PORTABILITY OF GWAS RESULTS BETWEEN ETHNIC POPULATIONS: GENETIC MARKERS FOR POLYCYSTIC OVARY SYNDROME (PCOS) IN MEDITERRANEAN AREA
| Autor: | Corinne Lautier, Zeineb Douma, Touhami Mahjoub, Sara Haydar, Florin Grigorescu |
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| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
Genetics Linkage disequilibrium Genetic diversity 030219 obstetrics & reproductive medicine Endocrine and Autonomic Systems business.industry Endocrinology Diabetes and Metabolism Polycystic ovary syndrome (PCOS) Hyperandrogenism Population genetics Genome-wide association study medicine.disease Polycystic ovary 03 medical and health sciences 030104 developmental biology 0302 clinical medicine Endocrinology Genetic marker Extensive Clinical Experience medicine business |
| Zdroj: | Acta endocrinologica (Bucharest, Romania : 2005). 15(3) |
| ISSN: | 1841-0987 |
| Popis: | Genome Wide Association Studies (GWAS) are excellent opportunities to define culprit genes in complex disorders such as the polycystic ovary syndrome (PCOS). PCOS is a prevalent disorder characterized by anovulation, hyperandrogenism and polycystic ovaries, which benefitted from several GWASs in Asians and Europeans revealing more than 20 potential culprit genes near associated single nucleotide variations (SNV). Translation of these findings into the clinical practice raises difficulties since positive hits are surrogate SNVs linked with causative mutations by linkage disequilibrium (LD). Studies in Mediterranean populations (e.g. Southern Europe and North Africa) raise supplementary problems because of a different LD-pattern, which may disrupt the link with causative mutations. Our experience in MEDIGENE program between Tunisia and France enforces the necessity of genetic anthropology studies before translating GWAS data. Tunisians are a heterogeneous population with ancestral Berbers, European, Arab and Sub-Saharan African components while South Europeans display a high level of genetic diversity, partially explained by gene flow from North Africa. Human diversity studies require sampling from Middle East and North Africa (MENA) region that will help to understand genetic factors in complex diseases. |
| Databáze: | OpenAIRE |
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