Systems genetics in diversity outbred mice inform BMD GWAS and identify determinants of bone strength.
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ABSTRACT:
SUBMITTER: Al-Barghouthi BM
PROVIDER: S-EPMC8184749 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Genome-wide association studies (GWASs) for osteoporotic traits have identified over 1000 associations; however, their impact has been limited by the difficulties of causal gene identification and a strict focus on bone mineral density (BMD). Here, we used Diversity Outbred (DO) mice to directly address these limitations by performing the first systems genetics analysis of over 50 complex skeletal phenotypes. We applied a network approach to cortical bone RNA-seq data to discover 46 genes likely to be causal for human BMD GWAS associations, including the novel genes SERTAD4 and GLT8D2. We also performed GWAS in the DO for a wide-range of bone traits and identify Qsox1 as a novel gene influencing cortical bone accrual and bone strength. Our results provide a new perspective on the genetics of osteoporosis and highlight the ability of the mouse to inform human genetics.
2020-06-18 | GSE152708 | GEO
Project description:Osteoporosis is one of the most common chronic forms of disability in postmenopausal women and represents a major health burden around the world. Bone fragility is affected by bone mineral density (BMD), and, one of the most important factors in preventing osteoporosis is optimizing peak bone mass, which is achieved during growth in childhood and adolescence. BMD is a complex trait resulting from environmental and genetic factors. Genome-wide association studies have discovered robust genetic signals influencing BMD in adults, and similar studies have also been conducted to investigate the genetics of BMD in the pediatric setting. These latter studies have revealed that many adult osteoporosis-related loci also regulate BMD during growth. These investigations have the potential to profoundly impact public health and will allow for the eventual development of effective interventions for the prevention of osteoporosis.
| S-EPMC4954586 | biostudies-literature
Project description:Recent and classical work has revealed biologically and medically significant subtypes in complex diseases and traits. However, relevant subtypes are often unknown, unmeasured, or actively debated, making automated statistical approaches to subtype definition valuable. We propose reverse GWAS (RGWAS) to identify and validate subtypes using genetics and multiple traits: while GWAS seeks the genetic basis of a given trait, RGWAS seeks to define trait subtypes with distinct genetic bases. Unlike existing approaches relying on off-the-shelf clustering methods, RGWAS uses a novel decomposition, MFMR, to model covariates, binary traits, and population structure. We use extensive simulations to show that modelling these features can be crucial for power and calibration. We validate RGWAS in practice by recovering a recently discovered stress subtype in major depression. We then show the utility of RGWAS by identifying three novel subtypes of metabolic traits. We biologically validate these metabolic subtypes with SNP-level tests and a novel polygenic test: the former recover known metabolic GxE SNPs; the latter suggests subtypes may explain substantial missing heritability. Crucially, statins, which are widely prescribed and theorized to increase diabetes risk, have opposing effects on blood glucose across metabolic subtypes, suggesting the subtypes have potential translational value.
| S-EPMC6469799 | biostudies-literature
Project description:The regulation of bone mineral density (BMD) is highly influenced by genetics and age. Although genome-wide association studies (GWAS) for BMD have uncovered many genes through their proximity to associated variants (variant nearest-neighbor [VNN] genes), the cell-specific mechanisms of each VNN gene remain unclear. This is primarily due to the inability to prioritize these genes by cell type and age-related expression. Using age-related transcriptomics, we found that the expression of many VNN genes was upregulated in the bone and marrow from aged mice. Candidate genes from GWAS were investigated using single-cell RNA-sequencing (scRNA-seq) datasets to enrich for cell-specific expression signatures. VNN candidate genes are highly enriched in osteo-lineage cells, osteocytes, hypertrophic chondrocytes, and Lepr+ mesenchymal stem cells. These data were used to generate a "blueprint" for Cre-loxp mouse line selection for functional validation of candidate genes and further investigation of their role in BMD maintenance throughout aging. In VNN-gene-enriched cells, Sparc, encoding the extracellular matrix (ECM) protein osteonectin, was robustly expressed. This, along with expression of numerous other ECM genes, indicates that many VNN genes likely have roles in ECM deposition by osteoblasts. Overall, we provide data supporting streamlined translation of GWAS candidate genes to potential novel therapeutic targets for the treatment of osteoporosis. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
| S-EPMC10556272 | biostudies-literature
Project description:Bone area is one measure of bone size that is easily derived from dual-energy X-ray absorptiometry (DXA) scans. In a GWA study of DXA bone area of the hip and lumbar spine (N ≥ 28,954), we find thirteen independent association signals at twelve loci that replicate in samples of European and East Asian descent (N = 13,608 - 21,277). Eight DXA area loci associate with osteoarthritis, including rs143384 in GDF5 and a missense variant in COL11A1 (rs3753841). The strongest DXA area association is with rs11614913[T] in the microRNA MIR196A2 gene that associates with lumbar spine area (P = 2.3 × 10-42, β = -0.090) and confers risk of hip fracture (P = 1.0 × 10-8, OR = 1.11). We demonstrate that the risk allele is less efficient in repressing miR-196a-5p target genes. We also show that the DXA area measure contributes to the risk of hip fracture independent of bone density.
| S-EPMC6499783 | biostudies-literature
Project description:Estrogen receptor α (ESR1) is involved in E2 signaling and plays a major role in postmenopausal bone loss. However, the molecular network underlying ESR1 has not been explored. We used systems genetics and bioinformatics to identify important genes associated with Esr1 in postmenopausal bone loss. We identified ~2300 Esr1-coexpressed genes in female BXD bone femur, functional analysis of which revealed 'osteoblast signaling' as the most enriched pathway. PPI network led to the identification of 25 'female bone candidates'. The gene-regulatory analysis revealed RUNX2 as a key TF. ANKRD1 and RUNX2 were significantly different between osteoporosis patients and healthy controls. Sp7, Col1a1 and Pth1r correlated with multiple femur bone phenotypes in BXD mice. miR-3121-3p targeted Csf1, Ankrd1, Sp7 and Runx2. β-estradiol treatment markedly increased the expression of these candidates in mouse osteoblast. Our study revealed that Esr1-correlated genes Ankrd1, Runx2, Csf1 and Sp7 may play important roles in female bone development.
| S-EPMC10811775 | biostudies-literature
Project description:Numerous quantitative trait loci (QTLs) affecting bone traits have been identified in the mouse; however, few of the underlying genes have been discovered. To improve the process of transitioning from QTL to gene, we describe an integrative genetics approach, which combines linkage analysis, expression QTL (eQTL) mapping, causality modeling, and genetic association in outbred mice. In C57BL/6J x C3H/HeJ (BXH) F(2) mice, nine QTLs regulating femoral BMD were identified. To select candidate genes from within each QTL region, microarray gene expression profiles from individual F(2) mice were used to identify 148 genes whose expression was correlated with BMD and regulated by local eQTLs. Many of the genes that were the most highly correlated with BMD have been previously shown to modulate bone mass or skeletal development. Candidates were further prioritized by determining whether their expression was predicted to underlie variation in BMD. Using network edge orienting (NEO), a causality modeling algorithm, 18 of the 148 candidates were predicted to be causally related to differences in BMD. To fine-map QTLs, markers in outbred MF1 mice were tested for association with BMD. Three chromosome 11 SNPs were identified that were associated with BMD within the Bmd11 QTL. Finally, our approach provides strong support for Wnt9a, Rasd1, or both underlying Bmd11. Integration of multiple genetic and genomic data sets can substantially improve the efficiency of QTL fine-mapping and candidate gene identification.
| S-EPMC2661539 | biostudies-literature
Project description:Genome-wide association studies (GWAS) have successfully identified associations for cervical cancer, but the underlying mechanisms of cervical biology and pathology remain uncharacterised. Our GWAS meta-analyses fill this gap, as we characterise the genetic architecture of cervical phenotypes, including cervical ectropion, cervicitis, cervical dysplasia, as well as up to 9229 cases and 490 304 controls for cervical cancer from diverse ancestries. Leveraging the latest computational methods and gene expression data, we refine the association signals for cervical cancer and propose potential causal variants and genes at each locus. We prioritise PAX8/PAX8-AS1, LINC00339, CDC42, CLPTM1L, HLA-DRB1 and GSDMB as the most likely candidate genes for cervical cancer signals, providing insights into cervical cancer pathogenesis and supporting the involvement of reproductive tract development, immune response and cellular proliferation/apoptosis. We construct a genetic risk score (GRS) that is associated with cervical cancer [hazard ratios (HR) = 3.1 (1.7-5.6) for the top 15% vs lowest 15% of individuals], and with other HPV- and immune-system-related diagnoses in a phenome-wide association study analysis. Our results propose valuable leads for further functional studies and present a GRS for cervical cancer that allows additional risk stratification and could potentially be used to personalise the conventional screening strategies for groups more susceptible to cervical cancer.
| S-EPMC10244231 | biostudies-literature
Project description:Significant advances have been made in the discovery of genes affecting bone mineral density (BMD); however, our understanding of its genetic basis remains incomplete. In the current study, genome-wide association (GWA) and co-expression network analysis were used in the recently described Hybrid Mouse Diversity Panel (HMDP) to identify and functionally characterize novel BMD genes. In the HMDP, a GWA of total body, spinal, and femoral BMD revealed four significant associations (-log10P>5.39) affecting at least one BMD trait on chromosomes (Chrs.) 7, 11, 12, and 17. The associations implicated a total of 163 genes with each association harboring between 14 and 112 genes. This list was reduced to 26 functional candidates by identifying those genes that were regulated by local eQTL in bone or harbored potentially functional non-synonymous (NS) SNPs. This analysis revealed that the most significant BMD SNP on Chr. 12 was a NS SNP in the additional sex combs like-2 (Asxl2) gene that was predicted to be functional. The involvement of Asxl2 in the regulation of bone mass was confirmed by the observation that Asxl2 knockout mice had reduced BMD. To begin to unravel the mechanism through which Asxl2 influenced BMD, a gene co-expression network was created using cortical bone gene expression microarray data from the HMDP strains. Asxl2 was identified as a member of a co-expression module enriched for genes involved in the differentiation of myeloid cells. In bone, osteoclasts are bone-resorbing cells of myeloid origin, suggesting that Asxl2 may play a role in osteoclast differentiation. In agreement, the knockdown of Asxl2 in bone marrow macrophages impaired their ability to form osteoclasts. This study identifies a new regulator of BMD and osteoclastogenesis and highlights the power of GWA and systems genetics in the mouse for dissecting complex genetic traits.
| S-EPMC3072371 | biostudies-literature
Project description:Mycobacterium tuberculosis infects two billion people across the globe, and results in 8-9 million new tuberculosis (TB) cases and 1-1.5 million deaths each year. Most patients have no known genetic basis that predisposes them to disease. Here, we investigate the complex genetic basis of pulmonary TB by modelling human genetic diversity with the Diversity Outbred mouse population. When infected with M. tuberculosis, one-third develop early onset, rapidly progressive, necrotizing granulomas and succumb within 60 days. The remaining develop non-necrotizing granulomas and survive longer than 60 days. Genetic mapping using immune and inflammatory mediators; and clinical, microbiological, and granuloma correlates of disease identified five new loci on mouse chromosomes 1, 2, 4, 16; and three known loci on chromosomes 3 and 17. Further, multiple positively correlated traits shared loci on chromosomes 1, 16, and 17 and had similar patterns of allele effects, suggesting these loci contain critical genetic regulators of inflammatory responses to M. tuberculosis. To narrow the list of candidate genes, we used a machine learning strategy that integrated gene expression signatures from lungs of M. tuberculosis-infected Diversity Outbred mice with gene interaction networks to generate scores representing functional relationships. The scores were used to rank candidates for each mapped trait, resulting in 11 candidate genes: Ncf2, Fam20b, S100a8, S100a9, Itgb5, Fstl1, Zbtb20, Ddr1, Ier3, Vegfa, and Zfp318. Although all candidates have roles in infection, inflammation, cell migration, extracellular matrix remodeling, or intracellular signaling, and all contain single nucleotide polymorphisms (SNPs), SNPs in only four genes (S100a8, Itgb5, Fstl1, Zfp318) are predicted to have deleterious effects on protein functions. We performed methodological and candidate validations to (i) assess biological relevance of predicted allele effects by showing that Diversity Outbred mice carrying PWH/PhJ alleles at the H-2 locus on chromosome 17 QTL have shorter survival; (ii) confirm accuracy of predicted allele effects by quantifying S100A8 protein in inbred founder strains; and (iii) infection of C57BL/6 mice deficient for the S100a8 gene. Overall, this body of work demonstrates that systems genetics using Diversity Outbred mice can identify new (and known) QTLs and functionally relevant gene candidates that may be major regulators of complex host-pathogens interactions contributing to granuloma necrosis and acute inflammation in pulmonary TB.
2024-06-15 | GSE267006 | GEO