ArticleCell systems2017
Integrating GWAS and Co-expression Network Data Identifies Bone Mineral Density Genes SPTBN1 and MARK3 and an Osteoblast Functional Module.
Article in Cell systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
73 citing papers in PubMed, 1 synthesis or guideline pooled it, 122 citations in OpenAlex.
- Meta-Analysis of Genomewide Association Studies Reveals Genetic Variants for Hip Bone Geometry.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2019Pooled it
- Identifying independent causal cell types for human diseases and risk variants.Cell genomics · 2026Article
- Unveiling muscle fatigue: identifying key gene biomarkers and therapeutic targets.Molecular and cellular biochemistry · 2026Article
- Mitochondria-Related Genome-Wide Mendelian Randomization Identifies Putatively Genes for Chronic Fatigue.Molecular neurobiology · 2026Article
- Article
- GWAS-informed data integration and non-coding CRISPRi screen illuminate genetic etiology of bone mineral density.Genome biology · 2025Article
- The Importance of Regulatory Network Structure for Complex Trait Heritability and Evolution.Molecular biology and evolution · 2025Article
- GWAS-Informed data integration and non-coding CRISPRi screen illuminate genetic etiology of bone mineral density.bioRxiv : the preprint server for biology · 2024Article
- From Genomics to Metabolomics: Molecular Insights into Osteoporosis for Enhanced Diagnostic and Therapeutic Approaches.Biomedicines · 2024Review
- Tmem263 deletion disrupts the GH/IGF-1 axis and causes dwarfism and impairs skeletal acquisition.eLife · 2024Article
- Article
- Interaction between MARK3 (rs11623869), PLCB4 (rs6086746) and GEMIN2 (rs2277458) variants with bone mineral density and serum 25-hidroxivitamin D levels in Mexican Mestizo women.Frontiers in endocrinology · 2024Article
- Article
- Genetic and Gene Expression Resources for Osteoporosis and Bone Biology Research.Current osteoporosis reports · 2023Review
- Systems genetics approaches for understanding complex traits with relevance for human disease.eLife · 2023Review
- Tmem263 deletion disrupts the GH/IGF-1 axis and causes dwarfism and impairs skeletal acquisition.bioRxiv : the preprint server for biology · 2023Article
- Single-Cell Transcriptomics of Bone Marrow Stromal Cells in Diversity Outbred Mice: A Model for Population-Level scRNA-Seq Studies.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2023Article
- Anaphase-Promoting Complex Subunit 1 Associates with Bone Mineral Density in Human Osteoporotic Bone.International journal of molecular sciences · 2023Article
- A study of the influence of genetic variance and sex on the density and thickness of the calvarial bone in collaborative cross mice.Animal models and experimental medicine · 2023Article
- Genome-wide family prediction unveils molecular mechanisms underlying the regulation of agronomic traits inFrontiers in plant science · 2023Article
13 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
Abstract
Bone mineral density (BMD) is a highly heritable predictor of osteoporotic fracture. Genome-wide association studies (GWAS) for BMD have identified dozens of associations; yet, the genes responsible for most associations remain elusive. Here, we used a bone co-expression network to predict causal genes at BMD GWAS loci based on the premise that genes underlying a disease are often functionally related and functionally related genes are often co-expressed. By mapping genes implicated by BMD GWAS onto a bone co-expression network, we predicted and inferred the function of causal genes for 30 of 64 GWAS loci. We experimentally confirmed that two of the genes predicted to be causal, SPTBN1 and MARK3, are potentially responsible for the effects of GWAS loci on chromosomes 2p16.2 and 14q32.32, respectively. This approach provides a roadmap for the dissection of additional BMD GWAS associations. Furthermore, it should be applicable to GWAS data for a wide range of diseases.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.