Background: Nonsyndromic cleft lip with or without cleft palate (nsCL/P) is the most common orofacial birth defect with an aetiology involving both genetic and environmental factors. Genome-wide association studies (GWAS) have identified several genomic susceptibility regions for nsCL/P. In the present study, the three well established single nucleotide polymorphisms (SNPs) identified by GWAS (rs987525 at 8q24, rs7078160 at 10q25, and rs227731 at 17q22 loci) and one SNP identified by candidate gene study (rs642961 in IRF6 gene at 1q32 locus) were analysed for an association with nsCL/P in Slovak population.
Methods: Nucleotide variants were genotyped in 165 nsCL/P patients and 326 unaffected controls. All variants of interest were genotyped using high-resolution melting analysis after real-time PCR.
Results: We found significant differences between patient and control groups with respect to the allele and genotype frequencies for the SNPs at the 1q32, 8q24, and 17q22 loci. SNP at the 10q25 locus showed a trend toward association with nsCL/P risk.
Conclusions: The results suggest that SNPs at the 1q32, 8q24 and 17q22 loci may contribute to the nsCL/P risk in Slovak population.
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http://dx.doi.org/10.5507/bp.2017.009 | DOI Listing |
Eur J Cancer
September 2022
Faculty of Medicine and Biomedical Sciences, Gambelas Campus, 805-139 Faro, Portugal; Center for Research in Health Technologies and Information Systems (CINTESIS), Universidade do Algarve, Faro, Portugal. Electronic address:
Introduction: Translation of genome-wide association study (GWAS) findings into preventive approaches is challenged by the identification of the causal risk variants and the understanding of the biological mechanisms by which they act. We present using allelic expression (AE) ratios to perform quantitative case-control analysis as a novel approach to identify risk associations, causal regulatory variants, and target genes.
Methods: Using the breast cancer (BC) risk locus 17q22 to validate this approach, we measured AE ratios in normal breast tissue samples from controls and cases, as well as from unmatched blood samples.
PLoS Genet
July 2021
Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States of America.
Based on epidemiologic and embryologic patterns, nonsyndromic orofacial clefts- the most common craniofacial birth defects in humans- are commonly categorized into cleft lip with or without cleft palate (CL/P) and cleft palate alone (CP), which are traditionally considered to be etiologically distinct. However, some evidence of shared genetic risk in IRF6, GRHL3 and ARHGAP29 regions exists; only FOXE1 has been recognized as significantly associated with both CL/P and CP in genome-wide association studies (GWAS). We used a new statistical approach, PLACO (pleiotropic analysis under composite null), on a combined multi-ethnic GWAS of 2,771 CL/P and 611 CP case-parent trios.
View Article and Find Full Text PDFCancer Res
April 2021
Program in Biological and Medical Informatics, University of California San Francisco, San Francisco, California.
To identify rare variants associated with prostate cancer susceptibility and better characterize the mechanisms and cumulative disease risk associated with common risk variants, we conducted an integrated study of prostate cancer genetic etiology in two cohorts using custom genotyping microarrays, large imputation reference panels, and functional annotation approaches. Specifically, 11,984 men (6,196 prostate cancer cases and 5,788 controls) of European ancestry from Northern California Kaiser Permanente were genotyped and meta-analyzed with 196,269 men of European ancestry (7,917 prostate cancer cases and 188,352 controls) from the UK Biobank. Three novel loci, including two rare variants (European ancestry minor allele frequency < 0.
View Article and Find Full Text PDFClin Oral Investig
March 2021
Department of Oral Diagnosis, School of Dentistry, University of Campinas, Piracicaba, São Paulo, CEP 13414-018, Brazil.
Objectives: Genetic variants in multiple genes and loci have been associated with the risk of nonsyndromic cleft lip with or without cleft palate (NSCL ± P). However, the estimation of risk remains challenge, because most of these variants are population-specific rendering the identification of the underlying genetic risk difficult. Herein we examined the use of machine learning network in previously reported single nucleotide polymorphisms (SNPs) to predict risk of NSCL ± P in the Brazilian population.
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