Identification of a new locus at 16q12 associated with time-to-asthma onset

International audienceBackground: Asthma is a heterogeneous disease in which age-of-onset plays an important role.Objective: We sought to identify the genetic variants associated with time-to-asthma onset.Methods: We conducted a large-scale meta-analysis of nine genome-wide association studies of time-to-asthma onset (total of 5,462 asthmatics with a broad range of age-of-asthma onset and 8,424 controls of European ancestry) performed using survival analysis techniques.Results: We detected five regions associated with time-to-asthma onset at genome-wide significant level (P<5x10-8). We evidenced a new locus in 16q12 region (near cylindromatosis turban tumor syndrome gene (CYLD)) and confirmed four asthma risk regions: 2q12 (IL1RL1), 6p21 (HLA-DQA1), 9p24 (IL33) and 17q12-q21 (ZPBP2-GSDMA). Conditional analyses identified two distinct signals at 9p24 (both upstream of IL33) and at 17q12-q21 (near ZPBP2 and within GSDMA). These seven distinct loci explained together 6.0% of the variance in time-to-asthma onset. In addition, we showed that genetic variants at 9p24 and 17q12-q21 were strongly associated with an earlier onset of childhood asthma (P≤0.002) whereas 16q12 SNP was associated with a later asthma onset (P=0.04). A high burden of disease risk alleles at these loci was associated with earlier age-of-asthma onset (4 years versus 9-12 years, P=10-4).Conclusion: The new susceptibility region for time-to-asthma onset at 16q12 harbors variants that correlate with the expression of CYLD and NOD2 (nucleotide-binding oligomerization domain 2), two strong candidates for asthma. This study demonstrates that incorporating the variability of age-of-asthma onset in asthma modeling is a helpful approach in the search for disease susceptibility genes

Genomic analyses inform on migration events during the peopling of Eurasia.

High-coverage whole-genome sequence studies have so far focused on a limited number of geographically restricted populations, or been targeted at specific diseases, such as cancer. Nevertheless, the availability of high-resolution genomic data has led to the development of new methodologies for inferring population history and refuelled the debate on the mutation rate in humans. Here we present the Estonian Biocentre Human Genome Diversity Panel (EGDP), a dataset of 483 high-coverage human genomes from 148 populations worldwide, including 379 new genomes from 125 populations, which we group into diversity and selection sets. We analyse this dataset to refine estimates of continent-wide patterns of heterozygosity, long- and short-distance gene flow, archaic admixture, and changes in effective population size through time as well as for signals of positive or balancing selection. We find a genetic signature in present-day Papuans that suggests that at least 2% of their genome originates from an early and largely extinct expansion of anatomically modern humans (AMHs) out of Africa. Together with evidence from the western Asian fossil record, and admixture between AMHs and Neanderthals predating the main Eurasian expansion, our results contribute to the mounting evidence for the presence of AMHs out of Africa earlier than 75,000 years ago.Support was provided by: Estonian Research Infrastructure Roadmap grant no 3.2.0304.11-0312; Australian Research Council Discovery grants (DP110102635 and DP140101405) (D.M.L., M.W. and E.W.); Danish National Research Foundation; the Lundbeck Foundation and KU2016 (E.W.); ERC Starting Investigator grant (FP7 - 261213) (T.K.); Estonian Research Council grant PUT766 (G.C. and M.K.); EU European Regional Development Fund through the Centre of Excellence in Genomics to Estonian Biocentre (R.V.; M.Me. and A.Me.), and Centre of Excellence for Genomics and Translational Medicine Project No. 2014-2020.4.01.15-0012 to EGC of UT (A.Me.) and EBC (M.Me.); Estonian Institutional Research grant IUT24-1 (L.S., M.J., A.K., B.Y., K.T., C.B.M., Le.S., H.Sa., S.L., D.M.B., E.M., R.V., G.H., M.K., G.C., T.K. and M.Me.) and IUT20-60 (A.Me.); French Ministry of Foreign and European Affairs and French ANR grant number ANR-14-CE31-0013-01 (F.-X.R.); Gates Cambridge Trust Funding (E.J.); ICG SB RAS (No. VI.58.1.1) (D.V.L.); Leverhulme Programme grant no. RP2011-R-045 (A.B.M., P.G. and M.G.T.); Ministry of Education and Science of Russia; Project 6.656.2014/K (S.A.F.); NEFREX grant funded by the European Union (People Marie Curie Actions; International Research Staff Exchange Scheme; call FP7-PEOPLE-2012-IRSES-number 318979) (M.Me., G.H. and M.K.); NIH grants 5DP1ES022577 05, 1R01DK104339-01, and 1R01GM113657-01 (S.Tis.); Russian Foundation for Basic Research (grant N 14-06-00180a) (M.G.); Russian Foundation for Basic Research; grant 16-04-00890 (O.B. and E.B); Russian Science Foundation grant 14-14-00827 (O.B.); The Russian Foundation for Basic Research (14-04-00725-a), The Russian Humanitarian Scientific Foundation (13-11-02014) and the Program of the Basic Research of the RAS Presidium “Biological diversity” (E.K.K.); Wellcome Trust and Royal Society grant WT104125AIA & the Bristol Advanced Computing Research Centre (http://www.bris.ac.uk/acrc/) (D.J.L.); Wellcome Trust grant 098051 (Q.A.; C.T.-S. and Y.X.); Wellcome Trust Senior Research Fellowship grant 100719/Z/12/Z (M.G.T.); Young Explorers Grant from the National Geographic Society (8900-11) (C.A.E.); ERC Consolidator Grant 647787 ‘LocalAdaptatio’ (A.Ma.); Program of the RAS Presidium “Basic research for the development of the Russian Arctic” (B.M.); Russian Foundation for Basic Research grant 16-06-00303 (E.B.); a Rutherford Fellowship (RDF-10-MAU-001) from the Royal Society of New Zealand (M.P.C.)

MicroRNA Processing Pathway-Based Polygenic Score for Clear Cell Renal Cell Carcinoma in the Volga-Ural Region Populations of Eurasian Continent

The polygenic scores (PGSs) are developed to help clinicians in distinguishing individuals at high risk of developing disease outcomes from the general population. Clear cell renal cell carcinoma (ccRCC) is a complex disorder that involves numerous biological pathways, one of the most important of which is responsible for the microRNA biogenesis machinery. Here, we defined the biological-pathway-specific PGS in a case-control study of ccRCC in the Volga-Ural region of the Eurasia continent. We evaluated 28 DNA SNP variants, located in microRNA biogenesis genes, in 464 individuals with clinically diagnosed ccRCC and 1042 individuals without the disease. Individual genetic risks were defined using the SNP-variant effects derived from the ccRCC association analysis. The final weighted and unweighted PGS models were based on 21 SNPs, and 7 SNPs were excluded due to high LD. In our dataset, microRNA-machinery-weighted PGS revealed 1.69-fold higher odds (95% CI [1.51&ndash;1.91]) for ccRCC risk in individuals with ccRCC compared with controls with a p-value of 2.0 &times; 10&minus;16. The microRNA biogenesis pathway weighted PGS predicted the risk of ccRCC with an area under the curve (AUC) = 0.642 (95%nCI [0.61&ndash;0.67]). Our findings indicate that DNA variants of microRNA machinery genes modulate the risk of ccRCC in Volga-Ural populations. Moreover, larger powerful genome-wide association studies are needed to reveal a wider range of genetic variants affecting microRNA processing. Biological-pathway-based PGSs will advance the development of innovative screening systems for future stratified medicine approaches in ccRCC

Host Genetic Variants Linked to COVID-19 Neurological Complications and Susceptibility in Young Adults—A Preliminary Analysis

To date, multiple efforts have been made to use genome-wide association studies (GWAS) to untangle the genetic basis for SARS-CoV-2 infection susceptibility and severe COVID-19. However, data on the genetic-related effects of SARS-CoV-2 infection on the presence of accompanying and long-term post-COVID-19 neurological symptoms in younger individuals remain absent. We aimed to examine the possible association between SNPs found in a GWAS of COVID-19 outcomes and three phenotypes: SARS-CoV-2 infection, neurological complications during disease progression, and long-term neurological complications in young adults with a mild-to-moderate disease course. University students (N = 336, age 18–25 years, European ancestry) with or without COVID-19 and neurological symptoms in anamnesis comprised the study sample. Logistic regression was performed with COVID-19-related phenotypes as outcomes, and the top 25 SNPs from GWAS meta-analyses and an MR study linking COVID-19 and cognitive deficits were found. We replicated previously reported associations of the FURIN and SLC6A20 gene variants (OR = 2.36, 95% CI 1.31–4.24) and OR = 1.94, 95% CI 1.08–3.49, respectively) and remaining neurological complications (OR = 2.12, 95% CI 1.10–4.35 for SLC6A20), while NR1H2 (OR = 2.99, 95% CI 1.39–6.69) and TMPRSS2 (OR = 2.03, 95% CI 1.19–3.50) SNPs were associated with neurological symptoms accompanying COVID-19. Our findings indicate that genetic variants related to a severe COVID-19 course in adults may contribute to the occurrence of neurological repercussions in individuals at a young age

MicroRNA Expression Signatures in Clear Cell Renal Cell Carcinoma: High-Throughput Searching for Key miRNA Markers in Patients from the Volga-Ural Region of Eurasian Continent

Clear cell renal cell carcinoma (ccRCC) is characterized by high molecular genetic heterogeneity, metastatic activity and unfavorable prognosis. MicroRNAs (miRNA) are 22-nucleotide noncoding RNAs that are aberrantly expressed in cancer cells and have gained serious consideration as non-invasive cancer biomarkers. We investigated possible differential miRNA signatures that may differentiate high-grade ccRCC from primary disease stages. High-throughput miRNAs expression profiling, using TaqMan OpenArray Human MicroRNA panel, was performed in a group of 21 ccRCC patients. The obtained data was validated in 47 ccRCC patients. We identified nine dysregulated miRNAs (miRNA-210, -642, -18a, -483-5p, -455-3p, -487b, -582-3p, -199b and -200c) in tumor ccRCC tissue compared to normal renal parenchyma. Our results show that the combination of miRNA-210, miRNA-483-5p, miRNA-455 and miRNA-200c is able to distinguish low and high TNM ccRCC stages. Additionally, miRNA-18a, -210, -483-5p and -642 showed statistically significant differences between the low stage tumor ccRCC tissue and normal renal tissue. Contrariwise, the high stages of the tumor process were accompanied by alteration in the expression levels of miRNA-200c, -455-3p and -582-3p. Although the biological roles of these miRNAs in ccRCC are not totally clear, our findings need additional investigations into their involvement in the pathogenesis of ccRCC. Prospective studies with large study cohorts of ccRCC patients are important to further establish the clinical validity of our miRNA markers to predict ccRCC