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Chen Y, Xu F, Munkhsaikhan U, Boyle C, Borcky T, Zhao W, Purevjav E, Towbin JA, Liao F, Williams RW, Bhattacharya SK, Lu L, Sun Y. Identifying modifier genes for hypertrophic cardiomyopathy. J Mol Cell Cardiol 2020; 144:119-126. [DOI: 10.1016/j.yjmcc.2020.05.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 04/29/2020] [Accepted: 05/11/2020] [Indexed: 12/19/2022]
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An Age-Related Hearing Protection Locus on Chromosome 16 of BXD Strain Mice. Neural Plast 2020; 2020:8889264. [PMID: 32587610 PMCID: PMC7298343 DOI: 10.1155/2020/8889264] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 05/15/2020] [Accepted: 05/21/2020] [Indexed: 12/21/2022] Open
Abstract
Inbred mouse models are widely used to study age-related hearing loss (AHL). Many genes associated with AHL have been mapped in a variety of strains. However, little is known about gene variants that have the converse function—protective genes that confer strong resistance to hearing loss. Previously, we reported that C57BL/6J (B6) and DBA/2J (D2) strains share a common hearing loss allele in Cdh23. The cadherin 23 (Cdh23) gene is a key contributor to early-onset hearing loss in humans. In this study, we tested hearing across a large family of 54 BXD strains generated from B6 to D2 crosses. Five of 54 strains maintain the normal threshold (20 dB SPL) even at 2 years old—an age at which both parental strains are essentially deaf. Further analyses revealed an age-related hearing protection (ahp) locus on chromosome 16 (Chr 16) at 57~76 Mb with a maximum LOD of 5.7. A small number of BXD strains at 2 years with good hearing correspond roughly to the percentage of humans who have good hearing at 90 years old. Further studies to define candidate genes in the ahp locus and related molecular mechanisms involved in age-related resilience or resistance to AHL are warranted.
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Lin YJ, Cheng CF, Wang CH, Liang WM, Tang CH, Tsai LP, Chen CH, Wu JY, Hsieh AR, Lee MTM, Lin TH, Liao CC, Huang SM, Zhang Y, Tsai CH, Tsai FJ. Genetic Architecture Associated With Familial Short Stature. J Clin Endocrinol Metab 2020; 105:5805154. [PMID: 32170311 DOI: 10.1210/clinem/dgaa131] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Accepted: 03/10/2020] [Indexed: 12/21/2022]
Abstract
CONTEXT Human height is an inheritable, polygenic trait under complex and multilocus genetic regulation. Familial short stature (FSS; also called genetic short stature) is the most common type of short stature and is insufficiently known. OBJECTIVE To investigate the FSS genetic profile and develop a polygenic risk predisposition score for FSS risk prediction. DESIGN AND SETTING The FSS participant group of Han Chinese ancestry was diagnosed by pediatric endocrinologists in Taiwan. PATIENTS AND INTERVENTIONS The genetic profiles of 1163 participants with FSS were identified by using a bootstrapping subsampling and genome-wide association studies (GWAS) method. MAIN OUTCOME MEASURES Genetic profile, polygenic risk predisposition score for risk prediction. RESULTS Ten novel genetic single nucleotide polymorphisms (SNPs) and 9 reported GWAS human height-related SNPs were identified for FSS risk. These 10 novel SNPs served as a polygenic risk predisposition score for FSS risk prediction (area under the curve: 0.940 in the testing group). This FSS polygenic risk predisposition score was also associated with the height reduction regression tendency in the general population. CONCLUSION A polygenic risk predisposition score composed of 10 genetic SNPs is useful for FSS risk prediction and the height reduction tendency. Thus, it might contribute to FSS risk in the Han Chinese population from Taiwan.
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Affiliation(s)
- Ying-Ju Lin
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
- School of Chinese Medicine, China Medical University, Taichung, Taiwan
| | - Chi-Fung Cheng
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
- Department of Health Services Administration, China Medical University, Taichung, Taiwan
| | - Chung-Hsing Wang
- Children's Hospital of China Medical University, Taichung, Taiwan
| | - Wen-Miin Liang
- Department of Health Services Administration, China Medical University, Taichung, Taiwan
| | - Chih-Hsin Tang
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan
| | - Li-Ping Tsai
- Department of Pediatrics, Taipei Tzu Chi Hospital, New Taipei City, Taiwan
| | - Chien-Hsiun Chen
- School of Chinese Medicine, China Medical University, Taichung, Taiwan
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Jer-Yuarn Wu
- School of Chinese Medicine, China Medical University, Taichung, Taiwan
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Ai-Ru Hsieh
- Department of Statistics, Tamkang University, New Taipei City, Taiwan
| | | | - Ting-Hsu Lin
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Chiu-Chu Liao
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Shao-Mei Huang
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Yanfei Zhang
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania, USA
| | - Chang-Hai Tsai
- Department of Biotechnology and Bioinformatics, Asia University, Taichung, Taiwan
| | - Fuu-Jen Tsai
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
- School of Chinese Medicine, China Medical University, Taichung, Taiwan
- Children's Hospital of China Medical University, Taichung, Taiwan
- Department of Biotechnology and Bioinformatics, Asia University, Taichung, Taiwan
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54
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Zhai C, Djimsa BA, Prenni JE, Woerner DR, Belk KE, Nair MN. Tandem mass tag labeling to characterize muscle-specific proteome changes in beef during early postmortem period. J Proteomics 2020; 222:103794. [DOI: 10.1016/j.jprot.2020.103794] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Revised: 04/15/2020] [Accepted: 04/20/2020] [Indexed: 02/06/2023]
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Hosur V, Skelly DA, Francis C, Low BE, Kohar V, Burzenski LM, Amiji MM, Shultz LD, Wiles MV. Improved mouse models and advanced genetic and genomic technologies for the study of neutrophils. Drug Discov Today 2020; 25:1013-1025. [PMID: 32387410 DOI: 10.1016/j.drudis.2020.03.018] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Revised: 03/16/2020] [Accepted: 03/30/2020] [Indexed: 12/31/2022]
Abstract
Mice have been excellent surrogates for studying neutrophil biology and, furthermore, murine models of human disease have provided fundamental insights into the roles of human neutrophils in innate immunity. The emergence of novel humanized mice and high-diversity mouse populations offers the research community innovative and powerful platforms for better understanding, respectively, the mechanisms by which human neutrophils drive pathogenicity, and how genetic differences underpin the variation in neutrophil biology observed among humans. Here, we review key examples of these new resources. Additionally, we provide an overview of advanced genetic engineering tools available to further improve such murine model systems, of sophisticated neutrophil-profiling technologies, and of multifunctional nanoparticle (NP)-based neutrophil-targeting strategies.
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Affiliation(s)
- Vishnu Hosur
- The Jackson Laboratory for Mammalian Genetics, 600 Main Street, Bar Harbor, ME 04609 USA.
| | - Daniel A Skelly
- The Jackson Laboratory for Mammalian Genetics, 600 Main Street, Bar Harbor, ME 04609 USA
| | - Christopher Francis
- Department of Pharmaceutical Sciences, School of Pharmacy, Northeastern University, 360 Huntington Avenue, Boston, MA 02115 USA
| | - Benjamin E Low
- The Jackson Laboratory for Mammalian Genetics, 600 Main Street, Bar Harbor, ME 04609 USA
| | - Vivek Kohar
- The Jackson Laboratory for Mammalian Genetics, 600 Main Street, Bar Harbor, ME 04609 USA
| | - Lisa M Burzenski
- The Jackson Laboratory for Mammalian Genetics, 600 Main Street, Bar Harbor, ME 04609 USA
| | - Mansoor M Amiji
- Department of Pharmaceutical Sciences, School of Pharmacy, Northeastern University, 360 Huntington Avenue, Boston, MA 02115 USA
| | - Leonard D Shultz
- The Jackson Laboratory for Mammalian Genetics, 600 Main Street, Bar Harbor, ME 04609 USA
| | - Michael V Wiles
- The Jackson Laboratory for Mammalian Genetics, 600 Main Street, Bar Harbor, ME 04609 USA
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56
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Molenaars M, Janssens GE, Williams EG, Jongejan A, Lan J, Rabot S, Joly F, Moerland PD, Schomakers BV, Lezzerini M, Liu YJ, McCormick MA, Kennedy BK, van Weeghel M, van Kampen AHC, Aebersold R, MacInnes AW, Houtkooper RH. A Conserved Mito-Cytosolic Translational Balance Links Two Longevity Pathways. Cell Metab 2020; 31:549-563.e7. [PMID: 32084377 PMCID: PMC7214782 DOI: 10.1016/j.cmet.2020.01.011] [Citation(s) in RCA: 71] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Revised: 08/22/2019] [Accepted: 01/22/2020] [Indexed: 12/13/2022]
Abstract
Slowing down translation in either the cytosol or the mitochondria is a conserved longevity mechanism. Here, we found a non-interventional natural correlation of mitochondrial and cytosolic ribosomal proteins (RPs) in mouse population genetics, suggesting a translational balance. Inhibiting mitochondrial translation in C. elegans through mrps-5 RNAi repressed cytosolic translation. Transcriptomics integrated with proteomics revealed that this inhibition specifically reduced translational efficiency of mRNAs required in growth pathways while increasing stress response mRNAs. The repression of cytosolic translation and extension of lifespan from mrps-5 RNAi were dependent on atf-5/ATF4 and independent from metabolic phenotypes. We found the translational balance to be conserved in mammalian cells upon inhibiting mitochondrial translation pharmacologically with doxycycline. Lastly, extending this in vivo, doxycycline repressed cytosolic translation in the livers of germ-free mice. These data demonstrate that inhibiting mitochondrial translation initiates an atf-5/ATF4-dependent cascade leading to coordinated repression of cytosolic translation, which could be targeted to promote longevity.
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Affiliation(s)
- Marte Molenaars
- Laboratory Genetic Metabolic Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam Gastroenterology and Metabolism, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Georges E Janssens
- Laboratory Genetic Metabolic Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam Gastroenterology and Metabolism, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Evan G Williams
- Institute of Molecular Systems Biology, ETH Zurich, Zürich, Switzerland
| | - Aldo Jongejan
- Bioinformatics Laboratory, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Jiayi Lan
- Institute of Molecular Systems Biology, ETH Zurich, Zürich, Switzerland
| | - Sylvie Rabot
- Micalis Institute, INRA, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, France
| | - Fatima Joly
- Micalis Institute, INRA, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, France
| | - Perry D Moerland
- Bioinformatics Laboratory, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Bauke V Schomakers
- Laboratory Genetic Metabolic Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam Gastroenterology and Metabolism, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands; Core Facility Metabolomics, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Marco Lezzerini
- Laboratory Genetic Metabolic Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam Gastroenterology and Metabolism, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Yasmine J Liu
- Laboratory Genetic Metabolic Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam Gastroenterology and Metabolism, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Mark A McCormick
- Department of Biochemistry and Molecular Biology, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, USA; Autophagy, Inflammation, and Metabolism Center of Biological Research Excellence, University of New Mexico Health Sciences Center, Albuquerque, NM, USA
| | - Brian K Kennedy
- Buck Institute for Research on Aging, Novato, CA, USA; Departments of Biochemistry and Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Michel van Weeghel
- Laboratory Genetic Metabolic Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam Gastroenterology and Metabolism, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands; Core Facility Metabolomics, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Antoine H C van Kampen
- Bioinformatics Laboratory, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Ruedi Aebersold
- Institute of Molecular Systems Biology, ETH Zurich, Zürich, Switzerland; Faculty of Science, University of Zürich, Switzerland
| | - Alyson W MacInnes
- Laboratory Genetic Metabolic Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam Gastroenterology and Metabolism, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Riekelt H Houtkooper
- Laboratory Genetic Metabolic Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam Gastroenterology and Metabolism, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands.
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57
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Stiemke AB, Sah E, Simpson RN, Lu L, Williams RW, Jablonski MM. Systems Genetics of Optic Nerve Axon Necrosis During Glaucoma. Front Genet 2020; 11:31. [PMID: 32174956 PMCID: PMC7056908 DOI: 10.3389/fgene.2020.00031] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Accepted: 01/09/2020] [Indexed: 12/28/2022] Open
Abstract
In this study, we identify genomic regions that modulate the number of necrotic axons in optic nerves of a family of mice, some of which have severe glaucoma, and define a set of high priority positional candidate genes that modulate retinal ganglion cell (RGC) axonal degeneration. A large cohort of the BXD family were aged to greater than 13 months of age. Optic nerves from 74 strains and the DBA/2J (D2) parent were harvested, sectioned, and stained with p-phenylenediamine. Numbers of necrotic axons per optic nerve cross-section were counted from 1 to 10 replicates per genotype. Strain means and standard errors were uploaded into GeneNetwork 2 for mapping and systems genetics analyses (Trait 18614). The number of necrotic axons per nerve ranged from only a few hundred to more than 4,000. Using conventional interval mapping as well as linear mixed model mapping, we identified a single locus on chromosome 12 between 109 and 112.5 Mb with a likelihood ratio statistic (LRS) of ~18.5 (p genome-wide ~0.1). Axon necrosis is not linked to locations of major known glaucoma genes in this family, including Gpnmb, Tyrp1, Cdh11, Pou6f2, and Cacna2d1. This indicates that although these genes contribute to pigmentary dispersion or elevated IOP, none directly modulates axon necrosis. Of 156 positional candidates, eight genes—CDC42 binding protein kinase beta (Cdc42bpb); eukaryotic translation initiation factor 5 (Eif5); BCL2-associated athanogene 5 (Bag5); apoptogenic 1, mitochondrial (Apopt1); kinesin light chain 1 (Klc1); X-ray repair cross complementing 3 (Xrcc3); protein phosphatase 1, regulatory subunit 13B (Ppp1r13b); and transmembrane protein 179 (Tmem179)—passed stringent criteria and are high priority candidates. Several candidates are linked to mitochondria and/or axons, strengthening their plausible role as modulators of ON necrosis. Additional studies are required to validate and/or eliminate plausible candidates. Surprisingly, IOP and ON necrosis are inversely correlated across the BXD family in mice >13 months of age and these two traits share few genes among their top ocular and retinal correlates. These data suggest that the two traits are independently modulated or that a more complex and multifaceted approach is required to reveal their association.
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Affiliation(s)
- Andrew B Stiemke
- Department of Genetics, Genomics and Informatics, The University of Tennessee Health Science Center, Memphis, TN, United States
| | - Eric Sah
- Department of Ophthalmology, The Hamilton Eye Institute, The University of Tennessee Health Science Center, Memphis, TN, United States
| | - Raven N Simpson
- Department of Ophthalmology, The Hamilton Eye Institute, The University of Tennessee Health Science Center, Memphis, TN, United States
| | - Lu Lu
- Department of Genetics, Genomics and Informatics, The University of Tennessee Health Science Center, Memphis, TN, United States
| | - Robert W Williams
- Department of Genetics, Genomics and Informatics, The University of Tennessee Health Science Center, Memphis, TN, United States.,Department of Ophthalmology, The Hamilton Eye Institute, The University of Tennessee Health Science Center, Memphis, TN, United States
| | - Monica M Jablonski
- Department of Ophthalmology, The Hamilton Eye Institute, The University of Tennessee Health Science Center, Memphis, TN, United States
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58
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Mouse Systems Genetics as a Prelude to Precision Medicine. Trends Genet 2020; 36:259-272. [PMID: 32037011 DOI: 10.1016/j.tig.2020.01.004] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Revised: 01/06/2020] [Accepted: 01/08/2020] [Indexed: 12/17/2022]
Abstract
Mouse models have been instrumental in understanding human disease biology and proposing possible new treatments. The precise control of the environment and genetic composition of mice allows more rigorous observations, but limits the generalizability and translatability of the results into human applications. In the era of precision medicine, strategies using mouse models have to be revisited to effectively emulate human populations. Systems genetics is one promising paradigm that may promote the transition to novel precision medicine strategies. Here, we review the state-of-the-art resources and discuss how mouse systems genetics helps to understand human diseases and to advance the development of precision medicine, with an emphasis on the existing resources and strategies.
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59
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Xu F, Wang M, Hu S, Zhou Y, Collyer J, Li K, Xu H, Xiao J. Candidate Regulators of Dyslipidemia in Chromosome 1 Substitution Lines Using Liver Co-Expression Profiling Analysis. Front Genet 2020; 10:1258. [PMID: 31998355 PMCID: PMC6962132 DOI: 10.3389/fgene.2019.01258] [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: 08/28/2019] [Accepted: 11/14/2019] [Indexed: 11/13/2022] Open
Abstract
Dyslipidemia is a major risk factor for cardiovascular disease. Although many genetic factors have been unveiled, a large fraction of the phenotypic variance still needs further investigation. Chromosome 1 (Chr 1) harbors multiple gene loci that regulate blood lipid levels, and identifying functional genes in these loci has proved challenging. We constructed a mouse population, Chr 1 substitution lines (C1SLs), where only Chr 1 differs from the recipient strain C57BL/6J (B6), while the remaining chromosomes are unchanged. Therefore, any phenotypic variance between C1SLs and B6 can be attributed to the differences in Chr 1. In this study, we assayed plasma lipid and glucose levels in 13 C1SLs and their recipient strain B6. Through weighted gene co-expression network analysis of liver transcriptome and “guilty-by-association” study, eight associated modules of plasma lipid and glucose were identified. Further joint analysis of human genome wide association studies revealed 48 candidate genes. In addition, 38 genes located on Chr 1 were also uncovered, and 13 of which have been functionally validated in mouse models. These results suggest that C1SLs are ideal mouse models to identify functional genes on Chr 1 associated with complex traits, like dyslipidemia, by using gene co-expression network analysis.
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Affiliation(s)
- Fuyi Xu
- College of Chemistry, Chemical Engineering, and Biotechnology, Donghua University, Shanghai, China
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Maochun Wang
- College of Chemistry, Chemical Engineering, and Biotechnology, Donghua University, Shanghai, China
| | - Shixian Hu
- Department of Gastroenterology and Hepatology, University of Groningen and University Medical Center Groningen, Groningen, Netherlands
| | - Yuxun Zhou
- College of Chemistry, Chemical Engineering, and Biotechnology, Donghua University, Shanghai, China
| | - John Collyer
- Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Kai Li
- College of Chemistry, Chemical Engineering, and Biotechnology, Donghua University, Shanghai, China
| | - Hongyan Xu
- Department of Biostatistics and Epidemiology, Medical College of Georgia, Augusta University, Augusta, GA, United States
| | - Junhua Xiao
- College of Chemistry, Chemical Engineering, and Biotechnology, Donghua University, Shanghai, China
- *Correspondence: Junhua Xiao,
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60
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Lu L, Huang J, Xu F, Xiao Z, Wang J, Zhang B, David NV, Arends D, Gu W, Ackert-Bicknell C, Sabik OL, Farber CR, Quarles LD, Williams RW. Genetic Dissection of Femoral and Tibial Microarchitecture. JBMR Plus 2019; 3:e10241. [PMID: 31844829 PMCID: PMC6894729 DOI: 10.1002/jbm4.10241] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Revised: 09/09/2019] [Accepted: 09/16/2019] [Indexed: 12/29/2022] Open
Abstract
Our understanding of the genetic control of bone strength has relied mainly on estimates of bone mineral density. Here we have mapped genetic factors that influence femoral and tibial microarchitecture using high‐resolution x‐ray computed tomography (8‐μm isotropic voxels) across a family of 61 BXD strains of mice, roughly 10 isogenic cases per strain and balanced by sex. We computed heritabilities for 25 cortical and trabecular traits. Males and females have well‐matched heritabilities, ranging from 0.25 to 0.75. We mapped 16 genetic loci most of which were detected only in females. There is also a bias in favor of loci that control cortical rather than trabecular bone. To evaluate candidate genes, we combined well‐established gene ontologies with bone transcriptome data to compute bone‐enrichment scores for all protein‐coding genes. We aligned candidates with those of human genome‐wide association studies. A subset of 50 strong candidates fell into three categories: (1) experimentally validated genes already known to modulate bone function (Adamts4, Ddr2, Darc, Adam12, Fkbp10, E2f6, Adam17, Grem2, Ifi204); (2) candidates without any experimentally validated function in bone (eg, Greb1, Ifi202b), but linked to skeletal phenotypes in human cohorts; and (3) candidates that have high bone‐enrichment scores, but for which there is not yet any functional link to bone biology or skeletal system disease (including Ifi202b, Ly9, Ifi205, Mgmt, F2rl1, Iqgap2). Our results highlight contrasting genetic architecture between sexes and among major bone compartments. The alignment of murine and human data facilitates function analysis and should prove of value for preclinical testing of molecular control of bone structure. © 2019 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research.
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Affiliation(s)
- Lu Lu
- Department of Genetics, Genomics and Informatics University of Tennessee Health Science Center Memphis TN USA
| | - Jinsong Huang
- Department of Genetics, Genomics and Informatics University of Tennessee Health Science Center Memphis TN USA
| | - Fuyi Xu
- Department of Genetics, Genomics and Informatics University of Tennessee Health Science Center Memphis TN USA
| | - Zhousheng Xiao
- Department of Medicine University of Tennessee Health Science Center Memphis TN USA
| | - Jing Wang
- Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA
| | - Bing Zhang
- Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA
| | - Nicolae Valentin David
- Department of Medicine Northwestern University Feinberg School of Medicine Chicago IL USA
| | - Danny Arends
- Breeding Biology and Molecular Animal Breeding Humboldt University Berlin Germany
| | - Weikuan Gu
- Department of Orthopaedic Surgery and Biomedical Engineering University of Tennessee Health Science Center Memphis TN USA
| | | | - Olivia L Sabik
- Center for Public Health Genomics University of Virginia Charlottesville VA USA
| | - Charles R Farber
- Center for Public Health Genomics University of Virginia Charlottesville VA USA
| | - Leigh Darryl Quarles
- Department of Medicine University of Tennessee Health Science Center Memphis TN USA
| | - Robert W Williams
- Department of Genetics, Genomics and Informatics University of Tennessee Health Science Center Memphis TN USA
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Diet modulates cecum bacterial diversity and physiological phenotypes across the BXD mouse genetic reference population. PLoS One 2019; 14:e0224100. [PMID: 31634382 PMCID: PMC6802831 DOI: 10.1371/journal.pone.0224100] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Accepted: 10/05/2019] [Indexed: 12/02/2022] Open
Abstract
The BXD family has become one of the preeminent genetic reference populations to understand the genetic and environmental control of phenotypic variation. Here we evaluate the responses to different levels of fat in the diet using both chow diet (CD, 13–18% fat) and a high-fat diet (HFD, 45–60% fat). We studied cohorts of BXD strains, both inbred parents C57BL/6J and DBA/2J (commonly known as B6 and D2, respectively), as well as B6D2 and D2B6 reciprocal F1 hybrids. The comparative impact of genetic and dietary factors was analyzed by profiling a range of phenotypes, most prominently their cecum bacterial composition. The parents of the BXDs and F1 hybrids express limited differences in terms of weight and body fat gain on CD. In contrast, the strain differences on HFD are substantial for percent body fat, with DBA/2J accumulating 12.5% more fat than C57BL/6J (P < 0.0001). The F1 hybrids born to DBA/2J dams (D2B6F1) have 10.6% more body fat (P < 0.001) than those born to C57BL/6J dams. Sequence analysis of the cecum microbiota reveals important differences in bacterial composition among BXD family members with a substantial shift in composition caused by HFD. Relative to CD, the HFD induces a decline in diversity at the phylum level with a substantial increase in Firmicutes (+13.8%) and a reduction in Actinobacteria (-7.9%). In the majority of BXD strains, the HFD also increases cecal sIgA (P < 0.0001)—an important component of the adaptive immunity response against microbial pathogens. Host genetics modulates variation in cecum bacterial composition at the genus level in CD, with significant quantitative trait loci (QTLs) for Oscillibacter mapped to Chr 3 (18.7–19.2 Mb, LRS = 21.4) and for Bifidobacterium mapped to Chr 6 (89.21–89.37 Mb, LRS = 19.4). Introduction of HFD served as an environmental suppressor of these QTLs due to a reduction in the contribution of both genera (P < 0.001). Relations among liver metabolites and cecum bacterial composition were predominant in CD cohort, but these correlations do not persist following the shift to HFD. Overall, these findings demonstrate the important impact of environmental/dietary manipulation on the relationships between host genetics, gastrointestinal bacterial composition, immunological parameters, and metabolites—knowledge that will help in the understanding of the causal sources of metabolic disorders.
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Signaling and Regulation of the Mitochondrial Unfolded Protein Response. Cold Spring Harb Perspect Biol 2019; 11:cshperspect.a033944. [PMID: 30617048 DOI: 10.1101/cshperspect.a033944] [Citation(s) in RCA: 95] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
The mitochondrial proteome encompasses more than a thousand proteins, which are encoded by the mitochondrial and nuclear genomes. Mitochondrial biogenesis and network health relies on maintenance of protein import pathways and the protein-folding environment. Cell-extrinsic or -intrinsic stressors that challenge mitochondrial proteostasis negatively affect organellar function. During conditions of stress, cells use impaired protein import as a sensor for mitochondrial dysfunction to activate a stress response called the mitochondrial unfolded protein response (UPRmt). UPRmt activation leads to an adaptive transcriptional program that promotes mitochondrial recovery, metabolic adaptations, and innate immunity. In this review, we discuss the regulation of UPRmt activation as well as its role in maintaining mitochondrial homeostasis in physiological and pathological scenarios.
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63
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Saul MC, Philip VM, Reinholdt LG, Chesler EJ. High-Diversity Mouse Populations for Complex Traits. Trends Genet 2019; 35:501-514. [PMID: 31133439 DOI: 10.1016/j.tig.2019.04.003] [Citation(s) in RCA: 102] [Impact Index Per Article: 20.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 04/19/2019] [Accepted: 04/22/2019] [Indexed: 12/21/2022]
Abstract
Contemporary mouse genetic reference populations are a powerful platform to discover complex disease mechanisms. Advanced high-diversity mouse populations include the Collaborative Cross (CC) strains, Diversity Outbred (DO) stock, and their isogenic founder strains. When used in systems genetics and integrative genomics analyses, these populations efficiently harnesses known genetic variation for precise and contextualized identification of complex disease mechanisms. Extensive genetic, genomic, and phenotypic data are already available for these high-diversity mouse populations and a growing suite of data analysis tools have been developed to support research on diverse mice. This integrated resource can be used to discover and evaluate disease mechanisms relevant across species.
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Affiliation(s)
- Michael C Saul
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA
| | - Vivek M Philip
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA
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- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA; UNC Chapel Hill, Chapel Hill, NC, USA; SUNY Binghamton, Binghamton, NY, USA; Pittsburgh University, Pittsburgh, PA, USA
| | - Elissa J Chesler
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA.
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64
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Parks C, Giorgianni F, Jones BC, Beranova-Giorgianni S, Moore Ii BM, Mulligan MK. Comparison and Functional Genetic Analysis of Striatal Protein Expression Among Diverse Inbred Mouse Strains. Front Mol Neurosci 2019; 12:128. [PMID: 31178692 PMCID: PMC6543464 DOI: 10.3389/fnmol.2019.00128] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2019] [Accepted: 05/01/2019] [Indexed: 11/19/2022] Open
Abstract
C57BL/6J (B6) and DBA/2J (D2) inbred mouse strains are highly variable genetically and differ in a large number of behavioral traits related to striatal function, including depression, anxiety, stress response, and response to drugs of abuse. The genetic basis of these phenotypic differences are, however, unknown. Here, we present a comparison of the striatal proteome between B6 and D2 and relate differences at the protein level to strain differences at the mRNA level. We also leverage a recombinant inbred BXD population derived from B6 and D2 strains to investigate the role of genetic variation on the regulation of mRNA and protein levels. Finally, we test the hypothesis that differential protein expression contributes to differential behavioral responses between the B6 and D2 strain. We detected the expression of over 2,500 proteins in membrane-enriched protein fractions from B6 and D2 striatum. Of these, 160 proteins demonstrated significant differential expression between B6 and D2 strains at a 10% false discovery level, including COMT, GABRA2, and cannabinoid receptor 1 (CNR1)—key proteins involved in synaptic transmission and behavioral response. Similar to previous reports, there was little overlap between protein and transcript levels (25%). However, the overlap was greater (51%) for proteins demonstrating genetic regulation of cognate gene expression. We also found that striatal proteins with significantly higher or lower relative expression in B6 and D2 were enriched for dopaminergic and glutamatergic synapses and processes involved in synaptic plasticity [e.g., long-term potentiation (LTP) and long-term depression (LTD)]. Finally, we validated higher expression of CNR1 in B6 striatum and demonstrated greater sensitivity of this strain to the locomotor inhibiting effects of the CNR1 agonist, Δ9-tetrahydrocannabinol (THC). Our study is the first comparison of differences in striatal proteins between the B6 and D2 strains and suggests that alterations in the striatal proteome may underlie strain differences in related behaviors, such as drug response. Furthermore, we propose that genetic variants that impact transcript levels are more likely to also exhibit differential expression at the protein level.
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Affiliation(s)
- Cory Parks
- Department of Genetics, Genomics and Informatics, College of Medicine, University of Tennessee Health Science Center (UTHSC), Memphis, TN, United States
| | - Francesco Giorgianni
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Tennessee Health Science Center (UTHSC), Memphis, TN, United States
| | - Byron C Jones
- Department of Genetics, Genomics and Informatics, College of Medicine, University of Tennessee Health Science Center (UTHSC), Memphis, TN, United States
| | - Sarka Beranova-Giorgianni
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Tennessee Health Science Center (UTHSC), Memphis, TN, United States
| | - Bob M Moore Ii
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Tennessee Health Science Center (UTHSC), Memphis, TN, United States
| | - Megan K Mulligan
- Department of Genetics, Genomics and Informatics, College of Medicine, University of Tennessee Health Science Center (UTHSC), Memphis, TN, United States
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65
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Terenina EE, Cavigelli S, Mormede P, Zhao W, Parks C, Lu L, Jones BC, Mulligan MK. Genetic Factors Mediate the Impact of Chronic Stress and Subsequent Response to Novel Acute Stress. Front Neurosci 2019; 13:438. [PMID: 31164799 PMCID: PMC6536627 DOI: 10.3389/fnins.2019.00438] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Accepted: 04/16/2019] [Indexed: 12/31/2022] Open
Abstract
Individual differences in physiological and biobehavioral adaptation to chronic stress are important predictors of health and fitness; genetic differences play an important role in this adaptation. To identify these differences we measured the biometric, neuroendocrine, and transcriptional response to stress among inbred mouse strains with varying degrees of genetic similarity, C57BL/6J (B), C57BL/6NJ (N), and DBA/2J (D). The B and D strains are highly genetically diverse whereas the B and N substrains are highly similar. Strain differences in hypothalamic-pituitary-adrenal (HPA) axis cross-sensitization were determined by plasma corticosterone (CORT) levels and hippocampal gene expression following 7-weeks of chronic mild stress (CMS) or normal housing (NH) and subsequent exposure to novel acute restraint. Fecal CORT metabolites and body and organ weights were also measured. All strains exposed to CMS had reduced heart weights, whereas body weight gain was attenuated only in B and N strains. Acute stress alone produced larger plasma CORT responses in the D and N strains compared to the B strain. CMS paired with acute stress produced cross-sensitization of the CORT response in the N strain. The N strain also had the largest number of hippocampal transcripts with up-regulated expression in response to stress. In contrast, the D strain had the largest number of transcripts with down-regulated expression following CMS and acute stress. In summary, we observed differential responses to CMS at both the physiological and molecular level among genetically diverse strains, indicating that genetic factors drive individual differences in experience-dependent regulation of the stress response.
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Affiliation(s)
- Elena E Terenina
- GenPhySE, ENVT, INRA, Université de Toulouse, Castanet-Tolosan, France.,Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Sonia Cavigelli
- Department of Biobehavioral Health, Pennsylvania State University, University Park, PA, United States
| | - Pierre Mormede
- GenPhySE, ENVT, INRA, Université de Toulouse, Castanet-Tolosan, France.,Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Wenyuan Zhao
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Cory Parks
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Lu Lu
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Byron C Jones
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Megan K Mulligan
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
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66
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Yuan J, Tickner J, Mullin BH, Zhao J, Zeng Z, Morahan G, Xu J. Advanced Genetic Approaches in Discovery and Characterization of Genes Involved With Osteoporosis in Mouse and Human. Front Genet 2019; 10:288. [PMID: 31001327 PMCID: PMC6455049 DOI: 10.3389/fgene.2019.00288] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Accepted: 03/18/2019] [Indexed: 12/14/2022] Open
Abstract
Osteoporosis is a complex condition with contributions from, and interactions between, multiple genetic loci and environmental factors. This review summarizes key advances in the application of genetic approaches for the identification of osteoporosis susceptibility genes. Genome-wide linkage analysis (GWLA) is the classical approach for identification of genes that cause monogenic diseases; however, it has shown limited success for complex diseases like osteoporosis. In contrast, genome-wide association studies (GWAS) have successfully identified over 200 osteoporosis susceptibility loci with genome-wide significance, and have provided most of the candidate genes identified to date. Phenome-wide association studies (PheWAS) apply a phenotype-to-genotype approach which can be used to complement GWAS. PheWAS is capable of characterizing the association between osteoporosis and uncommon and rare genetic variants. Another alternative approach, whole genome sequencing (WGS), will enable the discovery of uncommon and rare genetic variants in osteoporosis. Meta-analysis with increasing statistical power can offer greater confidence in gene searching through the analysis of combined results across genetic studies. Recently, new approaches to gene discovery include animal phenotype based models such as the Collaborative Cross and ENU mutagenesis. Site-directed mutagenesis and genome editing tools such as CRISPR/Cas9, TALENs and ZNFs have been used in functional analysis of candidate genes in vitro and in vivo. These resources are revolutionizing the identification of osteoporosis susceptibility genes through the use of genetically defined inbred mouse libraries, which are screened for bone phenotypes that are then correlated with known genetic variation. Identification of osteoporosis-related susceptibility genes by genetic approaches enables further characterization of gene function in animal models, with the ultimate aim being the identification of novel therapeutic targets for osteoporosis.
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Affiliation(s)
- Jinbo Yuan
- School of Biomedical Sciences, The University of Western Australia, Perth, WA, Australia
| | - Jennifer Tickner
- School of Biomedical Sciences, The University of Western Australia, Perth, WA, Australia
| | - Benjamin H Mullin
- School of Biomedical Sciences, The University of Western Australia, Perth, WA, Australia.,Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, Australia
| | - Jinmin Zhao
- Research Centre for Regenerative Medicine, Guangxi Medical University, Nanning, China
| | - Zhiyu Zeng
- The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Grant Morahan
- Centre for Diabetes Research, Harry Perkins Institute of Medical Research, The University of Western Australia, Perth, WA, Australia
| | - Jiake Xu
- School of Biomedical Sciences, The University of Western Australia, Perth, WA, Australia
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67
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Mulligan MK, Abreo T, Neuner SM, Parks C, Watkins CE, Houseal MT, Shapaker TM, Hook M, Tan H, Wang X, Ingels J, Peng J, Lu L, Kaczorowski CC, Bryant CD, Homanics GE, Williams RW. Identification of a Functional Non-coding Variant in the GABA A Receptor α2 Subunit of the C57BL/6J Mouse Reference Genome: Major Implications for Neuroscience Research. Front Genet 2019; 10:188. [PMID: 30984232 PMCID: PMC6449455 DOI: 10.3389/fgene.2019.00188] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Accepted: 02/21/2019] [Indexed: 12/16/2022] Open
Abstract
GABA type-A (GABA-A) receptors containing the α2 subunit (GABRA2) are expressed in most brain regions and are critical in modulating inhibitory synaptic function. Genetic variation at the GABRA2 locus has been implicated in epilepsy, affective and psychiatric disorders, alcoholism and drug abuse. Gabra2 expression varies as a function of genotype and is modulated by sequence variants in several brain structures and populations, including F2 crosses originating from C57BL/6J (B6J) and the BXD recombinant inbred family derived from B6J and DBA/2J. Here we demonstrate a global reduction of GABRA2 brain protein and mRNA in the B6J strain relative to other inbred strains, and identify and validate the causal mutation in B6J. The mutation is a single base pair deletion located in an intron adjacent to a splice acceptor site that only occurs in the B6J reference genome. The deletion became fixed in B6J between 1976 and 1991 and is now pervasive in many engineered lines, BXD strains generated after 1991, the Collaborative Cross, and the majority of consomic lines. Repair of the deletion using CRISPR-Cas9-mediated gene editing on a B6J genetic background completely restored brain levels of GABRA2 protein and mRNA. Comparison of transcript expression in hippocampus, cortex, and striatum between B6J and repaired genotypes revealed alterations in GABA-A receptor subunit expression, especially in striatum. These results suggest that naturally occurring variation in GABRA2 levels between B6J and other substrains or inbred strains may also explain strain differences in anxiety-like or alcohol and drug response traits related to striatal function. Characterization of the B6J private mutation in the Gabra2 gene is of critical importance to molecular genetic studies in neurobiological research because this strain is widely used to generate genetically engineered mice and murine genetic populations, and is the most widely utilized strain for evaluation of anxiety-like, depression-like, pain, epilepsy, and drug response traits that may be partly modulated by GABRA2 function.
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Affiliation(s)
- Megan K Mulligan
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Timothy Abreo
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Sarah M Neuner
- Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, United States.,The Jackson Laboratory, Bar Harbor, ME, United States
| | - Cory Parks
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Christine E Watkins
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - M Trevor Houseal
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Thomas M Shapaker
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Michael Hook
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Haiyan Tan
- Departments of Structural Biology and Developmental Neurobiology, Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, United States
| | - Xusheng Wang
- Departments of Structural Biology and Developmental Neurobiology, Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, United States
| | - Jesse Ingels
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Junmin Peng
- Departments of Structural Biology and Developmental Neurobiology, Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, United States
| | - Lu Lu
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
| | | | - Camron D Bryant
- Laboratory of Addiction Genetics, Department of Pharmacology and Experimental Therapeutics and Psychiatry, Boston University School of Medicine, Boston, MA, United States
| | - Gregg E Homanics
- Departments of Anesthesiology and Perioperative Medicine, Neurobiology, and Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Robert W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
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68
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Neuner SM, Heuer SE, Zhang JG, Philip VM, Kaczorowski CC. Identification of Pre-symptomatic Gene Signatures That Predict Resilience to Cognitive Decline in the Genetically Diverse AD-BXD Model. Front Genet 2019; 10:35. [PMID: 30787942 PMCID: PMC6372563 DOI: 10.3389/fgene.2019.00035] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2018] [Accepted: 01/18/2019] [Indexed: 12/23/2022] Open
Abstract
Across the population, individuals exhibit a wide variation of susceptibility or resilience to developing Alzheimer’s disease (AD). Identifying specific factors that promote resilience would provide insight into disease mechanisms and nominate potential targets for therapeutic intervention. Here, we use transcriptome profiling to identify gene networks present in the pre-symptomatic AD mouse brain relating to neuroinflammation, brain vasculature, extracellular matrix organization, and synaptic signaling that predict cognitive performance at an advanced age. We highlight putative drivers of these observed relationships, including Itgb2, Fcgr2b, Slc6a14, and Gper1, which represent prime targets through which to promote resilience prior to overt symptom onset. In addition, we identify a genomic region on chromosome 2 containing variants that directly modulate resilience network expression. Overall, work here highlights new potential drivers of resilience to AD and contributes significantly to our understanding of early, potentially causal, disease mechanisms.
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Affiliation(s)
- Sarah M Neuner
- University of Tennessee Health Science Center, Memphis, TN, United States.,The Jackson Laboratory, Bar Harbor, ME, United States
| | - Sarah E Heuer
- The Jackson Laboratory, Bar Harbor, ME, United States.,Tufts University Sackler School of Graduate Biomedical Sciences, Boston, MA, United States
| | - Ji-Gang Zhang
- The Jackson Laboratory, Bar Harbor, ME, United States
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69
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Neuner SM, Heuer SE, Huentelman MJ, O'Connell KMS, Kaczorowski CC. Harnessing Genetic Complexity to Enhance Translatability of Alzheimer's Disease Mouse Models: A Path toward Precision Medicine. Neuron 2018; 101:399-411.e5. [PMID: 30595332 DOI: 10.1016/j.neuron.2018.11.040] [Citation(s) in RCA: 132] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Revised: 10/02/2018] [Accepted: 11/20/2018] [Indexed: 01/15/2023]
Abstract
An individual's genetic makeup plays a large role in determining susceptibility to Alzheimer's disease (AD) but has largely been ignored in preclinical studies. To test the hypothesis that incorporating genetic diversity into mouse models of AD would improve translational potential, we combined a well-established mouse model of AD with a genetically diverse reference panel to generate mice that harbor identical high-risk human mutations but differ across the remainder of their genome. We first show that genetic variation profoundly modifies the impact of human AD mutations on both cognitive and pathological phenotypes. We then validate this complex AD model by demonstrating high degrees of genetic, transcriptomic, and phenotypic overlap with human AD. Overall, work here both introduces a novel AD mouse population as an innovative and reproducible resource for the study of mechanisms underlying AD and provides evidence that preclinical models incorporating genetic diversity may better translate to human disease.
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Affiliation(s)
- Sarah M Neuner
- The Neuroscience Institute, University of Tennessee Health Science Center, Memphis, TN 38163, USA; The Jackson Laboratory, Bar Harbor, ME 04609, USA
| | - Sarah E Heuer
- The Jackson Laboratory, Bar Harbor, ME 04609, USA; Sackler School of Graduate Biomedical Sciences, Tufts University, Boston, MA 02111, USA
| | - Matthew J Huentelman
- Neurogenomics Division, Translational Genomics Research Institute, Phoenix, AZ 85004, USA
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70
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Farris SP, Riley BP, Williams RW, Mulligan MK, Miles MF, Lopez MF, Hitzemann R, Iancu OD, Colville A, Walter NAR, Darakjian P, Oberbeck DL, Daunais JB, Zheng CL, Searles RP, McWeeney SK, Grant KA, Mayfield RD. Cross-species molecular dissection across alcohol behavioral domains. Alcohol 2018; 72:19-31. [PMID: 30213503 PMCID: PMC6309876 DOI: 10.1016/j.alcohol.2017.11.036] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2017] [Revised: 11/17/2017] [Accepted: 11/28/2017] [Indexed: 12/14/2022]
Abstract
This review summarizes the proceedings of a symposium presented at the "Alcoholism and Stress: A Framework for Future Treatment Strategies" conference held in Volterra, Italy on May 9-12, 2017. Psychiatric diseases, including alcohol-use disorders (AUDs), are influenced through complex interactions of genes, neurobiological pathways, and environmental influences. A better understanding of the common neurobiological mechanisms underlying an AUD necessitates an integrative approach, involving a systematic assessment of diverse species and phenotype measures. As part of the World Congress on Stress and Alcoholism, this symposium provided a detailed account of current strategies to identify mechanisms underlying the development and progression of AUDs. Dr. Sean Farris discussed the integration and organization of transcriptome and postmortem human brain data to identify brain regional- and cell type-specific differences related to excessive alcohol consumption that are conserved across species. Dr. Brien Riley presented the results of a genome-wide association study of DSM-IV alcohol dependence; although replication of genetic associations with alcohol phenotypes in humans remains challenging, model organism studies show that COL6A3, KLF12, and RYR3 affect behavioral responses to ethanol, and provide substantial evidence for their role in human alcohol-related traits. Dr. Rob Williams expanded upon the systematic characterization of extensive genetic-genomic resources for quantifying and clarifying phenotypes across species that are relevant to precision medicine in human disease. The symposium concluded with Dr. Robert Hitzemann's description of transcriptome studies in a mouse model selectively bred for high alcohol ("binge-like") consumption and a non-human primate model of long-term alcohol consumption. Together, the different components of this session provided an overview of systems-based approaches that are pioneering the experimental prioritization and validation of novel genes and gene networks linked with a range of behavioral phenotypes associated with stress and AUDs.
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Affiliation(s)
- Sean P Farris
- University of Texas at Austin, Austin, TX, United States
| | - Brien P Riley
- Virginia Commonwealth University, Richmond, VA, United States
| | - Robert W Williams
- University of Tennessee Health Science Center, Memphis, TN, United States
| | - Megan K Mulligan
- University of Tennessee Health Science Center, Memphis, TN, United States
| | - Michael F Miles
- University of Tennessee Health Science Center, Memphis, TN, United States
| | - Marcelo F Lopez
- University of Tennessee Health Science Center, Memphis, TN, United States
| | - Robert Hitzemann
- Oregon Health and Science University, Portland, OR, United States
| | - Ovidiu D Iancu
- Oregon Health and Science University, Portland, OR, United States
| | | | | | | | | | - James B Daunais
- Wake Forest School of Medicine, Winston-Salem, NC, United States
| | | | - Robert P Searles
- Oregon Health and Science University, Portland, OR, United States
| | | | - Kathleen A Grant
- Oregon Health and Science University, Portland, OR, United States
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71
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Ashbrook DG, Roy S, Clifford BG, Riede T, Scattoni ML, Heck DH, Lu L, Williams RW. Born to Cry: A Genetic Dissection of Infant Vocalization. Front Behav Neurosci 2018; 12:250. [PMID: 30420800 PMCID: PMC6216097 DOI: 10.3389/fnbeh.2018.00250] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2018] [Accepted: 10/05/2018] [Indexed: 12/15/2022] Open
Abstract
Infant vocalizations are one of the most fundamental and innate forms of behavior throughout avian and mammalian orders. They have a critical role in motivating parental care and contribute significantly to fitness and reproductive success. Dysregulation of these vocalizations has been reported to predict risk of central nervous system pathologies such as hypoxia, meningitis, or autism spectrum disorder. Here, we have used the expanded BXD family of mice, and a diallel cross between DBA/2J and C57BL/6J parental strains, to begin the process of genetically dissecting the numerous facets of infant vocalizations. We calculate heritability, estimate the role of parent-of-origin effects, and identify novel quantitative trait loci (QTLs) that control ultrasonic vocalizations (USVs) on postnatal days 7, 8, and 9; a stage that closely matches human infants at birth. Heritability estimates for the number and frequency of calls are low, suggesting that these traits are under high selective pressure. In contrast, duration and amplitude of calls have higher heritabilities, indicating lower selection, or their importance for kin recognition. We find suggestive evidence that amplitude of infant calls is dependent on the maternal genotype, independent of shared genetic variants. Finally, we identify two loci on Chrs 2 and 14 influencing call frequency, and a third locus on Chr 8 influencing the amplitude of vocalizations. All three loci contain strong candidate genes that merit further analysis. Understanding the genetic control of infant vocalizations is not just important for understanding the evolution of parent–offspring interactions, but also in understanding the earliest innate behaviors, the development of parent–offspring relations, and the early identification of behavioral abnormalities.
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Affiliation(s)
- David George Ashbrook
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Snigdha Roy
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Brittany G Clifford
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Tobias Riede
- Department of Physiology, College of Veterinary Medicine, Midwestern University, Glendale, AZ, United States
| | - Maria Luisa Scattoni
- Research Coordination and Support Service, Istituto Superiore di Sanità, Rome, Italy
| | - Detlef H Heck
- Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Lu Lu
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States.,Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Robert W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States.,Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, United States
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72
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O'Brien MA, Weston RM, Sheth NU, Bradley S, Bigbee J, Pandey A, Williams RW, Wolstenholme JT, Miles MF. Ethanol-Induced Behavioral Sensitization Alters the Synaptic Transcriptome and Exon Utilization in DBA/2J Mice. Front Genet 2018; 9:402. [PMID: 30319688 PMCID: PMC6166094 DOI: 10.3389/fgene.2018.00402] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Accepted: 09/03/2018] [Indexed: 11/15/2022] Open
Abstract
Alcoholism is a complex behavioral disorder characterized by loss of control in limiting intake, and progressive compulsion to seek and consume ethanol. Prior studies have suggested that the characteristic behaviors associated with escalation of drug use are caused, at least in part, by ethanol-evoked changes in gene expression affecting synaptic plasticity. Implicit in this hypothesis is a dependence on new protein synthesis and remodeling at the synapse. It is well established that mRNA can be transported to distal dendritic processes, where it can undergo localized translation. It is unknown whether such modulation of the synaptic transcriptome might contribute to ethanol-induced synaptic plasticity. Using ethanol-induced behavioral sensitization as a model of neuroplasticity, we investigated whether repeated exposure to ethanol altered the synaptic transcriptome, contributing to mechanisms underlying subsequent increases in ethanol-evoked locomotor activity. RNAseq profiling of DBA/2J mice subjected to acute ethanol or ethanol-induced behavioral sensitization was performed on frontal pole synaptoneurosomes to enrich for synaptic mRNA. Genomic profiling showed distinct functional classes of mRNA enriched in the synaptic vs. cytosolic fractions, consistent with their role in synaptic function. Ethanol sensitization regulated more than twice the number of synaptic localized genes compared to acute ethanol exposure. Synaptic biological processes selectively perturbed by ethanol sensitization included protein folding and modification as well as and mitochondrial respiratory function, suggesting repeated ethanol exposure alters synaptic energy production and the processing of newly translated proteins. Additionally, marked differential exon usage followed ethanol sensitization in both synaptic and non-synaptic cellular fractions, with little to no perturbation following acute ethanol exposure. Altered synaptic exon usage following ethanol sensitization strongly affected genes related to RNA processing and stability, translational regulation, and synaptic function. These genes were also enriched for targets of the FMRP RNA-binding protein and contained consensus sequence motifs related to other known RNA binding proteins, suggesting that ethanol sensitization altered selective mRNA trafficking mechanisms. This study provides a foundation for investigating the role of ethanol in modifying the synaptic transcriptome and inducing changes in synaptic plasticity.
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Affiliation(s)
- Megan A O'Brien
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, Richmond, VA, United States
| | - Rory M Weston
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, Richmond, VA, United States
| | - Nihar U Sheth
- VCU Alcohol Research Center, Virginia Commonwealth University, Richmond, VA, United States
| | - Steven Bradley
- VCU Alcohol Research Center, Virginia Commonwealth University, Richmond, VA, United States
| | - John Bigbee
- Department of Anatomy and Neurobiology, Virginia Commonwealth University, Richmond, VA, United States
| | - Ashutosh Pandey
- Department of Genetics, Genomics and Informatics, The University of Tennessee Health Science Center, Memphis, TN, United States
| | - Robert W Williams
- Department of Genetics, Genomics and Informatics, The University of Tennessee Health Science Center, Memphis, TN, United States
| | - Jennifer T Wolstenholme
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, Richmond, VA, United States.,VCU Alcohol Research Center, Virginia Commonwealth University, Richmond, VA, United States
| | - Michael F Miles
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, Richmond, VA, United States.,VCU Alcohol Research Center, Virginia Commonwealth University, Richmond, VA, United States.,Department of Neurology, Virginia Commonwealth University, Richmond, VA, United States
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73
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Williams EG, Wu Y, Wolski W, Kim JY, Lan J, Hasan M, Halter C, Jha P, Ryu D, Auwerx J, Aebersold R. Quantifying and Localizing the Mitochondrial Proteome Across Five Tissues in A Mouse Population. Mol Cell Proteomics 2018; 17:1766-1777. [PMID: 29945935 PMCID: PMC6126393 DOI: 10.1074/mcp.ra118.000554] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Revised: 04/17/2018] [Indexed: 12/12/2022] Open
Abstract
We have used SWATH mass spectrometry to quantify 3648 proteins across 76 proteomes collected from genetically diverse BXD mouse strains in two fractions (mitochondria and total cell) from five tissues: liver, quadriceps, heart, brain, and brown adipose (BAT). Across tissues, expression covariation between genes' proteins and transcripts-measured in the same individuals-broadly aligned. Covariation was however far stronger in certain subsets than others: only 8% of transcripts in the lowest expression and variance quintile covaried with their protein, in contrast to 65% of transcripts in the highest quintiles. Key functional differences among the 3648 genes were also observed across tissues, with electron transport chain (ETC) genes particularly investigated. ETC complex proteins covary and form strong gene networks according to tissue, but their equivalent transcripts do not. Certain physiological consequences, such as the depletion of ATP synthase in BAT, are thus obscured in transcript data. Lastly, we compared the quantitative proteomic measurements between the total cell and mitochondrial fractions for the five tissues. The resulting enrichment score highlighted several hundred proteins which were strongly enriched in mitochondria, which included several dozen proteins were not reported in literature to be mitochondrially localized. Four of these candidates were selected for biochemical validation, where we found MTAP, SOAT2, and IMPDH2 to be localized inside the mitochondria, whereas ABCC6 was in the mitochondria-associated membrane. These findings demonstrate the synergies of a multi-omics approach to study complex metabolic processes, and this provides a resource for further discovery and analysis of proteoforms, modified proteins, and protein localization.
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Affiliation(s)
- Evan G Williams
- From the ‡Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich CH-8093, Switzerland
- §Interfaculty Institute of Bioengineering, Laboratory of Integrative and Systems Physiology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland
| | - Yibo Wu
- From the ‡Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich CH-8093, Switzerland
- **Current address: RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho Tsurumi-ku Yokohama City, Kanagawa, 230-0045, Japan
| | - Witold Wolski
- ¶Functional Genomics Center Zurich, ETH Zurich, Zurich CH-8057, Switzerland
| | - Jun Yong Kim
- §Interfaculty Institute of Bioengineering, Laboratory of Integrative and Systems Physiology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland
| | - Jiayi Lan
- From the ‡Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich CH-8093, Switzerland
| | - Moaraj Hasan
- From the ‡Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich CH-8093, Switzerland
| | - Christian Halter
- From the ‡Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich CH-8093, Switzerland
| | - Pooja Jha
- §Interfaculty Institute of Bioengineering, Laboratory of Integrative and Systems Physiology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland
| | - Dongryeol Ryu
- §Interfaculty Institute of Bioengineering, Laboratory of Integrative and Systems Physiology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland
- ‡‡Current address: Healthy Aging-Korean Medical Research Center, Pusan National University, School of Korean Medicine, Yangsan 50612, Republic of Korea
| | - Johan Auwerx
- §Interfaculty Institute of Bioengineering, Laboratory of Integrative and Systems Physiology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland;
| | - Ruedi Aebersold
- From the ‡Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich CH-8093, Switzerland;
- ‖Faculty of Science, University of Zurich, Zurich CH-8057, Switzerland
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74
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Hook M, Roy S, Williams EG, Bou Sleiman M, Mozhui K, Nelson JF, Lu L, Auwerx J, Williams RW. Genetic cartography of longevity in humans and mice: Current landscape and horizons. Biochim Biophys Acta Mol Basis Dis 2018; 1864:2718-2732. [PMID: 29410319 PMCID: PMC6066442 DOI: 10.1016/j.bbadis.2018.01.026] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Revised: 01/24/2018] [Accepted: 01/28/2018] [Indexed: 12/14/2022]
Abstract
Aging is a complex and highly variable process. Heritability of longevity among humans and other species is low, and this finding has given rise to the idea that it may be futile to search for DNA variants that modulate aging. We argue that the problem in mapping longevity genes is mainly one of low power and the genetic and environmental complexity of aging. In this review we highlight progress made in mapping genes and molecular networks associated with longevity, paying special attention to work in mice and humans. We summarize 40 years of linkage studies using murine cohorts and 15 years of studies in human populations that have exploited candidate gene and genome-wide association methods. A small but growing number of gene variants contribute to known longevity mechanisms, but a much larger set have unknown functions. We outline these and other challenges and suggest some possible solutions, including more intense collaboration between research communities that use model organisms and human cohorts. Once hundreds of gene variants have been linked to differences in longevity in mammals, it will become feasible to systematically explore gene-by-environmental interactions, dissect mechanisms with more assurance, and evaluate the roles of epistasis and epigenetics in aging. A deeper understanding of complex networks-genetic, cellular, physiological, and social-should position us well to improve healthspan.
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Affiliation(s)
- Michael Hook
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Suheeta Roy
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Evan G Williams
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich CH-8093, Switzerland
| | - Maroun Bou Sleiman
- Interfaculty Institute of Bioengineering, Laboratory of Integrative and Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland
| | - Khyobeni Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - James F Nelson
- Department of Cellular and Integrative Physiology and Barshop Institute for Longevity and Aging Studies, The University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA
| | - Lu Lu
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Johan Auwerx
- Interfaculty Institute of Bioengineering, Laboratory of Integrative and Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland
| | - Robert W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA.
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75
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Diessler S, Jan M, Emmenegger Y, Guex N, Middleton B, Skene DJ, Ibberson M, Burdet F, Götz L, Pagni M, Sankar M, Liechti R, Hor CN, Xenarios I, Franken P. A systems genetics resource and analysis of sleep regulation in the mouse. PLoS Biol 2018; 16:e2005750. [PMID: 30091978 PMCID: PMC6085075 DOI: 10.1371/journal.pbio.2005750] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2018] [Accepted: 07/06/2018] [Indexed: 12/30/2022] Open
Abstract
Sleep is essential for optimal brain functioning and health, but the biological substrates through which sleep delivers these beneficial effects remain largely unknown. We used a systems genetics approach in the BXD genetic reference population (GRP) of mice and assembled a comprehensive experimental knowledge base comprising a deep "sleep-wake" phenome, central and peripheral transcriptomes, and plasma metabolome data, collected under undisturbed baseline conditions and after sleep deprivation (SD). We present analytical tools to interactively interrogate the database, visualize the molecular networks altered by sleep loss, and prioritize candidate genes. We found that a one-time, short disruption of sleep already extensively reshaped the systems genetics landscape by altering 60%-78% of the transcriptomes and the metabolome, with numerous genetic loci affecting the magnitude and direction of change. Systems genetics integrative analyses drawing on all levels of organization imply α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor trafficking and fatty acid turnover as substrates of the negative effects of insufficient sleep. Our analyses demonstrate that genetic heterogeneity and the effects of insufficient sleep itself on the transcriptome and metabolome are far more widespread than previously reported.
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Affiliation(s)
- Shanaz Diessler
- Center for Integrative Genomics, University of Lausanne, Switzerland
| | - Maxime Jan
- Center for Integrative Genomics, University of Lausanne, Switzerland
- Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Yann Emmenegger
- Center for Integrative Genomics, University of Lausanne, Switzerland
| | - Nicolas Guex
- Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Benita Middleton
- Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom
| | - Debra J. Skene
- Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom
| | - Mark Ibberson
- Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Frederic Burdet
- Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Lou Götz
- Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Marco Pagni
- Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Martial Sankar
- Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Robin Liechti
- Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Charlotte N. Hor
- Center for Integrative Genomics, University of Lausanne, Switzerland
| | - Ioannis Xenarios
- Center for Integrative Genomics, University of Lausanne, Switzerland
- Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Paul Franken
- Center for Integrative Genomics, University of Lausanne, Switzerland
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76
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Systems Analyses Reveal Physiological Roles and Genetic Regulators of Liver Lipid Species. Cell Syst 2018; 6:722-733.e6. [PMID: 29909277 DOI: 10.1016/j.cels.2018.05.016] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Revised: 04/24/2018] [Accepted: 05/11/2018] [Indexed: 12/11/2022]
Abstract
The genetics of individual lipid species and their relevance in disease is largely unresolved. We profiled a subset of storage, signaling, membrane, and mitochondrial liver lipids across 385 mice from 47 strains of the BXD mouse population fed chow or high-fat diet and integrated these data with complementary multi-omics datasets. We identified several lipid species and lipid clusters with specific phenotypic and molecular signatures and, in particular, cardiolipin species with signatures of healthy and fatty liver. Genetic analyses revealed quantitative trait loci for 68% of the lipids (lQTL). By multi-layered omics analyses, we show the reliability of lQTLs to uncover candidate genes that can regulate the levels of lipid species. Additionally, we identified lQTLs that mapped to genes associated with abnormal lipid metabolism in human GWASs. This work provides a foundation and resource for understanding the genetic regulation and physiological significance of lipid species.
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77
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Jha P, McDevitt MT, Halilbasic E, Williams EG, Quiros PM, Gariani K, Sleiman MB, Gupta R, Ulbrich A, Jochem A, Coon JJ, Trauner M, Pagliarini DJ, Auwerx J. Genetic Regulation of Plasma Lipid Species and Their Association with Metabolic Phenotypes. Cell Syst 2018; 6:709-721.e6. [PMID: 29909275 PMCID: PMC6397773 DOI: 10.1016/j.cels.2018.05.009] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Revised: 04/24/2018] [Accepted: 05/11/2018] [Indexed: 02/07/2023]
Abstract
The genetic regulation and physiological impact of most lipid species are unexplored. Here, we profiled 129 plasma lipid species across 49 strains of the BXD mouse genetic reference population fed either chow or a high-fat diet. By integrating these data with genomics and phenomics datasets, we elucidated genes by environment (diet) interactions that regulate systemic metabolism. We found quantitative trait loci (QTLs) for ~94% of the lipids measured. Several QTLs harbored genes associated with blood lipid levels and abnormal lipid metabolism in human genome-wide association studies. Lipid species from different classes provided signatures of metabolic health, including seven plasma triglyceride species that associated with either healthy or fatty liver. This observation was further validated in an independent mouse model of non-alcoholic fatty liver disease (NAFLD) and in plasma from NAFLD patients. This work provides a resource to identify plausible genes regulating the measured lipid species and their association with metabolic traits. Jha et al. provide a resource of genetic loci regulating individual plasma lipid species identified by studying a large mouse population and demonstrate the potential of lipid species to reflect metabolic health status of individuals. Several lipid-regulating loci in the mouse population harbor genes associated with abnormal lipid metabolism in human GWAS. The potential of lipid species to reflect health status was validated in dietary and therapeutic models of NAFLD in mice and human NAFLD patients.
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Affiliation(s)
- Pooja Jha
- Laboratory of Integrative and Systems Physiology, École Polytchnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Molly T McDevitt
- Morgridge Institute for Research, Madison, WI 53715, USA; Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Emina Halilbasic
- Hans Popper Laboratory of Molecular Hepatology, Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria
| | - Evan G Williams
- Laboratory of Integrative and Systems Physiology, École Polytchnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Pedro M Quiros
- Laboratory of Integrative and Systems Physiology, École Polytchnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Karim Gariani
- Laboratory of Integrative and Systems Physiology, École Polytchnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Maroun B Sleiman
- Laboratory of Integrative and Systems Physiology, École Polytchnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Rahul Gupta
- Morgridge Institute for Research, Madison, WI 53715, USA
| | - Arne Ulbrich
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Adam Jochem
- Morgridge Institute for Research, Madison, WI 53715, USA
| | - Joshua J Coon
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA; Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Michael Trauner
- Hans Popper Laboratory of Molecular Hepatology, Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria
| | - David J Pagliarini
- Morgridge Institute for Research, Madison, WI 53715, USA; Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA.
| | - Johan Auwerx
- Laboratory of Integrative and Systems Physiology, École Polytchnique Fédérale de Lausanne, Lausanne 1015, Switzerland.
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78
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Li J, Dawson PA. Animal models to study bile acid metabolism. Biochim Biophys Acta Mol Basis Dis 2018; 1865:895-911. [PMID: 29782919 DOI: 10.1016/j.bbadis.2018.05.011] [Citation(s) in RCA: 132] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Revised: 05/11/2018] [Accepted: 05/14/2018] [Indexed: 12/19/2022]
Abstract
The use of animal models, particularly genetically modified mice, continues to play a critical role in studying the relationship between bile acid metabolism and human liver disease. Over the past 20 years, these studies have been instrumental in elucidating the major pathways responsible for bile acid biosynthesis and enterohepatic cycling, and the molecular mechanisms regulating those pathways. This work also revealed bile acid differences between species, particularly in the composition, physicochemical properties, and signaling potential of the bile acid pool. These species differences may limit the ability to translate findings regarding bile acid-related disease processes from mice to humans. In this review, we focus primarily on mouse models and also briefly discuss dietary or surgical models commonly used to study the basic mechanisms underlying bile acid metabolism. Important phenotypic species differences in bile acid metabolism between mice and humans are highlighted.
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Affiliation(s)
- Jianing Li
- Department of Pediatrics, Division of Gastroenterology, Hepatology, and Nutrition, Emory University, Atlanta, GA 30322, United States
| | - Paul A Dawson
- Department of Pediatrics, Division of Gastroenterology, Hepatology, and Nutrition, Emory University, Atlanta, GA 30322, United States.
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79
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Luo J, Xu P, Cao P, Wan H, Lv X, Xu S, Wang G, Cook MN, Jones BC, Lu L, Wang X. Integrating Genetic and Gene Co-expression Analysis Identifies Gene Networks Involved in Alcohol and Stress Responses. Front Mol Neurosci 2018; 11:102. [PMID: 29674951 PMCID: PMC5895640 DOI: 10.3389/fnmol.2018.00102] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2017] [Accepted: 03/15/2018] [Indexed: 02/06/2023] Open
Abstract
Although the link between stress and alcohol is well recognized, the underlying mechanisms of how they interplay at the molecular level remain unclear. The purpose of this study is to identify molecular networks underlying the effects of alcohol and stress responses, as well as their interaction on anxiety behaviors in the hippocampus of mice using a systems genetics approach. Here, we applied a gene co-expression network approach to transcriptomes of 41 BXD mouse strains under four conditions: stress, alcohol, stress-induced alcohol and control. The co-expression analysis identified 14 modules and characterized four expression patterns across the four conditions. The four expression patterns include up-regulation in no restraint stress and given an ethanol injection (NOE) but restoration in restraint stress followed by an ethanol injection (RSE; pattern 1), down-regulation in NOE but rescue in RSE (pattern 2), up-regulation in both restraint stress followed by a saline injection (RSS) and NOE, and further amplification in RSE (pattern 3), and up-regulation in RSS but reduction in both NOE and RSE (pattern 4). We further identified four functional subnetworks by superimposing protein-protein interactions (PPIs) to the 14 co-expression modules, including γ-aminobutyric acid receptor (GABA) signaling, glutamate signaling, neuropeptide signaling, cAMP-dependent signaling. We further performed module specificity analysis to identify modules that are specific to stress, alcohol, or stress-induced alcohol responses. Finally, we conducted causality analysis to link genetic variation to these identified modules, and anxiety behaviors after stress and alcohol treatments. This study underscores the importance of integrative analysis and offers new insights into the molecular networks underlying stress and alcohol responses.
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Affiliation(s)
- Jie Luo
- Central Laboratory of Zhejiang Academy of Agricultural Sciences, Zhejiang Academy of Agricultural Sciences Hangzhou, China.,Institute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences Hangzhou, China
| | - Pei Xu
- Institute of Vegetables, Zhejiang Academy of Agricultural Sciences Hangzhou, China.,State Key Laboratory Breeding Base for Sustainable Control of Plant Pest and Disease, Zhejiang Academy of Agricultural Sciences Hangzhou, China
| | - Peijian Cao
- China Tobacco Gene Research Center, Zhengzhou Tobacco Research Institute of CNTC Zhengzhou, China
| | - Hongjian Wan
- Institute of Vegetables, Zhejiang Academy of Agricultural Sciences Hangzhou, China
| | - Xiaonan Lv
- Institute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences Hangzhou, China
| | - Shengchun Xu
- Central Laboratory of Zhejiang Academy of Agricultural Sciences, Zhejiang Academy of Agricultural Sciences Hangzhou, China
| | - Gangjun Wang
- Central Laboratory of Zhejiang Academy of Agricultural Sciences, Zhejiang Academy of Agricultural Sciences Hangzhou, China
| | - Melloni N Cook
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center Memphis, TN, United States.,Department of Psychology, University of Memphis Memphis, TN, United States
| | - Byron C Jones
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center Memphis, TN, United States
| | - Lu Lu
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center Memphis, TN, United States.,Department of Neurology, Affiliated Hospital of Nantong University Nantong, China
| | - Xusheng Wang
- St. Jude Proteomics Facility, St. Jude Children's Research Hospital Memphis, TN, United States
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80
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Gujar H, Liang JW, Wong NC, Mozhui K. Profiling DNA methylation differences between inbred mouse strains on the Illumina Human Infinium MethylationEPIC microarray. PLoS One 2018. [PMID: 29529061 PMCID: PMC5846735 DOI: 10.1371/journal.pone.0193496] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
The Illumina Infinium MethylationEPIC provides an efficient platform for profiling DNA methylation in humans at over 850,000 CpGs. Model organisms such as mice do not currently benefit from an equivalent array. Here we used this array to measure DNA methylation in mice. We defined probes targeting conserved regions and performed differential methylation analysis and compared between the array-based assay and affinity-based DNA sequencing of methyl-CpGs (MBD-seq) and reduced representation bisulfite sequencing. Mouse samples consisted of 11 liver DNA from two strains, C57BL/6J (B6) and DBA/2J (D2), that varied widely in age. Linear regression was applied to detect differential methylation. In total, 13,665 probes (1.6% of total probes) aligned to conserved CpGs. Beta-values (β-value) for these probes showed a distribution similar to that in humans. Overall, there was high concordance in methylation signal between the EPIC array and MBD-seq (Pearson correlation r = 0.70, p-value < 0.0001). However, the EPIC probes had higher quantitative sensitivity at CpGs that are hypo- (β-value < 0.3) or hypermethylated (β-value > 0.7). In terms of differential methylation, no EPIC probe detected a significant difference between age groups at a Benjamini-Hochberg threshold of 10%, and the MBD-seq performed better at detecting age-dependent change in methylation. However, the top most significant probe for age (cg13269407; uncorrected p-value = 1.8 x 10-5) is part of the clock CpGs used to estimate the human epigenetic age. For strain, 219 EPIC probes detected significant differential methylation (FDR cutoff 10%) with ~80% CpGs associated with higher methylation in D2. This higher methylation profile in D2 compared to B6 was also replicated by the MBD-seq data. To summarize, we found only a small subset of EPIC probes that target conserved sites. However, for this small subset the array provides a reliable assay of DNA methylation and can be effectively used to measure differential methylation in mice.
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Affiliation(s)
- Hemant Gujar
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, United States of America
| | - Jane W. Liang
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, United States of America
| | - Nicholas C. Wong
- Monash Bioinformatics Platform, Monash University, Clayton VIC, Australia
| | - Khyobeni Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, United States of America
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Centre, Memphis, Tennessee, United States of America
- * E-mail:
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81
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Ashbrook DG, Mulligan MK, Williams RW. Post-genomic behavioral genetics: From revolution to routine. GENES, BRAIN, AND BEHAVIOR 2018; 17:e12441. [PMID: 29193773 PMCID: PMC5876106 DOI: 10.1111/gbb.12441] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Revised: 11/02/2017] [Accepted: 11/20/2017] [Indexed: 12/16/2022]
Abstract
What was once expensive and revolutionary-full-genome sequence-is now affordable and routine. Costs will continue to drop, opening up new frontiers in behavioral genetics. This shift in costs from the genome to the phenome is most notable in large clinical studies of behavior and associated diseases in cohorts that exceed hundreds of thousands of subjects. Examples include the Women's Health Initiative (www.whi.org), the Million Veterans Program (www. RESEARCH va.gov/MVP), the 100 000 Genomes Project (genomicsengland.co.uk) and commercial efforts such as those by deCode (www.decode.com) and 23andme (www.23andme.com). The same transition is happening in experimental neuro- and behavioral genetics, and sample sizes of many hundreds of cases are becoming routine (www.genenetwork.org, www.mousephenotyping.org). There are two major consequences of this new affordability of massive omics datasets: (1) it is now far more practical to explore genetic modulation of behavioral differences and the key role of gene-by-environment interactions. Researchers are already doing the hard part-the quantitative analysis of behavior. Adding the omics component can provide powerful links to molecules, cells, circuits and even better treatment. (2) There is an acute need to highlight and train behavioral scientists in how best to exploit new omics approaches. This review addresses this second issue and highlights several new trends and opportunities that will be of interest to experts in animal and human behaviors.
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Affiliation(s)
- D G Ashbrook
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Sciences Center, College of Medicine, Memphis, Tennessee
| | - M K Mulligan
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Sciences Center, College of Medicine, Memphis, Tennessee
| | - R W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Sciences Center, College of Medicine, Memphis, Tennessee
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82
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Kafkafi N, Agassi J, Chesler EJ, Crabbe JC, Crusio WE, Eilam D, Gerlai R, Golani I, Gomez-Marin A, Heller R, Iraqi F, Jaljuli I, Karp NA, Morgan H, Nicholson G, Pfaff DW, Richter SH, Stark PB, Stiedl O, Stodden V, Tarantino LM, Tucci V, Valdar W, Williams RW, Würbel H, Benjamini Y. Reproducibility and replicability of rodent phenotyping in preclinical studies. Neurosci Biobehav Rev 2018; 87:218-232. [PMID: 29357292 PMCID: PMC6071910 DOI: 10.1016/j.neubiorev.2018.01.003] [Citation(s) in RCA: 116] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Revised: 12/13/2017] [Accepted: 01/11/2018] [Indexed: 12/15/2022]
Abstract
The scientific community is increasingly concerned with the proportion of
published “discoveries” that are not replicated in subsequent
studies. The field of rodent behavioral phenotyping was one of the first to
raise this concern, and to relate it to other methodological issues: the complex
interaction between genotype and environment; the definitions of behavioral
constructs; and the use of laboratory mice and rats as model species for
investigating human health and disease mechanisms. In January 2015, researchers
from various disciplines gathered at Tel Aviv University to discuss these
issues. The general consensus was that the issue is prevalent and of concern,
and should be addressed at the statistical, methodological and policy levels,
but is not so severe as to call into question the validity and the usefulness of
model organisms as a whole. Well-organized community efforts, coupled with
improved data and metadata sharing, have a key role in identifying specific
problems and promoting effective solutions. Replicability is closely related to
validity, may affect generalizability and translation of findings, and has
important ethical implications.
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Affiliation(s)
| | | | | | - John C Crabbe
- Oregon Health & Science University, and VA Portland Health Care System, United States
| | | | | | | | | | | | | | | | | | - Natasha A Karp
- Discovery Sciences, IMED Biotech Unit, AstraZeneca, Cambridge, UK
| | | | | | | | | | | | | | | | | | | | - William Valdar
- University of North Carolina at Chapel Hill, United States
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Roman ÁC, Carvajal-Gonzalez JM, Merino JM, Mulero-Navarro S, Fernández-Salguero PM. The aryl hydrocarbon receptor in the crossroad of signalling networks with therapeutic value. Pharmacol Ther 2017; 185:50-63. [PMID: 29258844 DOI: 10.1016/j.pharmthera.2017.12.003] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The aryl hydrocarbon receptor (AhR) is well-known for its major contributions to the cellular responses against environmental toxins and carcinogens. Notably, AhR has also emerged as a key transcription factor controlling many physiological processes including cell proliferation and apoptosis, differentiation, adhesion and migration, pluripotency and stemness. These novel functions have broadened our understanding of the signalling pathways and molecular intermediates interacting with AhR under both homeostatic and pathological conditions. Recent discoveries link AhR with the function of essential organs such as liver, skin and gonads, and with complex organismal structures including the immune and cardiovascular systems. The identification of potential endogenous ligands able to regulate AhR activity, opens the possibility of designing ad hoc molecules with pharmacological and/or therapeutic value to treat human diseases in which AhR may have a causal role. Integration of experimental data from in vitro and in vivo studies with "omic" analyses of human patients affected with cancer, immune diseases, inflammation or neurological disorders will likely contribute to validate the clinical relevance of AhR and the possible benefits of modulating its activity by pharmacologically-driven strategies. In this review, we will highlight signalling pathways involved in human diseases that could be targetable by AhR modulators and discuss the feasibility of using such molecules in therapy. The pros and cons of AhR-aimed approaches will be also mentioned.
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Affiliation(s)
- Ángel C Roman
- Champalimaud Neuroscience Programme, Champalimoud Center for the Unknown, Lisbon, Portugal
| | - José M Carvajal-Gonzalez
- Departamento de Bioquímica y Biología Molecular y Genética, Facultad de Ciencias, Universidad de Extremadura, 06071 Badajoz, Spain
| | - Jaime M Merino
- Departamento de Bioquímica y Biología Molecular y Genética, Facultad de Ciencias, Universidad de Extremadura, 06071 Badajoz, Spain
| | - Sonia Mulero-Navarro
- Departamento de Bioquímica y Biología Molecular y Genética, Facultad de Ciencias, Universidad de Extremadura, 06071 Badajoz, Spain.
| | - Pedro M Fernández-Salguero
- Departamento de Bioquímica y Biología Molecular y Genética, Facultad de Ciencias, Universidad de Extremadura, 06071 Badajoz, Spain.
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84
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Abstract
PURPOSE OF REVIEW Over many decades, researchers have been designing studies to investigate the relationship between genotypes and phenotypes to gain an understanding about the effect of genetics on disease. Recently, a high-throughput approach called phenome-wide associations studies (PheWAS) have been extensively used to identify associations between genetic variants and many diseases and traits simultaneously. In this review, we describe the value of PheWAS along with methodological issues and challenges in interpretation for current applications of PheWAS. RECENT FINDINGS PheWAS have uncovered a paradigm to identify new associations for genetic loci across many diseases. The application of PheWAS have been effective with phenotype data from electronic health records, epidemiological studies, and clinical trials data. SUMMARY The key strength of a PheWAS is to identify the association of one or more genetic variants with multiple phenotypes, which can showcase interconnections among the phenotypes due to shared genetic associations. While the PheWAS approach appears promising, there are a number of challenges that need to be addressed to provide additional robustness to PheWAS findings.
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Affiliation(s)
- Anurag Verma
- Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA
- The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA
| | - Marylyn D Ritchie
- Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA
- The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA
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85
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Li H, Wang X, Rukina D, Huang Q, Lin T, Sorrentino V, Zhang H, Bou Sleiman M, Arends D, McDaid A, Luan P, Ziari N, Velázquez-Villegas LA, Gariani K, Kutalik Z, Schoonjans K, Radcliffe RA, Prins P, Morgenthaler S, Williams RW, Auwerx J. An Integrated Systems Genetics and Omics Toolkit to Probe Gene Function. Cell Syst 2017; 6:90-102.e4. [PMID: 29199021 DOI: 10.1016/j.cels.2017.10.016] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2017] [Revised: 08/31/2017] [Accepted: 10/25/2017] [Indexed: 01/20/2023]
Abstract
Identifying genetic and environmental factors that impact complex traits and common diseases is a high biomedical priority. Here, we developed, validated, and implemented a series of multi-layered systems approaches, including (expression-based) phenome-wide association, transcriptome-/proteome-wide association, and (reverse-) mediation analysis, in an open-access web server (systems-genetics.org) to expedite the systems dissection of gene function. We applied these approaches to multi-omics datasets from the BXD mouse genetic reference population, and identified and validated associations between genes and clinical and molecular phenotypes, including previously unreported links between Rpl26 and body weight, and Cpt1a and lipid metabolism. Furthermore, through mediation and reverse-mediation analysis we established regulatory relations between genes, such as the co-regulation of BCKDHA and BCKDHB protein levels, and identified targets of transcription factors E2F6, ZFP277, and ZKSCAN1. Our multifaceted toolkit enabled the identification of gene-gene and gene-phenotype links that are robust and that translate well across populations and species, and can be universally applied to any populations with multi-omics datasets.
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Affiliation(s)
- Hao Li
- Laboratory for Integrative and Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Xu Wang
- Laboratory for Integrative and Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Daria Rukina
- Institute of Mathematics, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Qingyao Huang
- Laboratory of Metabolic Signaling, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Tao Lin
- Laboratory for Integrative and Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Vincenzo Sorrentino
- Laboratory for Integrative and Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Hongbo Zhang
- Laboratory for Integrative and Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Maroun Bou Sleiman
- Laboratory for Integrative and Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Danny Arends
- Albrecht Daniel Thaer-Institut für Agrar- und Gartenbauwissenschaften, Humboldt-Universität zu Berlin, D-10115 Berlin, Germany
| | - Aaron McDaid
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland; Institute of Social and Preventive Medicine, University Hospital of Lausanne, Lausanne 1010, Switzerland
| | - Peiling Luan
- Laboratory for Integrative and Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Naveed Ziari
- Laboratory for Integrative and Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Laura A Velázquez-Villegas
- Laboratory of Metabolic Signaling, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Karim Gariani
- Laboratory for Integrative and Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Zoltan Kutalik
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland; Institute of Social and Preventive Medicine, University Hospital of Lausanne, Lausanne 1010, Switzerland
| | - Kristina Schoonjans
- Laboratory of Metabolic Signaling, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Richard A Radcliffe
- Department of Pharmaceutical Sciences, University of Colorado, Aurora, CO 80045, USA
| | - Pjotr Prins
- University Medical Center Utrecht, 3584CT Utrecht, the Netherlands; Department of Genetics, Genomics and Informatics, University of Tennessee, Memphis, TN 38163, USA
| | - Stephan Morgenthaler
- Institute of Mathematics, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Robert W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee, Memphis, TN 38163, USA
| | - Johan Auwerx
- Laboratory for Integrative and Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland.
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86
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Systems genetics identifies a role for Cacna2d1 regulation in elevated intraocular pressure and glaucoma susceptibility. Nat Commun 2017; 8:1755. [PMID: 29176626 PMCID: PMC5701146 DOI: 10.1038/s41467-017-00837-5] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Accepted: 06/28/2017] [Indexed: 12/21/2022] Open
Abstract
Glaucoma is a multi-factorial blinding disease in which genetic factors play an important role. Elevated intraocular pressure is a highly heritable risk factor for primary open angle glaucoma and currently the only target for glaucoma therapy. Our study helps to better understand underlying genetic and molecular mechanisms that regulate intraocular pressure, and identifies a new candidate gene, Cacna2d1, that modulates intraocular pressure and a promising therapeutic, pregabalin, which binds to CACNA2D1 protein and lowers intraocular pressure significantly. Because our study utilizes a genetically diverse population of mice with known sequence variants, we are able to determine that the intraocular pressure-lowering effect of pregabalin is dependent on the Cacna2d1 haplotype. Using human genome-wide association study (GWAS) data, evidence for association of a CACNA2D1 single-nucleotide polymorphism and primary open angle glaucoma is found. Importantly, these results demonstrate that our systems genetics approach represents an efficient method to identify genetic variation that can guide the selection of therapeutic targets. Elevated intraocular pressure (IOP) is a heritable risk factor for primary open angle glaucoma. Using forward mouse genetics, cell biology, pharmacology and human genetic data, the authors identify CACNA2D1 as an IOP risk gene that can be therapeutically targeted by the drug pregabalin in animal models.
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87
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Shpilka T, Haynes CM. The mitochondrial UPR: mechanisms, physiological functions and implications in ageing. Nat Rev Mol Cell Biol 2017; 19:109-120. [DOI: 10.1038/nrm.2017.110] [Citation(s) in RCA: 323] [Impact Index Per Article: 46.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
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88
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High AA, Tan H, Pagala VR, Niu M, Cho JH, Wang X, Bai B, Peng J. Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification. J Vis Exp 2017. [PMID: 29286450 DOI: 10.3791/56474] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Many exceptional advances have been made in mass spectrometry (MS)-based proteomics, with particular technical progress in liquid chromatography (LC) coupled to tandem mass spectrometry (LC-MS/MS) and isobaric labeling multiplexing capacity. Here, we introduce a deep-proteomics profiling protocol that combines 10-plex tandem mass tag (TMT) labeling with an extensive LC/LC-MS/MS platform, and post-MS computational interference correction to accurately quantitate whole proteomes. This protocol includes the following main steps: protein extraction and digestion, TMT labeling, 2-dimensional (2D) LC, high-resolution mass spectrometry, and computational data processing. Quality control steps are included for troubleshooting and evaluating experimental variation. More than 10,000 proteins in mammalian samples can be confidently quantitated with this protocol. This protocol can also be applied to the quantitation of post translational modifications with minor changes. This multiplexed, robust method provides a powerful tool for proteomic analysis in a variety of complex samples, including cell culture, animal tissues, and human clinical specimens.
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Affiliation(s)
- Anthony A High
- St. Jude Proteomics Facility, St. Jude Children's Research Hospital;
| | - Haiyan Tan
- St. Jude Proteomics Facility, St. Jude Children's Research Hospital
| | | | - Mingming Niu
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital; Heilongjiang University of Chinese Medicine
| | - Ji-Hoon Cho
- St. Jude Proteomics Facility, St. Jude Children's Research Hospital
| | - Xusheng Wang
- St. Jude Proteomics Facility, St. Jude Children's Research Hospital
| | - Bing Bai
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital
| | - Junmin Peng
- St. Jude Proteomics Facility, St. Jude Children's Research Hospital; Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital;
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89
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Watson DE, Hunziker R, Wikswo JP. Fitting tissue chips and microphysiological systems into the grand scheme of medicine, biology, pharmacology, and toxicology. Exp Biol Med (Maywood) 2017; 242:1559-1572. [PMID: 29065799 DOI: 10.1177/1535370217732765] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Microphysiological systems (MPS), which include engineered organoids (EOs), single organ/tissue chips (TCs), and multiple organs interconnected to create miniature in vitro models of human physiological systems, are rapidly becoming effective tools for drug development and the mechanistic understanding of tissue physiology and pathophysiology. The second MPS thematic issue of Experimental Biology and Medicine comprises 15 articles by scientists and engineers from the National Institutes of Health, the IQ Consortium, the Food and Drug Administration, and Environmental Protection Agency, an MPS company, and academia. Topics include the progress, challenges, and future of organs-on-chips, dissemination of TCs into Pharma, children's health protection, liver zonation, liver chips and their coupling to interconnected systems, gastrointestinal MPS, maturation of immature cardiomyocytes in a heart-on-a-chip, coculture of multiple cell types in a human skin construct, use of synthetic hydrogels to create EOs that form neural tissue models, the blood-brain barrier-on-a-chip, MPS models of coupled female reproductive organs, coupling MPS devices to create a body-on-a-chip, and the use of a microformulator to recapitulate endocrine circadian rhythms. While MPS hardware has been relatively stable since the last MPS thematic issue, there have been significant advances in cell sourcing, with increased reliance on human-induced pluripotent stem cells, and in characterization of the genetic and functional cell state in MPS bioreactors. There is growing appreciation of the need to minimize perfusate-to-cell-volume ratios and respect physiological scaling of coupled TCs. Questions asked by drug developers are followed by an analysis of the potential value, costs, and needs of Pharma. Of highest value and lowest switching costs may be the development of MPS disease models to aid in the discovery of disease mechanisms; novel compounds including probes, leads, and clinical candidates; and mechanism of action of drug candidates. Impact statement Microphysiological systems (MPS), which include engineered organoids and both individual and coupled organs-on-chips and tissue chips, are a rapidly growing topic of research that addresses the known limitations of conventional cellular monoculture on flat plastic - a well-perfected set of techniques that produces reliable, statistically significant results that may not adequately represent human biology and disease. As reviewed in this article and the others in this thematic issue, MPS research has made notable progress in the past three years in both cell sourcing and characterization. As the field matures, currently identified challenges are being addressed, and new ones are being recognized. Building upon investments by the Defense Advanced Research Projects Agency, National Institutes of Health, Food and Drug Administration, Defense Threat Reduction Agency, and Environmental Protection Agency of more than $200 million since 2012 and sizable corporate spending, academic and commercial players in the MPS community are demonstrating their ability to meet the translational challenges required to apply MPS technologies to accelerate drug development and advance toxicology.
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Affiliation(s)
| | - Rosemarie Hunziker
- 2 National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD 20892, USA
| | - John P Wikswo
- 3 Departments of Biomedical Engineering, Molecular Physiology & Biophysics, and Physics & Astronomy, Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt University, Nashville, TN 37235-1807, USA
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90
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Stöckli J, Fisher-Wellman KH, Chaudhuri R, Zeng XY, Fazakerley DJ, Meoli CC, Thomas KC, Hoffman NJ, Mangiafico SP, Xirouchaki CE, Yang CH, Ilkayeva O, Wong K, Cooney GJ, Andrikopoulos S, Muoio DM, James DE. Metabolomic analysis of insulin resistance across different mouse strains and diets. J Biol Chem 2017; 292:19135-19145. [PMID: 28982973 DOI: 10.1074/jbc.m117.818351] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2017] [Indexed: 01/16/2023] Open
Abstract
Insulin resistance is a major risk factor for many diseases. However, its underlying mechanism remains unclear in part because it is triggered by a complex relationship between multiple factors, including genes and the environment. Here, we used metabolomics combined with computational methods to identify factors that classified insulin resistance across individual mice derived from three different mouse strains fed two different diets. Three inbred ILSXISS strains were fed high-fat or chow diets and subjected to metabolic phenotyping and metabolomics analysis of skeletal muscle. There was significant metabolic heterogeneity between strains, diets, and individual animals. Distinct metabolites were changed with insulin resistance, diet, and between strains. Computational analysis revealed 113 metabolites that were correlated with metabolic phenotypes. Using these 113 metabolites, combined with machine learning to segregate mice based on insulin sensitivity, we identified C22:1-CoA, C2-carnitine, and C16-ceramide as the best classifiers. Strikingly, when these three metabolites were combined into one signature, they classified mice based on insulin sensitivity more accurately than each metabolite on its own or other published metabolic signatures. Furthermore, C22:1-CoA was 2.3-fold higher in insulin-resistant mice and correlated significantly with insulin resistance. We have identified a metabolomic signature composed of three functionally unrelated metabolites that accurately predicts whole-body insulin sensitivity across three mouse strains. These data indicate the power of simultaneous analysis of individual, genetic, and environmental variance in mice for identifying novel factors that accurately predict metabolic phenotypes like whole-body insulin sensitivity.
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Affiliation(s)
- Jacqueline Stöckli
- From the Charles Perkins Centre, School of Life and Environmental Sciences, the University of Sydney, Sydney NSW 2006, Australia
| | - Kelsey H Fisher-Wellman
- the Garvan Institute of Medical Research, Sydney NSW 2010, Australia.,the Duke Molecular Physiology Institute, Duke University, Durham, North Carolina 27708
| | - Rima Chaudhuri
- From the Charles Perkins Centre, School of Life and Environmental Sciences, the University of Sydney, Sydney NSW 2006, Australia
| | - Xiao-Yi Zeng
- From the Charles Perkins Centre, School of Life and Environmental Sciences, the University of Sydney, Sydney NSW 2006, Australia
| | - Daniel J Fazakerley
- From the Charles Perkins Centre, School of Life and Environmental Sciences, the University of Sydney, Sydney NSW 2006, Australia
| | | | - Kristen C Thomas
- From the Charles Perkins Centre, School of Life and Environmental Sciences, the University of Sydney, Sydney NSW 2006, Australia
| | - Nolan J Hoffman
- From the Charles Perkins Centre, School of Life and Environmental Sciences, the University of Sydney, Sydney NSW 2006, Australia
| | | | | | - Chieh-Hsin Yang
- the Department of Medicine, University of Melbourne, Melbourne VIC 3010, Australia, and
| | - Olga Ilkayeva
- the Duke Molecular Physiology Institute, Duke University, Durham, North Carolina 27708
| | - Kari Wong
- the Duke Molecular Physiology Institute, Duke University, Durham, North Carolina 27708
| | - Gregory J Cooney
- the Sydney Medical School, the University of Sydney, Sydney NSW 2006, Australia
| | | | - Deborah M Muoio
- the Duke Molecular Physiology Institute, Duke University, Durham, North Carolina 27708
| | - David E James
- From the Charles Perkins Centre, School of Life and Environmental Sciences, the University of Sydney, Sydney NSW 2006, Australia, .,the Sydney Medical School, the University of Sydney, Sydney NSW 2006, Australia
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91
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Abstract
Mitochondria are essential organelles for many aspects of cellular homeostasis, including energy harvesting through oxidative phosphorylation. Alterations of mitochondrial function not only impact on cellular metabolism but also critically influence whole-body metabolism, health, and life span. Diseases defined by mitochondrial dysfunction have expanded from rare monogenic disorders in a strict sense to now also include many common polygenic diseases, including metabolic, cardiovascular, neurodegenerative, and neuromuscular diseases. This has led to an intensive search for new therapeutic and preventive strategies aimed at invigorating mitochondrial function by exploiting key components of mitochondrial biogenesis, redox metabolism, dynamics, mitophagy, and the mitochondrial unfolded protein response. As such, new findings linking mitochondrial function to the progression or outcome of this ever-increasing list of diseases has stimulated the discovery and development of the first true mitochondrial drugs, which are now entering the clinic and are discussed in this review.
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Affiliation(s)
- Vincenzo Sorrentino
- Laboratory of Integrative and Systems Physiology, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland;
| | - Keir J Menzies
- Interdisciplinary School of Health Sciences, University of Ottawa Brain and Mind Research Institute and Centre for Neuromuscular Disease, Ottawa K1H 8M5, Canada;
| | - Johan Auwerx
- Laboratory of Integrative and Systems Physiology, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland;
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92
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Variable cardiac α-actin (Actc1) expression in early adult skeletal muscle correlates with promoter methylation. BIOCHIMICA ET BIOPHYSICA ACTA-GENE REGULATORY MECHANISMS 2017; 1860:1025-1036. [PMID: 28847732 DOI: 10.1016/j.bbagrm.2017.08.004] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2017] [Revised: 08/02/2017] [Accepted: 08/21/2017] [Indexed: 11/20/2022]
Abstract
Different genes encode the α-actin isoforms that are predominantly expressed in heart and skeletal muscle. Mutations in the skeletal muscle α-actin gene (ACTA1) cause muscle diseases that are mostly lethal in the early postnatal period. We previously demonstrated that the disease phenotype of ACTA1 mouse models could be rescued by transgenic over-expression of cardiac α-actin (ACTC1). ACTC1 is the predominant striated α-actin isoform in the heart but is also expressed in developing skeletal muscle. To develop a translatable therapy, we investigated the genetic regulation of Actc1 expression. Using strains from The Collaborative Cross (CC) genetic resource, we found that Actc1 varies in expression by up to 24-fold in skeletal muscle. We defined significant expression quantitative trait loci (eQTL) associated with early adult Actc1 expression in soleus and heart. eQTL in both heart and soleus mapped to the Actc1 locus and replicate an eQTL mapped for Actc1 in BXD heart and quadriceps. We built on this previous work by analysing genes within the eQTL peak regions to prioritise likely candidates for modifying Actc1 expression. Additionally we interrogated the CC founder haplotype contributions to enable prioritisation of genetic variants for functional analyses. Methylation around the Actc1 transcriptional start site in early adult skeletal muscle negatively correlated with Actc1 expression in a strain-dependent manner, while other marks of regulatory potential (histone modification and chromatin accessibility) were unaltered. This study provides novel insights into the complex genetic regulation of Actc1 expression in early adult skeletal muscles.
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93
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Chang PL, Kopania E, Keeble S, Sarver BAJ, Larson E, Orth A, Belkhir K, Boursot P, Bonhomme F, Good JM, Dean MD. Whole exome sequencing of wild-derived inbred strains of mice improves power to link phenotype and genotype. Mamm Genome 2017; 28:416-425. [PMID: 28819774 DOI: 10.1007/s00335-017-9704-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2017] [Accepted: 06/23/2017] [Indexed: 12/30/2022]
Abstract
The house mouse is a powerful model to dissect the genetic basis of phenotypic variation, and serves as a model to study human diseases. Despite a wealth of discoveries, most classical laboratory strains have captured only a small fraction of genetic variation known to segregate in their wild progenitors, and existing strains are often related to each other in complex ways. Inbred strains of mice independently derived from natural populations have the potential to increase power in genetic studies with the addition of novel genetic variation. Here, we perform exome-enrichment and high-throughput sequencing (~8× coverage) of 26 wild-derived strains known in the mouse research community as the "Montpellier strains." We identified 1.46 million SNPs in our dataset, approximately 19% of which have not been detected from other inbred strains. This novel genetic variation is expected to contribute to phenotypic variation, as they include 18,496 nonsynonymous variants and 262 early stop codons. Simulations demonstrate that the higher density of genetic variation in the Montpellier strains provides increased power for quantitative genetic studies. Inasmuch as the power to connect genotype to phenotype depends on genetic variation, it is important to incorporate these additional genetic strains into future research programs.
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Affiliation(s)
- Peter L Chang
- Molecular and Computational Biology, University of Southern California, 1050 Childs Way, Los Angeles, CA, 90089, USA
| | - Emily Kopania
- Molecular and Computational Biology, University of Southern California, 1050 Childs Way, Los Angeles, CA, 90089, USA.,Division of Biological Sciences, University of Montana, Missoula, MT, USA
| | - Sara Keeble
- Molecular and Computational Biology, University of Southern California, 1050 Childs Way, Los Angeles, CA, 90089, USA.,Division of Biological Sciences, University of Montana, Missoula, MT, USA
| | - Brice A J Sarver
- Division of Biological Sciences, University of Montana, Missoula, MT, USA
| | - Erica Larson
- Division of Biological Sciences, University of Montana, Missoula, MT, USA.,Department of Biological Sciences, University of Denver, Denver, CO, 80210, USA
| | - Annie Orth
- Institut des Sciences de l'Evolution, CNRS UMR554, Université de Montpellier, Montpellier, France
| | - Khalid Belkhir
- Institut des Sciences de l'Evolution, CNRS UMR554, Université de Montpellier, Montpellier, France
| | - Pierre Boursot
- Institut des Sciences de l'Evolution, CNRS UMR554, Université de Montpellier, Montpellier, France
| | - François Bonhomme
- Institut des Sciences de l'Evolution, CNRS UMR554, Université de Montpellier, Montpellier, France
| | - Jeffrey M Good
- Division of Biological Sciences, University of Montana, Missoula, MT, USA
| | - Matthew D Dean
- Molecular and Computational Biology, University of Southern California, 1050 Childs Way, Los Angeles, CA, 90089, USA.
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94
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Quirós PM, Prado MA, Zamboni N, D'Amico D, Williams RW, Finley D, Gygi SP, Auwerx J. Multi-omics analysis identifies ATF4 as a key regulator of the mitochondrial stress response in mammals. J Cell Biol 2017; 216:2027-2045. [PMID: 28566324 PMCID: PMC5496626 DOI: 10.1083/jcb.201702058] [Citation(s) in RCA: 537] [Impact Index Per Article: 76.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2017] [Revised: 04/04/2017] [Accepted: 04/18/2017] [Indexed: 01/25/2023] Open
Abstract
Mitochondrial stress activates a mitonuclear response to safeguard and repair mitochondrial function and to adapt cellular metabolism to stress. Using a multiomics approach in mammalian cells treated with four types of mitochondrial stressors, we identify activating transcription factor 4 (ATF4) as the main regulator of the stress response. Surprisingly, canonical mitochondrial unfolded protein response genes mediated by ATF5 are not activated. Instead, ATF4 activates the expression of cytoprotective genes, which reprogram cellular metabolism through activation of the integrated stress response (ISR). Mitochondrial stress promotes a local proteostatic response by reducing mitochondrial ribosomal proteins, inhibiting mitochondrial translation, and coupling the activation of the ISR with the attenuation of mitochondrial function. Through a trans-expression quantitative trait locus analysis, we provide genetic evidence supporting a role for Fh1 in the control of Atf4 expression in mammals. Using gene expression data from mice and humans with mitochondrial diseases, we show that the ATF4 pathway is activated in vivo upon mitochondrial stress. Our data illustrate the value of a multiomics approach to characterize complex cellular networks and provide a versatile resource to identify new regulators of mitochondrial-related diseases.
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Affiliation(s)
- Pedro M Quirós
- Laboratory for Integrative and Systems Physiology, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Miguel A Prado
- Department of Cell Biology, Harvard Medical School, Boston, MA
| | - Nicola Zamboni
- Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule Zürich, Zurich, Switzerland
| | - Davide D'Amico
- Laboratory for Integrative and Systems Physiology, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Robert W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN
| | - Daniel Finley
- Department of Cell Biology, Harvard Medical School, Boston, MA
| | - Steven P Gygi
- Department of Cell Biology, Harvard Medical School, Boston, MA
| | - Johan Auwerx
- Laboratory for Integrative and Systems Physiology, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
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Alterations in the expression of a neurodevelopmental gene exert long-lasting effects on cognitive-emotional phenotypes and functional brain networks: translational evidence from the stress-resilient Ahi1 knockout mouse. Mol Psychiatry 2017; 22:884-899. [PMID: 27021817 PMCID: PMC5444025 DOI: 10.1038/mp.2016.29] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2015] [Revised: 12/29/2015] [Accepted: 02/03/2016] [Indexed: 12/19/2022]
Abstract
Many psychiatric disorders are highly heritable and may represent the clinical outcome of early aberrations in the formation of neural networks. The placement of brain connectivity as an 'intermediate phenotype' renders it an attractive target for exploring its interaction with genomics and behavior. Given the complexity of genetic make up and phenotypic heterogeneity in humans, translational studies are indicated. Recently, we demonstrated that a mouse model with heterozygous knockout of the key neurodevelopmental gene Ahi1 displays a consistent stress-resilient phenotype. Extending these data, the current research describes our multi-faceted effort to link early variations in Ahi1 expression with long-term consequences for functional brain networks and cognitive-emotional phenotypes. By combining behavioral paradigms with graph-based analysis of whole-brain functional networks, and then cross-validating the data with robust neuroinformatic data sets, our research suggests that physiological variation in gene expression during neurodevelopment is eventually translated into a continuum of global network metrics that serve as intermediate phenotypes. Within this framework, we suggest that organization of functional brain networks may result, in part, from an adaptive trade-off between efficiency and resilience, ultimately culminating in a phenotypic diversity that encompasses dimensions such as emotional regulation and cognitive function.
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96
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Martinelli-Boneschi F, Colombi M, Castori M, Devigili G, Eleopra R, Malik RA, Ritelli M, Zoppi N, Dordoni C, Sorosina M, Grammatico P, Fadavi H, Gerrits MM, Almomani R, Faber CG, Merkies ISJ, Toniolo D, Cocca M, Doglioni C, Waxman SG, Dib-Hajj SD, Taiana MM, Sassone J, Lombardi R, Cazzato D, Zauli A, Santoro S, Marchi M, Lauria G. COL6A5 variants in familial neuropathic chronic itch. Brain 2017; 140:555-567. [PMID: 28073787 DOI: 10.1093/brain/aww343] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2016] [Accepted: 11/22/2016] [Indexed: 11/14/2022] Open
Abstract
Itch is thought to represent the peculiar response to stimuli conveyed by somatosensory pathways shared with pain through the activation of specific neurons and receptors. It can occur in association with dermatological, systemic and neurological diseases, or be the side effect of certain drugs. However, some patients suffer from chronic idiopathic itch that is frequently ascribed to psychological distress and for which no biomarker is available to date. We investigated three multigenerational families, one of which diagnosed with joint hypermobility syndrome/Ehlers-Danlos syndrome hypermobility type (JHS/EDS-HT), characterized by idiopathic chronic itch with predominantly proximal distribution. Skin biopsy was performed in all eight affected members and revealed in six of them reduced intraepidermal nerve fibre density consistent with small fibre neuropathy. Whole exome sequencing identified two COL6A5 rare variants co-segregating with chronic itch in eight affected members and absent in non-affected members, and in one unrelated sporadic patient with type 1 painless diabetic neuropathy and chronic itch. Two families and the diabetic patient carried the nonsense c.6814G>T (p.Glu2272*) variant and another family carried the missense c.6486G>C (p.Arg2162Ser) variant. Both variants were predicted as likely pathogenic by in silico analyses. The two variants were rare (minor allele frequency < 0.1%) in 6271 healthy controls and absent in 77 small fibre neuropathy and 167 JHS/EDS-HT patients without itch. Null-allele test on cDNA from patients' fibroblasts of both families carrying the nonsense variant demonstrated functional haploinsufficiency due to activation of nonsense mediated RNA decay. Immunofluorescence microscopy and western blotting revealed marked disorganization and reduced COL6A5 synthesis, respectively. Indirect immunofluorescence showed reduced COL6A5 expression in the skin of patients carrying the nonsense variant. Treatment with gabapentinoids provided satisfactory itch relief in the patients carrying the mutations. Our findings first revealed an association between COL6A5 gene and familiar chronic itch, suggesting a new contributor to the pathogenesis of neuropathic itch and identifying a new candidate therapeutic target.
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Affiliation(s)
- Filippo Martinelli-Boneschi
- Laboratory of Human Genetics of Neurological Disorders and Department of Neurology, Institute of Experimental Neurology (INSPE), Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy
| | - Marina Colombi
- Division of Biology and Genetics, Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Marco Castori
- Unit of Medical Genetics, Department of Molecular Medicine, Sapienza University, San Camillo-Forlanini Hospital, Rome, Italy
| | - Grazia Devigili
- Neurological Unit, University-Hospital "S. Maria della Misericordia", Udine, Italy
| | - Roberto Eleopra
- Neurological Unit, University-Hospital "S. Maria della Misericordia", Udine, Italy
| | - Rayaz A Malik
- Institute of Human Development, Centre for Endocrinology and Diabetes, University of Manchester and Central Manchester NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Marco Ritelli
- Division of Biology and Genetics, Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Nicoletta Zoppi
- Division of Biology and Genetics, Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Chiara Dordoni
- Division of Biology and Genetics, Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Melissa Sorosina
- Laboratory of Human Genetics of Neurological Disorders and Department of Neurology, Institute of Experimental Neurology (INSPE), Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy
| | - Paola Grammatico
- Unit of Medical Genetics, Department of Molecular Medicine, Sapienza University, San Camillo-Forlanini Hospital, Rome, Italy
| | - Hassan Fadavi
- Institute of Human Development, Centre for Endocrinology and Diabetes, University of Manchester and Central Manchester NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Monique M Gerrits
- Clinical Genetics, Maastricht University Medical Center, Maastricht, The Netherlands.,Department of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Rowida Almomani
- Clinical Genetics, Maastricht University Medical Center, Maastricht, The Netherlands.,Department of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Catharina G Faber
- Clinical Genetics, Maastricht University Medical Center, Maastricht, The Netherlands.,Department of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Ingemar S J Merkies
- Clinical Genetics, Maastricht University Medical Center, Maastricht, The Netherlands.,Department of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands
| | | | | | - Massimiliano Cocca
- Department of Medical, Surgical and Health Sciences, University of Trieste, 34100 Trieste, Italy
| | - Claudio Doglioni
- Department of Pathology, IRCCS San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy
| | - Stephen G Waxman
- Department of Neurology and Center for Neuroscience and regeneration Research, Yale University School of Medicine, New Haven, CT 06515, USA.,Center for Neuroscience and Regeneration Research, Veterans Affairs Medical Center, West Haven, CT 06515, USA
| | - Sulayman D Dib-Hajj
- Department of Neurology and Center for Neuroscience and regeneration Research, Yale University School of Medicine, New Haven, CT 06515, USA.,Center for Neuroscience and Regeneration Research, Veterans Affairs Medical Center, West Haven, CT 06515, USA
| | - Michela M Taiana
- Neuroalgology Unit and Skin Biopsy, Peripheral Neuropathy and Neuropathic Pain Center, IRCCS Foundation "Carlo Besta" Neurological Institute, Milan, Italy
| | - Jenny Sassone
- Neuroalgology Unit and Skin Biopsy, Peripheral Neuropathy and Neuropathic Pain Center, IRCCS Foundation "Carlo Besta" Neurological Institute, Milan, Italy
| | - Raffaella Lombardi
- Neuroalgology Unit and Skin Biopsy, Peripheral Neuropathy and Neuropathic Pain Center, IRCCS Foundation "Carlo Besta" Neurological Institute, Milan, Italy
| | - Daniele Cazzato
- Neuroalgology Unit and Skin Biopsy, Peripheral Neuropathy and Neuropathic Pain Center, IRCCS Foundation "Carlo Besta" Neurological Institute, Milan, Italy
| | - Andrea Zauli
- Laboratory of Human Genetics of Neurological Disorders and Department of Neurology, Institute of Experimental Neurology (INSPE), Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy
| | - Silvia Santoro
- Laboratory of Human Genetics of Neurological Disorders and Department of Neurology, Institute of Experimental Neurology (INSPE), Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy
| | - Margherita Marchi
- Neuroalgology Unit and Skin Biopsy, Peripheral Neuropathy and Neuropathic Pain Center, IRCCS Foundation "Carlo Besta" Neurological Institute, Milan, Italy
| | - Giuseppe Lauria
- Neuroalgology Unit and Skin Biopsy, Peripheral Neuropathy and Neuropathic Pain Center, IRCCS Foundation "Carlo Besta" Neurological Institute, Milan, Italy
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97
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Adkins AE, Hack LM, Bigdeli TB, Williamson VS, McMichael GO, Mamdani M, Edwards A, Aliev F, Chan RF, Bhandari P, Raabe RC, Alaimo JT, Blackwell GG, Moscati AA, Poland RS, Rood B, Patterson DG, Walsh D, Whitfield JB, Zhu G, Montgomery GW, Henders AK, Martin NG, Heath AC, Madden PA, Frank J, Ridinger M, Wodarz N, Soyka M, Zill P, Ising M, Nöthen MM, Kiefer F, Rietschel M, Gelernter J, Sherva R, Koesterer R, Almasy L, Zhao H, Kranzler HR, Farrer LA, Maher BS, Prescott CA, Dick DM, Bacanu SA, Mathies LD, Davies AG, Vladimirov VI, Grotewiel M, Bowers MS, Bettinger JC, Webb BT, Miles MF, Kendler KS, Riley BP. Genomewide Association Study of Alcohol Dependence Identifies Risk Loci Altering Ethanol-Response Behaviors in Model Organisms. Alcohol Clin Exp Res 2017; 41:911-928. [PMID: 28226201 PMCID: PMC5404949 DOI: 10.1111/acer.13362] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2016] [Accepted: 02/16/2017] [Indexed: 01/23/2023]
Abstract
BACKGROUND Alcohol dependence (AD) shows evidence for genetic liability, but genes influencing risk remain largely unidentified. METHODS We conducted a genomewide association study in 706 related AD cases and 1,748 unscreened population controls from Ireland. We sought replication in 15,496 samples of European descent. We used model organisms (MOs) to assess the role of orthologous genes in ethanol (EtOH)-response behaviors. We tested 1 primate-specific gene for expression differences in case/control postmortem brain tissue. RESULTS We detected significant association in COL6A3 and suggestive association in 2 previously implicated loci, KLF12 and RYR3. None of these signals are significant in replication. A suggestive signal in the long noncoding RNA LOC339975 is significant in case:control meta-analysis, but not in a population sample. Knockdown of a COL6A3 ortholog in Caenorhabditis elegans reduced EtOH sensitivity. Col6a3 expression correlated with handling-induced convulsions in mice. Loss of function of the KLF12 ortholog in C. elegans impaired development of acute functional tolerance (AFT). Klf12 expression correlated with locomotor activation following EtOH injection in mice. Loss of function of the RYR3 ortholog reduced EtOH sensitivity in C. elegans and rapid tolerance in Drosophila. The ryanodine receptor antagonist dantrolene reduced motivation to self-administer EtOH in rats. Expression of LOC339975 does not differ between cases and controls but is reduced in carriers of the associated rs11726136 allele in nucleus accumbens (NAc). CONCLUSIONS We detect association between AD and COL6A3, KLF12, RYR3, and LOC339975. Despite nonreplication of COL6A3, KLF12, and RYR3 signals, orthologs of these genes influence behavioral response to EtOH in MOs, suggesting potential involvement in human EtOH response and AD liability. The associated LOC339975 allele may influence gene expression in human NAc. Although the functions of long noncoding RNAs are poorly understood, there is mounting evidence implicating these genes in multiple brain functions and disorders.
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Affiliation(s)
- Amy E. Adkins
- Virginia Commonwealth University Alcohol Research Center, PO Box
980424, Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Psychiatry, PO Box 980424, Virginia Commonwealth
University, Richmond, VA, 23298-0424, USA
| | - Laura M. Hack
- Virginia Commonwealth University Alcohol Research Center, PO Box
980424, Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Psychiatry, PO Box 980424, Virginia Commonwealth
University, Richmond, VA, 23298-0424, USA
| | - Tim B. Bigdeli
- Department of Psychiatry, PO Box 980424, Virginia Commonwealth
University, Richmond, VA, 23298-0424, USA
| | - Vernell S. Williamson
- Virginia Commonwealth University Alcohol Research Center, PO Box
980424, Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Psychiatry, PO Box 980424, Virginia Commonwealth
University, Richmond, VA, 23298-0424, USA
| | - G. Omari McMichael
- Virginia Commonwealth University Alcohol Research Center, PO Box
980424, Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Psychiatry, PO Box 980424, Virginia Commonwealth
University, Richmond, VA, 23298-0424, USA
| | - Mohammed Mamdani
- Virginia Commonwealth University Alcohol Research Center, PO Box
980424, Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Psychiatry, PO Box 980424, Virginia Commonwealth
University, Richmond, VA, 23298-0424, USA
| | - Alexis Edwards
- Virginia Commonwealth University Alcohol Research Center, PO Box
980424, Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Psychiatry, PO Box 980424, Virginia Commonwealth
University, Richmond, VA, 23298-0424, USA
| | - Fazil Aliev
- Virginia Commonwealth University Alcohol Research Center, PO Box
980424, Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Psychiatry, PO Box 980424, Virginia Commonwealth
University, Richmond, VA, 23298-0424, USA
| | - Robin F. Chan
- Virginia Commonwealth University Alcohol Research Center, PO Box
980424, Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Human & Molecular Genetics, PO Box 980424,
Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
| | - Poonam Bhandari
- Department of Human & Molecular Genetics, PO Box 980424,
Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
| | - Richard C. Raabe
- Department of Pharmacology & Toxicology, PO Box 980424,
Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
| | - Joseph T. Alaimo
- Department of Pharmacology & Toxicology, PO Box 980424,
Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
| | - GinaMari G. Blackwell
- Department of Pharmacology & Toxicology, PO Box 980424,
Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
| | - Arden A. Moscati
- Virginia Commonwealth University Alcohol Research Center, PO Box
980424, Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Psychiatry, PO Box 980424, Virginia Commonwealth
University, Richmond, VA, 23298-0424, USA
| | - Ryan S. Poland
- Department of Pharmacology & Toxicology, PO Box 980424,
Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
| | - Benjamin Rood
- Department of Pharmacology & Toxicology, PO Box 980424,
Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
| | - Diana G. Patterson
- Shaftesbury Square Hospital, 116-120 Great Victoria Street, Belfast,
BT2 7BG, United Kingdom
| | - Dermot Walsh
- Health Research Board, 67-72 Lower Mount Street, Dublin 2,
Ireland
| | | | - John B. Whitfield
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute,
Royal Brisbane and Women’s Hospital, 300 Herston Road, Brisbane, QLD 4006,
Australia
| | - Gu Zhu
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute,
Royal Brisbane and Women’s Hospital, 300 Herston Road, Brisbane, QLD 4006,
Australia
| | - Grant W. Montgomery
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute,
Royal Brisbane and Women’s Hospital, 300 Herston Road, Brisbane, QLD 4006,
Australia
| | - Anjali K. Henders
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute,
Royal Brisbane and Women’s Hospital, 300 Herston Road, Brisbane, QLD 4006,
Australia
| | - Nicholas G. Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute,
Royal Brisbane and Women’s Hospital, 300 Herston Road, Brisbane, QLD 4006,
Australia
| | - Andrew C. Heath
- Department of Psychiatry, Washington University School of Medicine,
4560 Clayton Ave., Suite 1000, St. Louis, MO, 63110, USA
| | - Pamela A.F. Madden
- Department of Psychiatry, Washington University School of Medicine,
4560 Clayton Ave., Suite 1000, St. Louis, MO, 63110, USA
| | - Josef Frank
- Department of Genetic Epidemiology in Psychiatry, Central Institute
of Mental Health, Medical Faculty Mannheim/Heidelberg University, J 5, 68159
Mannheim, Germany
| | - Monika Ridinger
- Department of Psychiatry, University Hospital Regensburg,
University of Regensburg, 93042 Regensburg, Germany
| | - Norbert Wodarz
- Department of Psychiatry, University Hospital Regensburg,
University of Regensburg, 93042 Regensburg, Germany
| | - Michael Soyka
- Privatklinik Meiringen, Willigen, 3860 Meiringen, Switzerland
- Department of Psychiatry and Psychotherapy, University of Munich,
Nussbaumstrasse 7, 80336 Munich, Germany
| | - Peter Zill
- Department of Psychiatry and Psychotherapy, University of Munich,
Nussbaumstrasse 7, 80336 Munich, Germany
| | - Marcus Ising
- Department of Molecular Psychology, Max-Planck-Institute of
Psychiatry, Kraepelinstrasse 2–10, 80804 Munich, Germany
| | - Markus M Nöthen
- Department of Genomics, Life & Brain Center, University of
Bonn, Sigmund-Freud-Strasse 25, D-53127 Bonn, Germany
- Department of Institute of Human Genetics, University of Bonn,
Sigmund-Freud-Strasse 25, D-53127 Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), University of
Bonn, Sigmund-Freud-Strasse 25, D-53127 Bonn, Germany
| | - Falk Kiefer
- Department of Addictive Behavior and Addiction Medicine, Central
Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, J 5,
68159 Mannheim, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute
of Mental Health, Medical Faculty Mannheim/Heidelberg University, J 5, 68159
Mannheim, Germany
| | | | - Joel Gelernter
- Department of Psychiatry, Yale University School of Medicine, 333
Cedar Street, New Haven, CT, 06510, USA
- Department of Neurobiology, Yale University School of Medicine, 333
Cedar Street, New Haven, CT, 06510, USA
- Department of Genetics, Yale University School of Medicine, 333
Cedar Street, New Haven, CT, 06510, USA
- Department of Psychiatry, VA CT Healthcare Center, 950 Campbell
Avenue, West Haven, CT, 06516, USA
| | - Richard Sherva
- Department of Medicine (Biomedical Genetics), Boston University
School of Medicine, 72 East Concord Street, Boston, MA, 02118, USA
| | - Ryan Koesterer
- Department of Medicine (Biomedical Genetics), Boston University
School of Medicine, 72 East Concord Street, Boston, MA, 02118, USA
| | - Laura Almasy
- Texas Biomedical Research Institute, Department of Genetics, P.O.
Box 760549, San Antonio, TX, 78245-0549, USA
| | - Hongyu Zhao
- Department of Genetics, Yale University School of Medicine, 333
Cedar Street, New Haven, CT, 06510, USA
- Department of Biostatistics, Yale University School of Medicine,
333 Cedar Street, New Haven, CT, 06510, USA
| | - Henry R. Kranzler
- Department of Psychiatry, University of Pennsylvania Perelman
School of Medicine, Treatment Research Center, 3900 Chestnut Street, Philadelphia,
PA 19104, USA
- VISN 4 MIRECC, Philadelphia VA Medical Center, 3900 Woodland
Avenue, Philadelphia, PA, 19104, USA
| | - Lindsay A. Farrer
- Department of Psychiatry, VA CT Healthcare Center, 950 Campbell
Avenue, West Haven, CT, 06516, USA
- Department of Neurology, Boston University School of Medicine, 72
East Concord Street, Boston, MA, 02118, USA
- Department of Ophthalmology, Boston University School of Medicine,
72 East Concord Street, Boston, MA, 02118, USA
- Department of Genetics and Genomics, Boston University School of
Medicine, 72 East Concord Street, Boston, MA, 02118, USA
- Department of Epidemiology and Biostatistics, Boston University
School of Public Health, 715 Albany Street, Boston, MA, 02118, USA
| | - Brion S. Maher
- Department of Mental Health, Johns Hopkins Bloomberg School of
Public Health, 624 N. Broadway, 8th Floor, Baltimore, MD, 21205, USA
| | - Carol A. Prescott
- Department of Psychology, University of Southern California, SGM
501, 3620 South McClintock Ave., Los Angeles, CA, 90089-1061, USA
| | - Danielle M. Dick
- Virginia Commonwealth University Alcohol Research Center, PO Box
980424, Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Psychiatry, PO Box 980424, Virginia Commonwealth
University, Richmond, VA, 23298-0424, USA
- Department of Human & Molecular Genetics, PO Box 980424,
Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
| | - Silviu A. Bacanu
- Virginia Commonwealth University Alcohol Research Center, PO Box
980424, Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Psychiatry, PO Box 980424, Virginia Commonwealth
University, Richmond, VA, 23298-0424, USA
| | - Laura D. Mathies
- Department of Pharmacology & Toxicology, PO Box 980424,
Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
| | - Andrew G. Davies
- Virginia Commonwealth University Alcohol Research Center, PO Box
980424, Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Pharmacology & Toxicology, PO Box 980424,
Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
| | - Vladimir I. Vladimirov
- Virginia Commonwealth University Alcohol Research Center, PO Box
980424, Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Psychiatry, PO Box 980424, Virginia Commonwealth
University, Richmond, VA, 23298-0424, USA
- Lieber Institute for Brain Development, Johns Hopkins University,
855 North Wolfe Street Suite 300, Baltimore, MD, 21205, USA
- Center for Biomarker Research and Personalized Medicine, School of
Pharmacy, PO Box 980533, Virginia Commonwealth University, Richmond, VA 23298-0533,
USA
| | - Mike Grotewiel
- Virginia Commonwealth University Alcohol Research Center, PO Box
980424, Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Human & Molecular Genetics, PO Box 980424,
Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
| | - M. Scott Bowers
- Virginia Commonwealth University Alcohol Research Center, PO Box
980424, Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Psychiatry, PO Box 980424, Virginia Commonwealth
University, Richmond, VA, 23298-0424, USA
- Department of Pharmacology & Toxicology, PO Box 980424,
Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
| | - Jill C. Bettinger
- Virginia Commonwealth University Alcohol Research Center, PO Box
980424, Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Pharmacology & Toxicology, PO Box 980424,
Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
| | - Bradley T. Webb
- Virginia Commonwealth University Alcohol Research Center, PO Box
980424, Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Psychiatry, PO Box 980424, Virginia Commonwealth
University, Richmond, VA, 23298-0424, USA
| | - Michael F. Miles
- Virginia Commonwealth University Alcohol Research Center, PO Box
980424, Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Human & Molecular Genetics, PO Box 980424,
Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Pharmacology & Toxicology, PO Box 980424,
Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
| | - Kenneth S. Kendler
- Virginia Commonwealth University Alcohol Research Center, PO Box
980424, Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Psychiatry, PO Box 980424, Virginia Commonwealth
University, Richmond, VA, 23298-0424, USA
- Department of Human & Molecular Genetics, PO Box 980424,
Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
| | - Brien P. Riley
- Virginia Commonwealth University Alcohol Research Center, PO Box
980424, Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
- Department of Psychiatry, PO Box 980424, Virginia Commonwealth
University, Richmond, VA, 23298-0424, USA
- Department of Human & Molecular Genetics, PO Box 980424,
Virginia Commonwealth University, Richmond, VA, 23298-0424, USA
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Attie AD, Churchill GA, Nadeau JH. How mice are indispensable for understanding obesity and diabetes genetics. Curr Opin Endocrinol Diabetes Obes 2017; 24:83-91. [PMID: 28107248 PMCID: PMC5837807 DOI: 10.1097/med.0000000000000321] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
PURPOSE OF REVIEW The task of cataloging human genetic variation and its relation to disease is rapidly approaching completion. The new challenge is to discover the function of disease-associated genes and to understand the pathways that lead to human disease. We propose that achieving this new level of understanding will increasingly rely on the use of model organisms. We discuss the advantages of the mouse as a model organism to our understanding of human disease. RECENT FINDINGS The collection of available mouse strains represents as much genetic and phenotypic variation as is found in the human population. However, unlike humans, mice can be subjected to experimental breeding protocols and the availability of tissues allows for a far greater and deeper level of phenotyping. New methods for gene editing make it relatively easy to create mouse models of known human mutations. The distinction between genetic and epigenetic inheritance can be studied in great detail. Various experimental protocols enable the exploration of the role of the microbiome in physiology and disease. SUMMARY We propose that there will be an interdependence between human and model organism research. Technological advances and new genetic screening platforms in the mouse have greatly improved the path to gene discovery and mechanistic studies of gene function.
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Affiliation(s)
- Alan D Attie
- aDepartment of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin bThe Jackson Laboratory, Bar Harbor, Maine cPacific Northwest Research Institute, Seattle, Washington, USA
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99
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Orbitofrontal Neuroadaptations and Cross-Species Synaptic Biomarkers in Heavy-Drinking Macaques. J Neurosci 2017; 37:3646-3660. [PMID: 28270566 DOI: 10.1523/jneurosci.0133-17.2017] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Revised: 02/17/2017] [Accepted: 02/28/2017] [Indexed: 02/08/2023] Open
Abstract
Cognitive impairments, uncontrolled drinking, and neuropathological cortical changes characterize alcohol use disorder. Dysfunction of the orbitofrontal cortex (OFC), a critical cortical subregion that controls learning, decision-making, and prediction of reward outcomes, contributes to executive cognitive function deficits in alcoholic individuals. Electrophysiological and quantitative synaptomics techniques were used to test the hypothesis that heavy drinking produces neuroadaptations in the macaque OFC. Integrative bioinformatics and reverse genetic approaches were used to identify and validate synaptic proteins with novel links to heavy drinking in BXD mice. In drinking monkeys, evoked firing of OFC pyramidal neurons was reduced, whereas the amplitude and frequency of postsynaptic currents were enhanced compared with controls. Bath application of alcohol reduced evoked firing in neurons from control monkeys, but not drinking monkeys. Profiling of the OFC synaptome identified alcohol-sensitive proteins that control glutamate release (e.g., SV2A, synaptogyrin-1) and postsynaptic signaling (e.g., GluA1, PRRT2) with no changes in synaptic GABAergic proteins. Western blot analysis confirmed the increase in GluA1 expression in drinking monkeys. An exploratory analysis of the OFC synaptome found cross-species genetic links to alcohol intake in discrete proteins (e.g., C2CD2L, DIRAS2) that discriminated between low- and heavy-drinking monkeys. Validation studies revealed that BXD mouse strains with the D allele at the C2cd2l interval drank less alcohol than B allele strains. Thus, by profiling of the OFC synaptome, we identified changes in proteins controlling glutamate release and postsynaptic signaling and discovered several proteins related to heavy drinking that have potential as novel targets for treating alcohol use disorder.SIGNIFICANCE STATEMENT Clinical research identified cognitive deficits in alcoholic individuals as a risk factor for relapse, and alcoholic individuals display deficits on cognitive tasks that are dependent upon the orbitofrontal cortex (OFC). To identify neurobiological mechanisms that underpin OFC dysfunction, this study used electrophysiology and integrative synaptomics in a translational nonhuman primate model of heavy alcohol consumption. We found adaptations in synaptic proteins that control glutamatergic signaling in chronically drinking monkeys. Our functional genomic exploratory analyses identified proteins with genetic links to alcohol and cocaine intake across mice, monkeys, and humans. Future work is necessary to determine whether targeting these novel targets reduces excessive and harmful levels of alcohol drinking.
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Mulligan MK, Mozhui K, Pandey AK, Smith ML, Gong S, Ingels J, Miles MF, Lopez MF, Lu L, Williams RW. Genetic divergence in the transcriptional engram of chronic alcohol abuse: A laser-capture RNA-seq study of the mouse mesocorticolimbic system. Alcohol 2017; 58:61-72. [PMID: 27894806 DOI: 10.1016/j.alcohol.2016.09.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2016] [Revised: 09/12/2016] [Accepted: 09/16/2016] [Indexed: 12/14/2022]
Abstract
Genetic factors that influence the transition from initial drinking to dependence remain enigmatic. Recent studies have leveraged chronic intermittent ethanol (CIE) paradigms to measure changes in brain gene expression in a single strain at 0, 8, 72 h, and even 7 days following CIE. We extend these findings using LCM RNA-seq to profile expression in 11 brain regions in two inbred strains - C57BL/6J (B6) and DBA/2J (D2) - 72 h following multiple cycles of ethanol self-administration and CIE. Linear models identified differential expression based on treatment, region, strain, or interactions with treatment. Nearly 40% of genes showed a robust effect (FDR < 0.01) of region, and hippocampus CA1, cortex, bed nucleus stria terminalis, and nucleus accumbens core had the highest number of differentially expressed genes after treatment. Another 8% of differentially expressed genes demonstrated a robust effect of strain. As expected, based on similar studies in B6, treatment had a much smaller impact on expression; only 72 genes (p < 0.01) are modulated by treatment (independent of region or strain). Strikingly, many more genes (415) show a strain-specific and largely opposite response to treatment and are enriched in processes related to RNA metabolism, transcription factor activity, and mitochondrial function. Over 3 times as many changes in gene expression were detected in D2 compared to B6, and weighted gene co-expression network analysis (WGCNA) module comparison identified more modules enriched for treatment effects in D2. Substantial strain differences exist in the temporal pattern of transcriptional neuroadaptation to CIE, and these may drive individual differences in risk of addiction following excessive alcohol consumption.
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Affiliation(s)
- Megan K Mulligan
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, United States.
| | - Khyobeni Mozhui
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, United States
| | - Ashutosh K Pandey
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, United States
| | - Maren L Smith
- Department of Molecular Biology and Genetics, Virginia Commonwealth University, United States
| | - Suzhen Gong
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, United States
| | - Jesse Ingels
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, United States
| | - Michael F Miles
- Department of Molecular Biology and Genetics, Virginia Commonwealth University, United States
| | - Marcelo F Lopez
- Charleston Alcohol Research Center, Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, United States
| | - Lu Lu
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, United States
| | - Robert W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, United States
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