Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study

Background Since screening programs identify only a small proportion of the population as eligible for an intervention, genomic prediction of heritable risk factors could decrease the number needing to be screened by removing individuals at low genetic risk. We therefore tested whether a polygenic risk score for heel quantitative ultrasound speed of sound (SOS)—a heritable risk factor for osteoporotic fracture—can identify low-risk individuals who can safely be excluded from a fracture risk screening program. Methods and findings A polygenic risk score for SOS was trained and selected in 2 separate subsets of UK Biobank (comprising 341,449 and 5,335 individuals). The top-performing prediction model was termed “gSOS”, and its utility in fracture risk screening was tested in 5 validation cohorts using the National Osteoporosis Guideline Group clinical guidelines (N = 10,522 eligible participants). All individuals were genome-wide genotyped and had measured fracture risk factors. Across the 5 cohorts, the average age ranged from 57 to 75 years, and 54% of studied individuals were women. The main outcomes were the sensitivity and specificity to correctly identify individuals requiring treatment with and without genetic prescreening. The reference standard was a bone mineral density (BMD)–based Fracture Risk Assessment Tool (FRAX) score. The secondary outcomes were the proportions of the screened population requiring clinical-risk-factor-based FRAX (CRF-FRAX) screening and BMD-based FRAX (BMD-FRAX) screening. gSOS was strongly correlated with measured SOS (r2 = 23.2%, 95% CI 22.7% to 23.7%). Without genetic prescreening, guideline recommendations achieved a sensitivity and specificity for correct treatment assignment of 99.6% and 97.1%, respectively, in the validation cohorts. However, 81% of the population required CRF-FRAX tests, and 37% required BMD-FRAX tests to achieve this accuracy. Using gSOS in prescreening and limiting further assessment to those with a low gSOS resulted in small changes to the sensitivity and specificity (93.4% and 98.5%, respectively), but the proportions of individuals requiring CRF-FRAX tests and BMD-FRAX tests were reduced by 37% and 41%, respectively. Study limitations include a reliance on cohorts of predominantly European ethnicity and use of a proxy of fracture risk. Conclusions Our results suggest that the use of a polygenic risk score in fracture risk screening could decrease the number of individuals requiring screening tests, including BMD measurement, while maintaining a high sensitivity and specificity to identify individuals who should be recommended an intervention

Genome-wide meta-analysis of muscle weakness identifies 15 susceptibility loci in older men and women

© 2021, The Author(s). Low muscle strength is an important heritable indicator of poor health linked to morbidity and mortality in older people. In a genome-wide association study meta-analysis of 256, 523 Europeans aged 60 years and over from 22 cohorts we identify 15 loci associated with muscle weakness (European Working Group on Sarcopenia in Older People definition: n = 48,596 cases, 18.9% of total), including 12 loci not implicated in previous analyses of continuous measures of grip strength. Loci include genes reportedly involved in autoimmune disease (HLA-DQA1p = 4 × 10−17), arthritis (GDF5p = 4 × 10−13), cell cycle control and cancer protection, regulation of transcription, and others involved in the development and maintenance of the musculoskeletal system. Using Mendelian randomization we report possible overlapping causal pathways, including diabetes susceptibility, haematological parameters, and the immune system. We conclude that muscle weakness in older adults has distinct mechanisms from continuous strength, including several pathways considered to be hallmarks of ageing

Genetic Determinants of Circulating Estrogen Levels and Evidence of a Causal Effect of Estradiol on Bone Density in Men.

CONTEXT: Serum estradiol (E2) and estrone (E1) levels exhibit substantial heritability. OBJECTIVE: To investigate the genetic regulation of serum E2 and E1 in men. DESIGN, SETTING, AND PARTICIPANTS: Genome-wide association study in 11,097 men of European origin from nine epidemiological cohorts. MAIN OUTCOME MEASURES: Genetic determinants of serum E2 and E1 levels. RESULTS: Variants in/near CYP19A1 demonstrated the strongest evidence for association with E2, resolving to three independent signals. Two additional independent signals were found on the X chromosome; FAMily with sequence similarity 9, member B (FAM9B), rs5934505 (P = 3.4 × 10-8) and Xq27.3, rs5951794 (P = 3.1 × 10-10). E1 signals were found in CYP19A1 (rs2899472, P = 5.5 × 10-23), in Tripartite motif containing 4 (TRIM4; rs17277546, P = 5.8 × 10-14), and CYP11B1/B2 (rs10093796, P = 1.2 × 10-8). E2 signals in CYP19A1 and FAM9B were associated with bone mineral density (BMD). Mendelian randomization analysis suggested a causal effect of serum E2 on BMD in men. A 1 pg/mL genetically increased E2 was associated with a 0.048 standard deviation increase in lumbar spine BMD (P = 2.8 × 10-12). In men and women combined, CYP19A1 alleles associated with higher E2 levels were associated with lower degrees of insulin resistance. CONCLUSIONS: Our findings confirm that CYP19A1 is an important genetic regulator of E2 and E1 levels and strengthen the causal importance of E2 for bone health in men. We also report two independent loci on the X-chromosome for E2, and one locus each in TRIM4 and CYP11B1/B2, for E1

Improved prediction of fracture risk leveraging a genome-wide polygenic risk score

Background Accurately quantifying the risk of osteoporotic fracture is important for directing appropriate clinical interventions. While skeletal measures such as heel quantitative speed of sound (SOS) and dual-energy X-ray absorptiometry bone mineral density are able to predict the risk of osteoporotic fracture, the utility of such measurements is subject to the availability of equipment and human resources. Using data from 341,449 individuals of white British ancestry, we previously developed a genome-wide polygenic risk score (PRS), called gSOS, that captured 25.0% of the total variance in SOS. Here, we test whether gSOS can improve fracture risk prediction. Methods We examined the predictive power of gSOS in five genome-wide genotyped cohorts, including 90,172 individuals of European ancestry and 25,034 individuals of Asian ancestry. We calculated gSOS for each individual and tested for the association between gSOS and incident major osteoporotic fracture and hip fracture. We tested whether adding gSOS to the risk prediction models had added value over models using other commonly used clinical risk factors. Results A standard deviation decrease in gSOS was associated with an increased odds of incident major osteoporotic fracture in populations of European ancestry, with odds ratios ranging from 1.35 to 1.46 in four cohorts. It was also associated with a 1.26-fold (95% confidence interval (CI) 1.13–1.41) increased odds of incident major osteoporotic fracture in the Asian population. We demonstrated that gSOS was more predictive of incident major osteoporotic fracture (area under the receiver operating characteristic curve (AUROC) = 0.734; 95% CI 0.727–0.740) and incident hip fracture (AUROC = 0.798; 95% CI 0.791–0.805) than most traditional clinical risk factors, including prior fracture, use of corticosteroids, rheumatoid arthritis, and smoking. We also showed that adding gSOS to the Fracture Risk Assessment Tool (FRAX) could refine the risk prediction with a positive net reclassification index ranging from 0.024 to 0.072. Conclusions We generated and validated a PRS for SOS which was associated with the risk of fracture. This score was more strongly associated with the risk of fracture than many clinical risk factors and provided an improvement in risk prediction. gSOS should be explored as a tool to improve risk stratification to identify individuals at high risk of fracture

Genetic Determinants of Circulating Estrogen Levels and Evidence of a Causal Effect of Estradiol on Bone Density in Men

Context: Serum estradiol (E2) and estrone (E1) levels exhibit substantial heritability.Objective: To investigate the genetic regulation of serum E2 and E1 in men.Design, Setting, and Participants: Genome-wide association study in 11,097 men of European origin from nine epidemiological cohorts.Main Outcome Measures: Genetic determinants of serum E2 and E1 levels.Results: Variants in/near CYP19A1 demonstrated the strongest evidence for association with E2, resolving to three independent signals. Two additional independent signals were found on the X chromosome; FAMily with sequence similarity 9, member B (FAM9B), rs5934505 (P = 3.4 × 10-8) and Xq27.3, rs5951794 (P = 3.1 × 10-10). E1 signals were found in CYP19A1 (rs2899472, P = 5.5 × 10-23), in Tripartite motif containing 4 (TRIM4; rs17277546, P = 5.8 × 10-14), and CYP11B1/B2 (rs10093796, P = 1.2 × 10-8). E2 signals in CYP19A1 and FAM9B were associated with bone mineral density (BMD). Mendelian randomization analysis suggested a causal effect of serum E2 on BMD in men. A 1 pg/mL genetically increased E2 was associated with a 0.048 standard deviation increase in lumbar spine BMD (P = 2.8 × 10-12). In men and women combined, CYP19A1 alleles associated with higher E2 levels were associated with lower degrees of insulin resistance.Conclusions: Our findings confirm that CYP19A1 is an important genetic regulator of E2 and E1 levels and strengthen the causal importance of E2 for bone health in men. We also report two independent loci on the X-chromosome for E2, and one locus each in TRIM4 and CYP11B1/B2, for E1

Identification of epigenetically regulated genes that predict patient outcome in neuroblastoma

<p>Abstract</p> <p>Background</p> <p>Epigenetic mechanisms such as DNA methylation and histone modifications are important regulators of gene expression and are frequently involved in silencing tumor suppressor genes.</p> <p>Methods</p> <p>In order to identify genes that are epigenetically regulated in neuroblastoma tumors, we treated four neuroblastoma cell lines with the demethylating agent 5-Aza-2'-deoxycytidine (5-Aza-dC) either separately or in conjunction with the histone deacetylase inhibitor trichostatin A (TSA). Expression was analyzed using whole-genome expression arrays to identify genes activated by the treatment. These data were then combined with data from genome-wide DNA methylation arrays to identify candidate genes silenced in neuroblastoma due to DNA methylation.</p> <p>Results</p> <p>We present eight genes (<it>KRT19</it>, <it>PRKCDBP</it>, <it>SCNN1A</it>, <it>POU2F2</it>, <it>TGFBI</it>, <it>COL1A2</it>, <it>DHRS3 </it>and <it>DUSP23</it>) that are methylated in neuroblastoma, most of them not previously reported as such, some of which also distinguish between biological subsets of neuroblastoma tumors. Differential methylation was observed for the genes <it>SCNN1A </it>(p < 0.001), <it>PRKCDBP </it>(p < 0.001) and <it>KRT19 </it>(p < 0.01). Among these, the mRNA expression of <it>KRT19 </it>and <it>PRKCDBP </it>was significantly lower in patients that have died from the disease compared with patients with no evidence of disease (fold change -8.3, p = 0.01 for <it>KRT19 </it>and fold change -2.4, p = 0.04 for <it>PRKCDBP</it>).</p> <p>Conclusions</p> <p>In our study, a low methylation frequency of <it>SCNN1A</it>, <it>PRKCDBP </it>and <it>KRT19 </it>is significantly associated with favorable outcome in neuroblastoma. It is likely that analysis of specific DNA methylation will be one of several methods in future patient therapy stratification protocols for treatment of childhood neuroblastomas.</p

Genetic insights into resting heart rate and its role in cardiovascular disease

Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.</p

Variation in the SERPINA6SERPINA1 locusalters morning plasma cortisol, hepatic corticosteroid binding globulin expression, gene expressionin peripheral tissues, and risk of cardiovascular disease

The stress hormone cortisol modulates fuel metabolism, cardiovascular homoeostasis, mood, inflammation and cognition. The CORtisol NETwork (CORNET) consortium previously identified a single locus associated with morning plasma cortisol. Identifying additional genetic variants that explain more of the variance in cortisol could provide new insights into cortisol biology and provide statistical power to test the causative role of cortisol in common diseases. The CORNET consortium extended its genome-wide association meta-analysis for morning plasma cortisol from 12,597 to 25,314 subjects and from ~2.2 M to ~7 M SNPs, in 17 population-based cohorts of European ancestries. We confirmed the genetic association with SERPINA6/SERPINA1. This locus contains genes encoding corticosteroid binding globulin (CBG) and α1-antitrypsin. Expression quantitative trait loci (eQTL) analyses undertaken in the STARNET cohort of 600 individuals showed that specific genetic variants within the SERPINA6/SERPINA1 locus influence expression of SERPINA6 rather than SERPINA1 in the liver. Moreover, trans-eQTL analysis demonstrated effects on adipose tissue gene expression, suggesting that variation

The complex genetics of gait speed:Genome-wide meta-analysis approach

Emerging evidence suggests that the basis for variation in late-life mobility is attributable, in part, to genetic factors, which may become increasingly important with age. Our objective was to systematically assess the contribution of genetic variation to gait speed in older individuals. We conducted a meta-analysis of gait speed GWASs in 31,478 older adults from 17 cohorts of the CHARGE consortium, and validated our results in 2,588 older adults from 4 independent studies. We followed our initial discoveries with network and eQTL analysis of candidate signals in tissues. The meta-analysis resulted in a list of 536 suggestive genome wide significant SNPs in or near 69 genes. Further interrogation with Pathway Analysis placed gait speed as a polygenic complex trait in five major networks. Subsequent eQTL analysis revealed several SNPs significantly associated with the expression of PRSS16, WDSUB1 and PTPRT, which in addition to the meta-analysis and pathway suggested that genetic effects on gait speed may occur through synaptic function and neuronal development pathways. No genome-wide significant signals for gait speed were identified from this moderately large sample of older adults, suggesting that more refined physical function phenotypes will be needed to identify the genetic basis of gait speed in aging