissue expression analysis indicated a strong association of CRP related genes with liver and whole blood gene expression. Phenome-wide association study identified 27 clinical outcomes associated with genetically determined CRP and subsequent Mendelian randomisation analyses supported a causal association with schizophrenia, chronic airway obstruction and prostate cancer. Our findings identified genetic loci and functional properties of chronic low-grade inflammation and provided evidence for causal associations with a range of diseases.UK Dementia Research Institute at Imperial College, which receives its funding from UK DRI Ltd. (funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK) and the British Heart Foundation Centre for Research Excellence at Imperial College London and the National Institute for Health Research Imperial Biomedical Research Centre, Imperial College London. S.S. received funding from the Medical Research Council – Public Health England (MRC-PHE) Centre for Environment and Health awarded studentship, of which funding is derived from the MRC Industrial Strategy Fund. I.T and F.K. have received funding from the Hellenic Foundation for Research and Innovation (HFRI) and the General Secretariat for Research and Technology (GSRT), under grant agreement No 1312. R.P. holds a fellowship supported by Rutherford Fund from Medical Research Council (MR/R0265051/1 and MR/R0265051/2). V.K. is funded by the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant (721567)

Genetics of Systemic Sclerosis: An Update

Systemic sclerosis (SSc) is an autoimmune disease characterized by vasculopathy, immune cell activation, and fibrosis of the skin and internal organs. Over the past few years, a role for genetics in the susceptibility for SSc has been established. This review aims to provide an update on the progress made in the past year or so within the field of SSc genetics research. This year has been of particular interest due to the publication of a large genome-wide association study, further investigations into gene–gene interactions, and the tendency to validate genetic results in functional models

Psychosis Endophenotypes:A Gene-Set-Specific Polygenic Risk Score Analysis

Background and Hypothesis:Endophenotypes can help to bridge the gap between psychosis and its genetic predispositions, but their underlying mechanisms remain largely unknown. This study aims to identify biological mechanisms that are relevant to the endophenotypes for psychosis, by partitioning polygenic risk scores into specific gene sets and testing their associations with endophenotypes.Study Design:We computed polygenic risk scores for schizophrenia and bipolar disorder restricted to brain-related gene sets retrieved from public databases and previous publications. Three hundred and seventy-eight gene-set-specific polygenic risk scores were generated for 4506 participants. Seven endophenotypes were also measured in the sample. Linear mixed-effects models were fitted to test associations between each endophenotype and each gene-set-specific polygenic risk score.Study Results:After correction for multiple testing, we found that a reduced P300 amplitude was associated with a higher schizophrenia polygenic risk score of the forebrain regionalization gene set (mean difference per SD increase in the polygenic risk score: −1.15 µV; 95% CI: −1.70 to −0.59 µV; P = 6 × 10−5). The schizophrenia polygenic risk score of forebrain regionalization also explained more variance of the P300 amplitude (R2 = 0.032) than other polygenic risk scores, including the genome-wide polygenic risk scores.Conclusions:Our finding on reduced P300 amplitudes suggests that certain genetic variants alter early brain development thereby increasing schizophrenia risk years later. Gene-set-specific polygenic risk scores are a useful tool to elucidate biological mechanisms of psychosis and endophenotypes, offering leads for experimental validation in cellular and animal models

Erratum to: Analysis of in vitro ADCC and clinical response to trastuzumab: possible relevance of Fc\u3b3RIIIA/Fc\u3b3RIIA gene polymorphisms and HER-2 expression levels on breast cancer cell lines

BACKGROUND: Trastuzumab is a humanized monoclonal antibody (mAb) currently used for the treatment of breast cancer (BC) patients with HER-2 overexpressing tumor subtype. Previous data reported the involvement of FcγRIIIA/IIA gene polymorphisms and/or antibody-dependent cellular cytotoxicity (ADCC) in the therapeutic efficacy of trastuzumab, although results on these issues are still controversial. This study was aimed to evaluate in vitro the functional relationships among FcγRIIIA/IIA polymorphisms, ADCC intensity and HER-2 expression on tumor target cells and to correlate them with response to trastuzumab. PATIENTS AND METHODS: Twenty-five patients with HER-2 overexpressing BC, receiving trastuzumab in a neoadjuvant (NEO) or metastatic (MTS) setting, were genotyped for the FcγRIIIA 158V>F and FcγRIIA 131H>R polymorphisms by a newly developed pyrosequencing assay and by multiplex Tetra-primer-ARMS PCR, respectively. Trastuzumab-mediated ADCC of patients’ peripheral blood mononuclear cells (PBMCs) was evaluated prior to therapy and measured by (51)Chromium release using as targets three human BC cell lines showing different levels of reactivity with trastuzumab. RESULTS: We found that the FcγRIIIA 158F and/or the FcγRIIA 131R variants, commonly reported as unfavorable in BC, may actually behave as ADCC favorable genotypes, in both the NEO (P ranging from 0.009 to 0.039 and from 0.007 to 0.047, respectively) and MTS (P ranging from 0.009 to 0.032 and P = 0.034, respectively) patients. The ADCC intensity was affected by different levels of trastuzumab reactivity with BC target cells. In this context, the MCF-7 cell line, showing the lowest reactivity with trastuzumab, resulted the most suitable cell line for evaluating ADCC and response to trastuzumab. Indeed, we found a statistically significant correlation between an increased frequency of patients showing ADCC of MCF-7 and complete response to trastuzumab in the NEO setting (P = 0.006). CONCLUSIONS: Although this study was performed in a limited number of patients, it would indicate a correlation of FcγR gene polymorphisms to the ADCC extent in combination with the HER-2 expression levels on tumor target cells in BC patients. However, to confirm our findings further experimental evidences obtained from a larger cohort of BC patients are mandatory. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12967-015-0680-0) contains supplementary material, which is available to authorized users

Survival dimensionality reduction (SDR): development and clinical application of an innovative approach to detect epistasis in presence of right-censored data

Contains fulltext : 89126.pdf (publisher's version ) (Open Access)BACKGROUND: Epistasis is recognized as a fundamental part of the genetic architecture of individuals. Several computational approaches have been developed to model gene-gene interactions in case-control studies, however, none of them is suitable for time-dependent analysis. Herein we introduce the Survival Dimensionality Reduction (SDR) algorithm, a non-parametric method specifically designed to detect epistasis in lifetime datasets. RESULTS: The algorithm requires neither specification about the underlying survival distribution nor about the underlying interaction model and proved satisfactorily powerful to detect a set of causative genes in synthetic epistatic lifetime datasets with a limited number of samples and high degree of right-censorship (up to 70%). The SDR method was then applied to a series of 386 Dutch patients with active rheumatoid arthritis that were treated with anti-TNF biological agents. Among a set of 39 candidate genes, none of which showed a detectable marginal effect on anti-TNF responses, the SDR algorithm did find that the rs1801274 SNP in the Fc gamma RIIa gene and the rs10954213 SNP in the IRF5 gene non-linearly interact to predict clinical remission after anti-TNF biologicals. CONCLUSIONS: Simulation studies and application in a real-world setting support the capability of the SDR algorithm to model epistatic interactions in candidate-genes studies in presence of right-censored data. Availability: http://sourceforge.net/projects/sdrproject/