Plasma periostin as a biomarker of osteoporosis in postmenopausal women with type 2 diabetes

Predictors of osteoporotic fracture in postmenopausal women: a meta-analysis

Osteoporosis affects more than 200 million women worldwide, with postmenopausal women being particularly susceptible to this condition and its severe sequelae disproportionately, such as osteoporotic fractures. To date, the current focus has been more on symptomatic treatment, rather than preventive measures. To address this, we performed a meta-analysis aiming to identify potential predictors of osteoporotic fractures in postmenopausal women, with the ultimate goal of identifying high-risk patients and exploring potential therapeutic approaches. We searched Embase, MEDLINE and Cochrane with search terms (postmenopausal AND fracture) AND ("risk factor" OR "predictive factor") in May 2022 for cohort and case-control studies on the predictors of osteoporotic fracture in postmenopausal women. Ten studies with 1,287,021 postmenopausal women were found eligible for analyses, in which the sample size ranged from 311 to 1,272,115. The surveyed date spanned from 1993 to 2021. Our results suggested that age, BMI, senior high school and above, parity ≥ 3, history of hypertension, history of diabetes mellitus, history of alcohol intake, age at menarche ≥ 15, age at menopause < 40, age at menopause > 50, estrogen use and vitamin D supplements were significantly associated with osteoporotic fracture in postmenopausal women. Our findings facilitate the early prediction of osteoporotic fracture in postmenopausal women and may contribute to potential therapeutic approaches. By focusing on preventive strategies and identifying high-risk individuals, we can work toward reducing the burden of osteoporosis-related fractures in this vulnerable population.

Periostin in Osteoporosis and Cardiovascular Disease

Context

Osteoporosis (OP) and cardiovascular disease (CVD), prevalent disorders worldwide, often coexist and share common risk factors. The identification of common biomarkers could significantly improve patients' preventive care.

Objectives

The objectives are 1, to review periostin (Postn) involvement in osteoporosis and in CVD, and 2, identify if Postn could be a common biomarker.

Design

This is a scoping review on Postn in OP and CVD.

Methods

Databases were searched, in vitro and in vivo, for publications in English on Postn, bone, and the cardiovascular system, with no limit regarding publication date.

Results

Postn appears as a key factor in OP and CVD. Its role as a potential biomarker in both pathologies is described in recent studies, but a number of limitations have been identified.

Conclusions

Current evidence provides fragmented views on Postn in OP and CVD and does not encapsulate Postn as a common pivotal thread linking these comorbidities. A number of gaps impede highlighting Postn as a common biomarker. There is room for future basic and clinical research with Postn as a marker and a target to provide new therapeutic options for aging patients with concomitant OP and CVD.

Prevalence of osteoporosis in patients with diabetes mellitus: a systematic review and meta-analysis of observational studies

BACKGROUND

Osteoporosis (OP) and diabetes mellitus (DM) are two major healthcare issues in the world. Numerous population based-studies have reported an increased prevalence of OP among individuals with DM, though, estimates vary significantly.

PURPOSE

The objective of this study is to estimate the prevalence of OP in patients with DM.

METHODS

To identify relevant literature, PubMed, Embase, Medline, CBM and Cochrane Library were searched for studies published from inception till July 2022, The search was conducted, and studies were included without countries and language restrictions. For full-text articles included in the study, the references were also independently searched. Random inverse variance-weighted models were used by Stata version 17.0 to estimate the prevalence of OP in patients with diabetes across studies. The heterogeneity was examined with I² via the χ² test on Cochrane's Q statistic. Subgroup analysis and meta-regression were used to explore potential sources of heterogeneity. Egger's test was used to assess publication bias.

RESULTS

A high OP prevalence of 27.67% (95% confidence interval (CI) 21.37-33.98%) was found in a pooled analysis of 21 studies involving 11,603 T2DM patients. Methodological value of the included articles was high, with only three medium-quality studies and no low-quality studies. A significantly high heterogeneity (I² = 98.5%) was observed.

CONCLUSIONS

Worldwide, a high prevalence of OP was found in patients with T2DM. Therefore, strong measures to prevent and treat osteoporosis in diabetic patients are required.

TRIAL REGISTRATION

This study has been registered on PROSPERO, number CRD42021286580 .

Perspective of the GEMSTONE Consortium on Current and Future Approaches to Functional Validation for Skeletal Genetic Disease Using Cellular, Molecular and Animal-Modeling Techniques

The availability of large human datasets for genome-wide association studies (GWAS) and the advancement of sequencing technologies have boosted the identification of genetic variants in complex and rare diseases in the skeletal field. Yet, interpreting results from human association studies remains a challenge. To bridge the gap between genetic association and causality, a systematic functional investigation is necessary. Multiple unknowns exist for putative causal genes, including cellular localization of the molecular function. Intermediate traits ("endophenotypes"), e.g. molecular quantitative trait loci (molQTLs), are needed to identify mechanisms of underlying associations. Furthermore, index variants often reside in non-coding regions of the genome, therefore challenging for interpretation. Knowledge of non-coding variance (e.g. ncRNAs), repetitive sequences, and regulatory interactions between enhancers and their target genes is central for understanding causal genes in skeletal conditions. Animal models with deep skeletal phenotyping and cell culture models have already facilitated fine mapping of some association signals, elucidated gene mechanisms, and revealed disease-relevant biology. However, to accelerate research towards bridging the current gap between association and causality in skeletal diseases, alternative in vivo platforms need to be used and developed in parallel with the current -omics and traditional in vivo resources. Therefore, we argue that as a field we need to establish resource-sharing standards to collectively address complex research questions. These standards will promote data integration from various -omics technologies and functional dissection of human complex traits. In this mission statement, we review the current available resources and as a group propose a consensus to facilitate resource sharing using existing and future resources. Such coordination efforts will maximize the acquisition of knowledge from different approaches and thus reduce redundancy and duplication of resources. These measures will help to understand the pathogenesis of osteoporosis and other skeletal diseases towards defining new and more efficient therapeutic targets.