Muscle-origin creatinine-cystatin C ratio is an osteoporosis marker in individuals with normal renal function: evidence from observational and Mendelian randomization analysis.

Background: Creatinine-cystatin C ratio (CCR) has been demonstrated as an objective marker of sarcopenia in clinical conditions but has not been evaluated as an osteoporosis marker in individuals with normal renal function. Methods: We selected 271,831 participants with normal renal function from UK Biobank cohort. Multivariable linear/logistic regression and Cox proportional hazards model were used to investigate the phenotypic relationship between CCR and osteoporosis in total subjects and gender-stratified subjects. Based on the genome-wide association study (GWAS) data, linkage disequilibrium regression (LDSC) and Mendelian randomization (MR) analysis were performed to reveal the shared genetic correlations and infer the causal effects, respectively. Results: Amongst total subjects and gender-stratified subjects, serum CCR was positively associated with eBMD after adjusting for potential risk factors (all P<0.05). The multivariable logistic regression model showed that the decrease in CCR was associated with a higher risk of osteoporosis/fracture in all models (all P<0.05). In the multivariable Cox regression analysis with adjustment for potential confounders, reduced CCR is associated with the incidence of osteoporosis and fracture in both total subjects and gender-stratified subjects (all P<0.05). A significant non-linear dose-response was observed between CCR and osteoporosis/fracture risk (P non-linearity < 0.05). LDSC found no significant shared genetic effects by them, but PLACO identified 42 pleiotropic SNPs shared by CCR and fracture (P<5×10-8). MR analyses indicated the causal effect from CCR to osteoporosis/fracture. Conclusions: Reduced CCR predicted increased risks of osteoporosis/fracture, and significant causal effects support their associations. These findings indicated that the muscle-origin serum CCR was a potential biomarker to assess the risks of osteoporosis and fracture.

Genetic effects and causal association analyses of 14 common conditions/diseases in multimorbidity patterns.

BACKGROUND: Multimorbidity has become an important health challenge in the aging population. Accumulated evidence has shown that multimorbidity has complex association patterns, but the further mechanisms underlying the association patterns are largely unknown. METHODS: Summary statistics of 14 conditions/diseases were available from the genome-wide association study (GWAS). Linkage disequilibrium score regression analysis (LDSC) was applied to estimate the genetic correlations. Pleiotropic SNPs between two genetically correlated traits were detected using pleiotropic analysis under the composite null hypothesis (PLACO). PLACO-identified SNPs were mapped to genes by Functional Mapping and Annotation of Genome-Wide Association Studies (FUMA), and gene set enrichment analysis and tissue differential expression were performed for the pleiotropic genes. Two-sample Mendelian randomization analyses assessed the bidirectional causality between conditions/diseases. RESULTS: LDSC analyses revealed the genetic correlations for 20 pairs based on different two-disease combinations of 14 conditions/diseases, and genetic correlations for 10 pairs were significant after Bonferroni adjustment (P<0.05/91 = 5.49E-04). Significant pleiotropic SNPs were detected for 11 pairs of correlated conditions/diseases. The corresponding pleiotropic genes were differentially expressed in the brain, nerves, heart, and blood vessels and enriched in gluconeogenesis and drug metabolism, biotransformation, and neurons. Comprehensive causal analyses showed strong causality between hypertension, stroke, and high cholesterol, which drive the development of multiple diseases. CONCLUSIONS: This study highlighted the complex mechanisms underlying the association patterns that include the shared genetic components and causal effects among the 14 conditions/diseases. These findings have important implications for guiding the early diagnosis, management, and treatment of comorbidities.

Accelerated biological aging as a potential risk factor for rheumatoid arthritis.

OBJECTS: Previous studies have suggested a potential correlation between rheumatoid arthritis (RA) and biological aging, but the intricate connections and mechanisms remain elusive. METHODS: In our study, we focused on two specific measures of biological age (PhenoAge and BioAge), which are derived from clinical biomarkers. The residuals of these measures, when compared to chronological age, are defined as biological age accelerations (BAAs). Utilizing the extensive UK Biobank dataset along with various genetic datasets, we conducted a thorough assessment of the relationship between BAAs and RA at both the individual and aggregate levels. RESULTS: Our observational studies revealed positive correlations between the two BAAs and the risk of developing both RA and seropositive RA. Furthermore, the genetic risk score (GRS) for PhenoAgeAccel was associated with an increased risk of RA and seropositive RA. Linkage disequilibrium score regression (LDSC) analysis further supported these findings, revealing a positive genetic correlation between PhenoAgeAccel and RA. PLACO analysis identified 38 lead pleiotropic single nucleotide polymorphisms linked to 301 genes, providing valuable insights into the potential mechanisms connecting PhenoAgeAccel and RA. CONCLUSION: In summary, our study has successfully revealed a positive correlation between accelerated biological aging, as measured by BAAs, and the susceptibility to RA.

Unraveling the relationship between high-sensitivity C-reactive protein and frailty: evidence from longitudinal cohort study and genetic analysis.

BACKGROUND: This study aimed to investigate the association of high-sensitivity C-reactive protein (hs-CRP) with incident frailty as well as its effects on pre-frailty progression and regression among middle-aged and older adults. METHODS: Based on the frailty index (FI) calculated with 41 items, 6890 eligible participants without frailty at baseline from China Health and Retirement Longitudinal Study (CHARLS) were categorized into health, pre-frailty, and frailty groups. Logistic regression models were used to estimate the longitudinal association between baseline hs-CRP and incident frailty. Furthermore, a series of genetic approaches were conducted to confirm the causal relationship between CRP and frailty, including Linkage disequilibrium score regression (LDSC), pleiotropic analysis, and Mendelian randomization (MR). Finally, we evaluated the association of hs-CRP with pre-frailty progression and regression. RESULTS: The risk of developing frailty was 1.18 times (95% CI: 1.03-1.34) higher in participants with high levels of hs-CRP at baseline than low levels of hs-CRP participants during the 3-year follow-up. MR analysis suggested that genetically determined hs-CRP was potentially positively associated with the risk of frailty (OR: 1.06, 95% CI: 1.03-1.08). Among 5241 participants with pre-frailty at baseline, we found pre-frailty participants with high levels of hs-CRP exhibit increased odds of progression to frailty (OR: 1.39, 95% CI: 1.09-1.79) and decreased odds of regression to health (OR: 0.84, 95% CI: 0.72-0.98) when compared with participants with low levels of hs-CRP. CONCLUSIONS: Our results suggest that reducing systemic inflammation is significant for developing strategies for frailty prevention and pre-frailty reversion in the middle-aged and elderly population.

PKM2 is a Novel Osteoporosis-Associated Protein in Chinese.

Purpose:Osteoporosis is characterized by low bone mineral density (BMD) and high risk of osteoporotic fracture (OF). Peripheral blood monocytes (PBM) can differentiate into osteoclasts to resorb bone. This study was to identify PBM-expressed proteins significant for osteoporosis in Chinese Han elderly population (>65 years), and focused on two phenotypes of osteoporosis: low BMD and OF. METHODS: Label-free quantitative proteomics was employed to profile PBM proteome and to identify differentially expressed proteins (DEPs) between OF (N=27) vs. non-fractured (NF, N=24) subjects and between low BMD (N=12) vs. high BMD (N=12) subjects in women. Western blotting (WB) was conducted to validate differential expression, and ELISA to evaluate translational value for secretory protein of interest. RESULTS: We discovered 59 DEPs with fold change (FC)>1.3 (P<1×10-5), and validated the significant up-regulation of pyruvate kinase isozyme 2 (PKM2) with osteoporosis (P<0.001). PKM2 protein upregulation with OF was replicated with PBM in men (P=0.04). Plasma PKM2 protein level was significantly elevated with OF in an independent sample (N=100, FC=1.68, P=0.01). Pursuant functional assays showed that extracellular PKM2 protein supplement not only promoted monocyte trans-endothelial migration, growth, and osteoclast differentiation (marker gene expression), but also inhibited osteoblast growth, differentiation (ALP gene expression), and activity. CONCLUSION: The above findings suggest that PKM2 protein is a novel osteoporosis-associated functional protein in Chinese Han elderly population. It may serve as a risk biomarker and drug target for osteoporosis.

High sensitivity C-reactive protein and prediabetes progression and regression in middle-aged and older adults: A prospective cohort study.

BACKGROUND: This study aimed to investigate the effect of systemic inflammation, assessed by high sensitivity C-reactive protein (hs-CRP) levels, on prediabetes progression and regression in middle-aged and older adults based on the China Health and Retirement Longitudinal Study (CHARLS). METHODS: Participants with prediabetes from CHARLS were followed up 4 years later with blood samples collected for measuring fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c). The level of hs-CRP was assessed at baseline and categorized into tertiles (low, middle, and high groups). Prediabetes at baseline and follow-up was defined primarily according to the American Diabetes Association (ADA) criteria. Logistic regression models were used to estimate the odds ratios (ORs) and confidence intervals (CIs). We also performed stratified analyses according to age, gender, BMI, the presence of hypertension, and the disease history of heart disease and dyslipidemia and sensitivity analyses excluding a subset of participants with incomplete data. RESULTS: Of the 2,874 prediabetes included at baseline, 834 participants remained as having prediabetes, 146 progressed to diabetes, and 1,894 regressed to normoglycemia based on ADA criteria with a 4 year follow-up. After multivariate logistics regression analysis, prediabetes with middle (0.67-1.62 mg/L) and high (>1.62 mg/L) hs-CRP levels had an increased incidence of progressing to diabetes compared with prediabetes with low hs-CRP levels (<0.67 mg/L; OR = 1.846, 95%CI: 1.129-3.018; and OR = 1.632, 95%CI: 0.985-2.703, respectively), and the incidence of regressing to normoglycemia decreased (OR = 0.793, 95%CI: 0.645-0.975; and OR = 0.769, 95%CI: 0.623-0.978, respectively). Stratified analyses and sensitivity analyses showed consistent results. CONCLUSIONS: Low levels of hs-CRP are associated with a high incidence of regression from prediabetes to normoglycemia and reduced odds of progression to diabetes.

Telomere Length Is a Driving Hallmark for Aging-Related Biochemical Hallmarks: Evidence From the Shared Genetic Effect and Causal Inference.

Telomere shortening is an important sign and driving factor of aging, but its association mechanisms and causal effects with other aging-related biochemical hallmarks are largely unknown. This study first performed comprehensive genetic analyses (eg, shared genetic analysis, pleiotropic analysis, and gene enrichment analysis) to detect the underlying molecular mechanisms for the associations between telomere length (TL) and aging-related biochemical hallmarks. Then, further bidirectional Mendelian randomization (MR) analyses investigated the causal effects between TL and other biochemical hallmarks. The genetic correlations were negative between TL and growth differentiation factor-15 (GDF15) (p = .024), C-reactive protein (p = .007), hemoglobin A1c (p = .007), and red blood cell (RBC) (p = .022), but positive between TL and insulin-like growth factor 1 (IGF-1) (p = .002) and white blood cell counts (p = .007). The increased TL has causal effects on the low levels of GDF15 (p = 3.73E-06), sex hormone binding globulin (p = 6.30E-06), testosterone (p = 5.56E-07), fasting insulin (p = 2.67E-05), and RBC (p = 1.54E-05), but the higher levels of IGF-1 (p = 3.24E-07). In conclusion, the observed phenotypic correlations between TL and aging-related biochemical hallmarks may arise from a combination of shared genetic components and causal effects. Telomere length is regarded as a driving hallmark for aging-related biochemical hallmarks.

The Casual Association Inference for the Chain of Falls Risk Factors-Falls-Falls Outcomes: A Mendelian Randomization Study.

Previous associations have been observed not only between risk factors and falls but also between falls and their clinical outcomes based on some cross-sectional designs, but their causal associations were still largely unclear. We performed Mendelian randomization (MR), multivariate Mendelian randomization (MVMR), and mediation analyses to explore the effects of falls. Our study data are mainly based on White European individuals (40-69 years) downloaded from the UK Biobank. MR analyses showed that osteoporosis (p = 0.006), BMI (p = 0.003), sleeplessness (p < 0.001), rheumatoid arthritis (p = 0.001), waist circumference (p < 0.001), and hip circumference (p < 0.001) have causal effects on falls. In addition, for every one standard deviation increase in fall risk, the risk of fracture increased by 1.148 (p < 0.001), the risk of stroke increased by 2.908 (p = 0.003), and a 1.016-fold risk increase in epilepsy (p = 0.009). The MVMR found that sleeplessness is an important risk factor for falls. Finally, our mediation analyses estimated the mediation effects of falls on the hip circumference and fracture (p < 0.001), waist circumference and epilepsy (p < 0.001), and sleeplessness and fracture (p = 0.005). Our study inferred the causal effects between risk factors and falls, falls, and outcomes, and also constructed three causal chains from risk factors → falls → falls outcomes.

Air pollution, genetic factors and the risk of osteoporosis: A prospective study in the UK biobank.

Purpose: To reveal relationship between air pollution exposure and osteoporosis (OP) risk. Methods: Based on large-scale data from the UK Biobank, we evaluated the relationship between OP risk and several air pollutants. Then air pollution scores (APS) were constructed to assess the combined effects of multiple air pollutants on OP risk. Finally, we constructed a genetic risk score (GRS) based on a large genome-wide association study of femoral neck bone mineral density and assessed whether single or combined exposure to air pollutants modifies the effect of genetic risk on OP and fracture risk. Results: PM2.5, NO2, NOx, and APS were significantly associated with an increased risk of OP/fracture. OP and fracture risk raised with increasing concentrations of air pollutants: compared to the lowest APS quintile group, subjects in the highest quintile group had a hazard ratio (HR) (95% CI) estimated at 1.140 (1.072-1.213) for OP and 1.080 (1.026-1.136) for fracture. Moreover, participants with low GRS and the highest air pollutant concentration had the highest risk of OP, the HRs (95% CI) of OP were 1.706 (1.483-1.964), 1.658 (1.434-1.916), 1.696 (1.478-1.947), 1.740 (1.506-2.001) and 1.659 (1.442-1.908), respectively, for PM2.5, PM10, PM2.5-10, NO2, and NOx. Similar results were also observed for fractures. Finally, we assessed the joint effect of APS and GRS on the risk of OP. Participants with higher APS and lower GRS had a higher risk of developing OP. Similar results were observed in the joint effect of GRS and APS on fracture. Conclusions: We found that exposure to air pollution, individually or jointly, could improve the risk of developing OP and fractures, and increased the risk by interacting with genetic factors.

Establishment of reference intervals for bone turnover markers in healthy Chinese older adults.

BACKGROUND: Reference ranges for bone turnover markers (BTMs) are still lacking in the healthy Chinese population. AIM: To establish reference intervals for BTMs and to investigate the correlations between BTMs and bone mineral density (BMD) in Chinese older adults. SUBJECTS AND METHODS: A community-based cross-sectional study was conducted among 2511 Chinese subjects aged over 50 yrs residing in Zhenjiang, Southeast China. Reference intervals for BTMs (i.e. procollagen type I N-terminal propeptide, P1NP; ß cross-linked C-terminal telopeptide of type I collagen, ß-CTX) were calculated as the central 95% range of all measurements in Chinese older adults. RESULTS: The reference intervals of P1NP, ß-CTX and P1NP/ß-CTX were 15.8-119.9 ng/mL, 0.041-0.675 ng/mL and 49.9-1261.5 for females and 13.6-111.4 ng/mL, 0.038-0.627 ng/mL and 41.0-1269.1 for males, respectively. In the multiple linear regression analysis, only ß-CTX was negatively associated with BMD after adjusting for age and body mass index (BMI) in both sex-stratified groups (all p < .05). CONCLUSION: This study established age- and sex-specific reference intervals for BTMs in a large sample of healthy Chinese participants ≥ 50 and < 80 years of age and explored the correlations between BTMs and BMD, which provides an effective reference for the assessment of bone turnover in the clinical practice of osteoporosis.

Genome-wide identification of RNA modification-related single nucleotide polymorphisms associated with rheumatoid arthritis.

BACKGROUND: RNA modification plays important roles in many biological processes, such as gene expression control. The aim of this study was to identify single nucleotide polymorphisms related to RNA modification (RNAm-SNPs) for rheumatoid arthritis (RA) as putative functional variants. METHODS: We examined the association of RNAm-SNPs with RA in summary data from a genome-wide association study of 19,234 RA cases and 61,565 controls. We performed eQTL and pQTL analyses for the RNAm-SNPs to find associated gene expression and protein levels. Furthermore, we examined the associations of gene expression and circulating protein levels with RA using two-sample Mendelian randomization analysis methods. RESULTS: A total of 160 RNAm-SNPs related to m6A, m1A, A-to-I, m7G, m5C, m5U and m6Am modifications were identified to be significantly associated with RA. These RNAm-SNPs were located in 62 protein-coding genes, which were significantly enriched in immune-related pathways. RNAm-SNPs in important RA susceptibility genes, such as PADI2, SPRED2, PLCL2, HLA-A, HLA-B, HLA-DRB1, HLA-DPB1, TRAF1 and TXNDC11, were identified. Most of these RNAm-SNPs showed eQTL effects, and the expression levels of 26 of the modifiable genes (e.g., PADI2, TRAF1, HLA-A, HLA-DRB1, HLA-DPB1 and HLA-B) in blood cells were associated with RA. Circulating protein levels, such as CFB, GZMA, HLA-DQA2, IL21, LRPAP1 and TFF3, were affected by RNAm-SNPs and were associated with RA. CONCLUSION: The present study identified RNAm-SNPs in the reported RA susceptibility genes and suggested that RNAm-SNPs may affect RA risk by affecting the expression levels of corresponding genes and proteins.

Body surface area is a potential obesity index: Its genetic determination and its causality for later-life diseases.

OBJECTIVE: This study aimed to identify novel genetic factors that contribute to body surface area (BSA) and explore its relationship with complex traits and diseases. METHODS: Based on more than 330,000 European individuals in the UK Biobank, the first large-scale genome-wide association study for BSA was performed. Comprehensive genetic analysis and enrichment analysis were then performed to explore the biological function of the identified loci. The genetic correlations and causal associations between BSA and other anthropometry parameters, early growth indices, and later-life diseases, respectively, were assessed by complex genetic approaches. RESULTS: Genome-wide association study analysis identified a total of 456 conditionally independent single-nucleotide polymorphism mapping genes with known functions in the regulation of adipogenesis and metabolism and enriched in adipogenesis-related pathways. BSA was highly genetically correlated with obesity phenotypes, and all the studied anthropometry parameters from the UK Biobank were significantly positively associated with BSA. BSA was phenotypically associated with 13 chronic diseases and genetically associated with 6 diseases. Mendelian randomization analyses showed that BSA has a causal effect in increasing the risk of some diseases. CONCLUSIONS: These findings increase understanding of genetic determinants for BSA and its relationship with complex traits and diseases, and BSA could be regarded as a potential obesity trait.

A novel long non-coding RNA, lnc-RNU12, influences the T-cell cycle via c-JUN and CCNL2 in rheumatoid arthritis.

OBJECTIVES: Long non-coding RNAs (lncRNAs) play important roles in RA pathogenesis. However, specific lncRNAs that regulate gene expression in RA pathogenesis are poorly known. This study was undertaken to characterize a novel lncRNA (lnc-RNU12) that has a lower-than-normal expression level in RA patients. METHODS: We performed initial genome-wide lncRNA microarray screening in peripheral blood mononuclear cells from 28 RA cases and 18 controls. Multiple methods were used to validate the detected associations between lncRNAs and RA. Furthermore, we identified the source and characteristics of the highlighted lncRNAs, detected the target genes, and determined the functional effect on immune cells through lncRNA knock-down in Jurkat T cell lines. RESULTS: lnc-RNU12 was downregulated in peripheral blood mononuclear cells and T cell subtypes of RA patients and was genetically associated with RA risk. lnc-RNU12 mediates the effect of microbiome alterations on RA risk. Activation of T cells caused low expression of lnc-RNU12. Knock-down of lnc-RNU12 in Jurkat T cells caused cell cycle S-phase arrest and altered the expression of protein-coding genes related to the cell cycle and apoptosis (e.g. c-JUN, CCNL2, CDK6, MYC, RNF40, PKM, VPS35, DNAJB6 and FLCN). Finally, c-JUN and CCNL2 were identified as target genes of lnc-RNU12 at the mRNA and protein expression levels. RNA-binding protein immunoprecipitation assays verified the interaction between lnc-RNU12 and the two proteins (c-Jun and cyclin L2) in Jurkat cells. CONCLUSIONS: Our study suggested that lnc-RNU12 was involved in the pathogenesis of RA by influencing the T cell cycle by targeting c-JUN and CCNL2.

The effect of a body shape index (ABSI) and its interaction with low estimated glomerular filtration rate (eGFR) on osteoporosis in elderly Chinese.

BACKGROUND: Both obesity and chronic kidney disease (CKD) contribute to osteoporosis risk, but the effect of a newly developed index (e.g., a body shape index, ABSI) of central obesity and its interaction with low estimated glomerular filtration rate (eGFR) on osteoporosis remains unknown. METHODS: A total of 2534 Chinese individuals were enrolled in our ongoing cohort study: Osteoporosis Preventive Project. ABSI and eGFR were calculated as obesity-related indexes and renal function markers, respectively. A logistic regression model was used to estimate the association between osteoporosis and related clinical parameters (e.g., ABSI, eGFR), and to assess the additive and multiplicative interactions between risk factors and osteoporosis. Relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP) and synergy index (SI) were calculated to assess the additive interaction. RESULTS: High ABSI was significantly associated with an increased risk of osteoporosis in participants compared with the lowest quartile of ABSI in both crude and adjusted models. Individuals in the lower quartiles of eGFR had a significantly increased risk of osteoporosis compared with those in the highest quartiles in crude models. After adding age and other variables in the model, the association was abolished. In addition, after adjusting for variables, high ABSI with low eGFR (RERI: 0.45, 95% CI: 0.15-0.75; AP: 0.39, 95% CI: 0.17-0.60) still displayed a noticeable interaction on the risk of osteoporosis. The multiplicative interactive effect between high ABSI with low eGFR on osteoporosis was statistically significant in the multivariable-adjusted model (P < 0.05). CONCLUSION: Our study indicated that higher ABSI increases the risk of osteoporosis independently and synergistically with low eGFR in Chinese elderly adults. The findings increase our understanding of the interactions of osteoporosis risk factors and may help provide potential interventions for osteoporosis.

The immune factors have complex causal regulation effects on bone mineral density.

Recent evidence has gradually recognized that the immune and skeletal systems are two closely correlated systems, but the specific immune factors on bone mineral density (BMD) are largely unknown. Based on the summary-level data of genome-wide association studies (GWASs), we performed a series of analyses including two-sample Mendelian randomization (MR) analysis to test potential causal links between 731 immune traits [including median fluorescence intensities (MFIs), absolute cell (AC) counts, relative cell (RC) counts, and morphological parameters (MP)] and BMD. After false discovery rate (FDR) correction, 9 MFI-BMD, 16 AC-BMD, 22 RC-BMD, and 5 MP-BMD pairs reached the level of significance (FDR-adjusted p< 0.05). For MFI traits, the T- and B-cell panels had the largest number of significant immune trait pairs than other panels. CD40, as a molecule expressed by four subsets of monocytes, was highlighted due to its consistently positive correlation with BMD at four sites. For both AC and RC traits, immune traits from the T-cell panel were also highlighted, with CD39-positive T-cell subsets being the most frequently observed feature. For MP traits, the most significant association immune trait with BMD was SSC-A on CD14+ monocyte. Sensitivity analyses suggested that the identified immune factors were robust to pleiotropy. Multivariable MR analysis confirmed the independent causal effect of several immune traits on BMD. Mediation analyses showed that CD40 on monocytes could mediate multiple immune traits, especially the suggestive associations of CD27 on several memory B cells with BMD mediated by CD40 on CD14+ CD16- monocyte. Our study represents the first comprehensive evaluation of the causal effects of immune traits on the risk of osteoporosis. The findings highlighted the complex and important role of immune-derived factors in the pathogenesis of osteoporosis.

RNA Modification-Related Genetic Variants in Genomic Loci Associated with Bone Mineral Density and Fracture.

Genome-wide association studies (GWASs) have identified more than 500 loci for bone mineral density (BMD), but functional variants in these loci are less known. The aim of this study was to identify RNA modification-related SNPs (RNAm-SNPs) for BMD in GWAS loci. We evaluated the association of RNAm-SNPs with quantitative heel ultrasound BMD (eBMD) in 426,824 individuals, femoral neck (FN) and lumbar spine (LS) BMD in 32,961 individuals and fracture in ~1.2 million individuals. Furthermore, we performed functional enrichment, QTL and Mendelian randomization analyses to support the functionality of the identified RNAm-SNPs. We found 300 RNAm-SNPs significantly associated with BMD, including 249 m6A-, 28 m1A-, 3 m5C-, 7 m7G- and 13 A-to-I-related SNPs. m6A-SNPs in OP susceptibility genes, such as WNT4, WLS, SPTBN1, SEM1, FUBP3, LRP5 and JAG1, were identified and functional enrichment for m6A-SNPs in the eBMD GWAS dataset was detected. eQTL signals were found for nearly half of the identified RNAm-SNPs, and the affected gene expression was associated with BMD and fracture. The RNAm-SNPs were also associated with the plasma levels of proteins in cytokine-cytokine receptor interaction, PI3K-Akt signaling, NF-kappa B signaling and MAPK signaling pathways. Moreover, the plasma levels of proteins (CCL19, COL1A1, CTSB, EFNA5, IL19, INSR, KDR, LIFR, MET and PLXNB2) in these pathways were found to be associated with eBMD in Mendelian randomization analysis. This study identified functional variants and potential causal genes for BMD and fracture in GWAS loci and suggested that RNA modification may play an important role in osteoporosis.

Genetic Risk for Osteoporosis and the Benefit of Adherence to Healthy Lifestyles.

Objectives: We aimed to explore how healthy lifestyles and genetic factors influence the risk of Osteoporosis (OP). Methods: In this prospective cohort study, we first performed a genome-wide association study (GWAS) of estimated bone mineral density (eBMD) and constructed the genetic risk score (GRS) based on the effect of single nucleotide polymorphism (SNP) on eBMD. We then assessed the effect of three-level GRS and adherence to healthy lifestyles on the risk of OP and fracture, respectively. Finally, we assessed the joint effects of GRS and lifestyle on the OP and fracture risk. Results: People with higher GRS have a lower risk of OP and fracture. Negative associations were detected between healthy lifestyle factors and the risk of OP and fracture. Compare with the group with high GRS and favorable lifestyles, the group with low GRS and unfavorable lifestyles had a high Hazard Ratio (HR). Conclusion: The findings suggest that adherence to healthy lifestyles can reduce the risk of OP and fracture in people with different genetic risks.

Systematic evaluation for the causal effects of blood metabolites on osteoporosis: Genetic risk score and Mendelian randomization.

Purpose: Osteoporosis is associated with metabolic alterations, but the causal roles of serum metabolites on osteoporosis have not been identified. Methods: Based on the large individual-level datasets from UK Biobank as well as GWAS summary datasets, we first constructed genetic risk scores (GRSs) for 308 of 486 human serum metabolites and evaluated the effect of each GRS on 2 major osteoporosis phenotypes, i.e., estimated bone miner density (eBMD) and fracture, respectively. Then, two-sample Mendelian Randomization (MR) was performed to validate the casual metabolites on osteoporosis. Multivariable MR analysis tested whether the effects of metabolites on osteoporosis are independent of possible confounders. Finally, we conducted metabolic pathway analysis for the metabolites involved in bone metabolism. Results: We identified causal effects of 18 metabolites on eBMD and 1 metabolite on fracture with the GRS method after adjusting for multiple tests. Then, 9 of them were further validated with MR as replication, where comprehensive sensitive analyses proved robust of the causal associations. Although not identified in GRS, 3 metabolites were associated with at least three osteoporosis traits in MR results. Multivariable MR analysis determined the independent causal effect of several metabolites on osteoporosis. Besides, 23 bone metabolic pathways were detected, such as valine, leucine, isoleucine biosynthesis (p = 0.053), and Aminoacyl-tRNA biosynthesis (p = 0.076), and D-glutamine and D-glutamate metabolism (p = 0.004). Conclusions: The systematic causal analyses strongly suggested that blood metabolites have causal effects on osteoporosis risk.

Systematic Evaluation of Rheumatoid Arthritis Risk by Integrating Lifestyle Factors and Genetic Risk Scores.

Background: Effective identification of high-risk rheumatoid arthritis (RA) individuals is still a challenge. Whether the combined effects of multiple previously reported genetic loci together with lifestyle factors can improve the prediction of RA risk remains unclear. Methods: Based on previously reported results and a large-scale Biobank dataset, we constructed a polygenic risk score (PRS) for RA to evaluate the combined effects of the previously identified genetic loci in both case-control and prospective cohorts. We then evaluated the relationships between several lifestyles and RA risk and determined healthy lifestyles. Then, the joint effects of healthy lifestyles and genetic risk on RA risk were evaluated. Results: We found a positive association between PRS and RA risk (OR = 1.407, 95% confidence interval (CI) = 1.354~1.463; HR = 1.316, 95% CI = 1.257~1.377). Compared with the low genetic risk group, the group with intermediate or high genetic risk had a higher risk (OR = 1.347, 95% CI = 1.213~1.496; HR = 1.246, 95% CI = 1.108~1.400) (OR = 2.169, 95% CI = 1.946~2.417; HR = 1.762, 95% CI = 1.557~1.995). After adjusting for covariates, we found protective effects of three lifestyles (no current smoking, regular physical activity, and moderate body mass index) on RA risk and defined them as healthy lifestyles. Compared with the individuals with low genetic risks and favorable lifestyles, those with high genetic risks and unfavorable lifestyles had as high as OR of 4.637 (95%CI = 3.767~5.708) and HR of 3.532 (95%CI = 2.799~4.458). Conclusions: In conclusion, the integration of PRS and lifestyles can improve the prediction of RA risk. High RA risk can be alleviated by adopting healthy lifestyles but aggravated by adopting unfavorable lifestyles.

RNA modification-related variants in genomic loci associated with body mass index.

BACKGROUND: Genome-wide association studies (GWASs) have identified hundreds of loci for body mass index (BMI), but functional variants in these loci are less known. The purpose of this study was to identify RNA modification-related SNPs (RNAm-SNPs) for BMI in GWAS loci. BMI-associated RNAm-SNPs were identified in a GWAS of approximately 700,000 individuals. Gene expression and circulating protein levels affected by the RNAm-SNPs were identified by QTL analyses. Mendelian randomization (MR) methods were applied to test whether the gene expression and protein levels were associated with BMI. RESULTS: A total of 78 RNAm-SNPs associated with BMI (P < 5.0 × 10-8) were identified, including 65 m6A-, 10 m1A-, 3 m7G- and 1 A-to-I-related SNPs. Two functional loss, high confidence level m6A-SNPs, rs6713978 (P = 6.4 × 10-60) and rs13410999 (P = 8.2 × 10-59), in the intron of ADCY3 were the top significant SNPs. These two RNAm-SNPs were associated with ADCY3 gene expression in adipose tissues, whole blood cells, the tibial nerve, the tibial artery and lymphocytes, and the expression levels in these tissues were associated with BMI. Proteins enriched in specific KEGG pathways, such as natural killer cell-mediated cytotoxicity, the Rap1 signaling pathway and the Ras signaling pathway, were affected by the RNAm-SNPs, and circulating levels of some of these proteins (ADH1B, DOCK9, MICB, PRDM1, STOM, TMPRSS11D and TXNDC12) were associated with BMI in MR analyses. CONCLUSIONS: Our study identified RNAm-SNPs in BMI-related genomic loci and suggested that RNA modification may affect BMI by affecting the expression levels of corresponding genes and proteins.