Cytokine Gene Polymorphisms in Chronic Adenoiditis

The aim of our research was to study the multiphase response in a system of pro-inflammatory and anti-inflammatory cytokines due to the additive contribution of homozygous and heterozygous genotypes for the polymorphic allelic variants of the interleukin-1β (IL-1β) and interleukin-4 (IL-4) genes in patients with chronic adenoiditis (CA). Materials and Methods: The study included 388 children with CA. Associations between the IL1B gene (rs1143634) (C+3954T) SNP and the IL-4 gene (rs2243250) (C-589T) SNP and the clinical manifestations and clinical outcome of CA were investigated. Genotyping for the studied SNPs was performed using real-time PCR. The study of genotype-associated cytokine production in accordance with the level of concentration of IL-1β, IL-4 in blood serum with the method of solidphase EIA using horseradish peroxidase as an indicating enzyme was carried out. Results: The presence of homozygous or heterozygous genotypes of the studied SNPs of the IL-1β and IL-4 genes was characterized with genetically determined cytokine-production forming the phenotypical polymorphism. The conducted research into congenital immunity factors with an assessment of genetically determined cytokine production has revealed 5 options of the cytokine response and their corresponding frequencies. We extrapolated the results on clinical and functional outcomes of chronic adenoiditis, which allowed us to identify non-randomness in the nature of chronic adenoiditis as a multifactorial disease. Conclusion: The obtained data are evidence of the phenotypic-genetic heterogeneity of CA

Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

Background Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease. Methods We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation. Findings Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16–36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10−7). Interpretation These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data. Funding The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources)