Rare germline copy number variants (CNVs) and breast cancer risk.

Funder: CIHRGermline copy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. Gene burden tests detected the strongest association for deletions in BRCA1 (P = 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P = 0.0008), ATM (P = 0.002) and BRCA2 (P = 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. To the best of our knowledge, this is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance

Genetic Aspects of Problematic and Risky Internet Use in Young Men—Analysis of ANKK1, DRD2 and NTRK3 Gene Polymorphism

Background: Internet addiction disorder (IAD) is characterized by an excess of uncontrolled preoccupations, urges, or behaviors related to computer use and Internet access that culminate in negative outcomes or individual distress. PIU includes excessive online activities (such as video gaming, social media use, streaming, pornography viewing, and shopping). The aim of this study was to analyze the association of gene polymorphisms that may influence the severity of risky behaviors in young men with the frequency of Internet use. We speculate that there are individual differences in the mechanisms of Internet addiction and that gene–hormone associations may represent useful biomarkers for subgroups of individuals. Materials and Methods: The study was conducted in a sample of 407 adult males. Subjects were asked to complete the Problematic Internet Use Test (PIUT). Serum was analyzed to determine concentrations of luteinizing hormone (LH), follicle stimulating hormone (FSH), testosterone (TT), sex hormone binding protein (SHBG), dehydroepiandrosterone sulfate (DHEA-S), estradiol (E2), prolactin (PRL), insulin (I), serotonin (5-HT), and dopamine (DA), as well as DRD2, ANKK1, and NTRK3 gene polymorphisms. Results: In the analysis of the ANKK1 gene, there was a specific association between ANKK1 polymorphisms and PRL and 5-HT blood concentrations. There was also an association between the ANKK1 polymorphisms and LH and DA concentrations. When analyzing the DRD2 gene polymorphism, we found that in the group with a moderate level of Internet dependence, there was an association between both the G/GG and GG/GG polymorphisms and FSH concentration. Conclusions: Our study found that there may be an association between the NTRK3 gene polymorphism and PIU. The polymorphisms of ANKK1 and DRD2 genes may be factors that influence the concentrations of hormones (PRL, 5-HT, DA) that are associated with the results obtained in PIU

Rare germline copy number variants (CNVs) and breast cancer risk

Germline copy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. Gene burden tests detected the strongest association for deletions in BRCA1 (P = 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P = 0.0008), ATM (P = 0.002) and BRCA2 (P = 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. To the best of our knowledge, this is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance

Rare germline copy number variants (CNVs) and breast cancer risk.

Germline copy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. Gene burden tests detected the strongest association for deletions in BRCA1 (P = 3.7E-18). Nine other genes were associated with a p-value &lt; 0.01 including known susceptibility genes CHEK2 (P = 0.0008), ATM (P = 0.002) and BRCA2 (P = 0.008). Outside the known genes we detected associations with p-values &lt; 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. To the best of our knowledge, this is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance

Rare germline copy number variants (CNVs) and breast cancer risk

Abstract Germline copy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. Gene burden tests detected the strongest association for deletions in BRCA1 (P = 3.7E-18). Nine other genes were associated with a p-value &lt; 0.01 including known susceptibility genes CHEK2 (P = 0.0008), ATM (P = 0.002) and BRCA2 (P = 0.008). Outside the known genes we detected associations with p-values &lt; 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. To the best of our knowledge, this is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance