ArticlePloS one2015
Integrative Analysis of Transcriptomic and Epigenomic Data to Reveal Regulation Patterns for BMD Variation.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 27 citations in OpenAlex.
- Glycolysis in bone remodeling: from energy supply to signaling regulation.Molecular biology reports · 2026Review
- An atlas of genetic effects on the monocyte methylome across European and African populations.Genome medicine · 2026Article
- CGRP Enhances the Regeneration of Bone Defects by Regulating Bone Marrow Mesenchymal Stem Cells Through Promoting ANGPTL4 Secretion by Bone Blood Vessels.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Nutrients and Metabolites as Signalling Molecules in Osteoclasts.Current osteoporosis reports · 2026Review
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- High Bone Mass Disorders: New Insights From Connecting the Clinic and the Bench.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2023Review
- Review
- Epigenetic regulation of bone mass.Best practice & research. Clinical endocrinology & metabolism · 2022Review
- Screening of Important Markers in Peripheral Blood Mononuclear Cells to Predict Female Osteoporosis Risk Using LASSO Regression Algorithm and SVM Method.Evolutionary bioinformatics online · 2022Article
- A road map for understanding molecular and genetic determinants of osteoporosis.Nature reviews. Endocrinology · 2020Review
- Genomic, Transcriptomic, and Epigenomic Features Differentiate Genes That Are Relevant for Muscular Polyunsaturated Fatty Acids in the Common Carp.Frontiers in genetics · 2019Article
- Network approaches to systems biology analysis of complex disease: integrative methods for multi-omics data.Briefings in bioinformatics · 2018Review
- Perinatal DNA Methylation at CDKN2A Is Associated With Offspring Bone Mass: Findings From the Southampton Women's Survey.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2017Article
- Cytosolic proteome profiling of monocytes for male osteoporosis.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2017Article
- Rapid phenotyping of knockout mice to identify genetic determinants of bone strength.The Journal of endocrinology · 2016Review
- Epigenetic Regulation of Bone Remodeling and Its Impacts in Osteoporosis.International journal of molecular sciences · 2016Review
- How to interpret epigenetic association studies: a guide for clinicians.BoneKEy reports · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
Abstract
Integration of multiple profiling data and construction of functional gene networks may provide additional insights into the molecular mechanisms of complex diseases. Osteoporosis is a worldwide public health problem, but the complex gene-gene interactions, post-transcriptional modifications and regulation of functional networks are still unclear. To gain a comprehensive understanding of osteoporosis etiology, transcriptome gene expression microarray, epigenomic miRNA microarray and methylome sequencing were performed simultaneously in 5 high hip BMD (Bone Mineral Density) subjects and 5 low hip BMD subjects. SPIA (Signaling Pathway Impact Analysis) and PCST (Prize Collecting Steiner Tree) algorithm were used to perform pathway-enrichment analysis and construct the interaction networks. Through integrating the transcriptomic and epigenomic data, firstly we identified 3 genes (FAM50A, ZNF473 and TMEM55B) and one miRNA (hsa-mir-4291) which showed the consistent association evidence from both gene expression and methylation data; secondly in network analysis we identified an interaction network module with 12 genes and 11 miRNAs including AKT1, STAT3, STAT5A, FLT3, hsa-mir-141 and hsa-mir-34a which have been associated with BMD in previous studies. This module revealed the crosstalk among miRNAs, mRNAs and DNA methylation and showed four potential regulatory patterns of gene expression to influence the BMD status. In conclusion, the integration of multiple layers of omics can yield in-depth results than analysis of individual omics data respectively. Integrative analysis from transcriptomics and epigenomic data improves our ability to identify causal genetic factors, and more importantly uncover functional regulation pattern of multi-omics for osteoporosis etiology.
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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.