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  • Title: Decisive gene strategy on osteoporosis: a comprehensive whole-literature-based approach for conclusive candidate gene targets.
    Author: Chen YC, Tsai YJ, Wang CC, Ko PS, Su W, Su SL.
    Journal: Aging (Albany NY); 2022 Apr 22; 14(8):3484-3528. PubMed ID: 35452412.
    Abstract:
    PURPOSE: Previous meta-analyses only examined the association between single gene polymorphisms and osteoporosis; there is no compilation of all gene loci that correlate with osteoporosis in the literature. In this study, we develop a new literature-based approach, a decisive gene strategy (DGS), to examine the sufficiency of the cumulative sample size for each gene locus and to assess whether a definite conclusion of the association between the gene locus and osteoporosis can be drawn. METHODS: The DGS was used to search PubMed, Embase, and Cochrane databases for all meta-analyses that correlated gene polymorphisms with osteoporosis. Trial sequential analysis was employed to examine the sufficiency of the cumulative sample size. Finally, we assessed the importance of gene loci in osteoporosis based on whether there were enough sample sizes and the heterogeneity of the literature with the I2 value. RESULTS: After excluding 169 irrelevant publications, 39 meta-analysis papers were obtained. Among Caucasians, in 17 gene loci, there were eight gene loci (e.g., vitamin D Receptor ApaI rs7975232) with sufficient cumulative sample size to confirm that they were unrelated to the disease. Among Asians, in 15 gene loci, four gene loci that had sufficient sample sizes were risk factors: VDR FokI rs2228570 (odds ratio (OR) = 1.44, 95% confidence interval (CI) = 1.22-1.70), TGF β1 rs1800470 (OR = 1.35, 95% CI = 1.10-1.65), IGF1 rs2288377 (OR = 1.44, 95% CI = 1.28-1.62), and IGF1 rs35767 (OR = 1.20, 95% CI = 1.06-1.36), respectively, whereas one gene locus, ESR2 RsaI rs1256049 (OR = 0.69, 95% CI = 0.59-0.81), was a protective factor. CONCLUSIONS: The DGS successfully identified five gene loci in osteoporosis that will apply to other diseases to find causal genes, which may contribute to further genetic therapy.
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