Dataset Information

Genome-wide polygenic risk score for major osteoporotic fractures in postmenopausal women using associated single nucleotide polymorphisms.

ABSTRACT:

Background

Osteoporosis is highly polygenic and heritable, with heritability ranging from 50 to 80%; most inherited susceptibility is associated with the cumulative effect of many common genetic variants. However, existing genetic risk scores (GRS) only provide a few percent predictive power for osteoporotic fracture.

Methods

We derived and validated a novel genome-wide polygenic score (GPS) comprised of 103,155 common genetic variants to quantify this susceptibility and tested this GPS prediction ability in an independent dataset (n = 15,776).

Results

Among postmenopausal women, we found a fivefold gradient in the risk of major osteoporotic fracture (MOF) (p < 0.001) and a 15.25-fold increased risk of severe osteoporosis (p < 0.001) across the GPS deciles. Compared with the remainder of the GPS distribution, the top GPS decile was associated with a 3.59-, 2.48-, 1.92-, and 1.58-fold increased risk of any fracture, MOF, hip fracture, and spine fracture, respectively. The top GPS decile also identified nearly twofold more high-risk osteoporotic patients than the top decile of conventional GRS based on 1103 conditionally independent genome-wide significant SNPs. Although the relative risk of severe osteoporosis for postmenopausal women at around 50 is relatively similar, the cumulative incident at 20-year follow-up is significantly different between the top GPS decile (13.7%) and the bottom decile (< 1%). In the subgroup analysis, the GPS transferability in non-Hispanic White is better than in other racial/ethnic groups.

Conclusions

This new method to quantify inherited susceptibility to osteoporosis and osteoporotic fracture affords new opportunities for clinical prevention and risk assessment.

SUBMITTER: Wu Q

PROVIDER: S-EPMC9933300 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Publications

Genome-wide polygenic risk score for major osteoporotic fractures in postmenopausal women using associated single nucleotide polymorphisms.

Wu Qing Q Jung Jongyun J

Journal of translational medicine 20230216 1

<h4>Background</h4>Osteoporosis is highly polygenic and heritable, with heritability ranging from 50 to 80%; most inherited susceptibility is associated with the cumulative effect of many common genetic variants. However, existing genetic risk scores (GRS) only provide a few percent predictive power for osteoporotic fracture.<h4>Methods</h4>We derived and validated a novel genome-wide polygenic score (GPS) comprised of 103,155 common genetic variants to quantify this susceptibility and tested th ...[more]

PMID: 36797788

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Project description:As life expectancy increases, the prevalence of osteoporosis is increasing. In addition to vitamin D which is well established to have an association with osteoporosis, B vitamins, such as thiamine, folate (vitamin B9), and cobalamin (vitamin B12), could affect bone metabolism, bone quality, and fracture risk in humans by influencing homocysteine/folate metabolism. Despite the crucial role of B vitamins in bone metabolism, there are few studies regarding associations between B vitamin-related genes and osteoporosis. In this study, we investigated the genetic association of four single nucleotide polymorphisms (SNPs) within the 3'-untranslated regions of vitamin B-related genes, including TCN2 (encodes transcobalamin II), CD320 (encodes transcobalamin II receptor), SLC19A1 (encodes reduced folate carrier protein 1), and SLC19A2 (encodes thiamine carrier 1), with osteoporosis and osteoporotic vertebral compression fracture (OVCF). We recruited 301 postmenopausal women and performed genotyping of CD320 rs9426C>T,TCN2 rs10418C>T, SLC19A1 rs1051296G>T, and SLC19A2 rs16862199C>T using a polymerization chain reaction-restriction fragment length polymorphism assay. There was a significantly higher incidence of both osteoporosis (AOR 5.019; 95% CI, 1.533-16.430, p < 0.05) and OVCF (AOR, 5.760; 95% CI, 1.480-22.417, p < 0.05) in individuals with genotype CD320 CT+TT and high homocysteine concentrations. Allele combination analysis revealed that two combinations, namely CD320 C-TCN2 T-SLC19A1 T-SLC19A2 C (OR, 3.244; 95% CI, 1.478-7.120, p < 0.05) and CD320 T-TCN2 C-SLC19A1 G-SLC19A2 C (OR, 2.287; 95% CI, 1.094-4.782, p < 0.05), were significantly more frequent among the osteoporosis group. Our findings suggest that SNPs within the CD320 gene in 3´-UTR may contribute to osteoporosis and OVCF occurrences in some individuals. Furthermore, specific allele combinations of CD320, TCN2, SLC19A1, and SLC19A2 may contribute to increased susceptibility to osteoporosis and OVCF.

Project description:The potential of bone mineral density (BMD)-related genome-wide polygenic score (PGS) in identifying individuals with a high risk of fractures remains unclear. This study suggests that an efficient PGS enables the identification of strata with up to a 1.5-fold difference in fracture incidence. Incorporating PGS into clinical diagnosis is anticipated to increase the population-level screening benefits.PurposeThis study sought to construct genome-wide polygenic scores for femoral neck and total body BMD and to estimate their potential in identifying individuals with a high risk of osteoporotic fractures.MethodsGenome-wide polygenic scores were developed and validated for femoral neck and total body BMD. We externally tested the PGSs, both by themselves and in combination with available clinical risk factors, in 455,663 European ancestry individuals from the UK Biobank. The predictive accuracy of the developed genome-wide PGS was also compared with previously published restricted PGS employed in fracture risk assessment.ResultsFor each unit decrease in PGSs, the genome-wide PGSs were associated with up to 1.17-fold increased fracture risk. Out of four studied PGSs, [Formula: see text] (HR: 1.03; 95%CI 1.01-1.05, p = 0.001) had the weakest and the [Formula: see text] (HR: 1.17; 95%CI 1.15-1.19, p < 0.0001) had the strongest association with an incident fracture. In the reclassification analysis, compared to the FRAX base model, the models with [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] improved the reclassification of fracture by 1.2% (95% CI, 1.0 to 1.3%), 0.2% (95% CI, 0.1 to 0.3%), 1.4% (95% CI, 1.3 to 1.5%), and 2.2% (95% CI, 2.1 to 2.4%), respectively.ConclusionsOur findings suggested that an efficient PGS estimate enables the identification of strata with up to a 1.7-fold difference in fracture incidence. Incorporating PGS information into clinical diagnosis is anticipated to increase the benefits of screening programs at the population level.

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Project description:Osteoporosis is the consequence of altered bone metabolism resulting in the systemic reduction of bone strength and increased risk of fragility fractures. MicroRNAs (miRNAs) regulate gene expression on a post-transcriptional level are known to take part in the control of bone formation and bone resorption. Recently, targeted secretion of miRNAs from cells originating from various tissues has been described, which allows for their minimal-invasive detection in serum/plasma and use as biomarkers for presence and progression of pathological conditions. One pilot study has reported circulating miRNAs in serum and tissue of fracture patients. However, further studies are required to explore whether a dysbalance in bone homeostasis of fracture patients can reliably be reflected by specific circulating miRNAs, and whether these miRNAs might serve as drugable targets. Here, we report results from a comprehensive multiplex study of 175 miRNAs in serum samples obtained from 7 patients with osteoporotic fractures at the femoral neck, and 7 age-matched controls. Following elaborate quality control statistical analysis of this exploratory dataset identified 9 microRNAs with altered serum levels in response to fracture (adjusted p-value < 0.1). Of these, hsa-miR-10a/b gave excellent discrimination of both groups (AUC = 1.0), and clustering of samples based on the top10 miRNAs confirmed the high discriminatory power of circulating microRNAs for osteoporotic fractures. In the next step 3 miRNAs with unknown roles in osteogenic differentiation and 4 miRNA from a previous study were tested for their effects on osteogenic differentiation. Of these, 3 miRNAs showed robust effects on osteogenic differentiation. Overall, these data provide important insights into changes in serum miRNA in post-traumatic patients. Future studies will show, whether this knowledge can be used to improve current diagnostic methodologies to predict fracture risk and design novel treatment strategies for osteoporosis patients. Two groups with n=7 per group; one groups represents cases with osteoporotic fractures, the control group is age-matched without fractures

Dataset Information

Genome-wide polygenic risk score for major osteoporotic fractures in postmenopausal women using associated single nucleotide polymorphisms.

Background

Methods

Results

Conclusions

Publications

Genome-wide polygenic risk score for major osteoporotic fractures in postmenopausal women using associated single nucleotide polymorphisms.

Similar Datasets

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