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Kepka, E.

Publications and source records attributed to Kepka, E..

2 recordsLinked to original sources

Large-scale genome-wide association meta-analysis of endometriosis reveals 13 novel loci and genetically-associated comorbidity with other pain conditions

Endometriosis is a common complex inflammatory condition characterised by the presence of endometrium-like tissue outside the uterus, mainly in the pelvic area. It is associated with chronic pelvic pain and infertility, and its pathogenesis remains poorly understood. The disease is typically classified according to the revised American Fertility Society (rAFS) 4-stage surgical assessment system, although stage does not correlate well with symptomatology or prognosis. Previously identified genetic variants mainly are associated with stage III/IV disease, highlighting the need for further phenotype-stratified analysis that requires larger datasets. We conducted a meta-analysis of 15 genome-wide association studies (GWAS) and a replication analysis, including 58,115 cases and 733,480 controls in total, and sub-phenotype analyses of stage I/II, stage III/IV and infertility-associated endometriosis cases. This revealed 27 genetic loci associated with endometriosis at the genome-wide p-value threshold (P<5x10-8), 13 of which are novel and an additional 8 novel genes identified from gene-based association analyses. Of the 27 loci, 21 (78%) had greater effect sizes in stage III/IV disease compared to stage I/II, 1 (4%) had greater effect size in stage I/II compared to stage III/IV and 17 (63%) had greater effect sizes when restricted to infertility-associated endometriosis cases compared to overall endometriosis. These results suggest that specific variants may confer risk for different sub-types of endometriosis through distinct pathways. Analyses of genetic variants underlying different pain symptoms reported in the UK Biobank showed that 7/9 had positive significant (p<1.28x103) positive genetic correlations with endometriosis, suggesting a genetic basis for sensitivity to pain in general. Additional conditions with significant positive genetic correlations with endometriosis included uterine fibroids, excessive and irregular menstrual bleeding, osteoarthritis, diabetes as well as menstrual cycle length and age at menarche. These results provide a basis for fine-mapping of the causal variants at these 27 loci, and for functional follow-up to understand their contribution to endometriosis and its potential subtypes.

genomics

New single nucleotide polymorphisms (SNPs) in homologous recombination repair genes detected by microarray analysis in Polish breast cancer patients

Purpose of the studyBreast cancer is the most common cause of malignancy mortality in women worldwide. This study aimed at localising homologous recombination repair (HR) genes and their chromosomal loci and correlating their nucleotide variants with susceptibility to breast cancer. In this study authors analysed the association between single nucleotide polymorphisms (SNPs) in homologous recombination repair genes and the incidence of breast cancer in the population of Polish women.\n\nMethodsBlood samples from 94 breast cancer patients were analysed as test group. Individuals were recruited into the study at the Department of Oncological Surgery and Breast Diseases of the Institute of the Polish Mothers Memorial Hospital in Lodz, Poland. Healthy controls (n=500) were obtained from the Biobank Laboratory, Department of Molecular Biophysics, University of Lodz. Then, DNA of breast cancer patients was compared with one of disease-free women. The test was supported by microarray analysis.\n\nResultsStatistically significant correlations were identified between breast cancer and 3 not described previously single nucleotide polymorphisms (SNPs) of homologous recombination repair genes BRCA1 and BRCA2: rs59004709, rs4986852 and rs1799950.\n\nConclusionsFurther studies on larger groups are warranted to support the hypothesis of correlation between the above-mentioned genetic variants and breast cancer risk.

genetics