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Association of Polymorphisms in Estrogen Receptor Genes ( ESR 1 and ESR 2) with Osteoporosis and Fracture-Involvement of Comorbidities and Epistasis.

M Davidnia García-RojasGrecia Palma-CorderoCeleste O Martínez-RamírezValeria Ponce de León-SuárezMargarita Valdés-FloresClementina Castro-HernándezJulieta Rubio-LightbournEdgar Hernández-ZamoraElba Reyes-MaldonadoRafael Velázquez-CruzBlanca Barredo-PrietoLeonora Casas-Avila
Published in: DNA and cell biology (2022)
Single-nucleotide polymorphisms (SNPs) in the ESR 1/ ESR 2 genes play a role in osteoporosis (OP). Our objective was to determine associations of polymorphisms in ESR genes with OP and fracture, SNP-SNP interactions, and involvement of comorbidities. We analyzed 170 Mexican osteoporotic women (FNOP), 173 with hip fracture (HFx), and 210 controls. The SNPs, ESR 1 rs2234693CC, rs851982CC and rs1999805AA, were associated with reduced OP risk (odds ratios [ORs] = 0.35, 0.40 and 0.32, respectively; p  < 0.05); rs2234693CC was associated with reduced fracture risk (OR = 0.24; p  < 0.05). The obese/overweight carriers of rs9340799GG had a lower OP (OR = 0.15, p  = 0.016) and fracture (OR = 0.12, p  = 0.0057) risk. The rs9479055AA and rs3020404AA hypertensive carriers had a higher OP risk (OR = 5.96, p  = 0.032; and OR = 5.29, p  = 0.02, respectively). In addition, rs3020404AA had a higher risk of fracture (OR = 4.90, p  = 0.045). The rs2228480GG hypertensive carriers had a higher risk of fracture (OR = 6.22, p  = 0.0038). We found a synergic relation between the ESR 1 rs3020331 and rs1999805 in femoral neck OP and HFx. The rs2234693 ( Pvu II) and rs9340799 ( Xba I) polymorphisms are associated with a high risk forming a haplotype. The epistasis analysis suggests the contribution of both genes ( ESR 1/ ESR 2) to the risk of OP and fracture. Epistasis and involvement of obesity and hypertension lead to a significant modification of the risk.
Keyphrases
  • estrogen receptor
  • hip fracture
  • genome wide
  • blood pressure
  • weight loss
  • metabolic syndrome
  • insulin resistance
  • pregnant women
  • body composition
  • obese patients
  • bioinformatics analysis