1
|
Teede H, Deeks A and Moran L: Polycystic
ovary syndrome: A complex condition with psychological,
reproductive and metabolic manifestations that impacts on health
across the lifespan. BMC Med. 8:412010. View Article : Google Scholar : PubMed/NCBI
|
2
|
Kar P and Cummings M: Polycystic ovary
syndrome. Pract Diabetes Int. 22:256–260. 2005. View Article : Google Scholar
|
3
|
Naderpoor N, Shorakae S, Joham A, Boyle J,
De Courten B and Teede HJ: Obesity and polycystic ovary syndrome.
Minerva Endocrinol. 40:37–51. 2015.
|
4
|
Tehrani FR, Simbar M, Tohidi M,
Hosseinpanah F and Azizi F: The prevalence of polycystic ovary
syndrome in a community sample of Iranian population: Iranian PCOS
prevalence study. Reprod Biol Endocrinol. 9:392011. View Article : Google Scholar : PubMed/NCBI
|
5
|
Palioura E and Diamanti-Kandarakis E:
Industrial endocrine disruptors and polycystic ovary syndrome. J
Endocrinol Invest. 36:1105–1111. 2013. View Article : Google Scholar
|
6
|
Wang F, Zhang Z and Wang Z, Xiao K, Wang
Q, Su J and Wang Z: Expression and clinical significance of the
HIF-1α/ET-2 signaling pathway during the development and treatment
of polycystic ovary syndrome. J Mol Histol. 46:173–181. 2015.
View Article : Google Scholar : PubMed/NCBI
|
7
|
Ding CF, Chen WQ, Zhu YT, Bo YL, Hu HM and
Zheng RH: Circulating microRNAs in patients with polycystic ovary
syndrome. Hum Fertil (Camb). 18:22–29. 2015. View Article : Google Scholar
|
8
|
Xu B, Zhang YW, Tong XH and Liu YS:
Characterization of microRNA profile in human cumulus granulosa
cells: Identification of microRNAs that regulate Notch signaling
and are associated with PCOS. Mol Cell Endocrinol. 404:26–36. 2015.
View Article : Google Scholar : PubMed/NCBI
|
9
|
Kaur S, Archer KJ, Devi MG, Kriplani A,
Strauss JF III and Singh R: Differential gene expression in
granulosa cells from polycystic ovary syndrome patients with and
without insulin resistance: Identification of susceptibility gene
sets through network analysis. J Clin Endocrinol Metab.
97:E2016–E2021. 2012. View Article : Google Scholar : PubMed/NCBI
|
10
|
Liu HY, Liu JQ, Mai ZX and Zeng YT: A
subpathway-based method of drug reposition for polycystic ovary
syndrome. Reprod Sci. 22:423–430. 2015. View Article : Google Scholar
|
11
|
Liu HY, Huang YL, Liu JQ and Huang Q:
Transcription factor microRNA synergistic regulatory network
revealing the mechanism of polycystic ovary syndrome. Mol Med Rep.
13:3920–3928. 2016. View Article : Google Scholar : PubMed/NCBI
|
12
|
Bohler A, Wu G, Kutmon M, Pradhana LA,
Coort SL, Hanspers K, Haw R, Pico AR and Evelo CT: Reactome from a
WikiPathways perspective. PLoS Comput Biol. 12:e10049412016.
View Article : Google Scholar : PubMed/NCBI
|
13
|
Wu G, Dawson E, Duong A, Haw R and Stein
L: ReactomeFIViz: A Cytoscape app for pathway and network-based
data analysis. F1000Res. 3:1462014.PubMed/NCBI
|
14
|
Edgar R, Domrachev M and Lash AE: Gene
Expression Omnibus: NCBI gene expression and hybridization array
data repository. Nucleic Acids Res. 30:207–210. 2002. View Article : Google Scholar :
|
15
|
Mitra PS, Ghosh S, Zang S, Sonneborn D,
Hertz-Picciotto I, Trnovec T, Palkovicova L, Sovcikova E,
Ghimbovschi S, Hoffman EP, et al: Analysis of the toxicogenomic
effects of exposure to persistent organic pollutants (POPs) in
Slovakian girls: Correlations between gene expression and disease
risk. Environ Int. 39:188–199. 2012. View Article : Google Scholar : PubMed/NCBI
|
16
|
Gautier L, Cope L, Bolstad BM and Irizarry
RA: affy - analysis of Affymetrix GeneChip data at the probe level.
Bioinformatics. 20:307–315. 2004. View Article : Google Scholar : PubMed/NCBI
|
17
|
Gentleman RC, Carey VJ, Bates DM, Bolstad
B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, et al:
Bioconductor: Open software development for computational biology
and bioinformatics. Genome Biol. 5:R802004. View Article : Google Scholar : PubMed/NCBI
|
18
|
Liu J, Yang XY and Shi WJ: Identifying
differentially expressed genes and pathways in two types of
non-small cell lung cancer: Adenocarcinoma and squamous cell
carcinoma. Genet Mol Res. 13:95–102. 2014. View Article : Google Scholar : PubMed/NCBI
|
19
|
Szekely GJ and Rizzo ML: Hierarchical
clustering via joint between-within distances: Extending Ward's
minimum variance method. J Classif. 22:151–183. 2005. View Article : Google Scholar
|
20
|
Bindea G, Mlecnik B, Hackl H, Charoentong
P, Tosolini M, Kirilovsky A, Fridman WH, Pagès F, Trajanoski Z and
Galon J: ClueGO: A Cytoscape plug-in to decipher functionally
grouped gene ontology and pathway annotation networks.
Bioinformatics. 25:1091–1093. 2009. View Article : Google Scholar : PubMed/NCBI
|
21
|
Bindea G, Galon J and Mlecnik B: CluePedia
Cytoscape plugin: Pathway insights using integrated experimental
and in silico data. Bioinformatics. 29:661–663. 2013. View Article : Google Scholar : PubMed/NCBI
|
22
|
Thissen D and Kuang D: Quick and easy
implementation of the Benjamini-Hochberg procedure for controlling
the false positive rate in multiple comparisons. J Educ Behav Stat.
27:77–83. 2002. View Article : Google Scholar
|
23
|
Luo W and Brouwer C: Pathview: An
R/Bioconductor package for pathway-based data integration and
visualization. Bioinformatics. 29:1830–1831. 2013. View Article : Google Scholar : PubMed/NCBI
|
24
|
Barabási AL, Gulbahce N and Loscalzo J:
Network medicine: A network-based approach to human disease. Nat
Rev Genet. 12:56–68. 2011. View
Article : Google Scholar :
|
25
|
Guzzi PH and Mina M: AlignMCL: Comparative
analysis of protein interaction networks through Markov clustering.
IEEE International Conference on Bioinformatics and Biomedicine
Workshops. 174–181. 2012.
|
26
|
Joshi-Tope G, Gillespie M, Vastrik I,
D'Eustachio P, Schmidt E, de Bono B, Jassal B, Gopinath GR, Wu GR,
Matthews L, et al: Reactome: A knowledgebase of biological
pathways. Nucleic Acids Res. 33:D428–D432. 2005. View Article : Google Scholar :
|
27
|
Schaefer CF, Anthony K, Krupa S, Buchoff
J, Day M, Hannay T and Buetow KH: PID: The pathway interaction
database. Nucleic Acids Res. 37:D674–D679. 2009. View Article : Google Scholar :
|
28
|
Mi H and Thomas P: PANTHER pathway: An
ontology-based pathway database coupled with data analysis tools.
Methods Mol Biol. 563:123–140. 2009. View Article : Google Scholar : PubMed/NCBI
|
29
|
Glintborg D and Andersen M: An update on
the pathogenesis, inflammation, and metabolism in hirsutism and
polycystic ovary syndrome. Gynecol Endocrinol. 26:281–296. 2010.
View Article : Google Scholar : PubMed/NCBI
|
30
|
Ojeda-Ojeda M, Murri M, Insenser M and
Escobar-Morreale HF: Mediators of low-grade chronic inflammation in
polycystic ovary syndrome (PCOS). Curr Pharm Des. 19:5775–5791.
2013. View Article : Google Scholar : PubMed/NCBI
|
31
|
Kovács M, Németh T, Jakus Z, Sitaru C,
Simon E, Futosi K, Botz B, Helyes Z, Lowell CA and Mócsai A: The
Src family kinases Hck, Fgr, and Lyn are critical for the
generation of the in vivo inflammatory environment without a direct
role in leukocyte recruitment. J Exp Med. 211:1993–2011. 2014.
View Article : Google Scholar : PubMed/NCBI
|
32
|
Scapini P, Pereira S, Zhang H and Lowell
CA: Multiple roles of Lyn kinase in myeloid cell signaling and
function. Immunol Rev. 228:23–40. 2009. View Article : Google Scholar : PubMed/NCBI
|
33
|
Toubiana J, Rossi AL, Belaidouni N,
Grimaldi D, Pene F, Chafey P, Comba B, Camoin L, Bismuth G,
Claessens YE, et al: Src-family-tyrosine kinase Lyn is critical for
TLR2-mediated NF-κB activation through the PI 3-kinase signaling
pathway. Innate Immun. 21:685–697. 2015. View Article : Google Scholar : PubMed/NCBI
|
34
|
Wieser V, Moschen AR and Tilg H:
Inflammation, cytokines and insulin resistance: A clinical
perspective. Arch Immunol Ther Exp (Warsz). 61:119–125. 2013.
View Article : Google Scholar
|
35
|
DeUgarte CM, Bartolucci AA and Azziz R:
Prevalence of insulin resistance in the polycystic ovary syndrome
using the homeostasis model assessment. Fertil Steril.
83:1454–1460. 2005. View Article : Google Scholar : PubMed/NCBI
|
36
|
Stankiewicz TR and Linseman DA: Rho family
GTPases: Key players in neuronal development, neuronal survival,
and neurodegeneration. Front Cell Neurosci. 8:3142014. View Article : Google Scholar : PubMed/NCBI
|
37
|
Liu X, Yan F, Yao H, Chang M, Qin J, Li Y,
Wang Y and Pei X: Involvement of RhoA/ROCK in insulin secretion of
pancreatic β-cells in 3D culture. Cell Tissue Res. 358:359–369.
2014. View Article : Google Scholar : PubMed/NCBI
|
38
|
Kanda T, Wakino S, Homma K, Yoshioka K,
Tatematsu S, Hasegawa K, Takamatsu I, Sugano N, Hayashi K and
Saruta T: Rho-kinase as a molecular target for insulin resistance
and hypertension. FASEB J. 20:169–171. 2006.
|
39
|
Sewer MB and Li D: Regulation of
adrenocortical steroid hormone production by RhoA-diaphanous 1
signaling and the cytoskeleton. Mol Cell Endocrinol. 371:79–86.
2013. View Article : Google Scholar
|
40
|
Vogt DL, Gray CD, Young WS III, Orellana
SA and Malouf AT: ARHGAP4 is a novel RhoGAP that mediates
inhibition of cell motility and axon outgrowth. Mol Cell Neurosci.
36:332–342. 2007. View Article : Google Scholar : PubMed/NCBI
|
41
|
Kim S, Dangelmaier C, Bhavanasi D, Meng S,
Wang H, Goldfinger LE and Kunapuli SP: RhoG protein regulates
glycoprotein VI-Fc receptor γ-chain complex-mediated platelet
activation and thrombus formation. J Biol Chem. 288:34230–34238.
2013. View Article : Google Scholar : PubMed/NCBI
|
42
|
Rajendran S, Willoughby SR, Chan WPA,
Liberts EA, Heresztyn T, Saha M, Marber MS, Norman RJ and Horowitz
JD: Polycystic ovary syndrome is associated with severe platelet
and endothelial dysfunction in both obese and lean subjects.
Atherosclerosis. 204:509–514. 2009. View Article : Google Scholar
|
43
|
Stokes KY and Granger DN: Platelets: A
critical link between inflammation and microvascular dysfunction. J
Physiol. 590:1023–1034. 2012. View Article : Google Scholar :
|
44
|
Salvetti NR, Gimeno EJ, Lorente JA and
Ortega HH: Expression of cytoskeletal proteins in the follicular
wall of induced ovarian cysts. Cells Tissues Organs. 178:117–125.
2004. View Article : Google Scholar : PubMed/NCBI
|
45
|
Cortón M, Botella-Carretero JI, Benguría
A, Villuendas G, Zaballos A, San Millán JL, Escobar-Morreale HF and
Peral B: Differential gene expression profile in omental adipose
tissue in women with polycystic ovary syndrome. J Clin Endocrinol
Metab. 92:328–337. 2007. View Article : Google Scholar
|
46
|
Ober C, Weil S, Steck T, Billstrand C,
Levrant S and Barnes R: Increased risk for polycystic ovary
syndrome associated with human leukocyte antigen
DQA1*0501. Am J Obstet Gynecol. 167:1803–1806. 1992.
View Article : Google Scholar : PubMed/NCBI
|
47
|
Kaibe M, Takakuwa K, Murakawa H, Ishii K,
Tamura M and Tanaka K: Studies on the human leukocyte antigens in
patients with polycystic ovary syndrome in a Japanese population -
possible susceptibility of HLA-A11 and -DRB1*0403 to
patient population with polycystic ovary syndrome. Am J Reprod
Immunol. 55:301–306. 2006. View Article : Google Scholar : PubMed/NCBI
|
48
|
Ozteki O, Fenkci SM, Fenkci V, Enli Y and
Cabus U: Serum HLA-G levels in women with polycystic ovary
syndrome. Gynecol Endocrinol. 31:243–246. 2015. View Article : Google Scholar
|
49
|
Strodthoff D, Ma Z, Wirström T,
Strawbridge RJ, Ketelhuth DF, Engel D, Clarke R, Falkmer S, Hamsten
A, Hansson GK, et al: Toll-like receptor 3 influences glucose
homeostasis and β-cell Insulin Secretion. Diabetes. 64:3425–3438.
2015. View Article : Google Scholar : PubMed/NCBI
|
50
|
Hemmati F, Ghasemi R, Mohamed Ibrahim N,
Dargahi L, Mohamed Z, Raymond AA and Ahmadiani A: Crosstalk between
insulin and Toll-like receptor signaling pathways in the central
nervous system. Mol Neurobiol. 50:797–810. 2014. View Article : Google Scholar : PubMed/NCBI
|