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

Maternal prednisone exposure during pregnancy elevates susceptibility to osteoporosis in female offspring: The role of mitophagy/FNDC5 alteration in skeletal muscle

Maternal exposure to glucocorticoids has been associated with adverse outcomes in offspring. However, the consequences and mechanisms of gestational exposure to prednisone on susceptibility to osteoporosis in the offspring remain unclear. Here, we found that gestational prednisone exposure enhanced susceptibility to osteoporosis in adult mouse offspring. In a further exploration of myogenic mechanisms, results showed that gestational prednisone exposure down-regulated FNDC5/irisin protein expression and activation of OPTN-dependent mitophagy in skeletal muscle of adult offspring. Additional experiments elucidated that activated mitophagy significantly inhibited the expression of FNDC5/irisin in skeletal muscle cells. Likewise, we observed delayed fetal bone development, downregulated FNDC5/irisin expression, and activated mitophagy in fetal skeletal muscle upon gestational prednisone exposure. In addition, an elevated total m6A level was observed in fetal skeletal muscle after gestational prednisone exposure. Finally, gestational supplementation with S-adenosylhomocysteine (SAH), an inhibitor of m6A activity, attenuated mitophagy and restored FNDC5/irisin expression in fetal skeletal muscle, which in turn reversed fetal bone development. Overall, these data indicate that gestational prednisone exposure increases m6A modification, activates mitophagy, and decreases FNDC5/irisin expression in skeletal muscle, thus elevating osteoporosis susceptibility in adult offspring. Our results provide a new perspective on the earlier prevention and treatment of fetal-derived osteoporosis.

Methodological approaches, challenges, and opportunities in the application of Mendelian randomisation to lifecourse epidemiology: A systematic literature review

Diseases diagnosed in adulthood may have antecedents throughout (including prenatal) life. Gaining a better understanding of how exposures at different stages in the lifecourse influence health outcomes is key to elucidating the potential benefits of disease prevention strategies. Mendelian randomisation (MR) is increasingly used to estimate causal effects of exposures across the lifecourse on later life outcomes. This systematic literature review explores MR methods used to perform lifecourse investigations and reviews previous work that has utilised MR to elucidate the effects of factors acting at different stages of the lifecourse. We conducted searches in PubMed, Embase, Medline and MedRXiv databases. Thirteen methodological studies were identified. Four studies focused on the impact of time-varying exposures in the interpretation of "standard" MR techniques, five presented methods for repeat measures of the same exposure, and four described methodological approaches to handling multigenerational exposures. A further 127 studies presented the results of an applied research question. Over half of these estimated effects in a single generation and were largely confined to the exploration of questions regarding body composition. The remaining mostly estimated maternal effects. There is a growing body of research focused on the development and application of MR methods to address lifecourse research questions. The underlying assumptions require careful consideration and the interpretation of results rely on select conditions. Whilst we do not advocate for a particular strategy, we encourage practitioners to make informed decisions on how to approach a research question in this field with a solid understanding of the limitations present and how these may be affected by the research question, modelling approach, instrument selection, and data availability.

Model Selection and Identification of Osteoporosis Risk Factors in Women to Improve Their Healthcare

Osteoporosis is characterized by low bone mineral density leading to enhanced bone fragility and a consequent increase in fracture risk. The focus of this case-control study was to identify significant socioeconomic risk factors of osteoporosis in Pakistani women and examine how the risk increases for different levels of risk factors. A case-control study was conducted from November 2018 to August 2019 in two main hospitals in Faisalabad, Pakistan. Multiple logistic regression was used to explore the significant risk factors of osteoporosis and how the risk increases in cases (cases = 120) as compared to the control group (controls = 120) in the presence of these risk factors. The mean age ± standard deviation for cases and controls was 59.62 ± 10.75 and 54.27 ± 10.09, respectively. The minimum and maximum ages were 36 and 80 years, respectively. In addition to age, bone fracture, family history, regular physical activity, family size, use of meat, type of birth, breastfeeding, premature menopause, loss of appetite, and use of anticoagulants were significant risk factors with p-values less than 0.05. The risk prediction model with significant risk factors was a good fit with a p-value of 0.28, corresponding to the Hosmer-Lemeshow test value (χ2 = 9.78). This parsimonious model with Cox-Snell R2 = 0.50 (with a maximum value = 0.75) and Nagelkerke R2 = 0.66 showed an AUC of 0.924 as compared to the full model with all risk factors under study that exhibited an AUC of 0.949.

Age-specific effects of weight-based body size on fracture risk in later life: a lifecourse Mendelian randomisation study

Musculoskeletal conditions, including fractures, can have severe and long-lasting consequences. Higher body mass index in adulthood is widely acknowledged to be protective for most fracture sites. However, sources of bias induced by confounding factors may have distorted previous findings. Employing a lifecourse Mendelian randomisation (MR) approach by using genetic instruments to separate effects at different life stages, this investigation aims to explore how prepubertal and adult body size independently influence fracture risk in later life.Using data from a large prospective cohort, univariable and multivariable MR were conducted to simultaneously estimate the effects of age-specific genetic proxies for body size (n = 453,169) on fracture risk (n = 416,795). A two-step MR framework was additionally applied to elucidate potential mediators. Univariable and multivariable MR indicated strong evidence that higher body size in childhood reduced fracture risk (OR, 95% CI: 0.89, 0.82 to 0.96, P = 0.005 and 0.76, 0.69 to 0.85, P = 1 × 10- 6, respectively). Conversely, higher body size in adulthood increased fracture risk (OR, 95% CI: 1.08, 1.01 to 1.16, P = 0.023 and 1.26, 1.14 to 1.38, P = 2 × 10- 6, respectively). Two-step MR analyses suggested that the effect of higher body size in childhood on reduced fracture risk was mediated by its influence on higher estimated bone mineral density (eBMD) in adulthood.This investigation provides novel evidence that higher body size in childhood reduces fracture risk in later life through its influence on increased eBMD. From a public health perspective, this relationship is complex since obesity in adulthood remains a major risk factor for co-morbidities. Results additionally indicate that higher body size in adulthood is a risk factor for fractures. Protective effect estimates previously observed are likely attributed to childhood effects.

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

PM_2.5, NO₂, NO_x, 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 PM_2.5, PM₁₀, PM_2.5-10, NO₂, and NO_x. 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.

Both indirect maternal and direct fetal genetic effects reflect the observational relationship between higher birth weight and lower adult bone mass

BACKGROUND

Birth weight is considered not only to undermine future growth, but also to induce lifelong diseases; the aim of this study is to explore the relationship between birth weight and adult bone mass.

METHODS

We performed multivariable regression analyses to assess the association of birth weight with bone parameters measured by dual-energy X-ray absorptiometry (DXA) and by quantitative ultrasound (QUS), independently. We also implemented a systemic Mendelian randomization (MR) analysis to explore the causal association between them with both fetal-specific and maternal-specific instrumental variables.

RESULTS

In the observational analyses, we found that higher birth weight could increase the adult bone area (lumbar spine, β-coefficient= 0.17, P < 2.00 × 10^-16; lateral spine, β-coefficient = 0.02, P = 0.04), decrease bone mineral content-adjusted bone area (BMCadjArea) (lumbar spine, β-coefficient= - 0.01, P = 2.27 × 10^-14; lateral spine, β-coefficient = - 0.05, P = 0.001), and decrease adult bone mineral density (BMD) (lumbar spine, β-coefficient = - 0.04, P = 0.007; lateral spine; β-coefficient = - 0.03, P = 0.02; heel, β-coefficient = - 0.06, P < 2.00 × 10^-16), and we observed that the effect of birth weight on bone size was larger than that on BMC. In MR analyses, the higher fetal-specific genetically determined birth weight was identified to be associated with higher bone area (lumbar spine; β-coefficient = 0.15, P = 1.26 × 10^-6, total hip, β-coefficient = 0.15, P = 0.005; intertrochanteric area, β-coefficient = 0.13, P = 0.0009; trochanter area, β-coefficient = 0.11, P = 0.03) but lower BMD (lumbar spine, β-coefficient = - 0.10, P = 0.01; lateral spine, β-coefficient = - 0.12, P = 0.0003, and heel β-coefficient = - 0.11, P = 3.33 × 10^-13). In addition, we found that the higher maternal-specific genetically determined offspring birth weight was associated with lower offspring adult heel BMD (β-coefficient = - 0.001, P = 0.04).

CONCLUSIONS

The observational analyses suggested that higher birth weight was associated with the increased adult bone area but decreased BMD. By leveraging the genetic instrumental variables with maternal- and fetal-specific effects on birth weight, the observed relationship could be reflected by both the direct fetal and indirect maternal genetic effects.

A Guide for Understanding and Designing Mendelian Randomization Studies in the Musculoskeletal Field

Mendelian randomization (MR) is an increasingly popular component of an epidemiologist's toolkit, used to provide evidence of a causal effect of one trait (an exposure, eg, body mass index [BMI]) on an outcome trait or disease (eg, osteoarthritis). Identifying these effects is important for understanding disease etiology and potentially identifying targets for therapeutic intervention. MR uses genetic variants as instrumental variables for the exposure, which should not be influenced by the outcome or confounding variables, overcoming key limitations of traditional epidemiological analyses. For MR to generate a valid estimate of effect, key assumptions must be met. In recent years, there has been a rapid rise in MR methods that aim to test, or are robust to violations of, these assumptions. In this review, we provide an overview of MR for a non-expert audience, including an explanation of these key assumptions and how they are often tested, to aid a better reading and understanding of the MR literature. We highlight some of these new methods and how they can be useful for specific methodological challenges in the musculoskeletal field, including for conditions or traits that share underlying biological pathways, such as bone and joint disease. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

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.

Exploring the association between birthweight and breast cancer using summary statistics from a perspective of genetic correlation, mediation, and causality

BACKGROUND

Previous studies demonstrated a positive relationship between birthweight and breast cancer; however, inconsistent, sometimes even controversial, observations also emerged, and the nature of such relationship remains unknown.

METHODS

Using summary statistics of birthweight and breast cancer, we assessed the fetal/maternal-specific genetic correlation between them via LDSC and prioritized fetal/maternal-specific pleiotropic genes through MAIUP. Relying on summary statistics we conducted Mendelian randomization (MR) to evaluate the fetal/maternal-specific origin of causal relationship between birthweight, age of menarche, age at menopause and breast cancer.

RESULTS

With summary statistics we identified a positive genetic correlation between fetal-specific birthweight and breast cancer (r_g = 0.123 and P = 0.013) as well as a negative but insignificant correlation between maternal-specific birthweight and breast cancer (r_g = - 0.068, P = 0.206); and detected 84 pleiotropic genes shared by fetal-specific birthweight and breast cancer, 49 shared by maternal-specific birthweight and breast cancer. We also revealed fetal-specific birthweight indirectly influenced breast cancer risk in adulthood via the path of age of menarche or age at menopause in terms of MR-based mediation analysis.

CONCLUSION

This study reveals that shared genetic foundation and causal mediation commonly drive the connection between the two traits, and that fetal/maternal-specific birthweight plays substantially distinct roles in such relationship. However, our work offers little supportive evidence for the fetal origins hypothesis of breast cancer originating in utero.

Identification of causal metabolites related to multiple autoimmune diseases

OBJECT

Observational studies provide evidence that metabolites may be involved in the development of autoimmune diseases (ADs), but whether it is causal is still unknown.

METHODS

Based on the large-scale GWAS summary statistics, two-sample Mendelian randomization (MR) was performed to evaluate the causal association between human serum metabolites and multiple ADs, which were inflammatory bowel disease (IBD), ulcerative Colitis (UC), crohn's 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). Comprehensive sensitive analysis was used to validate the robustness of MR results and multivariable MR analysis was conducted to avoid potential pleiotropic effect of other complex traits. Finally, metabolic pathway analysis was performed based on causal metabolites for each ad, respectively.

RESULTS

We identified 6 causal features of metabolite after Bonferroni adjustment, i.e. glycerol 2-phosphate for T1D, hexadecanedioate, phenylacetylglutamine and laurylcarnitine for RA, glycine and arachidonate (20:4n6) for CD. Then comprehensively sensitive analysis proved the robustness of the causal associations. We also observed some overlaps of metabolites among different ADs, indicating the similar mechanisms. After controlling for several common traits, multivariable MR analysis ruled out most of potential pleiotropic effects and validated the independence of identified metabolites. Additionally, a total of 6 metabolic pathways have been identified for different ADs.

CONCLUSIONS

This study provided novel insights into investigating causal role of serum metabolites in development of multiple ADs through a comprehensive genetic pathway.

Emerging roles of circular RNAs in osteoporosis

Osteoporosis is one bone disease characterized with skeletal impairment, bone strength reduced and fracture risk enhanced. The regulation processes of bone metabolism are associated with several factors such as mechanical stimulation, epigenetic regulation and hormones. However, the mechanism of osteoporosis remains unsatisfactory. Increasing high‐throughput RNA sequencing and circular RNAs (circRNAs) microarray studies indicated that circRNAs are differentially expressed in osteoporosis. Growing functional studies further pinpointed specific deregulated expressed circRNAs (e.g., circ_28313, circ_0016624, circ_0006393, circ_0076906 and circ_0048211) for their functions involved in bone metabolism, including bone marrow stromal cells (BMSCs) differentiation, proliferation and apoptosis. Moreover, CircRNAs (circ_0002060, Circ_0001275 and Circ_0001445) may be acted as diagnostic biomarkers for osteoporosis. This review discussed recent progresses in the circRNAs expression profiling analyses and their potential functions in regulating BMSCs differentiation, proliferation and apoptosis.