Genetic scores of ENOS, ACE and VEGFA genes are predictive of endothelial dysfunction associated osteoporosis in postmenopausal women
journal contributionposted on 22.03.2021, 11:34 by Puneetpal Singh, Monica Singh, Rubanpal Khinda, Srishti Valecha, Nitin Kumar, Surinderpal Singh, Pawan K Juneja, Taranpal Kaur, Sarabjit Mastana
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. The present study aimed to examine the participation and contribution of endothelial nitric oxide synthase (eNOS), angiotensin converting enzyme (ACE) and vascular endothelial growth factor (VEGFA) genes for the risk of endothelial dysfunction (ED)-associated osteoporosis risk in postmenopausal women of Punjab, India. Women with ED were categorized into women with osteoporosis (n = 346) and women without osteoporosis (n = 330). They were examined for selected SNPs within eNOS, ACE and VEGFA genes. Linear regression analysis revealed a positive association of ED with bone mineral densities (BMDs) at femoral neck (r2 = 0.78, p < 0.001) and lumbar spine (r2 = 0.24, p = 0.001) after Bonferroni correction. Three susceptibility haplotypes were exposed within eNOS (CTAAAT), ACE (ACDG) and VEGFA (GATA) genes. Bearers of CTAAAT (OR 2.43, p = 0.007), ACDG (OR 2.50, p = 0.002) and GATA (OR 2.10, p = 0.009) had substantial impact for osteoporosis after correcting the effects with traditional risk factors (TRD).With uncertainty measure (R2h) and Akaike information criterion (AIC), best fit models showed that CTAAAT manifested in multiplicative mode (β ± SE: 2.19 ± 0.86, p < 0.001), whereas ACDG (β ± SE: 1.73 ± 0.54, p = 0.001) and GATA (β ± SE: 3.07 ± 0.81, p < 0.001) expressed in dominant modes. Area under receiver operating characteristic curve using weighted risk scores (effect estimates) showed substantial strength for model comprising TRD + GATA (AUC = 0.8, p < 0.001) whereas, model comprising TRD + GATA + CTAAAT exhibited excellent ability to predict osteoporosis (AUC = 0.824, p < 0.001).
Department of Science and Technology, Science and Engineering Research Board (DST-SERB), New Delhi (EMR/2016/0061)
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