Title

PCOSDB:  PolyCystic Ovary Syndrome DataBase for manually curated genes associated with the disease

Authors

Affiliation

¹Dr. MGR Educational and Research Institute University, Chennai, Tamil Nadu, India.

²Vision Research Foundation, Sankara Nethralaya, Chennai, Tamil Nadu, India.

Email

jesintha_21@yahoo.com; *Corresponding author

Article Type

Database

Date

Received January 04, 2016; Accepted January 07, 2016; Published January 31, 2016

Polycystic ovary syndrome (PCOS) is a complex disorder affecting approximately 5–10% of all women of reproductive age. It is a multi-factorial endocrine disorder, which demonstrates menstrual disturbance, infertility, anovulation, hirsutism, hyper androgenism and others. It has been indicated that differential expression of genes, genetic level variations, and other molecular alterations interplay in PCOS and are the target sites for clinical applications. Therefore, integrating the PCOS-associated genes along with its alteration and underpinning the underlying mechanism might definitely provide valuable information to understand the disease mechanism. We manually curated the information from 234 published literatures, including gene, molecular alteration, details of association, significance of association, ethnicity, age, drug, and other annotated summaries. PCOSDB is an online resource that brings comprehensive information about the disease, and the implication of various genes and its mechanism. We present the curated information from peer reviewed literatures, and organized the information at various levels including differentially expressed genes in PCOS, genetic variations such as polymorphisms, mutations causing PCOS across various ethnicities. We have covered both significant and non-significant associations along with conflicting studies. PCOSDB v1.0 contains 208 gene reports, 427 molecular alterations, and 46 phenotypes associated with PCOS.

Keywords

PCOS; Polycystic Ovary Syndrome; SNP; Polymorphism

Citation

Mary et al.  Bioinformation 12(1): 4-8 (2016)
 

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.