Introduction: PCOS is a common endocrine disorder in women exhibiting characteristics ranging from hyperandrogenic to metabolic phenotypes, more prevalent in people of African/Caucasian and Asian ancestry, respectively. Since PCOS impairs fertility without diminishing in prevalence, it was discussed as an evolutionary paradox. GWAS identified 17 SNPs with different allele frequencies, depending on ethnicity, in various susceptibility loci (FSHR, LHCGR, DENND1A, THADA, C9ORF3, YAP1, HMGA2, RAB5B/SUOX, INSR, TOX3, and SUMO1P1). The aim of this study was to analyze in silico the PCOS phenotype–genotype relationship using these SNPs for analysis of genetic clustering and distance, two measures of the degree of similarity of genetic data. Methods: HapMap and HGDP databases (hapmap.ncbi.nlm.nih.gov; www.hagsc.org/hgdp/files.html) were used as source of allele frequencies of the 17 SNPs, using data from 622 male and female individuals of various populations, grouped in Africans, Americans, European-Caucasians, Mediterranean-Middle Easterns, Central Asians, Oceanians and East Asians. Genetic clustering was calculated from SNPs data by Bayesian analysis using the STRUCTURE software (burn-in=5000/50000 MCMC reps; iterations=20; 2<K<10). The inferred ancestry of individuals was matched with PCOS phenotype data of each group, extracted from a previous meta-analysis. The measure of genetic distance was plotted against the geographic distance between the populations. Results: The 622 male and female individuals were assigned to five genetic clusters, matching with different world regions (Kruskal–Wallis/Dunn’s post-test; P<0.0001), and converging in only two main PCOS phenotypes (Anova/Bonferroni post-test; P<0.0001). The overall genetic distance, calculated using PCOS markers, increased along with the geographic distance among the populations (linear regression; r2=0.2106; P<0.0001), in a phenotype-unrelated manner. Conclusions: Phenotype–genotype correlations were demonstrated for PCOS, suggesting that its genetic gradient results from genetic drift together with intralocus sexual conflict rather than natural selection of phenotypic traits in females. Recognizing the genetic background may be important for the correct pharmacological approach to PCOS treatment.

The PCOS evolutionary paradox: a GWAS-based, in silico, evolutionary explanation / Casarini, Livio; Simoni, Manuela. - (2014) 35:(2014). (Intervento presentato al convegno 16th European Congress of Endocrinology (ECE) tenutosi a Poland, Wrocław nel 03 May 2014 - 07 May 2014).

The PCOS evolutionary paradox: a GWAS-based, in silico, evolutionary explanation

CASARINI, Livio;SIMONI, Manuela
2014

Abstract

Introduction: PCOS is a common endocrine disorder in women exhibiting characteristics ranging from hyperandrogenic to metabolic phenotypes, more prevalent in people of African/Caucasian and Asian ancestry, respectively. Since PCOS impairs fertility without diminishing in prevalence, it was discussed as an evolutionary paradox. GWAS identified 17 SNPs with different allele frequencies, depending on ethnicity, in various susceptibility loci (FSHR, LHCGR, DENND1A, THADA, C9ORF3, YAP1, HMGA2, RAB5B/SUOX, INSR, TOX3, and SUMO1P1). The aim of this study was to analyze in silico the PCOS phenotype–genotype relationship using these SNPs for analysis of genetic clustering and distance, two measures of the degree of similarity of genetic data. Methods: HapMap and HGDP databases (hapmap.ncbi.nlm.nih.gov; www.hagsc.org/hgdp/files.html) were used as source of allele frequencies of the 17 SNPs, using data from 622 male and female individuals of various populations, grouped in Africans, Americans, European-Caucasians, Mediterranean-Middle Easterns, Central Asians, Oceanians and East Asians. Genetic clustering was calculated from SNPs data by Bayesian analysis using the STRUCTURE software (burn-in=5000/50000 MCMC reps; iterations=20; 2
2014
16th European Congress of Endocrinology (ECE)
Poland, Wrocław
03 May 2014 - 07 May 2014
Casarini, Livio; Simoni, Manuela
The PCOS evolutionary paradox: a GWAS-based, in silico, evolutionary explanation / Casarini, Livio; Simoni, Manuela. - (2014) 35:(2014). (Intervento presentato al convegno 16th European Congress of Endocrinology (ECE) tenutosi a Poland, Wrocław nel 03 May 2014 - 07 May 2014).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1084160
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