Sopova Julia, Krasnova Olga, Vasilieva Giomar, Zhuk Anna, Lesnyak Olga, Karelkin Vitaliy, Neganova Irina
Institute of Cytology, Russian Academy of Sciences, St. Petersburg 194064, Russia.
Laboratory of Amyloid Biology, Saint-Petersburg State University, St. Petersburg 199034, Russia.
Int J Mol Sci. 2024 Dec 19;25(24):13594. doi: 10.3390/ijms252413594.
G-protein-coupled receptors (GPCRs) have emerged as critical regulators of bone development and remodeling. In this study, we aimed to identify specific GPCR mutations in osteoporotic patients via next-generation sequencing (NGS). We performed NGS sequencing of six genomic DNA samples taken from osteoporotic patients and two genomic DNA samples from healthy donors. Next, we searched for single-nucleotide polymorphisms (SNPs) in GPCR genes that are associated with osteoporosis. For three osteoporotic patients and one healthy donor, bone biopsies were used to generate patient-specific mesenchymal stem cell (MSC) lines, and their ability to undergo osteodifferentiation was analyzed. We found that MSCs derived from osteoporotic patients have a different response to osteoinductive factors and impaired osteogenic differentiation using qPCR and histochemical staining assays. The NGS analysis revealed specific combinations of SNPs in GPCR genes in these patients, where SNPs in (rs1042713), (rs1800437), (rs2501431, rs3003336), and (rs3762371) were associated with impaired osteogenic differentiation capacity. By integrating NGS data with functional assessments of patient-specific cell lines, we linked GPCR mutations to impaired bone formation, providing a foundation for developing personalized therapeutic strategies. SNP analysis is recognized as a proactive approach to osteoporosis management, enabling earlier interventions and targeted preventive measures for individuals at risk. Furthermore, SNP analysis contributes to the development of robust, holistic risk prediction models that enhance the accuracy of risk assessments across the population. This integration of genetic data into public health strategies facilitates healthcare initiatives. This approach could guide treatment decisions tailored to the patient's genetic profile and provide a foundation for developing personalized therapeutic strategies.
G蛋白偶联受体(GPCRs)已成为骨骼发育和重塑的关键调节因子。在本研究中,我们旨在通过下一代测序(NGS)鉴定骨质疏松症患者中的特定GPCR突变。我们对取自骨质疏松症患者的6份基因组DNA样本和来自健康供体的2份基因组DNA样本进行了NGS测序。接下来,我们在与骨质疏松症相关的GPCR基因中寻找单核苷酸多态性(SNP)。对于3名骨质疏松症患者和1名健康供体,使用骨活检来生成患者特异性间充质干细胞(MSC)系,并分析其进行成骨分化的能力。我们发现,使用qPCR和组织化学染色分析,源自骨质疏松症患者的间充质干细胞对成骨诱导因子有不同反应,且成骨分化受损。NGS分析揭示了这些患者GPCR基因中SNP的特定组合,其中(rs1042713)、(rs1800437)、(rs2501431、rs3003336)和(rs3762371)中的SNP与成骨分化能力受损有关。通过将NGS数据与患者特异性细胞系的功能评估相结合,我们将GPCR突变与骨形成受损联系起来,为制定个性化治疗策略奠定了基础。SNP分析被认为是骨质疏松症管理的一种前瞻性方法,能够对有风险的个体进行更早的干预和有针对性的预防措施。此外,SNP分析有助于开发强大的整体风险预测模型,提高整个人群风险评估的准确性。将遗传数据整合到公共卫生策略中有助于医疗保健举措。这种方法可以指导根据患者基因概况量身定制的治疗决策,并为制定个性化治疗策略提供基础。