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Wright SN, Leger BS, Rosenthal SB, Liu SN, Jia T, Chitre AS, Polesskaya O, Holl K, Gao J, Cheng R, Garcia Martinez A, George A, Gileta AF, Han W, Netzley AH, King CP, Lamparelli A, Martin C, St Pierre CL, Wang T, Bimschleger H, Richards J, Ishiwari K, Chen H, Flagel SB, Meyer P, Robinson TE, Solberg Woods LC, Kreisberg JF, Ideker T, Palmer AA. Genome-wide association studies of human and rat BMI converge on synapse, epigenome, and hormone signaling networks. Cell Rep 2023; 42:112873. [PMID: 37527041 PMCID: PMC10546330 DOI: 10.1016/j.celrep.2023.112873] [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: 11/08/2022] [Revised: 07/05/2023] [Accepted: 07/11/2023] [Indexed: 08/03/2023] Open
Abstract
A vexing observation in genome-wide association studies (GWASs) is that parallel analyses in different species may not identify orthologous genes. Here, we demonstrate that cross-species translation of GWASs can be greatly improved by an analysis of co-localization within molecular networks. Using body mass index (BMI) as an example, we show that the genes associated with BMI in humans lack significant agreement with those identified in rats. However, the networks interconnecting these genes show substantial overlap, highlighting common mechanisms including synaptic signaling, epigenetic modification, and hormonal regulation. Genetic perturbations within these networks cause abnormal BMI phenotypes in mice, too, supporting their broad conservation across mammals. Other mechanisms appear species specific, including carbohydrate biosynthesis (humans) and glycerolipid metabolism (rodents). Finally, network co-localization also identifies cross-species convergence for height/body length. This study advances a general paradigm for determining whether and how phenotypes measured in model species recapitulate human biology.
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Affiliation(s)
- Sarah N Wright
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA; Program in Bioinformatics and Systems Biology, University of California San Diego, La Jolla, CA 92093, USA
| | - Brittany S Leger
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA; Program in Biomedical Sciences, University of California San Diego, La Jolla, CA 93093, USA
| | - Sara Brin Rosenthal
- Center for Computational Biology & Bioinformatics, Department of Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Sophie N Liu
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Tongqiu Jia
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Apurva S Chitre
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA
| | - Oksana Polesskaya
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA
| | - Katie Holl
- Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Jianjun Gao
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA
| | - Riyan Cheng
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA
| | - Angel Garcia Martinez
- Department of Pharmacology, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Anthony George
- Clinical and Research Institute on Addictions, University at Buffalo, Buffalo, NY 14203, USA
| | - Alexander F Gileta
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA; Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Wenyan Han
- Department of Pharmacology, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Alesa H Netzley
- Department of Psychiatry, University of Michigan, Ann Arbor, MI 48109, USA
| | - Christopher P King
- Clinical and Research Institute on Addictions, University at Buffalo, Buffalo, NY 14203, USA; Department of Psychology, University at Buffalo, Buffalo, NY 14260, USA
| | | | - Connor Martin
- Clinical and Research Institute on Addictions, University at Buffalo, Buffalo, NY 14203, USA; Department of Psychology, University at Buffalo, Buffalo, NY 14260, USA
| | | | - Tengfei Wang
- Department of Pharmacology, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Hannah Bimschleger
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA
| | - Jerry Richards
- Clinical and Research Institute on Addictions, University at Buffalo, Buffalo, NY 14203, USA
| | - Keita Ishiwari
- Clinical and Research Institute on Addictions, University at Buffalo, Buffalo, NY 14203, USA; Department of Pharmacology and Toxicology, University at Buffalo, Buffalo, NY 14203, USA
| | - Hao Chen
- Department of Pharmacology, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Shelly B Flagel
- Department of Psychiatry, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI 48109, USA
| | - Paul Meyer
- Department of Psychology, University at Buffalo, Buffalo, NY 14260, USA
| | - Terry E Robinson
- Department of Psychology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Leah C Solberg Woods
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | - Jason F Kreisberg
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Trey Ideker
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA; Institute for Genomic Medicine, University of California San Diego, La Jolla, CA 92093, USA.
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA; Institute for Genomic Medicine, University of California San Diego, La Jolla, CA 92093, USA.
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Musolf AM, Simpson CL, Moiz BA, Pikielny CW, Middlebrooks CD, Mandal D, de Andrade M, Cole MD, Gaba C, Yang P, You M, Li Y, Kupert EY, Anderson MW, Schwartz AG, Pinney SM, Amos CI, Bailey-Wilson JE. Genetic Variation and Recurrent Haplotypes on Chromosome 6q23-25 Risk Locus in Familial Lung Cancer. Cancer Res 2021; 81:3162-3173. [PMID: 33853833 PMCID: PMC8409178 DOI: 10.1158/0008-5472.can-20-3196] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 02/01/2021] [Accepted: 04/09/2021] [Indexed: 11/16/2022]
Abstract
Although lung cancer is known to be caused by environmental factors, it has also been shown to have genetic components, and the genetic etiology of lung cancer remains understudied. We previously identified a lung cancer risk locus on 6q23-25 using microsatellite data in families with a history of lung cancer. To further elucidate that signal, we performed targeted sequencing on nine of our most strongly linked families. Two-point linkage analysis of the sequencing data revealed that the signal was heterogeneous and that different families likely had different risk variants. Three specific haplotypes were shared by some of the families: 6q25.3-26 in families 42 and 44, 6q25.2-25.3 in families 47 and 59, and 6q24.2-25.1 in families 30, 33, and 35. Region-based logarithm of the odds scores and expression data identified the likely candidate genes for each haplotype overlap: ARID1B at 6q25.3, MAP3K4 at 6q26, and UTRN (6q24.1) and PHACTR2 (6q24.2). Further annotation was used to zero in on potential risk variants in those genes. All four genes are good candidate genes for lung cancer risk, having been linked to either lung cancer specifically or other cancers. However, this is the first time any of these genes has been implicated in germline risk. Functional analysis of these four genes is planned for future work. SIGNIFICANCE: This study identifies four genes associated with lung cancer risk, which could help guide future lung cancer prevention and treatment approaches.
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Affiliation(s)
- Anthony M Musolf
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, Maryland
| | - Claire L Simpson
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, Maryland
- Department of Genetics, Genomics and Informatics and Department of Ophthalmology, University of Tennessee Health Science Center, Memphis, Tennessee
| | - Bilal A Moiz
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, Maryland
| | | | - Candace D Middlebrooks
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, Maryland
| | - Diptasri Mandal
- Department of Genetics, Louisiana State University Health Science Center, New Orleans, Louisiana
| | | | - Michael D Cole
- Geisel School of Medicine, Dartmouth College, Lebanon, New Hampshire
| | - Colette Gaba
- Department of Medicine, University of Toledo Dana Cancer Center, Toledo, Ohio
| | | | - Ming You
- Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Yafang Li
- Baylor College of Medicine, Houston, Texas
| | | | | | - Ann G Schwartz
- Karmanos Cancer Institute, Wayne State University, Detroit, Michigan
| | - Susan M Pinney
- Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, Ohio
| | | | - Joan E Bailey-Wilson
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, Maryland.
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Bissahoyo AC, Xie Y, Yang L, Pearsall RS, Lee D, Elliott RW, Demant P, McMillan L, Pardo-Manuel de Villena F, Angel JM, Threadgill DW. A New Polygenic Model for Nonfamilial Colorectal Cancer Inheritance Based on the Genetic Architecture of the Azoxymethane-Induced Mouse Model. Genetics 2020; 214:691-702. [PMID: 31879319 PMCID: PMC7054011 DOI: 10.1534/genetics.119.302833] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 12/23/2019] [Indexed: 12/13/2022] Open
Abstract
The azoxymethane model of colorectal cancer (CRC) was used to gain insights into the genetic heterogeneity of nonfamilial CRC. We observed significant differences in susceptibility parameters across 40 mouse inbred strains, with 6 new and 18 of 24 previously identified mouse CRC modifier alleles detected using genome-wide association analysis. Tumor incidence varied in F1 as well as intercrosses and backcrosses between resistant and susceptible strains. Analysis of inheritance patterns indicates that resistance to CRC development is inherited as a dominant characteristic genome-wide, and that susceptibility appears to occur in individuals lacking a large-effect, or sufficient numbers of small-effect, polygenic resistance alleles. Our results suggest a new polygenic model for inheritance of nonfamilial CRC, and that genetic studies in humans aimed at identifying individuals with elevated susceptibility should be pursued through the lens of absence of dominant resistance alleles rather than for the presence of susceptibility alleles.
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Affiliation(s)
- Anika C Bissahoyo
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Yuying Xie
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Lynda Yang
- Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina 27599
| | - R Scott Pearsall
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Daekee Lee
- Division of Life and Pharmaceutical Sciences, Ewha Womans University, Seoul, 03760 South Korea
| | - Rosemary W Elliott
- Department of Molecular and Cellular Biology, Roswell Park Cancer Institute, Buffalo, New York 14263
| | - Peter Demant
- Department of Molecular and Cellular Biology, Roswell Park Cancer Institute, Buffalo, New York 14263
| | - Leonard McMillan
- Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina 27599
| | | | - Joe M Angel
- Department of Molecular and Cellular Medicine, Texas A&M University, College Station, Texas 77843
| | - David W Threadgill
- Department of Molecular and Cellular Medicine, Texas A&M University, College Station, Texas 77843
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas 77843
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