Corton Marta, Botella-Carretero Jose I, Benguria Alberto, Villuendas Gemma, Zaballos Angel, San Millan Jose L, Escobar-Morreale Hector F, Peral Belen

Instituto de Investigaciones Biomedicas, Consejo Superior de Investigaciones Cientificas and Universidad Autonoma de Madrid, E-28029 Madrid, Spain.

J Clin Endocrinol Metab. 2007 Jan;92(1):328-37. doi: 10.1210/jc.2006-1665. Epub

CONTEXT: The polycystic ovary syndrome (PCOS) is frequently associated with visceral obesity, suggesting that omental adipose tissue might play an important role in the pathogenesis of the syndrome.
OBJECTIVE: The objective was to study the expression profiles of omental fat biopsy samples obtained from morbidly obese women with or without PCOS at the time of bariatric surgery. DESIGN: This was a case-control study. SETTINGS: We conducted the study in an academic hospital. PATIENTS: Eight PCOS patients and seven nonhyperandrogenic women submitted to bariatric surgery because of morbid obesity. INTERVENTIONS: Biopsy samples of omental fat were obtained during bariatric surgery. MAIN OUTCOME MEASURE: The main outcome measure was high-density oligonucleotide arrays.
RESULTS: After statistical analysis, we identified changes in the expression patterns of 63 genes between PCOS and control samples. Gene classification was assessed through data mining of Gene Ontology annotations and cluster analysis of dysregulated genes between both groups. These methods highlighted abnormal expression of genes encoding certain components of several biological pathways related to insulin signaling and Wnt signaling, oxidative stress, inflammation, immune function, and lipid metabolism, as well as other genes previously related to PCOS or to the metabolic syndrome. CONCLUSION: The differences in the gene expression profiles in visceral adipose tissue of PCOS patients compared with nonhyperandrogenic women involve multiple genes related to several biological pathways, suggesting that the involvement of abdominal obesity in the pathogenesis of PCOS is more ample than previously thought and is not restricted to the induction of insulin resistance.

Jones Michelle R, Chua Angela, Chen Yii-Der I, Li Xiaohui, Krauss Ronald M, Rotter Jerome I, Legro Richard S, Azziz Ricardo, Goodarzi Mark O

Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, United States of America.

PLoS One. 2011;6(5):e20120. doi: 10.1371/journal.pone.0020120. Epub 2011 May 17.

Novel pathways in polycystic ovary syndrome (PCOS) are being identified in gene expression studies in PCOS tissues; such pathways may contain key genes in disease etiology. Previous expression studies identified both dickkopf homolog 1 (DKK1) and DnaJ (Hsp40) homolog, subfamily B, member 1 (DNAJB1) as differentially expressed in PCOS tissue, implicating them as candidates for PCOS susceptibility. To test this, we genotyped a discovery cohort of 335 PCOS cases and 198 healthy controls for three DKK1 single nucleotide polymorphisms (SNPs) and four DNAJB1 SNPs and a replication cohort of 396 PCOS cases and 306 healthy controls for 1 DKK1 SNP and 1 DNAJB1 SNP. SNPs and haplotypes were determined and tested for association with PCOS and component phenotypes. We found that no single nucleotide polymorphisms were associated with PCOS risk; however, the major allele of rs1569198 from DKK1 was associated with increased total testosterone (discovery cohort P = 0.0035) and dehydroepiandrosterone sulfate (replication cohort P = 0.05). Minor allele carriers at rs3962158 from DNAJB1 had increased fasting insulin (discovery cohort P = 0.003), increased HOMA-IR (discovery cohort P = 0.006; replication cohort P = 0.036), and increased HOMA-%B (discovery cohort P = 0.004). Carriers of haplotype 2 at DNAJB1 also had increased fasting insulin, HOMA-IR, and HOMA-%B. These findings suggest that genetic variation in DKK1 and DNAJB1 may have a role in the hyperandrogenic and metabolic dysfunction of PCOS, respectively. Our results also demonstrate the utility of gene expression data as a source of novel candidate genes in PCOS, a complex and still incompletely defined disease, for which alternative methods of gene identification are needed.