Inflammatory bowel disease and osteoporosis: Common genetic effects, pleiotropy, and causality.

INTRODUCTION: Previous studies have shown that inflammatory bowel disease (IBD) is associated with osteoporosis (OP) and bone mineral density (BMD), but the underlying genetic mechanisms are unclear. Our study wanted to explore the genetic and causal relationship between IBD and OP. MATERIALS AND METHODS: Based on large-scale genome-wide association summary statistics and individual-level datasets (i.e., the UK Biobank), this study performed linkage disequilibrium score regression (LDSC), pleiotropic analysis under the composite null hypothesis (PLACO), and Mendelian randomization (MR) analyses to explore the genetic association, the pleiotropic genes and the causal relationship between IBD and BMD. RESULTS: LDSC revealed significant genetic correlations between IBD and BMD (e.g., forearm BMD (rg = -0.3479, P = 0.019) and femoral neck BMD (rg = -0.1335, P = 0.0307). PLACO identified 14 overlapping pleiotropic loci, 1 shared risk gene (CDYL), and multiple shared pathways, revealing possible mechanisms for IBD and OP. MR analysis demonstrated a causal association between IBD and BMD. CONCLUSIONS: Our study indicates that IBD may increase the risk of OP and reveals a complex genetic mechanism linking IBD and the risk of osteoporosis, which has important implications for diagnosing and treating IBD and OP.

Predicting adverse pregnancy outcomes of pregnant mothers with syphilis based on a logistic regression model: a retrospective study.

Objective: Maternal syphilis could cause serious consequences. The aim of this study was to identify risk factors for maternal syphilis in order to predict an individual's risk of developing adverse pregnancy outcomes (APOs). Methods: A retrospective study was conducted on 768 pregnant women with syphilis. A questionnaire was completed and data analyzed. The data was divided into a training set and a testing set. Using logistic regression to establish predictive models in the training set, and its predictive performance was evaluated in the testing set. The probability of APOs occurrence is presented through a nomogram. Results: Compared with the APOs group, pregnant women in the non-APOs group participated in a longer treatment course. Course, time of the first antenatal care, gestation week at syphilis diagnosis, and gestation age at delivery in weeks were independent predictors of APOs, and they were used to establish the nomogram. Conclusions: Our study investigated the impact of various characteristics of syphilis pregnant women on pregnancy outcomes and established a prediction model of APOs in Suzhou. The incidence of APOs can be reduced by controlling for these risk factors.

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.

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.

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.

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.

Identification of causal metabolites related to multiple autoimmune diseases.

Observational studies provide evidence that metabolites may be involved in the development of autoimmune diseases (ADs), but whether it is causal is still unknown. Based on the large-scale genome-wide association studies (GWAS) summary statistics, we performed two-sample Mendelian randomization (MR) to evaluate the causal associations between human blood metabolites and multiple ADs, which were inflammatory bowel disease (IBD), ulcerative colitis (UC), crohns disease (CD), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), type 1 diabetes (T1D), multiple sclerosis (MS), primary biliary cirrhosis (PBC) and primary sclerosing cholangitis (PSC). After Bonferroni adjustment, we identified 6 causal features of metabolites, i.e., glycerol 2-phosphate for T1D, hexadecanedioate, phenylacetylglutamine and laurylcarnitine for RA, glycine and arachidonate (20:4n6) for CD. Comprehensive sensitive analysis was further performed to validate the robustness of associations. We also observed some overlaps of metabolites among different ADs, implying similar or shared underlying mechanisms in such pathogenic processes. Multivariable MR analysis was then conducted to avoid potential pleiotropic effect of other complex traits. After controlling for several common traits, multivariable MR analysis ruled out most of potential pleiotropic effects and validated independence of identified metabolites. Finally, metabolic pathway analysis was performed based on suggestive metabolites for each AD respectively and a total of seven metabolic pathways were identified. In conclusion, this study provided novel insights into investigating causal role of blood metabolites in development of multiple ADs through a comprehensive genetic pathway.

Rheumatoid arthritis and osteoporosis: shared genetic effect, pleiotropy and causality.

Rheumatoid arthritis (RA) is associated with increased localized and generalized bone loss, but the complex genetic mechanism between them is still unknown. By leveraging large-scale genome-wide association studies summary statistics and individual-level datasets (i.e. UK Biobank), a series of genetic approaches were conducted. Linkage disequilibrium score regression reveals a shared genetic correlation between RA and estimated bone mineral density (eBMD) (rg = -0.059, P = 0.005). The PLACO analysis has identified 74 lead (8 novel) pleiotropic loci that could be mapped to 99 genes, the genetic functions of which reveal the possible mechanism underlying RA and osteoporosis. In European, genetic risk score (GRS) and comprehensive Mendelian randomization (MR) were utilized to evaluate the causal association between RA and osteoporosis in European and Asian. The increase in GRS of RA could lead to a decrease of eBMD (beta = -0.008, P = 3.77E-6) and a higher risk of facture [odds ratio (OR) = 1.012, P = 0.044]. MR analysis identified that genetically determined RA was causally associated with eBMD (beta = -0.021, P = 4.14E-05) and fracture risk (OR = 1.036, P = 0.004). Similar results were also observed in Asian that osteoporosis risk could be causally increased by RA (OR = 1.130, P = 1.04E-03) as well as antibodies against citrullinated proteins-positive RA (OR = 1.083, P = 0.015). Overall, our study reveals complex genetic mechanism between RA and osteoporosis and provides strong evidence for crucial role of RA in pathogenesis of osteoporosis.

Birth weight is positively associated with adult osteoporosis risk: observational and Mendelian randomization studies.

The relationship between birth weight and osteoporosis was inconsistent in previous observational studies. Therefore, we performed a systematic evaluation to determine the inconsistent relationship and further make causal inference based on the UK Biobank datasets (~500,000 individuals) and individual/summary-level genetic datasets. Observational analyses found consistent negative associations either between birth weight and estimated bone mineral density (eBMD) or between genetic risk score (GRS) of birth weight and eBMD in total subjects, and sex-stratified subgroups. Mediation analyses detected significant mediation effects of adult weight and height on associations between birth weight and eBMD. Birth weight was causally associated not only with three BMD phenotypes (eBMD, total body [TB]-BMD, and femoral neck [FN]-BMD) under two effect models (total and fetal effect), but also with the risk of fracture using different Mendelian randomization (MR) methods. Multivariable MR analyses detected the pleiotropic effects of some environmental factors (e.g., gestational duration, head circumference, hip circumference) on the associations between birth weight and BMD/fracture. Three BMD phenotypes (eBMD, TB-BMD, and FN-BMD) have significant mediation effects on the associations between birth weight and fracture by using a novel mediation MR analysis under the multivariable MR framework. This multistage systematic study found consistent causal associations between birth weight and osteoporosis risk, fetal origin of genetic effects underlying the associations, and several mediation factors on the detected associations. The results enhanced our understanding of the effects of fetal original phenotypes on outcomes in late adulthood and provided helpful clues for early prevention research on osteoporosis. © 2021 American Society for Bone and Mineral Research (ASBMR).

The Role of Fibrocyte in the Pathogenesis of Silicosis.

Exposure to free silica induces silicosis and myofibroblasts are regarded as primary effector cells. Fibrocytes can differentiate into myofibroblast. Therefore, the present study was designed to investigate whether fibrocytes participate in silicosis. The rat model of silicosis was established. Hematoxylin-eosin stainings and Masson stainings were used to evaluate the histopathology and collagen deposition. Flow cytometry and immunofluorescence were performed to detect the number of fibrocytes and their contribution to myofibroblasts. Results showed that fibrocytes participate in silicosis. Trend analysis of different sources of myofibroblasts during silicosis indicated that fibrocytes and lung type II epithelial cell-derived myofibroblasts play an important role in the early stage of silicosis, while resident lung fibroblast-derived myofibroblasts play a predominant role during the fibrosis formative period.