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Dillard LJ, Calabrese GM, Mesner LD, Farber CR. Cell type-specific network analysis in Diversity Outbred mice identifies genes potentially responsible for human bone mineral density GWAS associations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.20.594981. [PMID: 38826475 PMCID: PMC11142079 DOI: 10.1101/2024.05.20.594981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Genome-wide association studies (GWASs) have identified many sources of genetic variation associated with bone mineral density (BMD), a clinical predictor of fracture risk and osteoporosis. Aside from the identification of causal genes, other difficult challenges to informing GWAS include characterizing the roles of predicted causal genes in disease and providing additional functional context, such as the cell type predictions or biological pathways in which causal genes operate. Leveraging single-cell transcriptomics (scRNA-seq) can assist in informing BMD GWAS by linking disease-associated variants to genes and providing a cell type context for which these causal genes drive disease. Here, we use large-scale scRNA-seq data from bone marrow-derived stromal cells cultured under osteogenic conditions (BMSC-OBs) from Diversity Outbred (DO) mice to generate cell type-specific networks and contextualize BMD GWAS-implicated genes. Using trajectories inferred from the scRNA-seq data, we identify networks enriched with genes that exhibit the most dynamic changes in expression across trajectories. We discover 21 network driver genes, which are likely to be causal for human BMD GWAS associations that colocalize with expression/splicing quantitative trait loci (eQTL/sQTL). These driver genes, including Fgfrl1 and Tpx2, along with their associated networks, are predicted to be novel regulators of BMD via their roles in the differentiation of mesenchymal lineage cells. In this work, we showcase the use of single-cell transcriptomics from mouse bone-relevant cells to inform human BMD GWAS and prioritize genetic targets with potential causal roles in the development of osteoporosis.
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Affiliation(s)
- Luke J Dillard
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908
| | - Gina M Calabrese
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908
| | - Larry D Mesner
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908
- Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA 22908
| | - Charles R Farber
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908
- Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA 22908
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22908
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Kim A, Zhang Z, Legros C, Lu Z, de Smith A, Moore JE, Mancuso N, Gazal S. Inferring causal cell types of human diseases and risk variants from candidate regulatory elements. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.17.24307556. [PMID: 38798383 PMCID: PMC11118635 DOI: 10.1101/2024.05.17.24307556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
The heritability of human diseases is extremely enriched in candidate regulatory elements (cRE) from disease-relevant cell types. Critical next steps are to infer which and how many cell types are truly causal for a disease (after accounting for co-regulation across cell types), and to understand how individual variants impact disease risk through single or multiple causal cell types. Here, we propose CT-FM and CT-FM-SNP, two methods that leverage cell-type-specific cREs to fine-map causal cell types for a trait and for its candidate causal variants, respectively. We applied CT-FM to 63 GWAS summary statistics (average N = 417K) using nearly one thousand cRE annotations, primarily coming from ENCODE4. CT-FM inferred 81 causal cell types with corresponding SNP-annotations explaining a high fraction of trait SNP-heritability (~2/3 of the SNP-heritability explained by existing cREs), identified 16 traits with multiple causal cell types, highlighted cell-disease relationships consistent with known biology, and uncovered previously unexplored cellular mechanisms in psychiatric and immune-related diseases. Finally, we applied CT-FM-SNP to 39 UK Biobank traits and predicted high confidence causal cell types for 2,798 candidate causal non-coding SNPs. Our results suggest that most SNPs impact a phenotype through a single cell type, and that pleiotropic SNPs target different cell types depending on the phenotype context. Altogether, CT-FM and CT-FM-SNP shed light on how genetic variants act collectively and individually at the cellular level to impact disease risk.
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Affiliation(s)
- Artem Kim
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Zixuan Zhang
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Come Legros
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Zeyun Lu
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Adam de Smith
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jill E Moore
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Nicholas Mancuso
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Steven Gazal
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
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Wu Y, Zhang C, Duan S, Li Y, Lu L, Bajpai A, Yang C, Mi J, Tian G, Xu F, Qi D, Xu Z, Chi XD. TEAD1, MYO7A and NDUFC2 are novel functional genes associated with glucose metabolism in BXD recombinant inbred population. Diabetes Obes Metab 2024; 26:1775-1788. [PMID: 38385898 DOI: 10.1111/dom.15491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2023] [Revised: 01/12/2024] [Accepted: 01/17/2024] [Indexed: 02/23/2024]
Abstract
AIM The liver is an important metabolic organ that governs glucolipid metabolism, and its dysfunction may cause non-alcoholic fatty liver disease, type 2 diabetes mellitus, dyslipidaemia, etc. We aimed to systematic investigate the key factors related to hepatic glucose metabolism, which may be beneficial for understanding the underlying pathogenic mechanisms for obesity and diabetes mellitus. MATERIALS AND METHODS Oral glucose tolerance test (OGTT) phenotypes and liver transcriptomes of BXD mice under chow and high-fat diet conditions were collected from GeneNetwork. QTL mapping was conducted to pinpoint genomic regions associated with glucose homeostasis. Candidate genes were further nominated using a multi-criteria approach and validated to confirm their functional relevance in vitro. RESULTS Our results demonstrated that plasma glucose levels in OGTT were significantly affected by both diet and genetic background, with six genetic regulating loci were mapped on chromosomes 1, 4, and 7. Moreover, TEAD1, MYO7A and NDUFC2 were identified as the candidate genes. Functionally, siRNA-mediated TEAD1, MYO7A and NDUFC2 knockdown significantly decreased the glucose uptake and inhibited the transcription of genes related to insulin and glucose metabolism pathways. CONCLUSIONS Our study contributes novel insights to the understanding of hepatic glucose metabolism, demonstrating the impact of TEAD1, MYO7A and NDUFC2 on mitochondrial function in the liver and their regulatory role in maintaining in glucose homeostasis.
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Affiliation(s)
- Yingying Wu
- The Second School of Clinical Medicine of Binzhou Medical University, Yantai, China
| | - Chao Zhang
- Yantai Affiliated Hospital of Binzhou Medical University, Yantai, China
| | - Shaofei Duan
- Shandong Technology Innovation Center of Molecular Targeting and Intelligent Diagnosis and Treatment, Binzhou Medical University, Yantai, China
| | - Yushan Li
- Shandong Technology Innovation Center of Molecular Targeting and Intelligent Diagnosis and Treatment, Binzhou Medical University, Yantai, China
| | - Lu Lu
- The University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Akhilesh Bajpai
- The University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Chunhua Yang
- Shandong Technology Innovation Center of Molecular Targeting and Intelligent Diagnosis and Treatment, Binzhou Medical University, Yantai, China
| | - Jia Mi
- Shandong Technology Innovation Center of Molecular Targeting and Intelligent Diagnosis and Treatment, Binzhou Medical University, Yantai, China
| | - Geng Tian
- Shandong Technology Innovation Center of Molecular Targeting and Intelligent Diagnosis and Treatment, Binzhou Medical University, Yantai, China
| | - Fuyi Xu
- Shandong Technology Innovation Center of Molecular Targeting and Intelligent Diagnosis and Treatment, Binzhou Medical University, Yantai, China
| | - Donglai Qi
- Shandong Technology Innovation Center of Molecular Targeting and Intelligent Diagnosis and Treatment, Binzhou Medical University, Yantai, China
| | - Zhaowei Xu
- Shandong Technology Innovation Center of Molecular Targeting and Intelligent Diagnosis and Treatment, Binzhou Medical University, Yantai, China
| | - Xiao Dong Chi
- Shandong Technology Innovation Center of Molecular Targeting and Intelligent Diagnosis and Treatment, Binzhou Medical University, Yantai, China
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Jung J, Wu Q. Identification of bone mineral density associated genes with shared genetic architectures across multiple tissues: Functional insights for EPDR1, PKDCC, and SPTBN1. PLoS One 2024; 19:e0300535. [PMID: 38683846 PMCID: PMC11057974 DOI: 10.1371/journal.pone.0300535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 02/28/2024] [Indexed: 05/02/2024] Open
Abstract
Recent studies suggest a shared genetic architecture between muscle and bone, yet the underlying molecular mechanisms remain elusive. This study aims to identify the functionally annotated genes with shared genetic architecture between muscle and bone using the most up-to-date genome-wide association study (GWAS) summary statistics from bone mineral density (BMD) and fracture-related genetic variants. We employed an advanced statistical functional mapping method to investigate shared genetic architecture between muscle and bone, focusing on genes highly expressed in muscle tissue. Our analysis identified three genes, EPDR1, PKDCC, and SPTBN1, which are highly expressed in muscle tissue and previously unlinked to bone metabolism. About 90% and 85% of filtered Single-Nucleotide Polymorphisms were in the intronic and intergenic regions for the threshold at P≤5×10-8 and P≤5×10-100, respectively. EPDR1 was highly expressed in multiple tissues, including muscles, adrenal glands, blood vessels, and the thyroid. SPTBN1 was highly expressed in all 30 tissue types except blood, while PKDCC was highly expressed in all 30 tissue types except the brain, pancreas, and skin. Our study provides a framework for using GWAS findings to highlight functional evidence of crosstalk between multiple tissues based on shared genetic architecture between muscle and bone. Further research should focus on functional validation, multi-omics data integration, gene-environment interactions, and clinical relevance in musculoskeletal disorders.
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Affiliation(s)
- Jongyun Jung
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio, United States of America
| | - Qing Wu
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio, United States of America
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Aparicio-Bautista DI, Jiménez-Ortega RF, Becerra-Cervera A, Aquino-Gálvez A, de León-Suárez VP, Casas-Ávila L, Salmerón J, Hidalgo-Bravo A, Rivera-Paredez B, Velázquez-Cruz R. Interaction between MARK3 (rs11623869), PLCB4 (rs6086746) and GEMIN2 (rs2277458) variants with bone mineral density and serum 25-hidroxivitamin D levels in Mexican Mestizo women. Front Endocrinol (Lausanne) 2024; 15:1392063. [PMID: 38715801 PMCID: PMC11074919 DOI: 10.3389/fendo.2024.1392063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 04/03/2024] [Indexed: 06/04/2024] Open
Abstract
Introduction Understanding the genetic factors contributing to variations in bone mineral density (BMD) and vitamin D could provide valuable insights into the pathogenesis of osteoporosis. This study aimed to evaluate the association of single nucleotide variants in MARK3 (rs11623869), PLCB4 (rs6086746), and GEMIN2 (rs2277458) with BMD in Mexican women. Methods The gene-gene interaction was evaluated in these variants in serum 25(OH)D levels and BMD. A genetic risk score (GRS) was created on the basis of the three genetic variants. Genotyping was performed using predesigned TaqMan assays. Results A significant association was found between the rs6086746-A variant and BMD at the total hip, femoral neck, and lumbar spine, in women aged 45 years or older. However, no association was observed between the variants rs11623869 and rs2277458. The rs11623869 × rs2277458 interaction was associated with total hip (p=0.002) and femoral neck BMD (p=0.013). Similarly, for vitamin D levels, we observed an interaction between the variants rs6086746 × rs2277458 (p=0.021). GRS revealed a significant association with total hip BMD (p trend=0.003) and femoral neck BMD (p trend=0.006), as well as increased vitamin D levels (p trend=0.0003). These findings provide evidence of the individual and joint effect of the MARK3, PLCB4, and GEMIN2 variants on BMD and serum vitamin D levels in Mexican women. Discussion This knowledge could help to elucidate the interaction mechanism between BMD-related genetic variants and 25OHD, contributing to the determination of the pathogenesis of osteoporosis and its potential implications during early interventions.
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Affiliation(s)
- Diana I. Aparicio-Bautista
- Laboratorio de Genómica del Metabolismo Óseo, Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City, Mexico
| | - Rogelio F. Jiménez-Ortega
- Laboratorio de Genómica del Metabolismo Óseo, Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City, Mexico
- Departamento de Ciencias de la Acupuntura. Universidad Estatal del Valle de Ecatepec. Ecatepec de Morelos, Estado de Mexico, Mexico
| | - Adriana Becerra-Cervera
- Laboratorio de Genómica del Metabolismo Óseo, Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City, Mexico
- Consejo Nacional de Humanidades, Ciencias y Tecnologías (CONAHCYT), Mexico City, Mexico
| | - Arnoldo Aquino-Gálvez
- Laboratorio de Biología Molecular, Departamento de Fibrosis Pulmonar, Instituto Nacional de Enfermedades Respiratorias “Ismael Cosío Villegas”, Mexico City, Mexico
| | | | - Leonora Casas-Ávila
- Departamento de Medicina Genómica, Instituto Nacional de Rehabilitación, Mexico City, Mexico
| | - Jorge Salmerón
- Centro de Investigación en Políticas, Población y Salud, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Alberto Hidalgo-Bravo
- Departamento de Medicina Genómica, Instituto Nacional de Rehabilitación, Mexico City, Mexico
| | - Berenice Rivera-Paredez
- Centro de Investigación en Políticas, Población y Salud, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Rafael Velázquez-Cruz
- Laboratorio de Genómica del Metabolismo Óseo, Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City, Mexico
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6
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Conery M, Pippin JA, Wagley Y, Trang K, Pahl MC, Villani DA, Favazzo LJ, Ackert-Bicknell CL, Zuscik MJ, Katsevich E, Wells AD, Zemel BS, Voight BF, Hankenson KD, Chesi A, Grant SF. GWAS-informed data integration and non-coding CRISPRi screen illuminate genetic etiology of bone mineral density. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.19.585778. [PMID: 38562830 PMCID: PMC10983984 DOI: 10.1101/2024.03.19.585778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Over 1,100 independent signals have been identified with genome-wide association studies (GWAS) for bone mineral density (BMD), a key risk factor for mortality-increasing fragility fractures; however, the effector gene(s) for most remain unknown. Informed by a variant-to-gene mapping strategy implicating 89 non-coding elements predicted to regulate osteoblast gene expression at BMD GWAS loci, we executed a single-cell CRISPRi screen in human fetal osteoblast 1.19 cells (hFOBs). The BMD relevance of hFOBs was supported by heritability enrichment from cross-cell type stratified LD-score regression involving 98 cell types grouped into 15 tissues. 24 genes showed perturbation in the screen, with four (ARID5B, CC2D1B, EIF4G2, and NCOA3) exhibiting consistent effects upon siRNA knockdown on three measures of osteoblast maturation and mineralization. Lastly, additional heritability enrichments, genetic correlations, and multi-trait fine-mapping revealed that many BMD GWAS signals are pleiotropic and likely mediate their effects via non-bone tissues that warrant attention in future screens.
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Affiliation(s)
- Mitchell Conery
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - James A. Pippin
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Yadav Wagley
- Department of Orthopaedic Surgery, University of Michigan Medical School, Ann Arbor, MI 48109
| | - Khanh Trang
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Matthew C. Pahl
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - David A. Villani
- Colorado Program for Musculoskeletal Research, University of Colorado Anschutz Medical Campus, Aurora, CO
- Cell Biology, Stems Cells and Development Ph.D. Program, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Lacey J. Favazzo
- Colorado Program for Musculoskeletal Research, University of Colorado Anschutz Medical Campus, Aurora, CO
- Department of Orthopedics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- University of Colorado Interdisciplinary Joint Biology Program, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Cheryl L. Ackert-Bicknell
- Colorado Program for Musculoskeletal Research, University of Colorado Anschutz Medical Campus, Aurora, CO
- Department of Orthopedics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- University of Colorado Interdisciplinary Joint Biology Program, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Michael J. Zuscik
- Colorado Program for Musculoskeletal Research, University of Colorado Anschutz Medical Campus, Aurora, CO
- Department of Orthopedics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- University of Colorado Interdisciplinary Joint Biology Program, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Eugene Katsevich
- Department of Statistics and Data Science, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Andrew D. Wells
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Babette S. Zemel
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Division of Gastroenterology, Hepatology and Nutrition, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Benjamin F. Voight
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kurt D. Hankenson
- Department of Orthopaedic Surgery, University of Michigan Medical School, Ann Arbor, MI 48109
| | - Alessandra Chesi
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Struan F.A. Grant
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Division of Endocrinology and Diabetes, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
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7
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Sarver DC, Garcia-Diaz J, Saqib M, Riddle RC, Wong GW. Tmem263 deletion disrupts the GH/IGF-1 axis and causes dwarfism and impairs skeletal acquisition. eLife 2024; 12:RP90949. [PMID: 38241182 PMCID: PMC10945605 DOI: 10.7554/elife.90949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2024] Open
Abstract
Genome-wide association studies (GWAS) have identified a large number of candidate genes believed to affect longitudinal bone growth and bone mass. One of these candidate genes, TMEM263, encodes a poorly characterized plasma membrane protein. Single nucleotide polymorphisms in TMEM263 are associated with bone mineral density in humans and mutations are associated with dwarfism in chicken and severe skeletal dysplasia in at least one human fetus. Whether this genotype-phenotype relationship is causal, however, remains unclear. Here, we determine whether and how TMEM263 is required for postnatal growth. Deletion of the Tmem263 gene in mice causes severe postnatal growth failure, proportional dwarfism, and impaired skeletal acquisition. Mice lacking Tmem263 show no differences in body weight within the first 2 weeks of postnatal life. However, by P21 there is a dramatic growth deficit due to a disrupted growth hormone (GH)/insulin-like growth factor 1 (IGF-1) axis, which is critical for longitudinal bone growth. Tmem263-null mice have low circulating IGF-1 levels and pronounced reductions in bone mass and growth plate length. The low serum IGF-1 in Tmem263-null mice is associated with reduced hepatic GH receptor (GHR) expression and GH-induced JAK2/STAT5 signaling. A deficit in GH signaling dramatically alters GH-regulated genes and feminizes the liver transcriptome of Tmem263-null male mice, with their expression profile resembling wild-type female, hypophysectomized male, and Stat5b-null male mice. Collectively, our data validates the causal role for Tmem263 in regulating postnatal growth and raises the possibility that rare mutations or variants of TMEM263 may potentially cause GH insensitivity and impair linear growth.
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Affiliation(s)
- Dylan C Sarver
- Department of Physiology, Johns Hopkins University School of MedicineBaltimoreUnited States
| | - Jean Garcia-Diaz
- Department of Orthopaedic Surgery, Johns Hopkins University School of MedicineBaltimoreUnited States
- Department of Orthopaedics, University of Maryland School of MedicineBaltimoreUnited States
- Cell and Molecular Medicine graduate program, Johns Hopkins University School of MedicineBaltimoreUnited States
| | - Muzna Saqib
- Department of Physiology, Johns Hopkins University School of MedicineBaltimoreUnited States
| | - Ryan C Riddle
- Department of Orthopaedic Surgery, Johns Hopkins University School of MedicineBaltimoreUnited States
- Department of Orthopaedics, University of Maryland School of MedicineBaltimoreUnited States
- Research and Development Service, Baltimore Veterans Administration Medical CenterBaltimoreUnited States
| | - G William Wong
- Department of Physiology, Johns Hopkins University School of MedicineBaltimoreUnited States
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8
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Shrestha AMS, Gonzales MEM, Ong PCL, Larmande P, Lee HS, Jeung JU, Kohli A, Chebotarov D, Mauleon RP, Lee JS, McNally KL. RicePilaf: a post-GWAS/QTL dashboard to integrate pangenomic, coexpression, regulatory, epigenomic, ontology, pathway, and text-mining information to provide functional insights into rice QTLs and GWAS loci. Gigascience 2024; 13:giae013. [PMID: 38832465 PMCID: PMC11148593 DOI: 10.1093/gigascience/giae013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 02/21/2024] [Accepted: 03/12/2024] [Indexed: 06/05/2024] Open
Abstract
BACKGROUND As the number of genome-wide association study (GWAS) and quantitative trait locus (QTL) mappings in rice continues to grow, so does the already long list of genomic loci associated with important agronomic traits. Typically, loci implicated by GWAS/QTL analysis contain tens to hundreds to thousands of single-nucleotide polmorphisms (SNPs)/genes, not all of which are causal and many of which are in noncoding regions. Unraveling the biological mechanisms that tie the GWAS regions and QTLs to the trait of interest is challenging, especially since it requires collating functional genomics information about the loci from multiple, disparate data sources. RESULTS We present RicePilaf, a web app for post-GWAS/QTL analysis, that performs a slew of novel bioinformatics analyses to cross-reference GWAS results and QTL mappings with a host of publicly available rice databases. In particular, it integrates (i) pangenomic information from high-quality genome builds of multiple rice varieties, (ii) coexpression information from genome-scale coexpression networks, (iii) ontology and pathway information, (iv) regulatory information from rice transcription factor databases, (v) epigenomic information from multiple high-throughput epigenetic experiments, and (vi) text-mining information extracted from scientific abstracts linking genes and traits. We demonstrate the utility of RicePilaf by applying it to analyze GWAS peaks of preharvest sprouting and genes underlying yield-under-drought QTLs. CONCLUSIONS RicePilaf enables rice scientists and breeders to shed functional light on their GWAS regions and QTLs, and it provides them with a means to prioritize SNPs/genes for further experiments. The source code, a Docker image, and a demo version of RicePilaf are publicly available at https://github.com/bioinfodlsu/rice-pilaf.
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Affiliation(s)
- Anish M S Shrestha
- Bioinformatics Lab, Advanced Research Institute for Informatics, Computing and Networking, College of Computer Studies, De La Salle University, Manila 1004, Philippines
- International Rice Research Institute (IRRI), Metro Manila 1301, Philippines
| | - Mark Edward M Gonzales
- Bioinformatics Lab, Advanced Research Institute for Informatics, Computing and Networking, College of Computer Studies, De La Salle University, Manila 1004, Philippines
| | - Phoebe Clare L Ong
- Bioinformatics Lab, Advanced Research Institute for Informatics, Computing and Networking, College of Computer Studies, De La Salle University, Manila 1004, Philippines
| | - Pierre Larmande
- DIADE, Univ Montpellier, Cirad, IRD, 34394 Montpellier, France
| | - Hyun-Sook Lee
- National Institute of Crop Science, Wanju-gun 55365, Republic of Korea
| | - Ji-Ung Jeung
- National Institute of Crop Science, Wanju-gun 55365, Republic of Korea
| | - Ajay Kohli
- International Rice Research Institute (IRRI), Metro Manila 1301, Philippines
| | - Dmytro Chebotarov
- International Rice Research Institute (IRRI), Metro Manila 1301, Philippines
| | - Ramil P Mauleon
- International Rice Research Institute (IRRI), Metro Manila 1301, Philippines
| | - Jae-Sung Lee
- International Rice Research Institute (IRRI), Metro Manila 1301, Philippines
| | - Kenneth L McNally
- International Rice Research Institute (IRRI), Metro Manila 1301, Philippines
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9
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Martins FB, Aono AH, Moraes ADCL, Ferreira RCU, Vilela MDM, Pessoa-Filho M, Rodrigues-Motta M, Simeão RM, de Souza AP. Genome-wide family prediction unveils molecular mechanisms underlying the regulation of agronomic traits in Urochloa ruziziensis. FRONTIERS IN PLANT SCIENCE 2023; 14:1303417. [PMID: 38148869 PMCID: PMC10749977 DOI: 10.3389/fpls.2023.1303417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 11/15/2023] [Indexed: 12/28/2023]
Abstract
Tropical forage grasses, particularly those belonging to the Urochloa genus, play a crucial role in cattle production and serve as the main food source for animals in tropical and subtropical regions. The majority of these species are apomictic and tetraploid, highlighting the significance of U. ruziziensis, a sexual diploid species that can be tetraploidized for use in interspecific crosses with apomictic species. As a means to support breeding programs, our study investigates the feasibility of genome-wide family prediction in U. ruziziensis families to predict agronomic traits. Fifty half-sibling families were assessed for green matter yield, dry matter yield, regrowth capacity, leaf dry matter, and stem dry matter across different clippings established in contrasting seasons with varying available water capacity. Genotyping was performed using a genotyping-by-sequencing approach based on DNA samples from family pools. In addition to conventional genomic prediction methods, machine learning and feature selection algorithms were employed to reduce the necessary number of markers for prediction and enhance predictive accuracy across phenotypes. To explore the regulation of agronomic traits, our study evaluated the significance of selected markers for prediction using a tree-based approach, potentially linking these regions to quantitative trait loci (QTLs). In a multiomic approach, genes from the species transcriptome were mapped and correlated to those markers. A gene coexpression network was modeled with gene expression estimates from a diverse set of U. ruziziensis genotypes, enabling a comprehensive investigation of molecular mechanisms associated with these regions. The heritabilities of the evaluated traits ranged from 0.44 to 0.92. A total of 28,106 filtered SNPs were used to predict phenotypic measurements, achieving a mean predictive ability of 0.762. By employing feature selection techniques, we could reduce the dimensionality of SNP datasets, revealing potential genotype-phenotype associations. The functional annotation of genes near these markers revealed associations with auxin transport and biosynthesis of lignin, flavonol, and folic acid. Further exploration with the gene coexpression network uncovered associations with DNA metabolism, stress response, and circadian rhythm. These genes and regions represent important targets for expanding our understanding of the metabolic regulation of agronomic traits and offer valuable insights applicable to species breeding. Our work represents an innovative contribution to molecular breeding techniques for tropical forages, presenting a viable marker-assisted breeding approach and identifying target regions for future molecular studies on these agronomic traits.
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Affiliation(s)
- Felipe Bitencourt Martins
- Center for Molecular Biology and Genetic Engineering (CBMEG), University of Campinas (UNICAMP), Campinas, São Paulo, Brazil
| | - Alexandre Hild Aono
- Center for Molecular Biology and Genetic Engineering (CBMEG), University of Campinas (UNICAMP), Campinas, São Paulo, Brazil
| | - Aline da Costa Lima Moraes
- Department of Plant Biology, Biology Institute, University of Campinas (UNICAMP), Campinas, São Paulo, Brazil
| | | | | | - Marco Pessoa-Filho
- Embrapa Cerrados, Brazilian Agricultural Research Corporation, Brasília, Brazil
| | | | - Rosangela Maria Simeão
- Embrapa Gado de Corte, Brazilian Agricultural Research Corporation, Campo Grande, Mato Grosso, Brazil
| | - Anete Pereira de Souza
- Center for Molecular Biology and Genetic Engineering (CBMEG), University of Campinas (UNICAMP), Campinas, São Paulo, Brazil
- Department of Plant Biology, Biology Institute, University of Campinas (UNICAMP), Campinas, São Paulo, Brazil
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10
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Kaya S, Alliston T, Evans DS. Genetic and Gene Expression Resources for Osteoporosis and Bone Biology Research. Curr Osteoporos Rep 2023; 21:637-649. [PMID: 37831357 PMCID: PMC11098148 DOI: 10.1007/s11914-023-00821-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/11/2023] [Indexed: 10/14/2023]
Abstract
PURPOSE OF REVIEW The integration of data from multiple genomic assays from humans and non-human model organisms is an effective approach to identify genes involved in skeletal fragility and fracture risk due to osteoporosis and other conditions. This review summarizes genome-wide genetic variation and gene expression data resources relevant to the discovery of genes contributing to skeletal fragility and fracture risk. RECENT FINDINGS Genome-wide association studies (GWAS) of osteoporosis-related traits are summarized, in addition to gene expression in bone tissues in humans and non-human organisms, with a focus on rodent models related to skeletal fragility and fracture risk. Gene discovery approaches using these genomic data resources are described. We also describe the Musculoskeletal Knowledge Portal (MSKKP) that integrates much of the available genomic data relevant to fracture risk. The available genomic resources provide a wealth of knowledge and can be analyzed to identify genes related to fracture risk. Genomic resources that would fill particular scientific gaps are discussed.
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Affiliation(s)
- Serra Kaya
- Department of Orthopedic Surgery, University of California, San Francisco, CA, USA
| | - Tamara Alliston
- Department of Orthopedic Surgery, University of California, San Francisco, CA, USA
| | - Daniel S Evans
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA.
- California Pacific Medical Center Research Institute, San Francisco, CA, USA.
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11
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Allayee H, Farber CR, Seldin MM, Williams EG, James DE, Lusis AJ. Systems genetics approaches for understanding complex traits with relevance for human disease. eLife 2023; 12:e91004. [PMID: 37962168 PMCID: PMC10645424 DOI: 10.7554/elife.91004] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 10/16/2023] [Indexed: 11/15/2023] Open
Abstract
Quantitative traits are often complex because of the contribution of many loci, with further complexity added by environmental factors. In medical research, systems genetics is a powerful approach for the study of complex traits, as it integrates intermediate phenotypes, such as RNA, protein, and metabolite levels, to understand molecular and physiological phenotypes linking discrete DNA sequence variation to complex clinical and physiological traits. The primary purpose of this review is to describe some of the resources and tools of systems genetics in humans and rodent models, so that researchers in many areas of biology and medicine can make use of the data.
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Affiliation(s)
- Hooman Allayee
- Departments of Population & Public Health Sciences, University of Southern CaliforniaLos AngelesUnited States
- Biochemistry & Molecular Medicine, Keck School of Medicine, University of Southern CaliforniaLos AngelesUnited States
| | - Charles R Farber
- Center for Public Health Genomics, University of Virginia School of MedicineCharlottesvilleUnited States
- Departments of Biochemistry & Molecular Genetics, University of Virginia School of MedicineCharlottesvilleUnited States
- Public Health Sciences, University of Virginia School of MedicineCharlottesvilleUnited States
| | - Marcus M Seldin
- Department of Biological Chemistry, University of California, IrvineIrvineUnited States
| | - Evan Graehl Williams
- Luxembourg Centre for Systems Biomedicine, University of LuxembourgLuxembourgLuxembourg
| | - David E James
- School of Life and Environmental Sciences, University of SydneyCamperdownAustralia
- Faculty of Medicine and Health, University of SydneyCamperdownAustralia
- Charles Perkins Centre, University of SydneyCamperdownAustralia
| | - Aldons J Lusis
- Departments of Human Genetics, University of California, Los AngelesLos AngelesUnited States
- Medicine, University of California, Los AngelesLos AngelesUnited States
- Microbiology, Immunology, & Molecular Genetics, David Geffen School of Medicine of UCLALos AngelesUnited States
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12
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Sarver DC, Garcia-Diaz J, Saqib M, Riddle RC, Wong GW. Tmem263 deletion disrupts the GH/IGF-1 axis and causes dwarfism and impairs skeletal acquisition. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.02.551694. [PMID: 37577461 PMCID: PMC10418210 DOI: 10.1101/2023.08.02.551694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Genome-wide association studies (GWAS) have identified a large number of candidate genes believed to affect longitudinal bone growth and bone mass. One of these candidate genes, TMEM263, encodes a poorly characterized plasma membrane protein. Single nucleotide polymorphisms in TMEM263 are associated with bone mineral density in humans and mutations are associated with dwarfism in chicken and severe skeletal dysplasia in at least one human fetus. Whether this genotype-phenotype relationship is causal, however, remains unclear. Here, we determine whether and how TMEM263 is required for postnatal growth. Deletion of the Tmem263 gene in mice causes severe postnatal growth failure, proportional dwarfism, and impaired skeletal acquisition. Mice lacking Tmem263 show no differences in body weight within the first two weeks of postnatal life. However, by P21 there is a dramatic growth deficit due to a disrupted GH/IGF-1 axis, which is critical for longitudinal bone growth. Tmem263-null mice have low circulating IGF-1 levels and pronounced reductions in bone mass and growth plate length. The low serum IGF-1 in Tmem263-null mice is associated with reduced hepatic GH receptor (GHR) expression and GH-induced JAK2/STAT5 signaling. A deficit in GH signaling dramatically alters GH-regulated genes and feminizes the liver transcriptome of Tmem263-null male mice, with their expression profile resembling a wild-type female, hypophysectomized male, and Stat5b-null male mice. Collectively, our data validates the causal role for Tmem263 in regulating postnatal growth and raises the possibility that rare mutations or variants of TMEM263 may potentially cause GH insensitivity and impair linear growth.
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Affiliation(s)
- Dylan C Sarver
- Department of Physiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Jean Garcia-Diaz
- Department of Orthopaedic Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Department of Orthopaedics, University of Maryland School of Medicine, Baltimore, Maryland, USA
- Cell and Molecular Medicine graduate program, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Muzna Saqib
- Department of Physiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Ryan C Riddle
- Department of Orthopaedic Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Department of Orthopaedics, University of Maryland School of Medicine, Baltimore, Maryland, USA
- Research and Development Service, Baltimore Veterans Administration Medical Center, Baltimore, Maryland, USA
| | - G William Wong
- Department of Physiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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Dillard LJ, Rosenow WT, Calabrese GM, Mesner LD, Al-Barghouthi BM, Abood A, Farber EA, Onengut-Gumuscu S, Tommasini SM, Horowitz MA, Rosen CJ, Yao L, Qin L, Farber CR. Single-Cell Transcriptomics of Bone Marrow Stromal Cells in Diversity Outbred Mice: A Model for Population-Level scRNA-Seq Studies. J Bone Miner Res 2023; 38:1350-1363. [PMID: 37436066 PMCID: PMC10528806 DOI: 10.1002/jbmr.4882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 06/30/2023] [Accepted: 07/06/2023] [Indexed: 07/13/2023]
Abstract
Genome-wide association studies (GWASs) have advanced our understanding of the genetics of osteoporosis; however, the challenge has been converting associations to causal genes. Studies have utilized transcriptomics data to link disease-associated variants to genes, but few population transcriptomics data sets have been generated on bone at the single-cell level. To address this challenge, we profiled the transcriptomes of bone marrow-derived stromal cells (BMSCs) cultured under osteogenic conditions from five diversity outbred (DO) mice using single-cell RNA-seq (scRNA-seq). The goal of the study was to determine if BMSCs could serve as a model to generate cell type-specific transcriptomic profiles of mesenchymal lineage cells from large populations of mice to inform genetic studies. By enriching for mesenchymal lineage cells in vitro, coupled with pooling of multiple samples and downstream genotype deconvolution, we demonstrate the scalability of this model for population-level studies. We demonstrate that dissociation of BMSCs from a heavily mineralized matrix had little effect on viability or their transcriptomic signatures. Furthermore, we show that BMSCs cultured under osteogenic conditions are diverse and consist of cells with characteristics of mesenchymal progenitors, marrow adipogenic lineage precursors (MALPs), osteoblasts, osteocyte-like cells, and immune cells. Importantly, all cells were similar from a transcriptomic perspective to cells isolated in vivo. We employed scRNA-seq analytical tools to confirm the biological identity of profiled cell types. SCENIC was used to reconstruct gene regulatory networks (GRNs), and we observed that cell types show GRNs expected of osteogenic and pre-adipogenic lineage cells. Further, CELLECT analysis showed that osteoblasts, osteocyte-like cells, and MALPs captured a significant component of bone mineral density (BMD) heritability. Together, these data suggest that BMSCs cultured under osteogenic conditions coupled with scRNA-seq can be used as a scalable and biologically informative model to generate cell type-specific transcriptomic profiles of mesenchymal lineage cells in large populations. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).
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Affiliation(s)
- Luke J Dillard
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Will T Rosenow
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Gina M Calabrese
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Larry D Mesner
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Basel M Al-Barghouthi
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, USA
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Abdullah Abood
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, USA
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Emily A Farber
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Steven M Tommasini
- Department of Orthopaedics and Rehabilitation, Yale School of Medicine, New Haven, CT, USA
| | - Mark A Horowitz
- Department of Orthopaedics and Rehabilitation, Yale School of Medicine, New Haven, CT, USA
| | | | - Lutian Yao
- Department of Orthopaedic Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ling Qin
- Department of Orthopaedic Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Charles R Farber
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA, USA
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA, USA
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14
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Malavašič P, Polajžer S, Lovšin N. Anaphase-Promoting Complex Subunit 1 Associates with Bone Mineral Density in Human Osteoporotic Bone. Int J Mol Sci 2023; 24:12895. [PMID: 37629076 PMCID: PMC10454667 DOI: 10.3390/ijms241612895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 08/10/2023] [Accepted: 08/14/2023] [Indexed: 08/27/2023] Open
Abstract
Genome-wide association studies (GWAS) are one of the most common approaches to identify genetic loci that are associated with bone mineral density (BMD). Such novel genetic loci represent new potential targets for the prevention and treatment of fragility fractures. GWAS have identified hundreds of associations with BMD; however, only a few have been functionally evaluated. A locus significantly associated with femoral neck BMD at the genome-wide level is intronic SNP rs17040773 located in the intronic region of the anaphase-promoting complex subunit 1 (ANAPC1) gene (p = 1.5 × 10-9). Here, we functionally evaluate the role of ANAPC1 in bone remodelling by examining the expression of ANAPC1 in human bone and muscle tissues and during the osteogenic differentiation of human primary mesenchymal stem cells (MSCs). The expression of ANAPC1 was significantly decreased 2.3-fold in bone tissues and 6.2-fold in muscle tissue from osteoporotic patients as compared to the osteoarthritic and control tissues. Next, we show that the expression of ANAPC1 changes during the osteogenic differentiation process of human MSCs. Moreover, the silencing of ANAPC1 in human osteosarcoma (HOS) cells reduced RUNX2 expression, suggesting that ANAPC1 affects osteogenic differentiation through RUNX2. Altogether, our results indicate that ANAPC1 plays a role in bone physiology and in the development of osteoporosis.
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Affiliation(s)
- Petra Malavašič
- General Hospital Novo Mesto, Šmihelska Cesta 1, 8000 Novo Mesto, Slovenia;
| | - Sara Polajžer
- Faculty of Pharmacy, University of Ljubljana, Aškerčeva Cesta 7, 1000 Ljubljana, Slovenia
| | - Nika Lovšin
- Faculty of Pharmacy, University of Ljubljana, Aškerčeva Cesta 7, 1000 Ljubljana, Slovenia
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15
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Kaspersky U, Levy R, Nashef A, Iraqi FA, Gabet Y. A study of the influence of genetic variance and sex on the density and thickness of the calvarial bone in collaborative cross mice. Animal Model Exp Med 2023; 6:355-361. [PMID: 37448168 PMCID: PMC10486330 DOI: 10.1002/ame2.12319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 03/13/2023] [Indexed: 07/15/2023] Open
Abstract
BACKGROUND Bone microarchitecture is affected by multiple genes, each having a small effect on the external appearance. It is thus challenging to characterize the genes and their specific effect on bone thickness and porosity. The purpose of this study was to assess the heritability and the genetic variation effect, as well as the sex effect on the calvarial bone thickness (Ca.Th) and calvarial porosity (%PoV) using the Collaborative Cross (CC) mouse population. METHODS In the study we examined the parietal bones of 56 mice from 9 lines of CC mice. Morphometric parameters were evaluated using microcomputed tomography (μCT) and included Ca.Th and %PoV. We then evaluated heritability, genetic versus environmental variance and the sex effect for these parameters. RESULTS Our morphometric analysis showed that Ca.Th and %PoV are both significantly different among the CC lines with a broad sense heritability of 0.78 and 0.90, respectively. The sex effect within the lines was significant in line IL111 and showed higher values of Ca.Th and %PoV in females compared to males. In line IL19 there was a borderline sex effect in Ca.Th in which males showed higher values than females. CONCLUSIONS These results stress the complexity of sex and genotype interactions controlling Ca.Th and %PoV, as the skeletal sexual dimorphism was dependent on the genetic background. This study also shows that the CC population is a powerful tool for establishing the genetic effect on these traits.
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Affiliation(s)
- Uriel Kaspersky
- Department of Anatomy and AnthropologyTel Aviv UniversityTel AvivIsrael
| | - Roei Levy
- Department of Anatomy and AnthropologyTel Aviv UniversityTel AvivIsrael
| | - Aysar Nashef
- Department of Clinical Microbiology and Immunology, Sackler Faculty of MedicineTel Aviv UniversityTel Aviv69978Israel
- Department of Oral and Maxillofacial SurgeryBaruch Padeh medical centerPoriyaIsrael
| | - Fuad A. Iraqi
- Department of Clinical Microbiology and Immunology, Sackler Faculty of MedicineTel Aviv UniversityTel Aviv69978Israel
| | - Yankel Gabet
- Department of Anatomy and AnthropologyTel Aviv UniversityTel AvivIsrael
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16
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Adhikari M, Kantar MB, Longman RJ, Lee CN, Oshiro M, Caires K, He Y. Genome-wide association study for carcass weight in pasture-finished beef cattle in Hawai'i. Front Genet 2023; 14:1168150. [PMID: 37229195 PMCID: PMC10203587 DOI: 10.3389/fgene.2023.1168150] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 04/11/2023] [Indexed: 05/27/2023] Open
Abstract
Introduction: Genome-wide association studies (GWAS) have identified genetic markers for cattle production and reproduction traits. Several publications have reported Single Nucleotide Polymorphisms (SNPs) for carcass-related traits in cattle, but these studies were rarely conducted in pasture-finished beef cattle. Hawai'i, however, has a diverse climate, and 100% of its beef cattle are pasture-fed. Methods: Blood samples were collected from 400 cattle raised in Hawai'i islands at the commercial harvest facility. Genomic DNA was isolated, and 352 high-quality samples were genotyped using the Neogen GGP Bovine 100 K BeadChip. SNPs that did not meet the quality control standards were removed using PLINK 1.9, and 85 k high-quality SNPs from 351 cattle were used for association mapping with carcass weight using GAPIT (Version 3.0) in R 4.2. Four models were used for the GWAS analysis: General Linear Model (GLM), the Mixed Linear Model (MLM), the Fixed and Random Model Circulating Probability Unification (FarmCPU), the Bayesian-Information and Linkage-Disequilibrium Iteratively Nested Keyway (BLINK). Results and Discussion: Our results indicated that the two multi-locus models, FarmCPU and BLINK, outperformed single-locus models, GLM and MLM, in beef herds in this study. Specifically, five significant SNPs were identified using FarmCPU, while BLINK and GLM each identified the other three. Also, three of these eleven SNPs ("BTA-40510-no-rs", "BovineHD1400006853", and "BovineHD2100020346") were shared by multiple models. The significant SNPs were mapped to genes such as EIF5, RGS20, TCEA1, LYPLA1, and MRPL15, which were previously reported to be associated with carcass-related traits, growth, and feed intake in several tropical cattle breeds. This confirms that the genes identified in this study could be candidate genes for carcass weight in pasture-fed beef cattle and can be selected for further breeding programs to improve the carcass yield and productivity of pasture-finished beef cattle in Hawai'i and beyond.
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Affiliation(s)
- Mandeep Adhikari
- Department of Molecular Biosciences and Bioengineering, University of Hawai’i at Mānoa, Honolulu, HI, United States
| | - Michael B. Kantar
- Department of Tropical Plant and Soil Sciences, University of Hawai’i at Mānoa, Honolulu, HI, United States
| | - Ryan J. Longman
- East West Center, Honolulu, HI, United States
- Department of Geography and Environment, University of Hawai’i at Mānoa, Honolulu, HI, United States
| | - C. N. Lee
- Department of Human Nutrition, Food, and Animal Sciences, University of Hawai’i at Mānoa, Honolulu, HI, United States
| | - Melelani Oshiro
- Department of Human Nutrition, Food, and Animal Sciences, University of Hawai’i at Mānoa, Honolulu, HI, United States
| | - Kyle Caires
- Department of Human Nutrition, Food, and Animal Sciences, University of Hawai’i at Mānoa, Honolulu, HI, United States
| | - Yanghua He
- Department of Molecular Biosciences and Bioengineering, University of Hawai’i at Mānoa, Honolulu, HI, United States
- Department of Human Nutrition, Food, and Animal Sciences, University of Hawai’i at Mānoa, Honolulu, HI, United States
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Huang Y, Luo J, Zhang Y, Zhang T, Fei X, Chen L, Zhu Y, Li S, Zhou C, Xu K, Ma Y, Lin J, Zhou J. Identification of MKNK1 and TOP3A as ovarian endometriosis risk-associated genes using integrative genomic analyses and functional experiments. Comput Struct Biotechnol J 2023; 21:1510-1522. [PMID: 36851918 PMCID: PMC9957794 DOI: 10.1016/j.csbj.2023.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 01/11/2023] [Accepted: 02/01/2023] [Indexed: 02/07/2023] Open
Abstract
The risk of endometriosis (EM), which is a common complex gynaecological disease, is related to genetic predisposition. However, it is unclear how genetic variants confer the risk of EM. Here, via Sherlock integrative analysis, we combined large-scale genome-wide association studies (GWAS) summary statistics on EM (N = 245,494) with a blood-based eQTL dataset (N = 1490) to identify EM risk-related genes. For validation, we leveraged two independent eQTL datasets (N = 769) for integration with the GWAS data. Thus, we prioritised 14 genes, including GIMAP4, TOP3A, and NMNAT3, which showed significant association with susceptibility to EM. We also utilised two independent methods, Multi-marker Analysis of GenoMic Annotation and S-PrediXcan, to further validate the EM risk-associated genes. Moreover, protein-protein interaction network analysis showed the 14 genes were functionally connected. Functional enrichment analyses further demonstrated that these genes were significantly enriched in metabolic and immune-related pathways. Differential gene expression analysis showed that in peripheral blood samples from patients with ovarian EM, TOP3A, MKNK1, SIPA1L2, and NUCB1 were significantly upregulated, while HOXB2, GIMAP5, and MGMT were significantly downregulated compared with their expression levels in samples from the controls. Immunohistochemistry further confirmed the increased expression levels of MKNK1 and TOP3A in the ectopic and eutopic endometrium compared to normal endometrium, while HOBX2 was downregulated in the endometrium of women with ovarian EM. Finally, in ex vivo functional experiments, MKNK1 knockdown inhibited ectopic endometrial stromal cells (EESCs) migration and invasion. TOP3A knockdown inhibited EESCs proliferation, migration, and invasion, while promoting their apoptosis. Convergent lines of evidence suggested that MKNK1 and TOP3A are novel EM risk-related genes.
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Affiliation(s)
- Yizhou Huang
- Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Jie Luo
- Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Yue Zhang
- Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Tao Zhang
- Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Xiangwei Fei
- Key Laboratory of Women's Reproductive Health of Zhejiang Province, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Liqing Chen
- Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Yingfan Zhu
- Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Songyue Li
- Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Caiyun Zhou
- Department of Pathology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Kaihong Xu
- Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Yunlong Ma
- Institute of Biomedical Big Data, School of Ophthalmology & Optometry and Eye Hospital, School of Biomedical Engineering, Wenzhou Medical University 325027 Wenzhou, Zhejiang Province, PR China
| | - Jun Lin
- Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Jianhong Zhou
- Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
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18
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Yang J, Niu H, Pang S, Liu M, Chen F, Li Z, He L, Mo J, Yi H, Xiao J, Huang Y. MARK3 kinase: Regulation and physiologic roles. Cell Signal 2023; 103:110578. [PMID: 36581219 DOI: 10.1016/j.cellsig.2022.110578] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 12/14/2022] [Accepted: 12/20/2022] [Indexed: 12/27/2022]
Abstract
Microtubule affinity-regulating kinase 3 (MARK3), a member of the MARK family, regulates several essential pathways, including the cell cycle, ciliated cell differentiation, and osteoclast differentiation. It is important to understand the control of their activities as MARK3 contains an N-terminal serine/threonine kinase domain, ubiquitin-associated domain, and C-terminal kinase-associated domain, which perform multiple regulatory functions. These functions include post-translational modification (e.g., phosphorylation) and interaction with scaffolding and other proteins. Differences in the amino acid sequence and domain position result in different three-dimensional protein structures and affect the function of MARK3, which distinguish it from the other MARK family members. Recent data indicate a potential role of MARK3 in several pathological conditions, including congenital blepharophimosis syndrome, osteoporosis, and tumorigenesis. The present review focuses on the physiological and pathological role of MARK3, its regulation, and recent developments in the small molecule inhibitors of the MARK3 signalling cascade.
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Affiliation(s)
- Jingyu Yang
- Surgery of Mammary Gland and Thyroid Gland, the First People's Hospital of Yunnan Province, Panlong Campus, 157 Jinbi Road, Kunming 650032, Yunnan, People's Republic of China
| | - Heng Niu
- Surgery of Mammary Gland and Thyroid Gland, the First People's Hospital of Yunnan Province, Panlong Campus, 157 Jinbi Road, Kunming 650032, Yunnan, People's Republic of China
| | - ShiGui Pang
- Cancer Research Institute, The Affiliated Hospital of Guilin Medical University, Xiufeng Campus, 15 Lequn Road, Guilin 541001, Guangxi, People's Republic of China
| | - Mignlong Liu
- Cancer Research Institute, The Affiliated Hospital of Guilin Medical University, Xiufeng Campus, 15 Lequn Road, Guilin 541001, Guangxi, People's Republic of China
| | - Feng Chen
- Cancer Research Institute, The Affiliated Hospital of Guilin Medical University, Xiufeng Campus, 15 Lequn Road, Guilin 541001, Guangxi, People's Republic of China
| | - Zhaoxin Li
- Cancer Research Institute, The Affiliated Hospital of Guilin Medical University, Xiufeng Campus, 15 Lequn Road, Guilin 541001, Guangxi, People's Republic of China
| | - Lifei He
- Cancer Research Institute, The Affiliated Hospital of Guilin Medical University, Xiufeng Campus, 15 Lequn Road, Guilin 541001, Guangxi, People's Republic of China
| | - Jianmei Mo
- Cancer Research Institute, The Affiliated Hospital of Guilin Medical University, Xiufeng Campus, 15 Lequn Road, Guilin 541001, Guangxi, People's Republic of China
| | - Huijun Yi
- Cancer Research Institute, The Affiliated Hospital of Guilin Medical University, Xiufeng Campus, 15 Lequn Road, Guilin 541001, Guangxi, People's Republic of China
| | - Juanjuan Xiao
- Cancer Research Institute, The Affiliated Hospital of Guilin Medical University, Xiufeng Campus, 15 Lequn Road, Guilin 541001, Guangxi, People's Republic of China
| | - Yingze Huang
- Cancer Research Institute, The Affiliated Hospital of Guilin Medical University, Xiufeng Campus, 15 Lequn Road, Guilin 541001, Guangxi, People's Republic of China.
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19
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Barrio-Hernandez I, Beltrao P. Network analysis of genome-wide association studies for drug target prioritisation. Curr Opin Chem Biol 2022; 71:102206. [PMID: 36087372 DOI: 10.1016/j.cbpa.2022.102206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 07/29/2022] [Accepted: 08/05/2022] [Indexed: 01/27/2023]
Abstract
Over the past decades, genome-wide association studies (GWAS) have led to a dramatic expansion of genetic variants implicated with human traits and diseases. These advances are expected to result in new drug targets but the identification of causal genes and the cell biology underlying human diseases from GWAS remains challenging. Here, we review protein interaction network-based methods to analyse GWAS data. These approaches can rank candidate drug targets at GWAS-associated loci or among interactors of disease genes without direct genetic support. These methods identify the cell biology affected in common across diseases, offering opportunities for drug repurposing, as well as be combined with expression data to identify focal tissues and cell types. Going forward, we expect that these methods will further improve from advances in the characterisation of context specific interaction networks and the joint analysis of rare and common genetic signals.
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Affiliation(s)
- Inigo Barrio-Hernandez
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge, CB10 1SD, UK; Open Targets, Wellcome Genome Campus, Cambridge, CB10 1SA, UK.
| | - Pedro Beltrao
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge, CB10 1SD, UK; Open Targets, Wellcome Genome Campus, Cambridge, CB10 1SA, UK; Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, 8093, Switzerland.
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20
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Targeted Resequencing of Otosclerosis Patients from Different Populations Replicates Results from a Previous Genome-Wide Association Study. J Clin Med 2022; 11:jcm11236978. [PMID: 36498562 PMCID: PMC9737413 DOI: 10.3390/jcm11236978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 11/17/2022] [Accepted: 11/22/2022] [Indexed: 11/29/2022] Open
Abstract
Otosclerosis is one of the most common causes of hearing loss in young adults. It has a prevalence of 0.3-0.4% in the European population. Clinical symptoms usually occur between the second and fifth decade of life. Different studies have been performed to unravel the genetic architecture of the disease. Recently, a genome-wide association study (GWAS) identified 15 novel risk loci and replicated the regions of three previously reported candidate genes. In this study, seven candidate genes from the GWAS were resequenced using single molecule molecular inversion probes (smMIPs). smMIPs were used to capture the exonic regions and the 3' and 5' untranslated regions (UTR). Discovered variants were tested for association with the disease using single variant and gene-based association analysis. The single variant results showed that 13 significant variants were associated with otosclerosis. Associated variants were found in five of the seven genes studied here, including AHSG, LINC01482, MARK3, SUPT3H and RELN. Conversely, burden testing did not show a major role of rare variants in the disease. In conclusion, this study was able to replicate five out of seven candidate genes reported in the previous GWAS. This association is likely mainly driven by common variants.
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21
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Xu J, Zhang S, Si H, Zeng Y, Wu Y, Liu Y, Li M, Wu L, Shen B. A genetic correlation scan identifies blood proteins associated with bone mineral density. BMC Musculoskelet Disord 2022; 23:530. [PMID: 35659283 PMCID: PMC9164489 DOI: 10.1186/s12891-022-05453-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 05/17/2022] [Indexed: 11/10/2022] Open
Abstract
Background Osteoporosis is a common metabolic bone disease that is characterized by low bone mass. However, limited efforts have been made to explore the functional relevance of the blood proteome to bone mineral density across different life stages. Methods Using genome-wide association study summary data of the blood proteome and two independent studies of bone mineral density, we conducted a genetic correlation scan of bone mineral density and the blood proteome. Linkage disequilibrium score regression analysis was conducted to assess genetic correlations between each of the 3283 plasma proteins and bone mineral density. Results Linkage disequilibrium score regression identified 18 plasma proteins showing genetic correlation signals with bone mineral density in the TB-BMD cohort, such as MYOM2 (coefficient = 0.3755, P value = 0.0328) among subjects aged 0 ~ 15, POSTN (coefficient = − 0.5694, P value = 0.0192) among subjects aged 30 ~ 45 and PARK7 (coefficient = − 0.3613, P value = 0.0052) among subjects aged over 60. Conclusions Our results identified multiple plasma proteins associated with bone mineral density and provided novel clues for revealing the functional relevance of plasma proteins to bone mineral density. Supplementary Information The online version contains supplementary material available at 10.1186/s12891-022-05453-z.
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22
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Al-Barghouthi BM, Rosenow WT, Du KP, Heo J, Maynard R, Mesner L, Calabrese G, Nakasone A, Senwar B, Gerstenfeld L, Larner J, Ferguson V, Ackert-Bicknell C, Morgan E, Brautigan D, Farber CR. Transcriptome-wide association study and eQTL colocalization identify potentially causal genes responsible for human bone mineral density GWAS associations. eLife 2022; 11:77285. [PMID: 36416764 PMCID: PMC9683789 DOI: 10.7554/elife.77285] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 11/16/2022] [Indexed: 11/24/2022] Open
Abstract
Genome-wide association studies (GWASs) for bone mineral density (BMD) in humans have identified over 1100 associations to date. However, identifying causal genes implicated by such studies has been challenging. Recent advances in the development of transcriptome reference datasets and computational approaches such as transcriptome-wide association studies (TWASs) and expression quantitative trait loci (eQTL) colocalization have proven to be informative in identifying putatively causal genes underlying GWAS associations. Here, we used TWAS/eQTL colocalization in conjunction with transcriptomic data from the Genotype-Tissue Expression (GTEx) project to identify potentially causal genes for the largest BMD GWAS performed to date. Using this approach, we identified 512 genes as significant using both TWAS and eQTL colocalization. This set of genes was enriched for regulators of BMD and members of bone relevant biological processes. To investigate the significance of our findings, we selected PPP6R3, the gene with the strongest support from our analysis which was not previously implicated in the regulation of BMD, for further investigation. We observed that Ppp6r3 deletion in mice decreased BMD. In this work, we provide an updated resource of putatively causal BMD genes and demonstrate that PPP6R3 is a putatively causal BMD GWAS gene. These data increase our understanding of the genetics of BMD and provide further evidence for the utility of combined TWAS/colocalization approaches in untangling the genetics of complex traits.
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Affiliation(s)
- Basel Maher Al-Barghouthi
- Center for Public Health Genomics, School of Medicine, University of VirginiaCharlottesvilleUnited States,Department of Biochemistry and Molecular Genetics, School of Medicine, University of VirginiaCharlottesvilleUnited States
| | - Will T Rosenow
- Center for Public Health Genomics, School of Medicine, University of VirginiaCharlottesvilleUnited States
| | - Kang-Ping Du
- Department of Radiation Oncology, University of VirginiaCharlottesvilleUnited States
| | - Jinho Heo
- Department of Microbiology, Immunology, and Cancer Biology, School of Medicine, University of VirginiaCharlottesvilleUnited States
| | - Robert Maynard
- Department of Orthopedics, Anschutz Medical Campus, University of ColoradoAuroraUnited States
| | - Larry Mesner
- Center for Public Health Genomics, School of Medicine, University of VirginiaCharlottesvilleUnited States,Department of Public Health Sciences, School of Medicine, University of VirginiaCharlottesvilleUnited States
| | - Gina Calabrese
- Center for Public Health Genomics, School of Medicine, University of VirginiaCharlottesvilleUnited States
| | - Aaron Nakasone
- Department of Mechanical Engineering, Boston UniversityBostonUnited States
| | - Bhavya Senwar
- Department of Mechanical Engineering, University of Colorado BoulderBoulderUnited States
| | - Louis Gerstenfeld
- Department of Orthopaedic Surgery, Boston University Medical CenterBostonUnited States
| | - James Larner
- Department of Radiation Oncology, University of VirginiaCharlottesvilleUnited States
| | - Virginia Ferguson
- Department of Mechanical Engineering, University of Colorado BoulderBoulderUnited States
| | - Cheryl Ackert-Bicknell
- Department of Orthopedics, Anschutz Medical Campus, University of ColoradoAuroraUnited States
| | - Elise Morgan
- Department of Mechanical Engineering, Boston UniversityBostonUnited States
| | - David Brautigan
- Department of Microbiology, Immunology, and Cancer Biology, School of Medicine, University of VirginiaCharlottesvilleUnited States
| | - Charles R Farber
- Center for Public Health Genomics, School of Medicine, University of VirginiaCharlottesvilleUnited States,Department of Biochemistry and Molecular Genetics, School of Medicine, University of VirginiaCharlottesvilleUnited States,Department of Public Health Sciences, School of Medicine, University of VirginiaCharlottesvilleUnited States
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23
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Francisco FR, Aono AH, da Silva CC, Gonçalves PS, Scaloppi Junior EJ, Le Guen V, Fritsche-Neto R, Souza LM, de Souza AP. Unravelling Rubber Tree Growth by Integrating GWAS and Biological Network-Based Approaches. FRONTIERS IN PLANT SCIENCE 2021; 12:768589. [PMID: 34992619 PMCID: PMC8724537 DOI: 10.3389/fpls.2021.768589] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 11/02/2021] [Indexed: 06/08/2023]
Abstract
Hevea brasiliensis (rubber tree) is a large tree species of the Euphorbiaceae family with inestimable economic importance. Rubber tree breeding programs currently aim to improve growth and production, and the use of early genotype selection technologies can accelerate such processes, mainly with the incorporation of genomic tools, such as marker-assisted selection (MAS). However, few quantitative trait loci (QTLs) have been used successfully in MAS for complex characteristics. Recent research shows the efficiency of genome-wide association studies (GWAS) for locating QTL regions in different populations. In this way, the integration of GWAS, RNA-sequencing (RNA-Seq) methodologies, coexpression networks and enzyme networks can provide a better understanding of the molecular relationships involved in the definition of the phenotypes of interest, supplying research support for the development of appropriate genomic based strategies for breeding. In this context, this work presents the potential of using combined multiomics to decipher the mechanisms of genotype and phenotype associations involved in the growth of rubber trees. Using GWAS from a genotyping-by-sequencing (GBS) Hevea population, we were able to identify molecular markers in QTL regions with a main effect on rubber tree plant growth under constant water stress. The underlying genes were evaluated and incorporated into a gene coexpression network modelled with an assembled RNA-Seq-based transcriptome of the species, where novel gene relationships were estimated and evaluated through in silico methodologies, including an estimated enzymatic network. From all these analyses, we were able to estimate not only the main genes involved in defining the phenotype but also the interactions between a core of genes related to rubber tree growth at the transcriptional and translational levels. This work was the first to integrate multiomics analysis into the in-depth investigation of rubber tree plant growth, producing useful data for future genetic studies in the species and enhancing the efficiency of the species improvement programs.
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Affiliation(s)
- Felipe Roberto Francisco
- Molecular Biology and Genetic Engineering Center (CBMEG), University of Campinas (UNICAMP), Campinas, Brazil
| | - Alexandre Hild Aono
- Molecular Biology and Genetic Engineering Center (CBMEG), University of Campinas (UNICAMP), Campinas, Brazil
| | - Carla Cristina da Silva
- Molecular Biology and Genetic Engineering Center (CBMEG), University of Campinas (UNICAMP), Campinas, Brazil
| | - Paulo S. Gonçalves
- Center of Rubber Tree and Agroforestry Systems, Agronomic Institute (IAC), Votuporanga, Brazil
| | | | - Vincent Le Guen
- Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), UMR AGAP, Montpellier, France
- AGAP, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France
| | - Roberto Fritsche-Neto
- Department of Genetics, Luiz de Queiroz College of Agriculture (ESALQ), University of São Paulo (USP), Piracicaba, Brazil
| | - Livia Moura Souza
- Molecular Biology and Genetic Engineering Center (CBMEG), University of Campinas (UNICAMP), Campinas, Brazil
- São Francisco University (USF), Itatiba, Brazil
| | - Anete Pereira de Souza
- Molecular Biology and Genetic Engineering Center (CBMEG), University of Campinas (UNICAMP), Campinas, Brazil
- Department of Plant Biology, Biology Institute, University of Campinas (UNICAMP), Campinas, Brazil
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24
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Somma T, DE Rosa A, Mastantuoni C, Esposito F, Meglio V, Romano F, Ricciardi L, DE Divitiis O, DI Somma C. Multidisciplinary management of osteoporotic vertebral fractures. An overview. Minerva Endocrinol (Torino) 2021; 47:189-202. [PMID: 34881854 DOI: 10.23736/s2724-6507.21.03515-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Vertebral fractures represent the most frequent complication associated with osteoporosis. Patients harboring a vertebral fracture complain physical impairment including low back pain and spine balance alteration, i.e., kyphosis, leading to subsequent systemic complication, with an increase in morbidity and mortality risk. Different strategies are available in the management of osteoporotic vertebral fractures: medical therapy acts as a prevention strategy while surgical vertebral augmentation procedures, when correctly indicated, aim to reduce pain and to restore the physiological vertebral height. Considering the growing prevalence and incidence of this condition and its socio-economic burden, prevention, diagnosis and treatment of osteoporotic vertebral fractures are of utmost importance. Our aim is to review the current strategies for the management of osteoporotic vertebral fractures providing an integrated multidisciplinary endocrinological, radiological and neurosurgical point of view.
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Affiliation(s)
- Teresa Somma
- Division of Neurosurgery, Department of Neurosciences, Reproductive and Odontostomatological Sciences, Università degli Studi di Napoli Federico II, Naples, Italy
| | - Andrea DE Rosa
- Division of Neurosurgery, Department of Neurosciences, Reproductive and Odontostomatological Sciences, Università degli Studi di Napoli Federico II, Naples, Italy -
| | - Ciro Mastantuoni
- Division of Neurosurgery, Department of Neurosciences, Reproductive and Odontostomatological Sciences, Università degli Studi di Napoli Federico II, Naples, Italy
| | - Felice Esposito
- Division of Neurosurgery, Department of Neurosciences, Reproductive and Odontostomatological Sciences, Università degli Studi di Napoli Federico II, Naples, Italy
| | - Vincenzo Meglio
- Division of Neurosurgery, Department of Neurosciences, Reproductive and Odontostomatological Sciences, Università degli Studi di Napoli Federico II, Naples, Italy
| | - Fiammetta Romano
- Unit of Endocrinology, Department of Clinical Medicine and Surgery, Federico II University Medical School, Naples, Italy
| | - Luca Ricciardi
- Neurosurgery, Department NESMOS, Sapienza University of Rome, Rome, Italy
| | - Oreste DE Divitiis
- Division of Neurosurgery, Department of Neurosciences, Reproductive and Odontostomatological Sciences, Università degli Studi di Napoli Federico II, Naples, Italy
| | - Carolina DI Somma
- Unit of Endocrinology, Department of Clinical Medicine and Surgery, Federico II University Medical School, Naples, Italy
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25
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Wu S, Chen D, Snyder MP. Network biology bridges the gaps between quantitative genetics and multi-omics to map complex diseases. Curr Opin Chem Biol 2021; 66:102101. [PMID: 34861483 DOI: 10.1016/j.cbpa.2021.102101] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 10/17/2021] [Accepted: 10/27/2021] [Indexed: 12/27/2022]
Abstract
With advances in high-throughput sequencing technologies, quantitative genetics approaches have provided insights into genetic basis of many complex diseases. Emerging in-depth multi-omics profiling technologies have created exciting opportunities for systematically investigating intricate interaction networks with different layers of biological molecules underlying disease etiology. Herein, we summarized two main categories of biological networks: evidence-based and statistically inferred. These different types of molecular networks complement each other at both bulk and single-cell levels. We also review three main strategies to incorporate quantitative genetics results with multi-omics data by network analysis: (a) network propagation, (b) functional module-based methods, (c) comparative/dynamic networks. These strategies not only aid in elucidating molecular mechanisms of complex diseases but can guide the search for therapeutic targets.
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Affiliation(s)
- Si Wu
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Dijun Chen
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, 210023, China
| | - Michael P Snyder
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
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26
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Brænne I, Onengut-Gumuscu S, Chen R, Manichaikul AW, Rich SS, Chen WM, Farber CR. Dynamic changes in immune gene co-expression networks predict development of type 1 diabetes. Sci Rep 2021; 11:22651. [PMID: 34811390 PMCID: PMC8609030 DOI: 10.1038/s41598-021-01840-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Accepted: 11/01/2021] [Indexed: 01/13/2023] Open
Abstract
Significant progress has been made in elucidating genetic risk factors influencing Type 1 diabetes (T1D); however, features other than genetic variants that initiate and/or accelerate islet autoimmunity that lead to the development of clinical T1D remain largely unknown. We hypothesized that genetic and environmental risk factors can both contribute to T1D through dynamic alterations of molecular interactions in physiologic networks. To test this hypothesis, we utilized longitudinal blood transcriptomic profiles in The Environmental Determinants of Diabetes in the Young (TEDDY) study to generate gene co-expression networks. In network modules that contain immune response genes associated with T1D, we observed highly dynamic differences in module connectivity in the 600 days (~ 2 years) preceding clinical diagnosis of T1D. Our results suggest that gene co-expression is highly plastic and that connectivity differences in T1D-associated immune system genes influence the timing and development of clinical disease.
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Affiliation(s)
- Ingrid Brænne
- Center for Public Health Genomics, University of Virginia, P.O. Box 800717, Charlottesville, VA, 22908, USA
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, University of Virginia, P.O. Box 800717, Charlottesville, VA, 22908, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, 22908, USA
| | - Ruoxi Chen
- Center for Public Health Genomics, University of Virginia, P.O. Box 800717, Charlottesville, VA, 22908, USA
| | - Ani W Manichaikul
- Center for Public Health Genomics, University of Virginia, P.O. Box 800717, Charlottesville, VA, 22908, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, 22908, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, P.O. Box 800717, Charlottesville, VA, 22908, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, 22908, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, 22908, USA
| | - Wei-Min Chen
- Center for Public Health Genomics, University of Virginia, P.O. Box 800717, Charlottesville, VA, 22908, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, 22908, USA
| | - Charles R Farber
- Center for Public Health Genomics, University of Virginia, P.O. Box 800717, Charlottesville, VA, 22908, USA.
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, 22908, USA.
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, 22908, USA.
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27
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Yang H, Arif M, Yuan M, Li X, Shong K, Türkez H, Nielsen J, Uhlén M, Borén J, Zhang C, Mardinoglu A. A network-based approach reveals the dysregulated transcriptional regulation in non-alcoholic fatty liver disease. iScience 2021; 24:103222. [PMID: 34712920 PMCID: PMC8529555 DOI: 10.1016/j.isci.2021.103222] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 09/16/2021] [Accepted: 09/30/2021] [Indexed: 12/22/2022] Open
Abstract
Non-alcoholic fatty liver disease (NAFLD) is a leading cause of chronic liver disease worldwide. We performed network analysis to investigate the dysregulated biological processes in the disease progression and revealed the molecular mechanism underlying NAFLD. Based on network analysis, we identified a highly conserved disease-associated gene module across three different NAFLD cohorts and highlighted the predominant role of key transcriptional regulators associated with lipid and cholesterol metabolism. In addition, we revealed the detailed metabolic differences between heterogeneous NAFLD patients through integrative systems analysis of transcriptomic data and liver-specific genome-scale metabolic model. Furthermore, we identified transcription factors (TFs), including SREBF2, HNF4A, SREBF1, YY1, and KLF13, showing regulation of hepatic expression of genes in the NAFLD-associated modules and validated the TFs using data generated from a mouse NAFLD model. In conclusion, our integrative analysis facilitates the understanding of the regulatory mechanism of these perturbed TFs and their associated biological processes. Disease-associated gene modules are conserved across multiple NAFLD cohorts The central genes in disease-associated modules are key enzymes in cholesterol synthesis YY1 and KLF13 are potential key transcriptional regulators of NAFLD development
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Affiliation(s)
- Hong Yang
- Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Muhammad Arif
- Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Meng Yuan
- Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Xiangyu Li
- Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Koeun Shong
- Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Hasan Türkez
- Department of Medical Biology, Faculty of Medicine, Atatürk University, Erzurum, Turkey
| | - Jens Nielsen
- Department of Biology and Biological Engineering, Chalmers University of Technology, 41296 Gothenburg, Sweden.,BioInnovation Institute, 2200 Copenhagen, Denmark
| | - Mathias Uhlén
- Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Jan Borén
- Department of Molecular and Clinical Medicine, University of Gothenburg and Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Cheng Zhang
- Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden.,School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, PR China
| | - Adil Mardinoglu
- Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden.,Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, London, UK
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28
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Sabik OL, Ackert-Bicknell CL, Farber CR. A computational approach for identification of core modules from a co-expression network and GWAS data. STAR Protoc 2021; 2:100768. [PMID: 34467232 PMCID: PMC8385446 DOI: 10.1016/j.xpro.2021.100768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022] Open
Abstract
This protocol describes the application of the "omnigenic" model of the genetic architecture of complex traits to identify novel "core" genes influencing a disease-associated phenotype. Core genes are hypothesized to directly regulate disease and may serve as therapeutic targets. This protocol leverages GWAS data, a co-expression network, and publicly available data, including the GTEx database and the International Mouse Phenotyping Consortium Database, to identify modules enriched for genes with "core-like" characteristics. For complete details on the use and execution of this protocol, please refer to Sabik et al. (2020).
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Affiliation(s)
- Olivia L. Sabik
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908 USA
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22908 USA
| | | | - Charles R. Farber
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908 USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA
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29
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Destouni A, Tsolis KC, Economou A, Papathanasiou I, Balis C, Mourmoura E, Tsezou A. Chondrocyte protein co-synthesis network analysis links ECM mechanosensing to metabolic adaptation in osteoarthritis. Expert Rev Proteomics 2021; 18:623-635. [PMID: 34348542 DOI: 10.1080/14789450.2021.1962299] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
BACKGROUND Knee osteoarthritis (OA) is one of the most common structural OA disorders globally. Incomplete understanding of the fundamental biological aspects of osteoarthritis underlies the current lack of effective treatment or disease modifying drugs. RESEARCH DESIGN AND METHODS We implemented a systems approach by making use of the statistical network concepts in Weighted Gene Co-expression Analysis to reconstruct the organization of the core proteome network in chondrocytes obtained from OA patients and healthy individuals. Protein modules reflect groups of tightly co-ordinated changes in protein abundance across healthy and OA chondrocytes. RESULTS The unbiased systems analysis identified extracellular matrix (ECM) mechanosensing and glycolysis as two modules that are most highly correlated with ΟΑ. The ECM module was enriched in the OA genetic risk factors tenascin-C (TNC) and collagen 11A1 (COL11A1), as well as in cartilage oligomeric matrix protein (COMP), a biomarker associated with cartilage integrity. Mapping proteins that are unique to OA or healthy chondrocytes onto the core interactome, which connects microenvironment sensing and regulation of glycolysis, identified differences in metabolic and anti-inflammatory adaptation. CONCLUSION The interconnection between cartilage ECM remodeling and metabolism is indicative of the dynamic chondrocyte states and their significance in osteoarthritis.
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Affiliation(s)
- Aspasia Destouni
- Laboratory of Cytogenetics and Molecular Genetics, Faculty of Medicine, University of Thessaly, Larissa, Greece
| | - Konstantinos C Tsolis
- KULeuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Molecular Bacteriology, Leuven, Belgium
| | - Anastassios Economou
- KULeuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Molecular Bacteriology, Leuven, Belgium
| | - Ioanna Papathanasiou
- Laboratory of Cytogenetics and Molecular Genetics, Faculty of Medicine, University of Thessaly, Larissa, Greece.,Department of Biology, Faculty of Medicine, University of Thessaly, Larissa, Greece
| | - Charalampos Balis
- Laboratory of Cytogenetics and Molecular Genetics, Faculty of Medicine, University of Thessaly, Larissa, Greece
| | - Evanthia Mourmoura
- Laboratory of Cytogenetics and Molecular Genetics, Faculty of Medicine, University of Thessaly, Larissa, Greece
| | - Aspasia Tsezou
- Laboratory of Cytogenetics and Molecular Genetics, Faculty of Medicine, University of Thessaly, Larissa, Greece.,Department of Biology, Faculty of Medicine, University of Thessaly, Larissa, Greece
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30
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Abood A, Farber CR. Using "-omics" Data to Inform Genome-wide Association Studies (GWASs) in the Osteoporosis Field. Curr Osteoporos Rep 2021; 19:369-380. [PMID: 34125409 PMCID: PMC8767463 DOI: 10.1007/s11914-021-00684-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/22/2021] [Indexed: 01/12/2023]
Abstract
PURPOSE OF REVIEW Osteoporosis constitutes a major societal health problem. Genome-wide association studies (GWASs) have identified over 1100 loci influencing bone mineral density (BMD); however, few of the causal genes have been identified. Here, we review approaches that use "-omics" data and genetic- and systems genetics-based analytical strategies to facilitate causal gene discovery. RECENT FINDINGS The bone field is beginning to adopt approaches that are commonplace in other disease disciplines. The slower progress has been due in part to the lack of large-scale "omics" data on bone and bone cells. This is however changing, and approaches such as eQTL colocalization, transcriptome-wide association studies (TWASs), network, and integrative approaches are beginning to provide significant insight into the genes responsible for BMD GWAS associations. The use of "-omics" data to inform BMD GWASs has increased in recent years, leading to the identification of novel regulators of BMD in humans. The ultimate goal will be to use this information to develop more effective therapies to treat and ultimately prevent osteoporosis.
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Affiliation(s)
- Abdullah Abood
- Center for Public Health Genomics, University of Virginia, 800717, Charlottesville, VA, 22908, USA
- Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, 22908, USA
| | - Charles R Farber
- Center for Public Health Genomics, University of Virginia, 800717, Charlottesville, VA, 22908, USA.
- Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, 22908, USA.
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, 22908, USA.
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Mohajeri MSA, Eslahi A, Khazaii Z, Moradi MR, Pazhoomand R, Farrokhi S, Feizabadi MH, Alizadeh F, Mojarrad M. TMEM263: a novel candidate gene implicated in human autosomal recessive severe lethal skeletal dysplasia. Hum Genomics 2021; 15:42. [PMID: 34238371 PMCID: PMC8268343 DOI: 10.1186/s40246-021-00343-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Accepted: 06/21/2021] [Indexed: 11/20/2022] Open
Abstract
INTRODUCTION Skeletal dysplasia is a common, clinically and genetically heterogeneous disorder in the human population. An increasing number of different genes are being identified causing this disorder. We used whole exome sequencing (WES) for detection of skeletal dysplasia causing mutation in a fetus affected to severe lethal skeletal dysplasia. PATIENT Fetus was assessed by ultrasonography in second trimester of pregnancy. He suffers from severe rhizomelic dysplasia and also pathologic shortening of ribs. WES was applied to finding of causal mutation. Furthermore, bioinformatics analysis was performed to predict mutation impact. RESULTS Whole exome sequencing (WES) identified a homozygous frameshift mutation in the TMEM263 gene in a fetus with severe lethal skeletal dysplasia. Mutations of this gene have been previously identified in dwarf chickens, but this is the first report of involvement of this gene in human skeletal dysplasia. This gene plays a key role in the growth hormone signaling pathway. CONCLUSION TMEM263 can be considered as a new gene responsible for skeletal dysplasia. Given the complications observed in the affected fetus, the mutation of this gene appears to produce much more intense complications than that found in chickens and is likely to play a more important role in bone development in human.
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Affiliation(s)
- Mahsa Sadat Asl Mohajeri
- Department of Medical Genetics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Atieh Eslahi
- Department of Medical Genetics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Medical Genetics Research Center, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | | | - Mohammad Reza Moradi
- Department of Medical Genetics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Reza Pazhoomand
- Legal Medicine Research Center, Legal Medicine Organization of Iran, Tehran, Iran
- Genetic Department, Shiraz Fertility Center, Shiraz, Iran
| | - Shima Farrokhi
- Department of Medical Genetics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Medical Genetics Research Center, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Masoumeh Heidari Feizabadi
- Department of Medical Genetics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Farzaneh Alizadeh
- Department of Medical Genetics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Majid Mojarrad
- Department of Medical Genetics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Medical Genetics Research Center, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Genetic Center of Khorasan Razavi, Mashhad, Iran
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Systems genetics in diversity outbred mice inform BMD GWAS and identify determinants of bone strength. Nat Commun 2021; 12:3408. [PMID: 34099702 PMCID: PMC8184749 DOI: 10.1038/s41467-021-23649-0] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Accepted: 05/10/2021] [Indexed: 12/14/2022] Open
Abstract
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 use Diversity Outbred (DO) mice to directly address these limitations by performing a systems genetics analysis of 55 complex skeletal phenotypes. We apply a network approach to cortical bone RNA-seq data to discover 66 genes likely to be causal for human BMD GWAS associations, including the genes SERTAD4 and GLT8D2. We also perform GWAS in the DO for a wide-range of bone traits and identify Qsox1 as a gene influencing cortical bone accrual and bone strength. In this work, we advance our understanding of the genetics of osteoporosis and highlight the ability of the mouse to inform human genetics. Osteoporosis GWAS faces two challenges, causal gene discovery and a lack of phenotypic diversity. Here, the authors use the Diversity Outbred mouse population to inform human GWAS using networks and map genetic loci for 55 bone traits, identifying new potential bone strength genes.
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Yuan J, Chen F, Fan D, Jiang Q, Xue Z, Zhang J, Yu X, Li K, Qu J, Su J. EyeDiseases: an integrated resource for dedicating to genetic variants, gene expression and epigenetic factors of human eye diseases. NAR Genom Bioinform 2021; 3:lqab050. [PMID: 34085038 PMCID: PMC8168129 DOI: 10.1093/nargab/lqab050] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 04/22/2021] [Accepted: 05/19/2021] [Indexed: 02/06/2023] Open
Abstract
Eye diseases are remarkably common and encompass a large and diverse range of morbidities that affect different components of the visual system and visual function. With advances in omics technology of eye disorders, genome-scale datasets have been rapidly accumulated in genetics and epigenetics field. However, the efficient collection and comprehensive analysis of different kinds of omics data are lacking. Herein, we developed EyeDiseases (https://eyediseases.bio-data.cn/), the first database for multi-omics data integration and interpretation of human eyes diseases. It contains 1344 disease-associated genes with genetic variation, 1774 transcription files of bulk cell expression and single-cell RNA-seq, 105 epigenomics data across 185 kinds of human eye diseases. Using EyeDiseases, we investigated SARS-CoV-2 potential tropism in eye infection and found that the SARS-CoV-2 entry factors, ACE2 and TMPRSS2 are highly correlated with cornea and keratoconus, suggest that ocular surface cells are susceptible to infection by SARS-CoV-2. Additionally, integrating analysis of Age-related macular degeneration (AMD) GWAS loci and co-expression data revealed 9 associated genes involved in HIF-1 signaling pathway and voltage-gate potassium channel complex. The EyeDiseases provides a valuable resource for accelerating the discovery and validation of candidate loci and genes contributed to the molecular diagnosis and therapeutic vulnerabilities with various eyes diseases.
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Affiliation(s)
- Jian Yuan
- School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Fukun Chen
- School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Dandan Fan
- School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Qi Jiang
- School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Zhengbo Xue
- School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Ji Zhang
- School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Xiangyi Yu
- School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Kai Li
- Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou 325011, Zhejiang, China
| | - Jia Qu
- School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Jianzhong Su
- School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
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Sabik OL, Calabrese GM, Taleghani E, Ackert-Bicknell CL, Farber CR. Identification of a Core Module for Bone Mineral Density through the Integration of a Co-expression Network and GWAS Data. Cell Rep 2021; 32:108145. [PMID: 32937138 DOI: 10.1016/j.celrep.2020.108145] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 03/31/2020] [Accepted: 08/21/2020] [Indexed: 12/12/2022] Open
Abstract
The "omnigenic" model of the genetic architecture of complex traits proposed two categories of causal genes: core and peripheral. Core genes are hypothesized to directly regulate disease and may serve as therapeutic targets. Using a cell-type- and time-point-specific gene co-expression network for mineralizing osteoblasts, we identify a co-expression module enriched for genes implicated by bone mineral density (BMD) genome-wide association studies (GWASs), correlated with in vitro osteoblast mineralization and associated with skeletal phenotypes in human monogenic disease and mouse knockouts. Four genes from this module (B4GALNT3, CADM1, DOCK9, and GPR133) are located within the BMD GWAS loci with colocalizing expression quantitative trait loci (eQTL) and exhibit altered BMD in mouse knockouts, suggesting that they are causal genetic drivers of BMD in humans. Our network-based approach identifies a "core" module for BMD and provides a resource for expanding our understanding of the genetics of bone mass.
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Affiliation(s)
- Olivia L Sabik
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA; Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
| | - Gina M Calabrese
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
| | - Eric Taleghani
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
| | - Cheryl L Ackert-Bicknell
- Center for Musculoskeletal Research, University of Rochester Medical Center, University of Rochester, Rochester, NY 14624, USA
| | - Charles R Farber
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA; Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA; Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA.
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35
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Zhang Q, Mesner LD, Calabrese GM, Dirckx N, Li Z, Verardo A, Yang Q, Tower RJ, Faugere MC, Farber CR, Clemens TL. Genomic variants within chromosome 14q32.32 regulate bone mass through MARK3 signaling in osteoblasts. J Clin Invest 2021; 131:142580. [PMID: 33792563 DOI: 10.1172/jci142580] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Accepted: 11/18/2020] [Indexed: 11/17/2022] Open
Abstract
Bone mineral density (BMD) is a highly heritable predictor of osteoporotic fracture. GWAS have identified hundreds of loci influencing BMD, but few have been functionally analyzed. In this study, we show that SNPs within a BMD locus on chromosome 14q32.32 alter splicing and expression of PAR-1a/microtubule affinity regulating kinase 3 (MARK3), a conserved serine/threonine kinase known to regulate bioenergetics, cell division, and polarity. Mice lacking Mark3 either globally or selectively in osteoblasts have increased bone mass at maturity. RNA profiling from Mark3-deficient osteoblasts suggested changes in the expression of components of the Notch signaling pathway. Mark3-deficient osteoblasts exhibited greater matrix mineralization compared with controls that was accompanied by reduced Jag1/Hes1 expression and diminished downstream JNK signaling. Overexpression of Jag1 in Mark3-deficient osteoblasts both in vitro and in vivo normalized mineralization capacity and bone mass, respectively. Together, these findings reveal a mechanism whereby genetically regulated alterations in Mark3 expression perturb cell signaling in osteoblasts to influence bone mass.
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Affiliation(s)
- Qian Zhang
- Department of Orthopaedic Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.,Baltimore Veterans Administration Medical Center, Baltimore, Maryland, USA
| | - Larry D Mesner
- Departments of Public Health Genomics and Biochemistry and Molecular Genetics, Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, Virginia, USA
| | - Gina M Calabrese
- Departments of Public Health Genomics and Biochemistry and Molecular Genetics, Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, Virginia, USA
| | - Naomi Dirckx
- Department of Orthopaedic Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Zhu Li
- Department of Orthopaedic Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.,Baltimore Veterans Administration Medical Center, Baltimore, Maryland, USA
| | - Angela Verardo
- Department of Orthopaedic Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Qian Yang
- Department of Orthopaedic Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Robert J Tower
- Department of Orthopaedic Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | | | - Charles R Farber
- Departments of Public Health Genomics and Biochemistry and Molecular Genetics, Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, Virginia, USA
| | - Thomas L Clemens
- Department of Orthopaedic Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.,Baltimore Veterans Administration Medical Center, Baltimore, Maryland, USA
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Abstract
PURPOSE OF REVIEW More than one hundred loci have been identified from human genome-wide association studies (GWAS) for blood lipids. Despite the success of GWAS in identifying loci, subsequent prioritization of causal genes related to these loci remains a challenge. To address this challenge, recent work suggests that candidate causal genes within loci can be prioritized through cross-species integration using genome-wide data from the mouse. RECENT FINDINGS Mouse model systems provide unparalleled access to primary tissues, like the liver, that are not readily available for human studies. Given the key role the liver plays in controlling blood lipid levels and the wealth of liver genome-wide transcript and protein data available in the mouse, these data can be leveraged. Using coexpression network analysis approaches with mouse genome-wide data, coupled with cross-species analysis of human lipid GWAS, causal genes within lipid loci can be prioritized. Prioritization through both mouse and human along with biochemical validation provide a systematic and valuable method to discover lipid metabolism genes. SUMMARY The prioritization of causal lipid genes within GWAS loci is a challenging process requiring a multidisciplinary approach. Integration of data types across species, such as the mouse, can aid in causal gene prioritization.
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Affiliation(s)
- James A. Votava
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - Brian W. Parks
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI, USA
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Integrative genomics analysis identifies five promising genes implicated in insomnia risk based on multiple omics datasets. Biosci Rep 2021; 40:226183. [PMID: 32830860 PMCID: PMC7468094 DOI: 10.1042/bsr20201084] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Revised: 08/15/2020] [Accepted: 08/21/2020] [Indexed: 12/27/2022] Open
Abstract
In recent decades, many genome-wide association studies on insomnia have reported numerous genes harboring multiple risk variants. Nevertheless, the molecular functions of these risk variants conveying risk to insomnia are still ill-studied. In the present study, we integrated GWAS summary statistics (N=386,533) with two independent brain expression quantitative trait loci (eQTL) datasets (N=329) to determine whether expression-associated SNPs convey risk to insomnia. Furthermore, we applied numerous bioinformatics analyses to highlight promising genes associated with insomnia risk. By using Sherlock integrative analysis, we detected 449 significant insomnia-associated genes in the discovery stage. These identified genes were significantly overrepresented in six biological pathways including Huntington’s disease (P=5.58 × 10−5), Alzheimer’s disease (P=5.58 × 10−5), Parkinson’s disease (P=6.34 × 10−5), spliceosome (P=1.17 × 10−4), oxidative phosphorylation (P=1.09 × 10−4), and wnt signaling pathways (P=2.07 × 10−4). Further, five of these identified genes were replicated in an independent brain eQTL dataset. Through a PPI network analysis, we found that there existed highly functional interactions among these five identified genes. Three genes of LDHA (P=0.044), DALRD3 (P=5.0 × 10−5), and HEBP2 (P=0.032) showed significantly lower expression level in brain tissues of insomnic patients than that in controls. In addition, the expression levels of these five genes showed prominently dynamic changes across different time points between behavioral states of sleep and sleep deprivation in mice brain cortex. Together, the evidence of the present study strongly suggested that these five identified genes may represent candidate genes and contributed risk to the etiology of insomnia.
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Zhong Y, Chen L, Li J, Yao Y, Liu Q, Niu K, Ma Y, Xu Y. Integration of summary data from GWAS and eQTL studies identified novel risk genes for coronary artery disease. Medicine (Baltimore) 2021; 100:e24769. [PMID: 33725943 PMCID: PMC7982177 DOI: 10.1097/md.0000000000024769] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 01/23/2021] [Indexed: 01/05/2023] Open
Abstract
Several genetic loci have been reported to be significantly associated with coronary artery disease (CAD) by multiple genome-wide association studies (GWAS). Nevertheless, the biological and functional effects of these genetic variants on CAD remain largely equivocal. In the current study, we performed an integrative genomics analysis by integrating large-scale GWAS data (N = 459,534) and 2 independent expression quantitative trait loci (eQTL) datasets (N = 1890) to determine whether CAD-associated risk single nucleotide polymorphisms (SNPs) exert regulatory effects on gene expression. By using Sherlock Bayesian, MAGMA gene-based, multidimensional scaling (MDS), functional enrichment, and in silico permutation analyses for independent technical and biological replications, we highlighted 4 susceptible genes (CHCHD1, TUBG1, LY6G6C, and MRPS17) associated with CAD risk. Based on the protein-protein interaction (PPI) network analysis, these 4 genes were found to interact with each other. We detected a remarkably altered co-expression pattern among these 4 genes between CAD patients and controls. In addition, 3 genes of CHCHD1 (P = .0013), TUBG1 (P = .004), and LY6G6C (P = .038) showed significantly different expressions between CAD patients and controls. Together, we provide evidence to support that these identified genes such as CHCHD1 and TUBG1 are indicative factors of CAD.
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Affiliation(s)
- Yigang Zhong
- Department of Cardiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine
| | | | - Jingjing Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou
| | - Yinghao Yao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou
| | - Qiang Liu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou
| | - Kaimeng Niu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou
| | - Yunlong Ma
- Institute of Biomedical Big Data, School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, China
| | - Yizhou Xu
- Department of Cardiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine
- Zhejiang Chinese Medical University
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Yang P, Yang Y, Sun P, Tian Y, Gao F, Wang C, Zong T, Li M, Zhang Y, Yu T, Jiang Z. βII spectrin (SPTBN1): biological function and clinical potential in cancer and other diseases. Int J Biol Sci 2021; 17:32-49. [PMID: 33390831 PMCID: PMC7757025 DOI: 10.7150/ijbs.52375] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Accepted: 10/22/2020] [Indexed: 12/16/2022] Open
Abstract
βII spectrin, the most common isoform of non-erythrocyte spectrin, is a cytoskeleton protein present in all nucleated cells. Interestingly, βII spectrin is essential for the development of various organs such as nerve, epithelium, inner ear, liver and heart. The functions of βII spectrin include not only establishing and maintaining the cell structure but also regulating a variety of cellular functions, such as cell apoptosis, cell adhesion, cell spreading and cell cycle regulation. Notably, βII spectrin dysfunction is associated with embryonic lethality and the DNA damage response. More recently, the detection of altered βII spectrin expression in tumors indicated that βII spectrin might be involved in the development and progression of cancer. Its mutations and disorders could result in developmental disabilities and various diseases. The versatile roles of βII spectrin in disease have been examined in an increasing number of studies; nonetheless, the exact mechanisms of βII spectrin are still poorly understood. Thus, we summarize the structural features and biological roles of βII spectrin and discuss its molecular mechanisms and functions in development, homeostasis, regeneration and differentiation. This review highlight the potential effects of βII spectrin dysfunction in cancer and other diseases, outstanding questions for the future investigation of therapeutic targets. The investigation of the regulatory mechanism of βII spectrin signal inactivation and recovery may bring hope for future therapy of related diseases.
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Affiliation(s)
- Panyu Yang
- Department of Cardiac Ultrasound, The Affiliated Hospital of Qingdao University, Qingdao 266000, China
| | - Yanyan Yang
- Department of Immunology, Basic Medicine School, Qingdao University, No. 308 Ningxia Road, Qingdao 266071, People's Republic of China
| | - Pin Sun
- Department of Cardiac Ultrasound, The Affiliated Hospital of Qingdao University, Qingdao 266000, China
| | - Yu Tian
- Department of Cardiac Ultrasound, The Affiliated Hospital of Qingdao University, Qingdao 266000, China
| | - Fang Gao
- Department of Physical Medicine and Rehabiliation, The Affiliated Hospital of Qingdao University, Qingdao, Shandong Province, China
| | - Chen Wang
- Department of Physical Medicine and Rehabiliation, The Affiliated Hospital of Qingdao University, Qingdao, Shandong Province, China
| | - Tingyu Zong
- Department of Cardiac Ultrasound, The Affiliated Hospital of Qingdao University, Qingdao 266000, China
| | - Min Li
- Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, No. 38 Dengzhou Road, Qingdao 266021, People's Republic of China
| | - Ying Zhang
- Department of Cardiac Ultrasound, The Affiliated Hospital of Qingdao University, Qingdao 266000, China
| | - Tao Yu
- Department of Cardiac Ultrasound, The Affiliated Hospital of Qingdao University, Qingdao 266000, China.,Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, No. 38 Dengzhou Road, Qingdao 266021, People's Republic of China
| | - Zhirong Jiang
- Department of Cardiac Ultrasound, The Affiliated Hospital of Qingdao University, Qingdao 266000, China
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40
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Liu Q, Li M, Wang S, Xiao Z, Xiong Y, Wang G. Recent Advances of Osterix Transcription Factor in Osteoblast Differentiation and Bone Formation. Front Cell Dev Biol 2020; 8:601224. [PMID: 33384998 PMCID: PMC7769847 DOI: 10.3389/fcell.2020.601224] [Citation(s) in RCA: 101] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 11/23/2020] [Indexed: 12/14/2022] Open
Abstract
With increasing life expectations, more and more patients suffer from fractures either induced by intensive sports or other bone-related diseases. The balance between osteoblast-mediated bone formation and osteoclast-mediated bone resorption is the basis for maintaining bone health. Osterix (Osx) has long been known to be an essential transcription factor for the osteoblast differentiation and bone mineralization. Emerging evidence suggests that Osx not only plays an important role in intramembranous bone formation, but also affects endochondral ossification by participating in the terminal cartilage differentiation. Given its essentiality in skeletal development and bone formation, Osx has become a new research hotspot in recent years. In this review, we focus on the progress of Osx's function and its regulation in osteoblast differentiation and bone mass. And the potential role of Osx in developing new therapeutic strategies for osteolytic diseases was discussed.
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Affiliation(s)
- Qian Liu
- Key Laboratory of Brain and Neuroendocrine Diseases, College of Hunan Province, Hunan University of Medicine, Huaihua, China
- Biomedical Research Center, Hunan University of Medicine, Huaihua, China
| | - Mao Li
- Biomedical Research Center, Hunan University of Medicine, Huaihua, China
| | - Shiyi Wang
- XiangYa School of Medicine, Central South University, Changsha, China
| | - Zhousheng Xiao
- Department of Medicine, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Yuanyuan Xiong
- Key Laboratory of Brain and Neuroendocrine Diseases, College of Hunan Province, Hunan University of Medicine, Huaihua, China
- Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Guangwei Wang
- Key Laboratory of Brain and Neuroendocrine Diseases, College of Hunan Province, Hunan University of Medicine, Huaihua, China
- Biomedical Research Center, Hunan University of Medicine, Huaihua, China
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41
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Discover novel disease-associated genes based on regulatory networks of long-range chromatin interactions. Methods 2020; 189:22-33. [PMID: 33096239 DOI: 10.1016/j.ymeth.2020.10.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 08/29/2020] [Accepted: 10/18/2020] [Indexed: 02/01/2023] Open
Abstract
Identifying genes and non-coding genetic variants that are genetically associated with complex diseases and the underlying mechanisms is one of the most important questions in functional genomics. Due to the limited statistical power and the lack of mechanistic modeling, traditional genome-wide association studies (GWAS) is restricted to fully address this question. Based on multi-omics data integration, cell-type specific regulatory networks can be built to improve GWAS analysis. In this study, we developed a new computational infrastructure, APRIL, to incorporate 3D chromatin interactions into regulatory network construction, which can extend the networks to include long-range cis-regulatory links between non-coding GWAS SNPs and target genes. Combinatorial transcription factors that co-regulate groups of genes are also inferred to further expand the networks with trans-regulation. A suite of machine learning predictions and statistical tests are incorporated in APRIL to predict novel disease-associated genes based on the expanded regulatory networks. Important features of non-coding regulatory elements and genetic variants are prioritized in network-based predictions, providing systems-level insights on the mechanisms of transcriptional dysregulation associated with complex diseases.
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42
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Dong Z, Ma Y, Zhou H, Shi L, Ye G, Yang L, Liu P, Zhou L. Integrated genomics analysis highlights important SNPs and genes implicated in moderate-to-severe asthma based on GWAS and eQTL datasets. BMC Pulm Med 2020; 20:270. [PMID: 33066754 PMCID: PMC7568423 DOI: 10.1186/s12890-020-01303-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Accepted: 09/27/2020] [Indexed: 02/06/2023] Open
Abstract
Background Severe asthma is a chronic disease contributing to disproportionate disease morbidity and mortality. From the year of 2007, many genome-wide association studies (GWAS) have documented a large number of asthma-associated genetic variants and related genes. Nevertheless, the molecular mechanism of these identified variants involved in asthma or severe asthma risk remains largely unknown. Methods In the current study, we systematically integrated 3 independent expression quantitative trait loci (eQTL) data (N = 1977) and a large-scale GWAS summary data of moderate-to-severe asthma (N = 30,810) by using the Sherlock Bayesian analysis to identify whether expression-related variants contribute risk to severe asthma. Furthermore, we performed various bioinformatics analyses, including pathway enrichment analysis, PPI network enrichment analysis, in silico permutation analysis, DEG analysis and co-expression analysis, to prioritize important genes associated with severe asthma. Results In the discovery stage, we identified 1129 significant genes associated with moderate-to-severe asthma by using the Sherlock Bayesian analysis. Two hundred twenty-eight genes were prominently replicated by using MAGMA gene-based analysis. These 228 replicated genes were enriched in 17 biological pathways including antigen processing and presentation (Corrected P = 4.30 × 10− 6), type I diabetes mellitus (Corrected P = 7.09 × 10− 5), and asthma (Corrected P = 1.72 × 10− 3). With the use of a series of bioinformatics analyses, we highlighted 11 important genes such as GNGT2, TLR6, and TTC19 as authentic risk genes associated with moderate-to-severe/severe asthma. With respect to GNGT2, there were 3 eSNPs of rs17637472 (PeQTL = 2.98 × 10− 8 and PGWAS = 3.40 × 10− 8), rs11265180 (PeQTL = 6.0 × 10− 6 and PGWAS = 1.99 × 10− 3), and rs1867087 (PeQTL = 1.0 × 10− 4 and PGWAS = 1.84 × 10− 5) identified. In addition, GNGT2 is significantly expressed in severe asthma compared with mild-moderate asthma (P = 0.045), and Gngt2 shows significantly distinct expression patterns between vehicle and various glucocorticoids (Anova P = 1.55 × 10− 6). Conclusions Our current study provides multiple lines of evidence to support that these 11 identified genes as important candidates implicated in the pathogenesis of severe asthma.
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Affiliation(s)
- Zhouzhou Dong
- Critical Care Unit, Ningbo Medical Center Lihuili Hospital, Taipei Medical University Ningbo Medical Center, Ningbo, Zhejiang, 315100, P.R. China
| | - Yunlong Ma
- Institute of Biomedical Big Data, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China.,School of Biomedical Engineering, School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China
| | - Hua Zhou
- Department of Respiratory Disease, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, P.R. China
| | - Linhui Shi
- Critical Care Unit, Ningbo Medical Center Lihuili Hospital, Taipei Medical University Ningbo Medical Center, Ningbo, Zhejiang, 315100, P.R. China
| | - Gongjie Ye
- Critical Care Unit, Ningbo Medical Center Lihuili Hospital, Taipei Medical University Ningbo Medical Center, Ningbo, Zhejiang, 315100, P.R. China
| | - Lei Yang
- Critical Care Unit, Ningbo Medical Center Lihuili Hospital, Taipei Medical University Ningbo Medical Center, Ningbo, Zhejiang, 315100, P.R. China
| | - Panpan Liu
- Critical Care Unit, Ningbo Medical Center Lihuili Hospital, Taipei Medical University Ningbo Medical Center, Ningbo, Zhejiang, 315100, P.R. China
| | - Li Zhou
- Department of Immunology and Rheumatology, Ningbo Medical Center Lihuili Hospital, Taipei Medical University Ningbo Medical Center, Ningbo, Zhejiang, 315100, P.R. China.
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Choi Y, Kim M, Hong CP, Kang JH, Jung JH. Is hull cleaning wastewater a potential source of developmental toxicity on coastal non-target organisms? AQUATIC TOXICOLOGY (AMSTERDAM, NETHERLANDS) 2020; 227:105615. [PMID: 32932041 DOI: 10.1016/j.aquatox.2020.105615] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 08/21/2020] [Accepted: 08/30/2020] [Indexed: 06/11/2023]
Abstract
Chemical contaminants can be discharged by vessel hull cleaning processes, such as scraping, jet spraying, and painting, all of which produce readily transportable contaminants into the marine environment, where they are referred to as 'hotspots' of contamination in coastal areas. However, many countries have not yet established effective evaluation methods for disposal of waste mixtures or management guidelines for areas of hull cleaning. To define the toxic effects of wastewater from vessel hull cleaning in dry docks on resident non-target organisms, we investigated the chemical concentrations and developmental toxicity on embryonic flounder, which is an organism sensitive to chemical contamination. In this study, the dominant inorganic metal discharged was zinc when cleaning Ship A (300 tons) and copper for Ship B (5,000 tons). The wastewater from high-pressure water blasting (WHPB) of Ship A (300 tons) and Ship B (5,000 tons) produced a largely overlapping suite of developmental malformations including pericardial edema, spinal curvature, and tail fin defects. Forty-eight hours after exposure, the frequency percentage of malformation began to increase in embryos exposed to a 500-fold dilution of WHPB from Ships A and B. We performed transcriptome sequencing to characterize the toxicological developmental effects of WHPB exposure at the molecular level. The results of the analysis revealed significantly altered expression of genes associated with muscle cell differentiation, actin-mediated cell contraction, and nervous system development (cutoff P < 0.01) in embryonic flounder exposed to high-pressure cleaning effluent from Ship A. Genes associated with chromatin remodeling, cell cycling, and insulin receptor signaling pathways were significantly altered in embryonic flounder exposed to WHPB of Ship B (cutoff P < 0.01). These findings provide a greater understanding of the developmental toxicity and potential effects of WHPB effluent on coastal embryonic fish. Furthermore, our results could inform WHPB effluent management practices to reduce impacts on non-target coastal organisms.
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Affiliation(s)
- Youmi Choi
- Risk Assessment Research Center, Korea Institute of Ocean Science and Technology, Geoje, 53201, Republic of Korea; Department of Ocean Science, Korea University of Science and Technology, Daejeon, 34113, Republic of Korea
| | - Moonkoo Kim
- Risk Assessment Research Center, Korea Institute of Ocean Science and Technology, Geoje, 53201, Republic of Korea; Department of Ocean Science, Korea University of Science and Technology, Daejeon, 34113, Republic of Korea
| | - Chang Pyo Hong
- Theragen Etex Bio Institute Inc., 145 Gwanggyo-ro, Yeongtong-gu, Suwon-si, 16229, Gyeonggi-do, Republic of Korea
| | - Jung-Hoon Kang
- Risk Assessment Research Center, Korea Institute of Ocean Science and Technology, Geoje, 53201, Republic of Korea; Department of Ocean Science, Korea University of Science and Technology, Daejeon, 34113, Republic of Korea
| | - Jee-Hyun Jung
- Risk Assessment Research Center, Korea Institute of Ocean Science and Technology, Geoje, 53201, Republic of Korea; Department of Ocean Science, Korea University of Science and Technology, Daejeon, 34113, Republic of Korea.
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44
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Ma X, Wang P, Xu G, Yu F, Ma Y. Integrative genomics analysis of various omics data and networks identify risk genes and variants vulnerable to childhood-onset asthma. BMC Med Genomics 2020; 13:123. [PMID: 32867763 PMCID: PMC7457797 DOI: 10.1186/s12920-020-00768-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Accepted: 08/17/2020] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Childhood-onset asthma is highly affected by genetic components. In recent years, many genome-wide association studies (GWAS) have reported a large group of genetic variants and susceptible genes associated with asthma-related phenotypes including childhood-onset asthma. However, the regulatory mechanisms of these genetic variants for childhood-onset asthma susceptibility remain largely unknown. METHODS In the current investigation, we conducted a two-stage designed Sherlock-based integrative genomics analysis to explore the cis- and/or trans-regulatory effects of genome-wide SNPs on gene expression as well as childhood-onset asthma risk through incorporating a large-scale GWAS data (N = 314,633) and two independent expression quantitative trait loci (eQTL) datasets (N = 1890). Furthermore, we applied various bioinformatics analyses, including MAGMA gene-based analysis, pathway enrichment analysis, drug/disease-based enrichment analysis, computer-based permutation analysis, PPI network analysis, gene co-expression analysis and differential gene expression analysis, to prioritize susceptible genes associated with childhood-onset asthma. RESULTS Based on comprehensive genomics analyses, we found 31 genes with multiple eSNPs to be convincing candidates for childhood-onset asthma risk; such as, PSMB9 (cis-rs4148882 and cis-rs2071534) and TAP2 (cis-rs9267798, cis-rs4148882, cis-rs241456, and trans-10,447,456). These 31 genes were functionally interacted with each other in our PPI network analysis. Our pathway enrichment analysis showed that numerous KEGG pathways including antigen processing and presentation, type I diabetes mellitus, and asthma were significantly enriched to involve in childhood-onset asthma risk. The co-expression patterns among 31 genes were remarkably altered according to asthma status, and 25 of 31 genes (25/31 = 80.65%) showed significantly or suggestively differential expression between asthma group and control group. CONCLUSIONS We provide strong evidence to highlight 31 candidate genes for childhood-onset asthma risk, and offer a new insight into the genetic pathogenesis of childhood-onset asthma.
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Affiliation(s)
- Xiuqing Ma
- Department of Pulmonary & Critical Care Medicine, Chinese PLA General Hospital, Beijing, 100853 China
| | - Peilan Wang
- Outpatient Department, Chinese PLA General Hospital, Beijing, 100853 China
| | - Guobing Xu
- Department of Cardiovascular Medicine, Zhongxiang People’s Hospital, Zhongxiang, 431900 Hubei Province China
| | - Fang Yu
- Department of Pediatrics, Chinese PLA General Hospital, Beijing, 100853 China
| | - Yunlong Ma
- Institute of Biomedical Big Data, School of Biomedical Engineering, School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, 325027 P. R. China
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou, China
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45
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Chiang TI, Lane HY, Lin CH. D2 dopamine receptor gene (DRD2) Taq1A (rs1800497) affects bone density. Sci Rep 2020; 10:13236. [PMID: 32764574 PMCID: PMC7414035 DOI: 10.1038/s41598-020-70262-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Accepted: 07/22/2020] [Indexed: 11/17/2022] Open
Abstract
Schizophrenia patients are susceptible to lower bone mineral density (BMD). However, studies exploring the genetic effects are lacking. Genes that affect the activity of antipsychotics may be associated with BMD, particularly in patients receiving long-term antipsychotic treatment. We aimed to explore the relationship between the dopamine receptor D2 (DRD2) gene Taq1A (rs1800497) polymorphism and BMD in chronic schizophrenia patients. We recruited schizophrenia patients (n = 47) and healthy controls (n = 39) from a medical center in Taiwan and collected data that may affect BMD. Patients’ BMD was measured by dual-energy X-ray absorptiometer (DEXA). DRD2 rs1800497 was genotyped through polymerase chain reaction–Restriction Fragment Length Polymorphism (PCR–RFLP). Among all participants, subjects with DRD2 rs1800497(T;T) allele had lower DEXA T score and DEXA Z score compared to those with rs1800497(C;T) and rs1800497(C;C) alleles (p = 0.008, 0.003, respectively). In schizophrenia patients, subjects with rs1800497(T;T) allele also had lower DEXA Z score compared to the other two alleles (p = 0.045). Our findings suggest that individuals with the DRD2 rs1800497(T;T) had lower BMD than those with the rs1800497(C;T) and rs1800497(C;C) genotypes. Therefore, genes should be considered as one of the risk factors of lower BMD.
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Affiliation(s)
- Ting-I Chiang
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, No. 123, Dapi Rd., Niaosong District, Kaohsiung City, 833, Taiwan
| | - Hsien-Yuan Lane
- Graduate Institute of Biomedical Sciences, China Medical University, No. 91, Hsueh-Shih Rd., North Dist., Taichung City, 404, Taiwan. .,Department of Psychiatry and Brain Disease Research Center, China Medical University Hospital, Taichung, Taiwan. .,Department of Psychology, College of Medical and Health Sciences, Asia University, Taichung, Taiwan.
| | - Chieh-Hsin Lin
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, No. 123, Dapi Rd., Niaosong District, Kaohsiung City, 833, Taiwan. .,Graduate Institute of Biomedical Sciences, China Medical University, No. 91, Hsueh-Shih Rd., North Dist., Taichung City, 404, Taiwan. .,School of Medicine, Chang Gung University, Taoyuan, Taiwan.
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Ratnakumar A, Weinhold N, Mar JC, Riaz N. Protein-Protein interactions uncover candidate 'core genes' within omnigenic disease networks. PLoS Genet 2020; 16:e1008903. [PMID: 32678846 PMCID: PMC7390454 DOI: 10.1371/journal.pgen.1008903] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Revised: 07/29/2020] [Accepted: 06/01/2020] [Indexed: 01/09/2023] Open
Abstract
Genome wide association studies (GWAS) of human diseases have generally identified many loci associated with risk with relatively small effect sizes. The omnigenic model attempts to explain this observation by suggesting that diseases can be thought of as networks, where genes with direct involvement in disease-relevant biological pathways are named ‘core genes’, while peripheral genes influence disease risk via their interactions or regulatory effects on core genes. Here, we demonstrate a method for identifying candidate core genes solely from genes in or near disease-associated SNPs (GWAS hits) in conjunction with protein-protein interaction network data. Applied to 1,381 GWAS studies from 5 ancestries, we identify a total of 1,865 candidate core genes in 343 GWAS studies. Our analysis identifies several well-known disease-related genes that are not identified by GWAS, including BRCA1 in Breast Cancer, Amyloid Precursor Protein (APP) in Alzheimer’s Disease, INS in A1C measurement and Type 2 Diabetes, and PCSK9 in LDL cholesterol, amongst others. Notably candidate core genes are preferentially enriched for disease relevance over GWAS hits and are enriched for both Clinvar pathogenic variants and known drug targets—consistent with the predictions of the omnigenic model. We subsequently use parent term annotations provided by the GWAS catalog, to merge related GWAS studies and identify candidate core genes in over-arching disease processes such as cancer–where we identify 109 candidate core genes. A recent theory suggests that only a small number of genes underpin the biology of a disease, these genes are called ‘core genes’, and for most diseases, these core genes remain unknown. The suggested methods for finding them requires complex and expensive experiments. We reasoned that if we merge currently available datasets in smart ways, we may be able to uncover these ‘core genes’. Our method finds “hub” proteins by merging lists of genes previously linked with disease to information on how proteins interact with each other. We found that many of these hub proteins have central roles in disease, such as insulin for both A1C measurement and Type 2 Diabetes, BRCA1 in Breast cancer, and Amyloid Precursor Protein in Alzheimer’s Disease. We think these ‘hub’ proteins are candidate ‘core genes’, and offer our method as a way to find ‘core genes’ by utilizing publicly available reference datasets.
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Affiliation(s)
- Abhirami Ratnakumar
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America
- * E-mail:
| | - Nils Weinhold
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America
| | - Jessica C. Mar
- Australian Institute for Bioengineering and Nanotechnology, University of Queensland, Brisbane, Australia
| | - Nadeem Riaz
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America
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47
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Analysis of the genes controlling three quantitative traits in three diverse plant species reveals the molecular basis of quantitative traits. Sci Rep 2020; 10:10074. [PMID: 32572040 PMCID: PMC7308372 DOI: 10.1038/s41598-020-66271-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Accepted: 04/28/2020] [Indexed: 02/08/2023] Open
Abstract
Most traits of agricultural importance are quantitative traits controlled by numerous genes. However, it remains unclear about the molecular mechanisms underpinning quantitative traits. Here, we report the molecular characteristics of the genes controlling three quantitative traits randomly selected from three diverse plant species, including ginsenoside biosynthesis in ginseng (Panax ginseng C.A. Meyer), fiber length in cotton (Gossypium hirsutum L. and G. barbadense L.) and grain yield in maize (Zea mays L.). We found that a vast majority of the genes controlling a quantitative trait were significantly more likely spliced into multiple transcripts while they expressed. Nevertheless, only one to four, but not all, of the transcripts spliced from each of the genes were significantly correlated with the phenotype of the trait. The genes controlling a quantitative trait were multiple times more likely to form a co-expression network than other genes expressed in an organ. The network varied substantially among genotypes of a species and was associated with their phenotypes. These findings indicate that the genes controlling a quantitative trait are more likely pleiotropic and functionally correlated, thus providing new insights into the molecular basis underpinning quantitative traits and knowledge necessary to develop technologies for efficient manipulation of quantitative traits.
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48
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Pereira M, Ko JH, Logan J, Protheroe H, Kim KB, Tan ALM, Croucher PI, Park KS, Rotival M, Petretto E, Bassett JD, Williams GR, Behmoaras J. A trans-eQTL network regulates osteoclast multinucleation and bone mass. eLife 2020; 9:55549. [PMID: 32553114 PMCID: PMC7351491 DOI: 10.7554/elife.55549] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Accepted: 06/12/2020] [Indexed: 12/11/2022] Open
Abstract
Functional characterisation of cell-type-specific regulatory networks is key to establish a causal link between genetic variation and phenotype. The osteoclast offers a unique model for interrogating the contribution of co-regulated genes to in vivo phenotype as its multinucleation and resorption activities determine quantifiable skeletal traits. Here we took advantage of a trans-regulated gene network (MMnet, macrophage multinucleation network) which we found to be significantly enriched for GWAS variants associated with bone-related phenotypes. We found that the network hub gene Bcat1 and seven other co-regulated MMnet genes out of 13, regulate bone function. Specifically, global (Pik3cb-/-, Atp8b2+/-, Igsf8-/-, Eml1-/-, Appl2-/-, Deptor-/-) and myeloid-specific Slc40a1 knockout mice displayed abnormal bone phenotypes. We report opposing effects of MMnet genes on bone mass in mice and osteoclast multinucleation/resorption in humans with strong correlation between the two. These results identify MMnet as a functionally conserved network that regulates osteoclast multinucleation and bone mass.
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Affiliation(s)
- Marie Pereira
- Centre for Inflammatory Disease, Department of Immunology and Inflammation, Hammersmith Hospital, Imperial College London, London, United Kingdom.,Molecular Endocrinology Laboratory, Department of Metabolism, Digestion and Reproduction, Hammersmith Hospital, Imperial College London, London, United Kingdom
| | - Jeong-Hun Ko
- Centre for Inflammatory Disease, Department of Immunology and Inflammation, Hammersmith Hospital, Imperial College London, London, United Kingdom.,Molecular Endocrinology Laboratory, Department of Metabolism, Digestion and Reproduction, Hammersmith Hospital, Imperial College London, London, United Kingdom
| | - John Logan
- Molecular Endocrinology Laboratory, Department of Metabolism, Digestion and Reproduction, Hammersmith Hospital, Imperial College London, London, United Kingdom
| | - Hayley Protheroe
- Molecular Endocrinology Laboratory, Department of Metabolism, Digestion and Reproduction, Hammersmith Hospital, Imperial College London, London, United Kingdom
| | - Kee-Beom Kim
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia School of Medicine, Charlottesville, United States
| | | | - Peter I Croucher
- The Garvan Institute of Medical Research and St. Vincent's Clinical School, University of NewSouth Wales Medicine, Sydney, Australia
| | - Kwon-Sik Park
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia School of Medicine, Charlottesville, United States
| | - Maxime Rotival
- Human Evolutionary Genetics Unit, Institut Pasteur, Centre National de la Recherche Scientifique, UMR 2000, Paris, France
| | | | - Jh Duncan Bassett
- Molecular Endocrinology Laboratory, Department of Metabolism, Digestion and Reproduction, Hammersmith Hospital, Imperial College London, London, United Kingdom
| | - Graham R Williams
- Molecular Endocrinology Laboratory, Department of Metabolism, Digestion and Reproduction, Hammersmith Hospital, Imperial College London, London, United Kingdom
| | - Jacques Behmoaras
- Centre for Inflammatory Disease, Department of Immunology and Inflammation, Hammersmith Hospital, Imperial College London, London, United Kingdom
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49
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Abstract
Cardiovascular diseases are the leading cause of death worldwide. Complex diseases with highly heterogenous disease progression among patient populations, cardiovascular diseases feature multifactorial contributions from both genetic and environmental stressors. Despite significant effort utilizing multiple approaches from molecular biology to genome-wide association studies, the genetic landscape of cardiovascular diseases, particularly for the nonfamilial forms of heart failure, is still poorly understood. In the past decade, systems-level approaches based on omics technologies have become an important approach for the study of complex traits in large populations. These advances create opportunities to integrate genetic variation with other biological layers to identify and prioritize candidate genes, understand pathogenic pathways, and elucidate gene-gene and gene-environment interactions. In this review, we will highlight some of the recent progress made using systems genetics approaches to uncover novel mechanisms and molecular bases of cardiovascular pathophysiological manifestations. The key technology and data analysis platforms necessary to implement systems genetics will be described, and the current major challenges and future directions will also be discussed. For complex cardiovascular diseases, such as heart failure, systems genetics represents a powerful strategy to obtain mechanistic insights and to develop individualized diagnostic and therapeutic regiments, paving the way for precision cardiovascular medicine.
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Affiliation(s)
- Christoph D. Rau
- Departments of Anesthesiology, Medicine, Physiology
- Current address: Department of Genetics, University of North Carolina School of Medicine, Chapel Hill, NC 27599
| | - Aldons J. Lusis
- Department of Human Genetics and Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA 90095
| | - Yibin Wang
- Departments of Anesthesiology, Medicine, Physiology
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50
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Åkerborg Ö, Spalinskas R, Pradhananga S, Anil A, Höjer P, Poujade FA, Folkersen L, Eriksson PP, Sahlén P. High-Resolution Regulatory Maps Connect Vascular Risk Variants to Disease-Related Pathways. CIRCULATION-GENOMIC AND PRECISION MEDICINE 2020; 12:e002353. [PMID: 30786239 PMCID: PMC8104016 DOI: 10.1161/circgen.118.002353] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Supplemental Digital Content is available in the text. Genetic variant landscape of coronary artery disease is dominated by noncoding variants among which many occur within putative enhancers regulating the expression levels of relevant genes. It is crucial to assign the genetic variants to their correct genes both to gain insights into perturbed functions and better assess the risk of disease.
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Affiliation(s)
- Örjan Åkerborg
- Science for Life Laboratory, Division of Gene Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden (Ö.Å., R.S., S.P., A.A., P.H., P.S.)
| | - Rapolas Spalinskas
- Science for Life Laboratory, Division of Gene Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden (Ö.Å., R.S., S.P., A.A., P.H., P.S.)
| | - Sailendra Pradhananga
- Science for Life Laboratory, Division of Gene Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden (Ö.Å., R.S., S.P., A.A., P.H., P.S.)
| | - Anandashankar Anil
- Science for Life Laboratory, Division of Gene Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden (Ö.Å., R.S., S.P., A.A., P.H., P.S.)
| | - Pontus Höjer
- Science for Life Laboratory, Division of Gene Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden (Ö.Å., R.S., S.P., A.A., P.H., P.S.)
| | - Flore-Anne Poujade
- Cardiovascular Medicine Unit, Department of Medicine, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden (F.-A.P., P.E.)
| | - Lasse Folkersen
- Department of Bioinformatics, Technical University of Denmark, Copenhagen, Denmark (L.F.)
| | - Professor Per Eriksson
- Cardiovascular Medicine Unit, Department of Medicine, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden (F.-A.P., P.E.)
| | - Pelin Sahlén
- Science for Life Laboratory, Division of Gene Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden (Ö.Å., R.S., S.P., A.A., P.H., P.S.)
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