Identification of New Genes and Loci Associated With Bone Mineral Density Based on Mendelian Randomization

Associations between the VDR Gene rs731236 (TaqI) Polymorphism and Bone Mineral Density in Postmenopausal Women from the RAC-OST-POL

BACKGROUND

Postmenopausal osteoporosis is not only related to hormonal factors but is also associated with environmental and genetic factors. One of the latter is the polymorphism of vitamin D receptor (VDR). The aim of the reported study was to comprehensively analyze the VDR gene polymorphic variants rs731236 (TaqI), rs1544410 (BsmI) and rs7975232 (ApaI) in the Polish population of postmenopausal women.

METHODS

The study group consisted of 611 women after menopause (their median age was 65.82 ± 6.29 years). Each of them underwent bone densitometry (DXA) of the non-dominant femoral neck and total hip with a biochemical analysis of vitamin D3 serum concentration and genotyping of the above-mentioned single nucleotide polymorphisms (SNPs); the obtained results were analyzed in the aspect of waist circumference (WC), body mass index (BMI) and past medical history.

RESULTS

The genotype prevalence rates of all SNPs were compatible with Hardy-Weinberg equilibrium (p > 0.050). Out of the studied polymorphisms, only rs731236 genotype variants affected DXA, with AG heterozygotes showing the worst bone parameters. Neither patient age nor vitamin D3 concentration, BMI, WC or comorbidities was associated with rs731236 genotype.

CONCLUSIONS

Out of the polymorphisms studied, only rs731236 genotypes differed among the DXA results, while the AG heterozygotes were characterized by the lowest median bone mineral density.

Leveraging electronic health records and knowledge networks for Alzheimer's disease prediction and sex-specific biological insights

Identification of Alzheimer's disease (AD) onset risk can facilitate interventions before irreversible disease progression. We demonstrate that electronic health records from the University of California, San Francisco, followed by knowledge networks (for example, SPOKE) allow for (1) prediction of AD onset and (2) prioritization of biological hypotheses, and (3) contextualization of sex dimorphism. We trained random forest models and predicted AD onset on a cohort of 749 individuals with AD and 250,545 controls with a mean area under the receiver operating characteristic of 0.72 (7 years prior) to 0.81 (1 day prior). We further harnessed matched cohort models to identify conditions with predictive power before AD onset. Knowledge networks highlight shared genes between multiple top predictors and AD (for example, APOE, ACTB, IL6 and INS). Genetic colocalization analysis supports AD association with hyperlipidemia at the APOE locus, as well as a stronger female AD association with osteoporosis at a locus near MS4A6A. We therefore show how clinical data can be utilized for early AD prediction and identification of personalized biological hypotheses.

Genetic insight into the putative causal proteins and druggable targets of osteoporosis: a large-scale proteome-wide mendelian randomization study

Background: Osteoporosis is a major causative factor of the global burden of disease and disability, characterized by low bone mineral density (BMD) and high risks of fracture. We aimed to identify putative causal proteins and druggable targets of osteoporosis. Methods: This study utilized the largest GWAS summary statistics on plasma proteins and estimated heel BMD (eBMD) to identify causal proteins of osteoporosis by mendelian randomization (MR) analysis. Different GWAS datasets were used to validate the results. Multiple sensitivity analyses were conducted to evaluate the robustness of primary MR findings. We have also performed an enrichment analysis for the identified causal proteins and evaluated their druggability. Results: After Bonferroni correction, 67 proteins were identified to be causally associated with estimated BMD (eBMD) (p < 4 × 10^-5). We further replicated 38 of the 67 proteins to be associated with total body BMD, lumbar spine BMD, femoral neck BMD as well as fractures, such as RSPO3, IDUA, SMOC2, and LRP4. The findings were supported by sensitivity analyses. Enrichment analysis identified multiple Gene Ontology items, including collagen-containing extracellular matrix (GO:0062023, p = 1.6 × 10^-10), collagen binding (GO:0005518, p = 8.6 × 10^-5), and extracellular matrix structural constituent (GO:0005201, p = 2.7 × 10^-5). Conclusion: The study identified novel putative causal proteins for osteoporosis which may serve as potential early screening biomarkers and druggable targets. Furthermore, the role of plasma proteins involved in collagen binding and extracellular matrix in the development of osteoporosis was highlighted. Further studies are warranted to validate our findings and investigate the underlying mechanism.

Functional Validation of Osteoporosis Genetic Findings Using Small Fish Models

The advancement of human genomics has revolutionized our understanding of the genetic architecture of many skeletal diseases, including osteoporosis. However, interpreting results from human association studies remains a challenge, since index variants often reside in non-coding regions of the genome and do not possess an obvious regulatory function. To bridge the gap between genetic association and causality, a systematic functional investigation is necessary, such as the one offered by animal models. These models enable us to identify causal mechanisms, clarify the underlying biology, and apply interventions. Over the past several decades, small teleost fishes, mostly zebrafish and medaka, have emerged as powerful systems for modeling the genetics of human diseases. Due to their amenability to genetic intervention and the highly conserved genetic and physiological features, fish have become indispensable for skeletal genomic studies. The goal of this review is to summarize the evidence supporting the utility of Zebrafish (Danio rerio) for accelerating our understanding of human skeletal genomics and outlining the remaining gaps in knowledge. We provide an overview of zebrafish skeletal morphophysiology and gene homology, shedding light on the advantages of human skeletal genomic exploration and validation. Knowledge of the biology underlying osteoporosis through animal models will lead to the translation into new, better and more effective therapeutic approaches.