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'Diabetes gene' may be linked to polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) occurs when ovarian cysts block a woman's normal ovulation and menstrual cycle. While the problem sounds straightforward, the disease is complex, born from both multiple genetic components and environmental factors.

PCOS affects up to five percent of the female population, and those diagnosed with the disease have a 2- to 7-fold risk of developing type 2 diabetes mellitus (T2DM). For this reason researchers believe a gene related to diabetes may also play a role in the onset of PCOS. A new study of 146 PCOS patients has found that the "diabetes gene" (calpain-10 (CAPN10)) is in fact an interesting candidate for explaining the syndrome.

A New Study

The findings are contained in a new study entitled "Calpain-10 Variants and Haplotypes are Associated with Polycystic Ovary Syndrome in Caucasians." The study was conducted by Caren Vollmert, Claudia Lamina, Cornelia Huth, Melanie Kolz, Andreas Schopfer-Wendels, Friedhelm Bongardt, Florian Kronenberg, Hannelore Lowel and Thomas Illig, all of the GSF-National Research Center for Environment and Health, Neuherberg; Susanne Hahn, Klaus Mann and Onno E. Janssen, University of Duisburg-Essen, Essen; H.-Erich Wichmann, Ludwig Maximilians University, Munich; Jakob C. Mueller, Technical University, Munich; Christian Herder, Heinrich Heine University, Dusseldorf; and Rolf Holle, GSF-National Research Center of Environment and Health, Neuherberg, Germany.

Their study appears in the online edition of the American Journal of Physiology-Endocrinology and Metabolism ( The journal is one of the 14 scientific publications published by the American Physiological Society (APS) ( each month.


The study comprised 752 females. Of the total, 146 were diagnosed with PCOS and 606 were unrelated non-diabetic female controls drawn from a previously conducted independent study of the German population.

Genomic DNA was taken from the PCOS group and isolated from whole blood, and genomic DNA was extracted from the blood leukocytes of the controls. Eight CAPN10 variants were genotyped: UCSNP-44, -43, -56, ins/del-19 (a fragment of gene CAPN10 UCSNP-19, which contains an insertion or deletion variation in the DNA sequence), -110, -58, -63, and -22.

The researchers extracted these eight specific single-nucleotide polymorphisms (SNPs) ¡V the small genetic variations that can occur within a person's DNA sequence because they are known to be associated with PCOS, type 2 diabetes, or related traits. Genotyping using comparative DNA analysis to determine the predisposition of individuals to certain diseases was then performed.

To estimate the genetic association of each of the eight SNPs with PCOS the differences in genotype distributions between the case and control groups were measured. The impact of the differences in age and body mass index (BMI) structures for both groups was also calculated. To better clarify the purported associations between CAPN10 and PCOS the researchers performed a meta-analysis using their own data and all available published data showing a genetic association between CAPN10 and PCOS.


Highlights of the researchers' findings include the following:

- clear evidence associating the diabetes gene areas CAPN10 UCSNP-56 and UCSNP-ins/del-19 with PCOS susceptibility

- an expected association between CAPN10 UCSNP-22 and PCOS

- no significant association between CAPN10 UCSNP-44, -43, -110, -58, or -63 and PCOS susceptibility


This study provides additional strong support for the theory that two areas of one gene -- CAPN10 UCSNP-56 and UCSNP-ins/del-19 -- are related to PCOS susceptibility. These data also suggest that the SNP ins/del-19 may be related to both PCOS and type 2 diabetes.

The findings are good news for the estimated five percent of the female population who are diagnosed with the painful and sometimes disabling disease. At the same time, the authors recommend that additional case-control studies and meta-analysis be undertaken to better understand these findings.

Donna Krupa | EurekAlert!
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