1. bookVolume 6 (2022): Edition 2 (April 2022)
Détails du magazine
License
Format
Magazine
eISSN
2564-615X
Première parution
30 Jan 2017
Périodicité
4 fois par an
Langues
Anglais
Accès libre

Genetically modified mice for research on human diseases: A triumph for Biotechnology or a work in progress?

Publié en ligne: 30 Apr 2022
Volume & Edition: Volume 6 (2022) - Edition 2 (April 2022)
Pages: 61 - 88
Détails du magazine
License
Format
Magazine
eISSN
2564-615X
Première parution
30 Jan 2017
Périodicité
4 fois par an
Langues
Anglais
Abstract

Genetically modified mice are engineered as models for human diseases. These mouse models include inbred strains, mutants, gene knockouts, gene knockins, and ‘humanized’ mice. Each mouse model is engineered to mimic a specific disease based on a theory of the genetic basis of that disease. For example, to test the amyloid theory of Alzheimer’s disease, mice with amyloid precursor protein genes are engineered, and to test the tau theory, mice with tau genes are engineered. This paper discusses the importance of mouse models in basic research, drug discovery, and translational research, and examines the question of how to define the “best” mouse model of a disease. The critiques of animal models and the caveats in translating the results from animal models to the treatment of human disease are discussed. Since many diseases are heritable, multigenic, age-related and experience-dependent, resulting from multiple gene-gene and gene-environment interactions, it will be essential to develop mouse models that reflect these genetic, epigenetic and environmental factors from a developmental perspective. Such models would provide further insight into disease emergence, progression and the ability to model two-hit and multi-hit theories of disease. The summary examines the biotechnology for creating genetically modified mice which reflect these factors and how they might be used to discover new treatments for complex human diseases such as cancers, neurodevelopmental and neurodegenerative diseases.

Keywords

1. List of Currently Incurable Diseases. Disabled World Available from: https://www.disabled-world.com/definitions/lists/incurable.php.2020. Accessed February 28, 2022. Search in Google Scholar

2. Beckers J, Wurst W, de Angelis MH. Towards better mouse models: enhanced genotypes, systemic phenotyping and envirotype modelling. Nat Rev Genet 2009;10:371–380.10.1038/nrg257819434078 Search in Google Scholar

3. Dawson TM, Golde TE, Lagier-Tourenne C. Animal models of neurodegenerative diseases. Nat Neurosci 2018;21:1370–1379.10.1038/s41593-018-0236-8661503930250265 Search in Google Scholar

4. Gitler AD, Dhillon P, Shorter J. Neurodegenerative disease: models, mechanisms, and a new hope. Dis Model Mech 2017;10:499–502.10.1242/dmm.030205545117728468935 Search in Google Scholar

5. Onaciu A, Munteanu R, Munteanu VC, et al. Spontaneous and Induced Animal Models for Cancer Research. Diagn Basel Switz 2020;10:E660.10.3390/diagnostics10090660755504432878340 Search in Google Scholar

6. Riehle C, Bauersachs J. Small animal models of heart failure. Cardiovasc Res 2019;115:1838–1849.10.1093/cvr/cvz161680381531243437 Search in Google Scholar

7. Tsuneyama K, Nishitsuji K, Matsumoto M, et al. Animal models for analyzing metabolic syndrome-associated liver diseases. Pathol Int 2017;67:539–546.10.1111/pin.1260029027308 Search in Google Scholar

8. Vaquer G, Rivière F, Mavris M, et al. Animal models for metabolic, neuromuscular and ophthalmological rare diseases. Nat Rev Drug Discov 2013;12:287–305.10.1038/nrd383123493083 Search in Google Scholar

9. Flora A. The Versatile Mouse Model for Rare Disease Research. The Jackson Laboratory Available from: https://www.jax.org/news-and-insights/jax-blog/2019/may/the-versatile-mouse-model-for-rare-disease-research. Accessed April 3, 2022. Search in Google Scholar

10. Moore M. A new world of opportunity in rare diseases. The Jackson Laboratory Available from: https://www.jax.org/news-and-insights/2018/october/a-new-world-of-opportunity-in-rare-diseases. Accessed April 3, 2022. Search in Google Scholar

11. Cacheiro P, Haendel MA, Smedley D, et al. New models for human disease from the International Mouse Phenotyping Consortium. Mamm Genome Off J Int Mamm Genome Soc 2019;30:143–150.10.1007/s00335-019-09804-5660666431127358 Search in Google Scholar

12. Brommage R, Ohlsson C. High Fidelity of Mouse Models Mimicking Human Genetic Skeletal Disorders. Front Endocrinol;10 Available from: https://www.frontiersin.org/article/10.3389/fendo.2019.00934. 2020. Accessed April 3, 2022. Search in Google Scholar

13. Sztretye M, Szabó L, Dobrosi N, et al. From Mice to Humans: An Overview of the Potentials and Limitations of Current Transgenic Mouse Models of Major Muscular Dystrophies and Congenital Myopathies. Int J Mol Sci 2020;21:8935.10.3390/ijms21238935772813833255644 Search in Google Scholar

14. Deshpande O, Lara RZ, Zhang OR, et al. ZNF423 patient variants, truncations, and in-frame deletions in mice define an allele-dependent range of midline brain abnormalities. PLOS Genet 2020;16:e1009017.10.1371/journal.pgen.1009017751520132925911 Search in Google Scholar

15. Nair RR, Corrochano S, Gasco S, et al. Uses for humanised mouse models in precision medicine for neurodegenerative disease. Mamm Genome Off J Int Mamm Genome Soc 2019;30:173–191.10.1007/s00335-019-09807-2 Search in Google Scholar

16. Murillo-Cuesta S, Artuch R, Asensio F, et al. The Value of Mouse Models of Rare Diseases: A Spanish Experience. Front Genet 2020;11:583932.10.3389/fgene.2020.583932 Search in Google Scholar

17. Zárybnický T, Heikkinen A, Kangas SM, et al. Modeling Rare Human Disorders in Mice: The Finnish Disease Heritage. Cells 2021;10:3158.10.3390/cells10113158 Search in Google Scholar

18. Wojczynski MK, Tiwari HK. Definition of phenotype. Adv Genet 2008;60:75–105.10.1016/S0065-2660(07)00404-X Search in Google Scholar

19. Brown SDM. Advances in mouse genetics for the study of human disease. Hum Mol Genet 2021;30:R274–R284.10.1093/hmg/ddab153849001434089057 Search in Google Scholar

20. Adhikary PP, Ul Ain Q, Hocke AC, et al. COVID-19 highlights the model dilemma in biomedical research. Nat Rev Mater 2021;6:374–376.10.1038/s41578-021-00305-z796777833747552 Search in Google Scholar

21. Flores-Santin J, Burggren WW. Beyond the Chicken: Alternative Avian Models for Developmental Physiological Research. Front Physiol 2021;12:712633.10.3389/fphys.2021.712633856688434744759 Search in Google Scholar

22. Howland D, Ellederova Z, Aronin N, et al. Large Animal Models of Huntington’s Disease: What We Have Learned and Where We Need to Go Next. J Huntingt Dis 2020;9:201–216.10.3233/JHD-200425759737132925082 Search in Google Scholar

23. Leong X-F, Ng C-Y, Jaarin K. Animal Models in Cardiovascular Research: Hypertension and Atherosclerosis. BioMed Res Int 2015;2015:528757. Search in Google Scholar

24. Obeid M, Khabbaz RC, Garcia KD, et al. Translational Animal Models for Liver Cancer. Am J Interv Radiol;2. Epub ahead of print February 24, 2018. DOI: 10.25259/AJIR-11-2017.10.25259/AJIR-11-2017 Search in Google Scholar

25. Vandamme TF. Use of rodents as models of human diseases. J Pharm Bioallied Sci 2014;6:2–9.10.4103/0975-7406.124301389528924459397 Search in Google Scholar

26. Homberg JR, Adan RAH, Alenina N, et al. The continued need for animals to advance brain research. Neuron 2021;109:2374–2379.10.1016/j.neuron.2021.07.01534352213 Search in Google Scholar

27. Ma X, Aravind A, Pfister BJ, et al. Animal Models of Traumatic Brain Injury and Assessment of Injury Severity. Mol Neurobiol 2019;56:5332–5345.10.1007/s12035-018-1454-530603958 Search in Google Scholar

28. Yee NS, Ignatenko N, Finnberg N, et al. Animal Models of Cancer Biology. Cancer Growth Metastasis 2015;8s1:CGM.S37907.10.4137/CGM.S37907467643326688665 Search in Google Scholar

29. Procaccini C, De Rosa V, Pucino V, et al. Animal models of Multiple Sclerosis. Eur J Pharmacol 2015;759:182–191.10.1016/j.ejphar.2015.03.042709466125823807 Search in Google Scholar

30. Wagar LE, DiFazio RM, Davis MM. Advanced model systems and tools for basic and translational human immunology. Genome Med 2018;10:73.10.1186/s13073-018-0584-8616294330266097 Search in Google Scholar

31. Yu X, Petersen F. A methodological review of induced animal models of autoimmune diseases. Autoimmun Rev 2018;17:473–479.10.1016/j.autrev.2018.03.00129526631 Search in Google Scholar

32. Zaragoza C, Gomez-Guerrero C, Martin-Ventura JL, et al. Animal models of cardiovascular diseases. J Biomed Biotechnol 2011;2011:497841.10.1155/2011/497841304266721403831 Search in Google Scholar

33. Harris JC. Animal models of neurodevelopmental disorders with behavioral phenotypes. Curr Opin Psychiatry 2021;34:87–93.10.1097/YCO.000000000000067533395099 Search in Google Scholar

34. Chadman KK. Animal models for autism in 2017 and the consequential implications to drug discovery. Expert Opin Drug Discov 2017;12:1187–1194.10.1080/17460441.2017.138398228971687 Search in Google Scholar

35. Varghese M, Keshav N, Jacot-Descombes S, et al. Autism spectrum disorder: neuropathology and animal models. Acta Neuropathol (Berl) 2017;134:537–566.10.1007/s00401-017-1736-4569371828584888 Search in Google Scholar

36. Sontag TA, Tucha O, Walitza S, et al. Animal models of attention deficit/hyperactivity disorder (ADHD): a critical review. Atten Deficit Hyperact Disord 2010;2:1–20.10.1007/s12402-010-0019-x21432586 Search in Google Scholar

37. de la Peña JB, Dela Peña IJ, Custodio RJ, et al. Exploring the Validity of Proposed Transgenic Animal Models of Attention-Deficit Hyperactivity Disorder (ADHD). Mol Neurobiol 2018;55:3739–3754. Search in Google Scholar

38. Winship IR, Dursun SM, Baker GB, et al. An Overview of Animal Models Related to Schizophrenia. Can J Psychiatry Rev Can Psychiatr 2019;64:5–17.10.1177/0706743718773728636413929742910 Search in Google Scholar

39. Götz J, Bodea L-G, Goedert M. Rodent models for Alzheimer disease. Nat Rev Neurosci 2018;19:583–598.10.1038/s41583-018-0054-830194347 Search in Google Scholar

40. Mullane K, Williams M. Preclinical Models of Alzheimer’s Disease: Relevance and Translational Validity. Curr Protoc Pharmacol 2019;84:e57.10.1002/cpph.5730802363 Search in Google Scholar

41. Scearce-Levie K, Sanchez PE, Lewcock JW. Leveraging preclinical models for the development of Alzheimer disease therapeutics. Nat Rev Drug Discov 2020;19:447–462.10.1038/s41573-020-0065-932612262 Search in Google Scholar

42. Barker RA, Björklund A. Animal Models of Parkinson’s Disease: Are They Useful or Not? J Park Dis 2020;10:1335–1342. Search in Google Scholar

43. Farshim PP, Bates GP. Mouse Models of Huntington’s Disease. In: Precious SV, Rosser AE, Dunnett SB (eds) Huntington’s Disease. New York, NY: Springer:97–120.10.1007/978-1-4939-7825-0_629856016 Search in Google Scholar

44. Menalled L, Brunner D. Animal models of Huntington’s disease for translation to the clinic: best practices. Mov Disord Off J Mov Disord Soc 2014;29:1375–1390.10.1002/mds.2600625216369 Search in Google Scholar

45. Lutz C. Mouse models of ALS: Past, present and future. Brain Res 2018;1693:1–10.10.1016/j.brainres.2018.03.02429577886 Search in Google Scholar

46. Kin K, Yasuhara T, Kameda M, et al. Animal Models for Parkinson’s Disease Research: Trends in the 2000s. Int J Mol Sci 2019;20:E5402.10.3390/ijms20215402686202331671557 Search in Google Scholar

47. Pingale T, Gupta GL. Classic and evolving animal models in Parkinson’s disease. Pharmacol Biochem Behav 2020;199:173060.10.1016/j.pbb.2020.17306033091373 Search in Google Scholar

48. Abboud C, Duveau A, Bouali-Benazzouz R, et al. Animal models of pain: Diversity and benefits. J Neurosci Methods 2021;348:108997.10.1016/j.jneumeth.2020.10899733188801 Search in Google Scholar

49. Brum ES, Becker G, Fialho MFP, et al. Animal models of fibromyalgia: What is the best choice? Pharmacol Ther 2022;230:107959. Search in Google Scholar

50. Brookes E, Shi Y. Diverse epigenetic mechanisms of human disease. Annu Rev Genet 2014;48:237–268.10.1146/annurev-genet-120213-09251825195505 Search in Google Scholar

51. Heindel JJ. The developmental basis of disease: Update on environmental exposures and animal models. Basic Clin Pharmacol Toxicol 2019;125 Suppl 3:5–13.10.1111/bcpt.1311830265444 Search in Google Scholar

52. Ong M-L, Lin X, Holbrook JD. Measuring epigenetics as the mediator of gene/environment interactions in DOHaD. J Dev Orig Health Dis 2015;6:10–16.10.1017/S204017441400050625315715 Search in Google Scholar

53. Phillips NLH, Roth TL. Animal Models and Their Contribution to Our Understanding of the Relationship Between Environments, Epigenetic Modifications, and Behavior. Genes 2019;10:E47.10.3390/genes10010047635718330650619 Search in Google Scholar

54. Heegaard PMH, Sturek M, Alloosh M, et al. Animal Models for COVID-19: More to the Picture Than ACE2, Rodents, Ferrets, and Non-human Primates. A Case for Porcine Respiratory Coronavirus and the Obese Ossabaw Pig. Front Microbiol 2020;11:573756.10.3389/fmicb.2020.573756754590433101246 Search in Google Scholar

55. Muñoz-Fontela C, Dowling WE, Funnell SGP, et al. Animal models for COVID-19. Nature 2020;586:509–515.10.1038/s41586-020-2787-6813686232967005 Search in Google Scholar

56. Pandey K, Acharya A, Mohan M, et al. Animal models for SARS-CoV-2 research: A comprehensive literature review. Transbound Emerg Dis 2021;68:1868–1885.10.1111/tbed.13907808518633128861 Search in Google Scholar

57. Singh A, Singh RS, Sarma P, et al. A Comprehensive Review of Animal Models for Coronaviruses: SARS-CoV-2, SARS-CoV, and MERS-CoV. Virol Sin 2020;35:290–304.10.1007/s12250-020-00252-z732448532607866 Search in Google Scholar

58. Genzel L, Adan R, Berns A, et al. How the COVID-19 pandemic highlights the necessity of animal research. Curr Biol CB 2020;30:R1014–R1018. Search in Google Scholar

59. Pechanova O. Why We Still Need Reliable Animal Models. Pathophysiology 2020;27:44–45.10.3390/pathophysiology27010006883046235366255 Search in Google Scholar

60. Walker A, Pottinger G, Scott A, et al. Anosmia and loss of smell in the era of covid-19. BMJ 2020;370:m2808.10.1136/bmj.m280832694187 Search in Google Scholar

61. Paolo G. Does COVID-19 cause permanent damage to olfactory and gustatory function? Med Hypotheses 2020;143:110086. Search in Google Scholar

62. Jafari Z, Kolb BE, Mohajerani MH. Hearing Loss, Tinnitus, and Dizziness in COVID-19: A Systematic Review and Meta-Analysis. Can J Neurol Sci 2022; 49(2): 184–195.10.1017/cjn.2021.63826734333843530 Search in Google Scholar

63. Wu Y, Xu X, Chen Z, et al. Nervous system involvement after infection with COVID-19 and other coronaviruses. Brain Behav Immun 2020;87:18–22.10.1016/j.bbi.2020.03.031714668932240762 Search in Google Scholar

64. Fotuhi M, Mian A, Meysami S, et al. Neurobiology of COVID-19. J Alzheimers Dis JAD 2020;76:3–19.10.3233/JAD-200581766099032538857 Search in Google Scholar

65. Iadecola C, Anrather J, Kamel H. Effects of COVID-19 on the Nervous System. Cell 2020;183:16-27.e1.10.1016/j.cell.2020.08.028743750132882182 Search in Google Scholar

66. Ghazavi A, Ganji A, Keshavarzian N, et al. Cytokine profile and disease severity in patients with COVID-19. Cytokine 2021;137:155323.10.1016/j.cyto.2020.155323752470833045526 Search in Google Scholar

67. Schultze JL, Aschenbrenner AC. COVID-19 and the human innate immune system. Cell 2021;184:1671–1692.10.1016/j.cell.2021.02.029788562633743212 Search in Google Scholar

68. Somasundaram NP, Ranathunga I, Ratnasamy V, et al. The Impact of SARS-Cov-2 Virus Infection on the Endocrine System. J Endocr Soc 2020;4:bvaa082.10.1210/jendso/bvaa082733783932728654 Search in Google Scholar

69. Raony Í, de Figueiredo CS, Pandolfo P, et al. Psycho-Neuroendocrine-Immune Interactions in COVID-19: Potential Impacts on Mental Health. Front Immunol 2020;11:1170.10.3389/fimmu.2020.01170726702532574266 Search in Google Scholar

70. Gurumurthy CB, Quadros RM, Richardson GP, et al. Genetically modified mouse models to help fight COVID-19. Nat Protoc 2020;15:3777–3787.10.1038/s41596-020-00403-2770493833106680 Search in Google Scholar

71. Ye W, Chen Q. Potential Applications and Perspectives of Humanized Mouse Models. Annu Rev Anim Biosci 2022;10:395–417.10.1146/annurev-animal-020420-03302934758273 Search in Google Scholar

72. Veenhuis RT, Zeiss CJ. Animal Models of COVID-19 II. Comparative Immunology. ILAR J 2021;ilab010.10.1093/ilar/ilab010813534033914873 Search in Google Scholar

73. Taft RA, Davisson M, Wiles MV. Know thy mouse. Trends Genet TIG 2006;22:649–653.10.1016/j.tig.2006.09.01017007958 Search in Google Scholar

74. Blake JA, Baldarelli R, Kadin JA, et al. Mouse Genome Database (MGD): Knowledgebase for mouse–human comparative biology. Nucleic Acids Res 2021;49:D981–D987.10.1093/nar/gkaa1083777903033231642 Search in Google Scholar

75. Bult CJ, Blake JA, Smith CL, et al. Mouse Genome Database (MGD) 2019. Nucleic Acids Res 2019;47:D801–D806.10.1093/nar/gky1056632392330407599 Search in Google Scholar

76. Ringwald M, Richardson JE, Baldarelli RM, et al. Mouse Genome Informatics (MGI): latest news from MGD and GXD. Mamm Genome 2022;33:4–18.10.1007/s00335-021-09921-0891353034698891 Search in Google Scholar

77. Bogue MA, Philip VM, Walton DO, et al. Mouse Phenome Database: a data repository and analysis suite for curated primary mouse phenotype data. Nucleic Acids Res 2020;48:D716–D723.10.1093/nar/gkz1032714561231696236 Search in Google Scholar

78. Chia R, Achilli F, Festing MFW, et al. The origins and uses of mouse outbred stocks. Nat Genet 2005;37:1181–1186.10.1038/ng166516254564 Search in Google Scholar

79. Tuttle AH, Philip VM, Chesler EJ, et al. Comparing phenotypic variation between inbred and outbred mice. Nat Methods 2018;15:994–996.10.1038/s41592-018-0224-7651839630504873 Search in Google Scholar

80. Tuttle AH, Philip VM, Chesler EJ, et al. Author Correction: Comparing phenotypic variation between inbred and outbred mice. Nat Methods 2019;16:206.10.1038/s41592-018-0298-230584248 Search in Google Scholar

81. Tuttle AH, Philip VM, Chesler EJ, et al. Author Correction: Comparing phenotypic variation between inbred and outbred mice. Nat Methods 2020;17:947.10.1038/s41592-020-0932-732728193 Search in Google Scholar

82. Saul MC, Philip VM, Reinholdt LG, et al. High-Diversity Mouse Populations for Complex Traits. Trends Genet 2019;35:501–514.10.1016/j.tig.2019.04.003657103131133439 Search in Google Scholar

83. Beck JA, Lloyd S, Hafezparast M, et al. Genealogies of mouse inbred strains. Nat Genet 2000;24:23–25.10.1038/7164110615122 Search in Google Scholar

84. Casellas J. Inbred mouse strains and genetic stability: a review. Anim Int J Anim Biosci 2011;5:1–7.10.1017/S175173111000166722440695 Search in Google Scholar

85. Simpson EM, Linder CC, Sargent EE, et al. Genetic variation among 129 substrains and its importance for targeted mutagenesis in mice. Nat Genet 1997;16:19–27.10.1038/ng0597-199140391 Search in Google Scholar

86. Threadgill DW, Yee D, Matin A, et al. Genealogy of the 129 inbred strains: 129/SvJ is a contaminated inbred strain. Mamm Genome Off J Int Mamm Genome Soc 1997;8:390–393.10.1007/s0033599004539166580 Search in Google Scholar

87. Mekada K, Yoshiki A. Substrains matter in phenotyping of C57BL/6 mice. Exp Anim 2021;70:145–160.10.1538/expanim.20-0158815024033441510 Search in Google Scholar

88. Fertan E, Wong AA, Purdon MK, et al. The effect of background strain on the behavioral phenotypes of the MDGA2+/- mouse model of autism spectrum disorder. Genes Brain Behav 2021;20:e12696.10.1111/gbb.1269632808443 Search in Google Scholar

89. Tam WY, Cheung K-K. Phenotypic characteristics of commonly used inbred mouse strains. J Mol Med 2020;98:1215–1234.10.1007/s00109-020-01953-432712726 Search in Google Scholar

90. Flaherty L, Bolivar V. Congenic and Consomic Strains. In: Byron C. Jones and Pierre Mormede (editors). Neurobehavioral Genetics: Methods and Applications, second edition. Boca Raton: CRC Press: 2006; 115-128.10.1201/9781420003567.ch8 Search in Google Scholar

91. Farkas C, Fuentes-Villalobos F, Rebolledo-Jaramillo B, et al. Streamlined computational pipeline for genetic background characterization of genetically engineered mice based on next generation sequencing data. BMC Genomics 2019;20:131.10.1186/s12864-019-5504-9637308230755158 Search in Google Scholar

92. Schellinck HM, Cyr DP, Brown RE. Chapter 7 - How Many Ways Can Mouse Behavioral Experiments Go Wrong? Confounding Variables in Mouse Models of Neurodegenerative Diseases and How to Control Them. In: Brockmann HJ, Roper TJ, Naguib M, et al. (eds) Advances in the Study of Behavior. Academic Press: 2010;41: 255–366. Search in Google Scholar

93. Vanden Berghe T, Hulpiau P, Martens L, et al. Passenger Mutations Confound Interpretation of All Genetically Modified Congenic Mice. Immunity 2015;43:200–209.10.1016/j.immuni.2015.06.011480081126163370 Search in Google Scholar

94. Gurumurthy CB, Lloyd KCK. Generating mouse models for biomedical research: technological advances. Dis Model Mech 2019;12:dmm029462.10.1242/dmm.029462636115730626588 Search in Google Scholar

95. Fujiwara S. Humanized mice: A brief overview on their diverse applications in biomedical research. J Cell Physiol 2018;233:2889–2901.10.1002/jcp.2602228543438 Search in Google Scholar

96. Acevedo-Arozena A, Wells S, Potter P, et al. ENU mutagenesis, a way forward to understand gene function. Annu Rev Genomics Hum Genet 2008;9:49–69.10.1146/annurev.genom.9.081307.16422418949851 Search in Google Scholar

97. Simon MM, Moresco EMY, Bull KR, et al. Current strategies for mutation detection in phenotype-driven screens utilising next generation sequencing. Mamm Genome Off J Int Mamm Genome Soc 2015;26:486–500.10.1007/s00335-015-9603-x460206026449678 Search in Google Scholar

98. Fuchs H, Gailus-Durner V, Adler T, et al. Mouse phenotyping. Methods 2011;53:120–135.10.1016/j.ymeth.2010.08.00620708688 Search in Google Scholar

99. Lalonde R, Filali M, Strazielle C. SHIRPA as a Neurological Screening Battery in Mice. Curr Protoc 2021;1:e135.10.1002/cpz1.13534000103 Search in Google Scholar

100. Rogers DC, Fisher EM, Brown SD, et al. Behavioral and functional analysis of mouse phenotype: SHIRPA, a proposed protocol for comprehensive phenotype assessment. Mamm Genome Off J Int Mamm Genome Soc 1997;8:711–713.10.1007/s0033599005519321461 Search in Google Scholar

101. Crawley JN. What’s wrong with my mouse?: behavioral phenotyping of transgenic and knockout mice. Hoboken, N.J.: Wiley-Interscience Available from: http://www.123library.org/book_details/?id=15036. 2007. Accessed March 8, 2022. Search in Google Scholar

102. Garcia-Gomes MSA, Zanatto DA, Yamamoto PK, et al. A Simple and Fast Battery Test for Phenotypic Characterization of Mice. Bio-Protoc 2020;10:e3568.10.21769/BioProtoc.3568784262833659538 Search in Google Scholar

103. van der Staay FJ, Steckler T. Behavioural phenotyping of mouse mutants. Behav Brain Res 2001;125:3–12.10.1016/S0166-4328(01)00278-9 Search in Google Scholar

104. Wahlsten D. Mouse behavioral testing: how to use mice in behavioral neuroscience. 1st ed. London; Burlington, VT: Academic, 2011. Search in Google Scholar

105. Jaisser F. Inducible gene expression and gene modification in transgenic mice. J Am Soc Nephrol JASN 2000;11 Suppl 16:S95–S100.10.1681/ASN.V11suppl_2s95 Search in Google Scholar

106. Si-Hoe SL, Wells S, Murphy D. Production of transgenic rodents by the microinjection of cloned DNA into fertilized one-cell eggs. Mol Biotechnol 2001;17:151–182.10.1385/MB:17:2:151 Search in Google Scholar

107. Doyle A, McGarry MP, Lee NA, et al. The construction of transgenic and gene knockout/knockin mouse models of human disease. Transgenic Res 2012;21:327–349.10.1007/s11248-011-9537-3 Search in Google Scholar

108. Hall B, Limaye A, Kulkarni AB. Overview: Generation of Gene Knockout Mice. Curr Protoc Cell Biol 2009;44:19.12.1-19.12.17.10.1002/0471143030.cb1912s44 Search in Google Scholar

109. Hamilton SM, Spencer CM, Harrison WR, et al. Multiple autism-like behaviors in a novel transgenic mouse model. Behav Brain Res 2011;218:29–41.10.1016/j.bbr.2010.11.026 Search in Google Scholar

110. Jacquot S, Chartoire N, Piguet F, et al. Optimizing PCR for Mouse Genotyping: Recommendations for Reliable, Rapid, Cost Effective, Robust and Adaptable to High-Throughput Genotyping Protocol for Any Type of Mutation. Curr Protoc Mouse Biol 2019;9:e65.10.1002/cpmo.65 Search in Google Scholar

111. Panneer SK, Arindkar SK, Nagarajan P. Mouse Genetics and Breeding. In: Nagarajan P, Gudde R, Srinivasan R (eds) Essentials of Laboratory Animal Science: Principles and Practices. Singapore: Springer: 2021;343–371.10.1007/978-981-16-0987-9_15 Search in Google Scholar

112. Vaisman BL. Genotyping of Transgenic Animals by Real-Time Quantitative PCR with TaqMan Probes. In: Freeman LA (ed) Lipoproteins and Cardiovascular Disease: Methods and Protocols. Totowa, NJ: Humana Press:233–251.10.1007/978-1-60327-369-5_11 Search in Google Scholar

113. Delic S, Streif S, Deussing JM, et al. Genetic mouse models for behavioral analysis through transgenic RNAi technology. Genes Brain Behav 2008;7:821–830.10.1111/j.1601-183X.2008.00412.x Search in Google Scholar

114. Mittal V. Improving the efficiency of RNA interference in mammals. Nat Rev Genet 2004;5:355–365.10.1038/nrg132315143318 Search in Google Scholar

115. Du P, Lou C, Zhao X, et al. CRISPR-Based Genetic Switches and Other Complex Circuits: Research and Application. Life 2021;11:1255.10.3390/life11111255862132134833131 Search in Google Scholar

116. Horii T, Arai Y, Yamazaki M, et al. Validation of microinjection methods for generating knockout mice by CRISPR/Cas-mediated genome engineering. Sci Rep 2014;4:4513.10.1038/srep04513538011024675426 Search in Google Scholar

117. Lanigan TM, Kopera HC, Saunders TL. Principles of Genetic Engineering. Genes 2020;11:291.10.3390/genes11030291714080832164255 Search in Google Scholar

118. Nakajima K, Kazuno A-A, Kelsoe J, et al. Exome sequencing in the knockin mice generated using the CRISPR/Cas system. Sci Rep 2016;6:34703.10.1038/srep34703504815027698470 Search in Google Scholar

119. Brehm MA, Shultz LD, Greiner DL. Humanized mouse models to study human diseases. Curr Opin Endocrinol Diabetes Obes 2010;17:120–125.10.1097/MED.0b013e328337282f289228420150806 Search in Google Scholar

120. Tian H, Lyu Y, Yang Y-G, et al. Humanized Rodent Models for Cancer Research. Front Oncol 2020;10:1696.10.3389/fonc.2020.01696751801533042811 Search in Google Scholar

121. Dash PK, Gorantla S, Poluektova L, et al. Humanized Mice for Infectious and Neurodegenerative disorders. Retrovirology 2021;18:13.10.1186/s12977-021-00557-1817971234090462 Search in Google Scholar

122. Devoy A, Bunton-Stasyshyn RKA, Tybulewicz VLJ, et al. Genomically humanized mice: technologies and promises. Nat Rev Genet 2012;13:14–20.10.1038/nrg3116478221722179716 Search in Google Scholar

123. Buffalo EA, Movshon JA, Wurtz RH. From basic brain research to treating human brain disorders. Proc Natl Acad Sci U S A 2019;201919895.10.1073/pnas.1919895116693668431871205 Search in Google Scholar

124. Molnár Z, Clowry G. Cerebral cortical development in rodents and primates. Prog Brain Res 2012;195:45–70.10.1016/B978-0-444-53860-4.00003-922230622 Search in Google Scholar

125. Savolainen SM, Foley JF, Elmore SA. Histology atlas of the developing mouse heart with emphasis on E11.5 to E18.5. Toxicol Pathol 2009;37:395–414.10.1177/0192623309335060277344619359541 Search in Google Scholar

126. Gensollen T, Iyer SS, Kasper DL, et al. How colonization by microbiota in early life shapes the immune system. Science 2016;352:539–544.10.1126/science.aad9378505052427126036 Search in Google Scholar

127. Ackert-Bicknell CL, Anderson LC, Sheehan S, et al. Aging Research Using Mouse Models. Curr Protoc Mouse Biol 2015;5:95–133.10.1002/9780470942390.mo140195459077526069080 Search in Google Scholar

128. Vanhooren V, Libert C. The mouse as a model organism in aging research: usefulness, pitfalls and possibilities. Ageing Res Rev 2013;12:8–21.10.1016/j.arr.2012.03.01022543101 Search in Google Scholar

129. Ximerakis M, Lipnick SL, Innes BT, et al. Single-cell transcriptomic profiling of the aging mouse brain. Nat Neurosci 2019;22:1696–1708.10.1038/s41593-019-0491-331551601 Search in Google Scholar

130. Shimada A, Hasegawa-Ishii S. Senescence-accelerated Mice (SAMs) as a Model for Brain Aging and Immunosenescence. Aging Dis 2011;2:414–435. Search in Google Scholar

131. Shirakabe A, Ikeda Y, Sciarretta S, et al. Aging and Autophagy in the Heart. Circ Res 2016;118:1563–1576.10.1161/CIRCRESAHA.116.307474486999927174950 Search in Google Scholar

132. Kaushal A, Wani WY, Anand R, et al. Spontaneous and induced nontransgenic animal models of AD: modeling AD using combinatorial approach. Am J Alzheimers Dis Other Demen 2013;28:318–326.10.1177/153331751348891423687185 Search in Google Scholar

133. Partridge B, Rossmeisl JH. Companion animal models of neurological disease. J Neurosci Methods 2020;331:108484.10.1016/j.jneumeth.2019.108484694221131733285 Search in Google Scholar

134. Cekanova M, Rathore K. Animal models and therapeutic molecular targets of cancer: utility and limitations. Drug Des Devel Ther 2014;8:1911–1921.10.2147/DDDT.S49584420619925342884 Search in Google Scholar

135. Vail DM, MacEwen EG. Spontaneously occurring tumors of companion animals as models for human cancer. Cancer Invest 2000;18:781–792.10.3109/0735790000901221011107448 Search in Google Scholar

136. Jackson JG, Lozano G. The mutant p53 mouse as a pre-clinical model. Oncogene 2013;32:4325–4330.10.1038/onc.2012.61023318424 Search in Google Scholar

137. Lampreht Tratar U, Horvat S, Cemazar M. Transgenic Mouse Models in Cancer Research. Front Oncol;2018;8.10.3389/fonc.2018.00268606259330079312 Search in Google Scholar

138. Reza Khorramizadeh M, Saadat F. Chapter 8 - Animal models for human disease. In: Verma AS, Singh A (eds) Animal Biotechnology (Second Edition). Boston: Academic Press:2020;153–171.10.1016/B978-0-12-811710-1.00008-2 Search in Google Scholar

139. Ruggeri BA, Camp F, Miknyoczki S. Animal models of disease: pre-clinical animal models of cancer and their applications and utility in drug discovery. Biochem Pharmacol 2014;87:150–161.10.1016/j.bcp.2013.06.02023817077 Search in Google Scholar

140. Rapoport B, Banuelos B, Aliesky HA, et al. Critical Differences between Induced and Spontaneous Mouse Models of Graves’ Disease with Implications for Antigen-Specific Immunotherapy in Humans. J Immunol 2016; 197(12): 4560–4568.10.4049/jimmunol.1601393513784127913646 Search in Google Scholar

141. Animals Behind Top Drugs. Foundation for Biomedical Research Available from: https://fbresearch.org/medical-advances/animal-research-achievements/animal-research-top-drugs/. 2021. Accessed February 28, 2022. Search in Google Scholar

142. Mohs RC, Greig NH. Drug discovery and development: Role of basic biological research. Alzheimers Dement Transl Res Clin Interv 2017;3:651–657.10.1016/j.trci.2017.10.005572528429255791 Search in Google Scholar

143. Ireson CR, Alavijeh MS, Palmer AM, et al. The role of mouse tumour models in the discovery and development of anticancer drugs. Br J Cancer 2019;121:101–108.10.1038/s41416-019-0495-5673803731231121 Search in Google Scholar

144. Wege AK. Humanized Mouse Models for the Preclinical Assessment of Cancer Immunotherapy. BioDrugs Clin Immunother Biopharm Gene Ther 2018;32:245–266.10.1007/s40259-018-0275-429589229 Search in Google Scholar

145. Berry-Kravis EM, Lindemann L, Jønch AE, et al. Drug development for neurodevelopmental disorders: lessons learned from fragile X syndrome. Nat Rev Drug Discov 2018;17:280–299.10.1038/nrd.2017.221690422529217836 Search in Google Scholar

146. Chadman KK, Fernandes S, DiLiberto E, et al. Do animal models hold value in Autism spectrum disorder (ASD) drug discovery? Expert Opin Drug Discov 2019;14:727–734. Search in Google Scholar

147. Díaz-Caneja CM, State MW, Hagerman RJ, et al. A white paper on a neurodevelopmental framework for drug discovery in autism and other neurodevelopmental disorders. Eur Neuropsychopharmacol J Eur Coll Neuropsychopharmacol 2021;48:49–88.10.1016/j.euroneuro.2021.02.02033781629 Search in Google Scholar

148. Howe JR, Bear MF, Golshani P, et al. The mouse as a model for neuropsychiatric drug development. Curr Biol CB 2018;28:R909–R914.10.1016/j.cub.2018.07.046816302230205056 Search in Google Scholar

149. Tricklebank MD, Robbins TW, Simmons C, et al. Time to re-engage psychiatric drug discovery by strengthening confidence in preclinical psychopharmacology. Psychopharmacology (Berl) 2021;238:1417–1436.10.1007/s00213-021-05787-x794597033694032 Search in Google Scholar

150. Cacabelos R, Carrera I, Martínez-Iglesias O, et al. What is the gold standard model for Alzheimer’s disease drug discovery and development? Expert Opin Drug Discov 2021;16:1415–1440. Search in Google Scholar

151. Koprich JB, Kalia LV, Brotchie JM. Animal models of α-synucleinopathy for Parkinson disease drug development. Nat Rev Neurosci 2017;18:515–529.10.1038/nrn.2017.7528747776 Search in Google Scholar

152. Vitek MP, Araujo JA, Fossel M, et al. Translational animal models for Alzheimer’s disease: An Alzheimer’s Association Business Consortium Think Tank. Alzheimers Dement N Y N 2020;6:e12114.10.1002/trc2.12114779831033457489 Search in Google Scholar

153. Sun W, Zheng W, Simeonov A. Drug discovery and development for rare genetic disorders. Am J Med Genet A 2017;173:2307–2322.10.1002/ajmg.a.38326566212928731526 Search in Google Scholar

154. Singh VK, Seed TM. How necessary are animal models for modern drug discovery? Expert Opin Drug Discov 2021;16:1391–1397. Search in Google Scholar

155. Jellinger KA. Towards a Biological Definition of Alzheimer Disease. Int J Neurol Neurother 2020; 7(1): 095. Search in Google Scholar

156. Jellinger KA. Recent update on the heterogeneity of the Alzheimer’s disease spectrum. J Neural Transm 2022;129:1–24.10.1007/s00702-021-02449-234919190 Search in Google Scholar

157. Fereshtehnejad S-M, Postuma RB. Subtypes of Parkinson’s Disease: What Do They Tell Us About Disease Progression? Curr Neurol Neurosci Rep 2017;17:34. Search in Google Scholar

158. Qian E, Huang Y. Subtyping of Parkinson’s Disease - Where Are We Up To? Aging Dis 2019;10:1130. Search in Google Scholar

159. Agelink van Rentergem JA, Deserno MK, Geurts HM. Validation strategies for subtypes in psychiatry: A systematic review of research on autism spectrum disorder. Clin Psychol Rev 2021;87:102033.10.1016/j.cpr.2021.10203333962352 Search in Google Scholar

160. Easson AK, Fatima Z, McIntosh AR. Functional connectivity-based subtypes of individuals with and without autism spectrum disorder. Netw Neurosci 2019;3:344–362.10.1162/netn_a_00067637047430793086 Search in Google Scholar

161. Drummond E, Wisniewski T. Alzheimer’s disease: experimental models and reality. Acta Neuropathol (Berl) 2017;133:155–175.10.1007/s00401-016-1662-x525310928025715 Search in Google Scholar

162. Gurdon B, Kaczorowski C. Pursuit of precision medicine: Systems biology approaches in Alzheimer’s disease mouse models. Neurobiol Dis 2021;161:105558.10.1016/j.nbd.2021.10555834767943 Search in Google Scholar

163. Devi G, Scheltens P. Heterogeneity of Alzheimer’s disease: consequence for drug trials? Alzheimers Res Ther 2018;10:122. Search in Google Scholar

164. Marras C, Chaudhuri KR, Titova N, et al. Therapy of Parkinson’s Disease Subtypes. Neurotherapeutics 2020;17:1366–1377.10.1007/s13311-020-00894-7785125332749651 Search in Google Scholar

165. Ringman JM, Goate A, Masters CL, et al. Genetic heterogeneity in Alzheimer disease and implications for treatment strategies. Curr Neurol Neurosci Rep 2014;14:499.10.1007/s11910-014-0499-8416298725217249 Search in Google Scholar

166. Forloni G. Alzheimer’s disease: from basic science to precision medicine approach. BMJ Neurol Open 2020;2:e000079.10.1136/bmjno-2020-000079790316833681801 Search in Google Scholar

167. Galvin JE. Advancing personalized treatment of Alzheimer’s disease: a call for the N-of-1 trial design. Future Neurol 2018;13:151–160.10.2217/fnl-2018-0004 Search in Google Scholar

168. Ryden LE, Lewis SJG. Parkinson’s Disease in the Era of Personalised Medicine: One Size Does Not Fit All. Drugs Aging 2019;36:103–113.10.1007/s40266-018-0624-530556112 Search in Google Scholar

169. Bhardwaj S, Kesari KK, Rachamalla M, et al. CRISPR/Cas9 gene editing: New hope for Alzheimer’s disease therapeutics. J Adv Res. 2021.10.1016/j.jare.2021.07.001 Search in Google Scholar

170. Cring MR, Sheffield VC. Gene therapy and gene correction: targets, progress, and challenges for treating human diseases. Gene Ther 2022;29:3–12.10.1038/s41434-020-00197-833037407 Search in Google Scholar

171. Dunbar CE, High KA, Joung JK, et al. Gene therapy comes of age. Science 2018;359:eaan4672.10.1126/science.aan467229326244 Search in Google Scholar

172. Carrillo MA, Zhen A, Kitchen SG. The Use of the Humanized Mouse Model in Gene Therapy and Immunotherapy for HIV and Cancer. Front Immunol 2018;9:746.10.3389/fimmu.2018.00746593240029755454 Search in Google Scholar

173. Gopinath C, Nathar TJ, Ghosh A, et al. Contemporary Animal Models For Human Gene Therapy Applications. Curr Gene Ther 2015;15:531–540.10.2174/1566523215666150929110424770957126415576 Search in Google Scholar

174. Ingusci S, Verlengia G, Soukupova M, et al. Gene Therapy Tools for Brain Diseases. Front Pharmacol 2019;10:724.10.3389/fphar.2019.00724661349631312139 Search in Google Scholar

175. Park H, Oh J, Shim G, et al. In vivo neuronal gene editing via CRISPR–Cas9 amphiphilic nanocomplexes alleviates deficits in mouse models of Alzheimer’s disease. Nat Neurosci 2019;22:524–528.10.1038/s41593-019-0352-030858603 Search in Google Scholar

176. Stepanichev M. Gene Editing and Alzheimer’s Disease: Is There Light at the End of the Tunnel? Front Genome Ed 2020;2:4. Search in Google Scholar

177. Yoo TJ. Anti-Inflammatory Gene Therapy Improves Spatial Memory Performance in a Mouse Model of Alzheimer’s Disease. J Alzheimers Dis 2022; 85(3): 1001–1008.10.3233/JAD-215270892511834897091 Search in Google Scholar

178. Van Laar AD, Van Laar VS, San Sebastian W, et al. An Update on Gene Therapy Approaches for Parkinson’s Disease: Restoration of Dopaminergic Function. J Park Dis 2021;11:S173–S182.10.3233/JPD-212724854324334366374 Search in Google Scholar

179. Wu Z, Parry M, Hou X-Y, et al. Gene therapy conversion of striatal astrocytes into GABAergic neurons in mouse models of Huntington’s disease. Nat Commun 2020;11:1105.10.1038/s41467-020-14855-3704661332107381 Search in Google Scholar

180. Yang S, Chang R, Yang H, et al. CRISPR/Cas9-mediated gene editing ameliorates neurotoxicity in mouse model of Huntington’s disease. J Clin Invest 2017;127:2719–2724.10.1172/JCI92087549074128628038 Search in Google Scholar

181. Davidsohn N, Pezone M, Vernet A, et al. A single combination gene therapy treats multiple age-related diseases. Proc Natl Acad Sci U S A 2019;116:23505–23511.10.1073/pnas.1910073116687621831685628 Search in Google Scholar

182. Blusztajn JK, Slack BE, Mellott TJ. Neuroprotective Actions of Dietary Choline. Nutrients 2017;9:E815.10.3390/nu9080815557960928788094 Search in Google Scholar

183. Zilkha N, Kuperman Y, Kimchi T. High-fat diet exacerbates cognitive rigidity and social deficiency in the BTBR mouse model of autism. Neuroscience 2017;345:142–154.10.1016/j.neuroscience.2016.01.07026855190 Search in Google Scholar

184. Lilamand M, Porte B, Cognat E, et al. Are ketogenic diets promising for Alzheimer’s disease? A translational review. Alzheimers Res Ther 2020;12:42.10.1186/s13195-020-00615-4715813532290868 Search in Google Scholar

185. Lin K-H, Chiu C-H, Kuo W-W, et al. The preventive effects of edible folic acid on cardiomyocyte apoptosis and survival in early onset triple-transgenic Alzheimer’s disease model mice. Environ Toxicol 2018;33:83–92.10.1002/tox.2249829068127 Search in Google Scholar

186. Gao X, Sanderson SM, Dai Z, et al. Dietary methionine influences therapy in mouse cancer models and alters human metabolism. Nature 2019;572:397–401.10.1038/s41586-019-1437-3695102331367041 Search in Google Scholar

187. Abid MA, Abid MB. Commentary: Dietary methionine influences therapy in mouse cancer models and alters human metabolism. Front Oncol 2020; 10. 2020. Accessed April 3, 2022. Search in Google Scholar

188. Wanders D, Hobson K, Ji X. Methionine Restriction and Cancer Biology. Nutrients 2020;12:684.10.3390/nu12030684714658932138282 Search in Google Scholar

189. Xu Y, Jiang C, Wu J, et al. Ketogenic diet ameliorates cognitive impairment and neuroinflammation in a mouse model of Alzheimer’s disease. CNS Neurosci Ther 2022;28:580–592.10.1111/cns.13779892892034889516 Search in Google Scholar

190. Brady M, Beltramini A, Vaughan G, et al. Benefits of a ketogenic diet on repetitive motor behavior in mice. Behav Brain Res 2022;422:113748.10.1016/j.bbr.2022.11374835038463 Search in Google Scholar

191. Norwitz NG, Dalai SS, Palmer CM. Ketogenic diet as a metabolic treatment for mental illness. Curr Opin Endocrinol Diabetes Obes 2020;27:269–274.10.1097/MED.000000000000056432773571 Search in Google Scholar

192. Wu J, de Theije CGM, da Silva SL, et al. Dietary interventions that reduce mTOR activity rescue autistic-like behavioral deficits in mice. Brain Behav Immun 2017;59:273–287.10.1016/j.bbi.2016.09.01627640900 Search in Google Scholar

193. Chin EWM, Lim WM, Ma D, et al. Choline Rescues Behavioural Deficits in a Mouse Model of Rett Syndrome by Modulating Neuronal Plasticity. Mol Neurobiol 2019;56:3882–3896.10.1007/s12035-018-1345-9650551530220058 Search in Google Scholar

194. Vuillermot S, Luan W, Meyer U, et al. Vitamin D treatment during pregnancy prevents autism-related phenotypes in a mouse model of maternal immune activation. Mol Autism 2017;8:9.10.1186/s13229-017-0125-0535121228316773 Search in Google Scholar

195. Ribeiro MC, MacDonald JL. Vitamin D modulates cortical transcriptome and behavioral phenotypes in an Mecp2 heterozygous Rett syndrome mouse model. Neurobiol Dis 2022;165:105636.10.1016/j.nbd.2022.105636 Search in Google Scholar

196. Lu W-T, Sun S-Q, Li Y, et al. Curcumin Ameliorates Memory Deficits by Enhancing Lactate Content and MCT2 Expression in APP/PS1 Transgenic Mouse Model of Alzheimer’s Disease. Anat Rec 2019;302:332–338.10.1002/ar.23969 Search in Google Scholar

197. Reddy PH, Manczak M, Yin X, et al. Protective Effects of Indian Spice Curcumin Against Amyloid-β in Alzheimer’s Disease. J Alzheimers Dis 2018;61:843–866.10.3233/JAD-170512 Search in Google Scholar

198. De Filippis F, Vitaglione P, Cuomo R, et al. Dietary Interventions to Modulate the Gut Microbiome—How Far Away Are We From Precision Medicine. Inflamm Bowel Dis 2018;24:2142–2154.10.1093/ibd/izy080 Search in Google Scholar

199. Newell C, Bomhof MR, Reimer RA, et al. Ketogenic diet modifies the gut microbiota in a murine model of autism spectrum disorder. Mol Autism 2016;7:37.10.1186/s13229-016-0099-3 Search in Google Scholar

200. Cryan JF, O’Riordan KJ, Sandhu K, et al. The gut microbiome in neurological disorders. Lancet Neurol 2020;19:179–194.10.1016/S1474-4422(19)30356-4 Search in Google Scholar

201. Kraeuter A-K, Phillips R, Sarnyai Z. Ketogenic therapy in neurodegenerative and psychiatric disorders: From mice to men. Prog Neuropsychopharmacol Biol Psychiatry 2020;101:109913.10.1016/j.pnpbp.2020.10991332151695 Search in Google Scholar

202. Zhang C, Franklin CL, Ericsson AC. Consideration of Gut Microbiome in Murine Models of Diseases. Microorganisms 2021;9:1062.10.3390/microorganisms9051062815671434068994 Search in Google Scholar

203. Rogers J, Renoir T, Hannan AJ. Gene-environment interactions informing therapeutic approaches to cognitive and affective disorders. Neuropharmacology 2019;145:37–48.10.1016/j.neuropharm.2017.12.03829277490 Search in Google Scholar

204. Eisinger BE, Zhao X. Identifying molecular mediators of environmentally enhanced neurogenesis. Cell Tissue Res 2018;371:7–21.10.1007/s00441-017-2718-5582658729127518 Search in Google Scholar

205. Garthe A, Roeder I, Kempermann G. Mice in an enriched environment learn more flexibly because of adult hippocampal neurogenesis. Hippocampus 2016;26:261–271.10.1002/hipo.22520504965426311488 Search in Google Scholar

206. Grońska-Pęski M, Gonçalves JT, Hébert JM. Enriched Environment Promotes Adult Hippocampal Neurogenesis through FGFRs. J Neurosci Off J Soc Neurosci 2021;41:2899–2910.10.1523/JNEUROSCI.2286-20.2021801888233637561 Search in Google Scholar

207. De Sousa RAL, Rodrigues CM, Mendes BF, et al. Physical exercise protocols in animal models of Alzheimer’s disease: a systematic review. Metab Brain Dis 2021;36:85–95.10.1007/s11011-020-00633-z33095371 Search in Google Scholar

208. da Silva WAB, Ferreira Oliveira K, Caroline Vitorino L, et al. Physical exercise increases the production of tyrosine hydroxylase and CDNF in the spinal cord of a Parkinson’s disease mouse model. Neurosci Lett 2021;760:136089.10.1016/j.neulet.2021.13608934182056 Search in Google Scholar

209. Houdebine L, Gallelli CA, Rastelli M, et al. Effect of physical exercise on brain and lipid metabolism in mouse models of multiple sclerosis. Chem Phys Lipids 2017;207:127–134.10.1016/j.chemphyslip.2017.06.00228606714 Search in Google Scholar

210. Forbes TA, Goldstein EZ, Dupree JL, et al. Environmental enrichment ameliorates perinatal brain injury and promotes functional white matter recovery. Nat Commun 2020;11:964.10.1038/s41467-020-14762-7703123732075970 Search in Google Scholar

211. Livingston-Thomas J, Nelson P, Karthikeyan S, et al. Exercise and Environmental Enrichment as Enablers of Task-Specific Neuroplasticity and Stroke Recovery. Neurother J Am Soc Exp Neurother 2016;13:395–402.10.1007/s13311-016-0423-9482401626868018 Search in Google Scholar

212. Huang Y, Jiang H, Zheng Q, et al. Environmental enrichment or selective activation of parvalbumin-expressing interneurons ameliorates synaptic and behavioral deficits in animal models with schizophrenia-like behaviors during adolescence. Mol Psychiatry 2021;26:2533–2552.10.1038/s41380-020-01005-w33473150 Search in Google Scholar

213. Robison LS, Francis N, Popescu DL, et al. Environmental Enrichment: Disentangling the Influence of Novelty, Social, and Physical Activity on Cerebral Amyloid Angiopathy in a Transgenic Mouse Model. Int J Mol Sci 2020;21:E843.10.3390/ijms21030843703818832012921 Search in Google Scholar

214. Gerdts V, Littel-van den Hurk S van D, Griebel PJ, et al. Use of animal models in the development of human vaccines. Future Microbiol 2007;2:667–675.10.2217/17460913.2.6.66718041907 Search in Google Scholar

215. Kiros TG, Levast B, Auray G, et al. The Importance of Animal Models in the Development of Vaccines. Innov Vaccinol 2012;251–264.10.1007/978-94-007-4543-8_11 Search in Google Scholar

216. Atlante S, Mongelli A, Barbi V, et al. The epigenetic implication in coronavirus infection and therapy. Clin Epigenetics 2020;12:156.10.1186/s13148-020-00946-x757697533087172 Search in Google Scholar

217. Nehme Z, Pasquereau S, Herbein G. Control of viral infections by epigenetic-targeted therapy. Clin Epigenetics 2019;11:55.10.1186/s13148-019-0654-9643795330917875 Search in Google Scholar

218. Hwang J-R, Park S-G. Mouse models for hepatitis B virus research. Lab Anim Res 2018;34:85–91.10.5625/lar.2018.34.3.85617022330310404 Search in Google Scholar

219. Krishnakumar V, Durairajan SSK, Alagarasu K, et al. Recent Updates on Mouse Models for Human Immunodeficiency, Influenza, and Dengue Viral Infections. Viruses 2019;11:252.10.3390/v11030252646616430871179 Search in Google Scholar

220. Sarkar S, Heise MT. Mouse Models as Resources for Studying Infectious Diseases. Clin Ther 2019;41:1912–1922.10.1016/j.clinthera.2019.08.010711255231540729 Search in Google Scholar

221. Ji W, Gong B, Jin H, et al. Recent Progress Towards Vaccines and Antibody-based Therapies Against Alzheimer’s Disease. Mini-Rev Med Chem 2021; 21(19): 3062–3072.10.2174/138955752166621080511092034353254 Search in Google Scholar

222. Carrera I, Etcheverría I, Fernández-Novoa L, et al. Vaccine Development to Treat Alzheimer’s Disease Neuropathology in APP/PS1 Transgenic Mice. Int J Alzheimers Dis 2012; 2012e376138.10.1155/2012/376138345767023024882 Search in Google Scholar

223. Cossu D, Ruberto S, Yokoyama K, et al. Efficacy of BCG vaccine in animal models of neurological disorders. Vaccine 2022;40:432–436.10.1016/j.vaccine.2021.12.00534906393 Search in Google Scholar

224. Herline K, Drummond E, Wisniewski T. Recent advancements toward therapeutic vaccines against Alzheimer’s disease. Expert Rev Vaccines 2018;17:707–721.10.1080/14760584.2018.150090530005578 Search in Google Scholar

225. Banik A, Brown RE, Bamburg J, et al. Translation of Pre-Clinical Studies into Successful Clinical Trials for Alzheimer’s Disease: What are the Roadblocks and How Can They Be Overcome? J Alzheimers Dis 2015; 47(4): 815–843. Search in Google Scholar

226. Homberg JR, Kyzar EJ, Stewart AM, et al. Improving treatment of neurodevelopmental disorders: recommendations based on preclinical studies. Expert Opin Drug Discov 2016;11:11–25.10.1517/17460441.2016.111583426558752 Search in Google Scholar

227. Bockamp E, Maringer M, Spangenberg C, et al. Of mice and models: improved animal models for biomedical research. Physiol Genomics 2002;11:115–132.10.1152/physiolgenomics.00067.200212464688 Search in Google Scholar

228. Cibelli J, Emborg ME, Prockop DJ, et al. Strategies for improving animal models for regenerative medicine. Cell Stem Cell 2013;12:271–274.10.1016/j.stem.2013.01.004438328023472868 Search in Google Scholar

229. Stewart AM, Kalueff AV. Developing better and more valid animal models of brain disorders. Behav Brain Res 2015;276:28–31.10.1016/j.bbr.2013.12.02424384129 Search in Google Scholar

230. Lama J, Buhidma Y, Fletcher EJR, et al. Animal models of Parkinson’s disease: a guide to selecting the optimal model for your research. Neuronal Signal 2021;5:NS20210026.10.1042/NS20210026866150734956652 Search in Google Scholar

231. Reardon S. Frustrated Alzheimer’s researchers seek better lab mice. Nature 2018;563:611–612.10.1038/d41586-018-07484-w30482928 Search in Google Scholar

232. Li C, Briner A, Götz J. The search for improved animal models of Alzheimer’s disease and novel strategies for therapeutic intervention. Future Med Chem 2019;11:1853–1857.10.4155/fmc-2019-015031517531 Search in Google Scholar

233. Veening-Griffioen DH, Ferreira GS, van Meer PJK, et al. Are some animal models more equal than others? A case study on the translational value of animal models of efficacy for Alzheimer’s disease. Eur J Pharmacol 2019;859:172524.10.1016/j.ejphar.2019.17252431291566 Search in Google Scholar

234. Tai LM, Maldonado Weng J, LaDu MJ, et al. Chapter One - Relevance of transgenic mouse models for Alzheimer’s disease. In: Teplow DB (ed) Progress in Molecular Biology and Translational Science. 2021;177: 1–48. Search in Google Scholar

235. Nadeau JH, Auwerx J. The virtuous cycle of human genetics and mouse models in drug discovery. Nat Rev Drug Discov 2019;18:255–272.10.1038/s41573-018-0009-930679805 Search in Google Scholar

236. Mckean NE, Handley RR, Snell RG. A Review of the Current Mammalian Models of Alzheimer’s Disease and Challenges That Need to Be Overcome. Int J Mol Sci 2021;22:13168.10.3390/ijms222313168865812334884970 Search in Google Scholar

237. Rahi V, Kumar P. Animal models of attention-deficit hyperactivity disorder (ADHD). Int J Dev Neurosci Off J Int Soc Dev Neurosci 2021;81:107–124.10.1002/jdn.1008933428802 Search in Google Scholar

238. Espíndola SL, Damianich A, Alvarez RJ, et al. Modulation of Tau Isoforms Imbalance Precludes Tau Pathology and Cognitive Decline in a Mouse Model of Tauopathy. Cell Rep 2018;23:709–715.10.1016/j.celrep.2018.03.07929669277 Search in Google Scholar

239. Fung CW, Guo J, Fu H, et al. Atrophy associated with tau pathology precedes overt cell death in a mouse model of progressive tauopathy. Sci Adv 2020;6:eabc8098.10.1126/sciadv.abc8098756758433067235 Search in Google Scholar

240. Jankowsky JL, Zheng H. Practical considerations for choosing a mouse model of Alzheimer’s disease. Mol Neurodegener 2017;12:89.10.1186/s13024-017-0231-7574195629273078 Search in Google Scholar

241. Kaye J, Reisine T, Finkbeiner S. Huntington’s disease mouse models: unraveling the pathology caused by CAG repeat expansion. Fac Rev 2021; 10(77).10.12703/r/10-77854659834746930 Search in Google Scholar

242. Gunn RK, Huentelman MJ, Brown RE. Are Sema5a mutant mice a good model of autism? A behavioral analysis of sensory systems, emotionality and cognition. Behav Brain Res 2011;225:142–150.10.1016/j.bbr.2011.07.008317044121777623 Search in Google Scholar

243. Verma V, Paul A, Amrapali Vishwanath A, et al. Understanding intellectual disability and autism spectrum disorders from common mouse models: synapses to behaviour. Open Biol 2019;9:180265.10.1098/rsob.180265659775731185809 Search in Google Scholar

244. Cortés N, Andrade V, Maccioni RB. Behavioral and Neuropsychiatric Disorders in Alzheimer’s Disease. J Alzheimers Dis JAD 2018;63:899–910.10.3233/JAD-18000529710717 Search in Google Scholar

245. Locci A, Orellana H, Rodriguez G, et al. Comparison of memory, affective behavior, and neuropathology in APPNLGF knock-in mice to 5xFAD and APP/PS1 mice. Behav Brain Res 2021;404:113192.10.1016/j.bbr.2021.113192798013133607163 Search in Google Scholar

246. Seo N-Y, Kim GH, Noh JE, et al. Selective Regional Loss of Cortical Synapses Lacking Presynaptic Mitochondria in the 5xFAD Mouse Model. Front Neuroanat 2021;15:690168.10.3389/fnana.2021.690168826706134248509 Search in Google Scholar

247. Whitesell JD, Buckley AR, Knox JE, et al. Whole brain imaging reveals distinct spatial patterns of amyloid beta deposition in three mouse models of Alzheimer’s disease. J Comp Neurol 2019;527:2122–2145.10.1002/cne.24555 Search in Google Scholar

248. Brown RE, Bolivar S. The importance of behavioural bioassays in neuroscience. J Neurosci Methods 2018;300:68–76.10.1016/j.jneumeth.2017.05.022 Search in Google Scholar

249. Puzzo D, Lee L, Palmeri A, et al. Behavioral assays with mouse models of Alzheimer’s disease: practical considerations and guidelines. Biochem Pharmacol 2014;88:450–467.10.1016/j.bcp.2014.01.011 Search in Google Scholar

250. Ameen-Ali KE, Wharton SB, Simpson JE, et al. Review: Neuropathology and behavioural features of transgenic murine models of Alzheimer’s disease. Neuropathol Appl Neurobiol 2017;43:553–570.10.1111/nan.12440 Search in Google Scholar

251. Belyaev ND, Kellett KAB, Beckett C, et al. The transcriptionally active amyloid precursor protein (APP) intracellular domain is preferentially produced from the 695 isosform of APP in a {beta}-secretase-dependent pathway. J Biol Chem 2010;285:41443–41454.10.1074/jbc.M110.141390 Search in Google Scholar

252. Andrä K, Abramowski D, Duke M, et al. Expression of APP in transgenic mice: a comparison of neuron-specific promoters. Neurobiol Aging 1996;17:183–190.10.1016/0197-4580(95)02066-7 Search in Google Scholar

253. Fontaine DA, Davis DB. Attention to Background Strain Is Essential for Metabolic Research: C57BL/6 and the International Knockout Mouse Consortium. Diabetes 2016;65:25–33.10.2337/db15-0982468694926696638 Search in Google Scholar

254. Bryant CD, Zhang NN, Sokoloff G, et al. Behavioral differences among C57BL/6 substrains: implications for transgenic and knockout studies. J Neurogenet 2008;22:315–331.10.1080/01677060802357388369782719085272 Search in Google Scholar

255. Doetschman T. Influence of genetic background on genetically engineered mouse phenotypes. Methods Mol Biol Clifton NJ 2009;530:423–433.10.1007/978-1-59745-471-1_23280584819266333 Search in Google Scholar

256. Reilly KM. The Effects of Genetic Background of Mouse Models of Cancer: Friend or Foe? Cold Spring Harb Protoc 2016;2016:pdb.top076273.10.1101/pdb.top076273670315626933251 Search in Google Scholar

257. Wong AA, Brown RE. Visual detection, pattern discrimination and visual acuity in 14 strains of mice. Genes Brain Behav 2006;5:389–403.10.1111/j.1601-183X.2005.00173.x16879633 Search in Google Scholar

258. Rae EA, Brown RE. The problem of genotype and sex differences in life expectancy in transgenic AD mice. Neurosci Biobehav Rev 2015;57:238–251.10.1016/j.neubiorev.2015.09.00226348702 Search in Google Scholar

259. O’Leary TP, Mantolino HM, Stover KR, et al. Age-related deterioration of motor function in male and female 5xFAD mice from 3 to 16 months of age. Genes Brain Behav 2020;19:e12538.10.1111/gbb.1253830426678 Search in Google Scholar

260. O’Leary TP, Brown RE. Visuo-spatial learning and memory impairments in the 5xFAD mouse model of Alzheimer’s disease: Effects of age, sex, albinism, and motor impairments. Genes Brain Behav 2022;e12794.10.1111/gbb.1279435238473 Search in Google Scholar

261. Stevens LM, Brown RE. Reference and working memory deficits in the 3xTg-AD mouse between 2 and 15-months of age: a cross-sectional study. Behav Brain Res 2015;278:496–505.10.1016/j.bbr.2014.10.03325446812 Search in Google Scholar

262. Lau JC, Lerch JP, Sled JG, et al. Longitudinal neuroanatomical changes determined by deformation-based morphometry in a mouse model of Alzheimer’s disease. NeuroImage 2008;42:19–27.10.1016/j.neuroimage.2008.04.25218547819 Search in Google Scholar

263. Foidl BM, Humpel C. Can mouse models mimic sporadic Alzheimer’s disease? Neural Regen Res 2020;15:401–406. Search in Google Scholar

264. Maciejewska K, Czarnecka K, Szymański P. A review of the mechanisms underlying selected comorbidities in Alzheimer’s disease. Pharmacol Rep PR 2021;73:1565–1581.10.1007/s43440-021-00293-5859932034121170 Search in Google Scholar

265. Martini AC, Forner S, Trujillo-Estrada L, et al. Past to Future: What Animal Models Have Taught Us About Alzheimer’s Disease. J Alzheimers Dis 2018; 64(s1): S365–S378.10.3233/JAD-17991729504540 Search in Google Scholar

266. Wong AA, Brown RE. Prevention of vision loss protects against age-related impairment in learning and memory performance in DBA/2J mice. Front Aging Neurosci 2013;5:52. Search in Google Scholar

267. Fakhoury M. Microglia and Astrocytes in Alzheimer’s Disease: Implications for Therapy. Curr Neuropharmacol 2018;16:508–518.10.2174/1570159X15666170720095240599786228730967 Search in Google Scholar

268. Li H, Wei C, Zhou R, et al. Mouse models in modeling aging and cancer. Exp Gerontol 2019;120:88–94.10.1016/j.exger.2019.03.00230876950 Search in Google Scholar

269. Bilkei-Gorzo A. Genetic mouse models of brain ageing and Alzheimer’s disease. Pharmacol Ther 2014;142:244–257.10.1016/j.pharmthera.2013.12.00924362083 Search in Google Scholar

270. Boche D, Gordon MN. Diversity of transcriptomic microglial phenotypes in aging and Alzheimer’s disease. Alzheimers Dement 2022;18:360–376.10.1002/alz.1238934223696 Search in Google Scholar

271. O’Leary TimothyP, Shin S, Fertan E, et al. Reduced acoustic startle response and peripheral hearing loss in the 5xFAD mouse model of Alzheimer’s disease. Genes Brain Behav 2017;16:554–563.10.1111/gbb.1237028133939 Search in Google Scholar

272. Blaney CE, Gunn RK, Stover KR, et al. Maternal genotype influences behavioral development of 3×Tg-AD mouse pups. Behav Brain Res 2013;252:40–48.10.1016/j.bbr.2013.05.03323711927 Search in Google Scholar

273. Weaver ICG, Cervoni N, Champagne FA, et al. Epigenetic programming by maternal behavior. Nat Neurosci 2004;7:847–854.10.1038/nn127615220929 Search in Google Scholar

274. Agarwal D, Kumari R, Ilyas A, et al. Crosstalk between epigenetics and mTOR as a gateway to new insights in pathophysiology and treatment of Alzheimer’s disease. Int J Biol Macromol 2021;192:895–903.10.1016/j.ijbiomac.2021.10.02634662652 Search in Google Scholar

275. Griñán-Ferré C, Izquierdo V, Otero E, et al. Environmental Enrichment Improves Cognitive Deficits, AD Hallmarks and Epigenetic Alterations Presented in 5xFAD Mouse Model. Front Cell Neurosci 2018;12:224.10.3389/fncel.2018.00224610416430158856 Search in Google Scholar

276. Zhang X, Hong R, Chen W, et al. The role of long noncoding RNA in major human disease. Bioorganic Chem 2019;92:103214.10.1016/j.bioorg.2019.10321431499258 Search in Google Scholar

277. Jakovcevski M, Akbarian S. Epigenetic mechanisms in neurological disease. Nat Med 2012;18:1194–1204.10.1038/nm.2828359687622869198 Search in Google Scholar

278. Cholewa-Waclaw J, Bird A, Schimmelmann M von, et al. The Role of Epigenetic Mechanisms in the Regulation of Gene Expression in the Nervous System. J Neurosci 2016;36:11427–11434.10.1523/JNEUROSCI.2492-16.2016512521027911745 Search in Google Scholar

279. Banik A, Kandilya D, Ramya S, et al. Maternal Factors that Induce Epigenetic Changes Contribute to Neurological Disorders in Offspring. Genes 2017;8:E150.10.3390/genes8060150548551428538662 Search in Google Scholar

280. Bale TL. Epigenetic and transgenerational reprogramming of brain development. Nat Rev Neurosci 2015;16:332–344.10.1038/nrn3818706415525921815 Search in Google Scholar

281. Darwiche N. Epigenetic mechanisms and the hallmarks of cancer: an intimate affair. Am J Cancer Res 2020;10:1954–1978. Search in Google Scholar

282. Herceg Z, Vaissière T. Epigenetic mechanisms and cancer: an interface between the environment and the genome. Epigenetics 2011;6:804–819.10.4161/epi.6.7.1626221758002 Search in Google Scholar

283. Zhang Q, Cao X. Epigenetic regulation of the innate immune response to infection. Nat Rev Immunol 2019;19:417–432.10.1038/s41577-019-0151-630918351 Search in Google Scholar

284. Lim TB, Foo SYR, Chen CK. The Role of Epigenetics in Congenital Heart Disease. Genes 2021;12:390.10.3390/genes12030390799856133803261 Search in Google Scholar

285. Saul D, Kosinsky RL. Epigenetics of Aging and Aging-Associated Diseases. Int J Mol Sci 2021;22:401.10.3390/ijms22010401779492633401659 Search in Google Scholar

286. Bertogliat MJ, Morris-Blanco KC, Vemuganti R. Epigenetic mechanisms of neurodegenerative diseases and acute brain injury. Neurochem Int 2020;133:104642.10.1016/j.neuint.2019.104642807440131838024 Search in Google Scholar

287. Deegan DF, Nigam P, Engel N. Sexual Dimorphism of the Heart: Genetics, Epigenetics, and Development. Front Cardiovasc Med 2021;8:668252.10.3389/fcvm.2021.668252818917634124200 Search in Google Scholar

288. McCarthy MM, Nugent BM. Epigenetic Contributions to Hormonally-Mediated Sexual Differentiation of the Brain. J Neuroendocrinol 2013;25:1133–1140.10.1111/jne.12072533067323919286 Search in Google Scholar

289. Yu YE, Xing Z, Do C, et al. Chapter 1 - Genetic and epigenetic pathways in Down syndrome: Insights to the brain and immune system from humans and mouse models. In: Dierssen M (ed) Progress in Brain Research. 2020;251:1–28. Search in Google Scholar

290. Berdasco M, Esteller M. Genetic syndromes caused by mutations in epigenetic genes. Hum Genet 2013;132:359–383.10.1007/s00439-013-1271-x23370504 Search in Google Scholar

291. Jaenisch R, Bird A. Epigenetic regulation of gene expression: how the genome integrates intrinsic and environmental signals. Nat Genet 2003;33 Suppl:245–254.10.1038/ng108912610534 Search in Google Scholar

292. Zapata-Martín Del Campo CM, Martínez-Rosas M, Guarner-Lans V. Epigenetic Programming of Synthesis, Release, and/or Receptor Expression of Common Mediators Participating in the Risk/Resilience for Comorbid Stress-Related Disorders and Coronary Artery Disease. Int J Mol Sci 2018;19:E1224.10.3390/ijms19041224597950029670001 Search in Google Scholar

293. Zhang T-Y, Meaney MJ. Epigenetics and the Environmental Regulation of the Genome and Its Function. Annu Rev Psychol 2010;61:439–466.10.1146/annurev.psych.60.110707.16362519958180 Search in Google Scholar

294. Linnér A, Almgren M. Epigenetic programming-The important first 1000 days. Acta Paediatr Oslo Nor 1992 2020;109:443–452.10.1111/apa.1505031603247 Search in Google Scholar

295. Blewitt M, Whitelaw E. The Use of Mouse Models to Study Epigenetics. Cold Spring Harb Perspect Biol 2013;5:a017939.10.1101/cshperspect.a017939380957924186070 Search in Google Scholar

296. Seki Y, Williams L, Vuguin PM, et al. Minireview: Epigenetic programming of diabetes and obesity: animal models. Endocrinology 2012;153:1031–1038.10.1210/en.2011-1805328153422253432 Search in Google Scholar

297. Bianco-Miotto T, Craig JM, Gasser YP, et al. Epigenetics and DOHaD: from basics to birth and beyond. J Dev Orig Health Dis 2017;8:513–519.10.1017/S204017441700073328889823 Search in Google Scholar

298. Kubota T, Miyake K, Hariya N, et al. Understanding the epigenetics of neurodevelopmental disorders and DOHaD. J Dev Orig Health Dis 2015;6:96–104.10.1017/S204017441500005725708304 Search in Google Scholar

299. Simeoni U, Armengaud J-B, Siddeek B, et al. Perinatal Origins of Adult Disease. Neonatology 2018;113:393–399.10.1159/00048761829852488 Search in Google Scholar

300. Bernstein BE, Meissner A, Lander ES. The mammalian epigenome. Cell 2007;128:669–681.10.1016/j.cell.2007.01.03317320505 Search in Google Scholar

301. Borrelli E, Nestler EJ, Allis CD, et al. Decoding the epigenetic language of neuronal plasticity. Neuron 2008;60:961–974.10.1016/j.neuron.2008.10.012273747319109904 Search in Google Scholar

302. Bonifer C, Cockerill PN. Chromatin priming of genes in development: Concepts, mechanisms and consequences. Exp Hematol 2017;49:1–8.10.1016/j.exphem.2017.01.00328185904 Search in Google Scholar

303. Ernst C, Jefri M. Epigenetic priming in neurodevelopmental disorders. Trends Mol Med 2021;27:1106–1114.10.1016/j.molmed.2021.09.00534690045 Search in Google Scholar

304. Mastrototaro G, Zaghi M, Sessa A. Epigenetic Mistakes in Neurodevelopmental Disorders. J Mol Neurosci MN 2017;61:590–602.10.1007/s12031-017-0900-628255957 Search in Google Scholar

305. Gore AC, Krishnan K, Reilly MP. Endocrine-disrupting chemicals: Effects on neuroendocrine systems and the neurobiology of social behavior. Horm Behav 2019;111:7–22.10.1016/j.yhbeh.2018.11.006652747230476496 Search in Google Scholar

306. León-Olea M, Martyniuk CJ, Orlando EF, et al. Current concepts in neuroendocrine disruption. Gen Comp Endocrinol 2014;203:158–173.10.1016/j.ygcen.2014.02.005413333724530523 Search in Google Scholar

307. Patisaul HB, Fenton SE, Aylor D. Animal models of endocrine disruption. Best Pract Res Clin Endocrinol Metab 2018;32:283–297.10.1016/j.beem.2018.03.011602971029779582 Search in Google Scholar

308. Vicente-Dueñas C, Hauer J, Cobaleda C, et al. Epigenetic Priming in Cancer Initiation. Trends Cancer 2018;4:408–417.10.1016/j.trecan.2018.04.00729860985 Search in Google Scholar

309. Berson A, Nativio R, Berger SL, et al. Epigenetic Regulation in Neurodegenerative Diseases. Trends Neurosci 2018;41:587–598.10.1016/j.tins.2018.05.005617453229885742 Search in Google Scholar

310. Burns AM, Gräff J. Cognitive epigenetic priming: leveraging histone acetylation for memory amelioration. Curr Opin Neurobiol 2021;67:75–84.10.1016/j.conb.2020.08.01133120188 Search in Google Scholar

311. Qureshi IA, Mehler MF. Chapter 5 - Epigenetic mechanisms underlying nervous system diseases. In: Geschwind DH, Paulson HL, Klein C (eds) Handbook of Clinical Neurology. Elsevier:2018;43–58.10.1016/B978-0-444-63233-3.00005-1682239129325627 Search in Google Scholar

312. Takeshima H, Ushijima T. Accumulation of genetic and epigenetic alterations in normal cells and cancer risk. Npj Precis Oncol 2019;3:1–8.10.1038/s41698-019-0079-0640333930854468 Search in Google Scholar

313. Hoeijmakers L, Heinen Y, van Dam A-M, et al. Microglial Priming and Alzheimer’s Disease: A Possible Role for (Early) Immune Challenges and Epigenetics? Front Hum Neurosci 2016;10:398. Search in Google Scholar

314. Martins-Ferreira R, Leal B, Costa PP, et al. Microglial innate memory and epigenetic reprogramming in neurological disorders. Prog Neurobiol 2021;200:101971.10.1016/j.pneurobio.2020.10197133309803 Search in Google Scholar

315. Perry VH, Holmes C. Microglial priming in neurodegenerative disease. Nat Rev Neurol 2014;10:217–224.10.1038/nrneurol.2014.3824638131 Search in Google Scholar

316. Ganesan A, Arimondo PB, Rots MG, et al. The timeline of epigenetic drug discovery: from reality to dreams. Clin Epigenetics 2019;11:174.10.1186/s13148-019-0776-0688892131791394 Search in Google Scholar

317. Good KV, Vincent JB, Ausió J. MeCP2: The Genetic Driver of Rett Syndrome Epigenetics. Front Genet 2021;12:620859.10.3389/fgene.2021.620859785952433552148 Search in Google Scholar

318. Vashi N, Justice MJ. Treating Rett syndrome: from mouse models to human therapies. Mamm Genome Off J Int Mamm Genome Soc 2019;30:90–110.10.1007/s00335-019-09793-5660666530820643 Search in Google Scholar

319. Mossink B, Negwer M, Schubert D, et al. The emerging role of chromatin remodelers in neurodevelopmental disorders: a developmental perspective. Cell Mol Life Sci CMLS 2021;78:2517–2563.10.1007/s00018-020-03714-5800449433263776 Search in Google Scholar

320. Bustos FJ, Ampuero E, Jury N, et al. Epigenetic editing of the Dlg4/PSD95 gene improves cognition in aged and Alzheimer’s disease mice. Brain J Neurol 2017;140:3252–3268.10.1093/brain/awx272584103529155979 Search in Google Scholar

321. Coppedè F. Epigenetic regulation in Alzheimer’s disease: is it a potential therapeutic target? Expert Opin Ther Targets 2021;25:283–298. Search in Google Scholar

322. Ricq EL, Hooker JM, Haggarty SJ. Toward development of epigenetic drugs for central nervous system disorders: Modulating neuroplasticity via H3K4 methylation. Psychiatry Clin Neurosci 2016;70:536–550.10.1111/pcn.12426576416427485392 Search in Google Scholar

323. Hogg SJ, Beavis PA, Dawson MA, et al. Targeting the epigenetic regulation of antitumour immunity. Nat Rev Drug Discov 2020;19:776–800.10.1038/s41573-020-0077-532929243 Search in Google Scholar

324. Rugo HS, Jacobs I, Sharma S, et al. The Promise for Histone Methyltransferase Inhibitors for Epigenetic Therapy in Clinical Oncology: A Narrative Review. Adv Ther 2020;37:3059–3082.10.1007/s12325-020-01379-x746740932445185 Search in Google Scholar

325. Chen Z, Li S, Subramaniam S, et al. Epigenetic Regulation: A New Frontier for Biomedical Engineers. Annu Rev Biomed Eng 2017;19:195–219.10.1146/annurev-bioeng-071516-04472028301736 Search in Google Scholar

326. Horii T, Morita S, Hino S, et al. Successful generation of epigenetic disease model mice by targeted demethylation of the epigenome. Genome Biol 2020;21:77.10.1186/s13059-020-01991-8711079332234052 Search in Google Scholar

327. Pajovic S, Siddaway R, Bridge T, et al. Epigenetic activation of a RAS/MYC axis in H3.3K27M-driven cancer. Nat Commun 2020;11:6216.10.1038/s41467-020-19972-7771827633277484 Search in Google Scholar

328. Lardenoije R, van den Hove DLA, Havermans M, et al. Age-related epigenetic changes in hippocampal subregions of four animal models of Alzheimer’s disease. Mol Cell Neurosci 2018;86:1–15.10.1016/j.mcn.2017.11.002686335529113959 Search in Google Scholar

329. Momoi T, Fujita E, Senoo H, et al. Genetic factors and epigenetic factors for autism: endoplasmic reticulum stress and impaired synaptic function. Cell Biol Int 2009;34:13–19. Search in Google Scholar

330. Schepici G, Cavalli E, Bramanti P, et al. Autism Spectrum Disorder and miRNA: An Overview of Experimental Models. Brain Sci 2019;9:E265.10.3390/brainsci9100265682702031623367 Search in Google Scholar

331. Schmitz RL, Weissbach J, Kleilein J, et al. Targeting HDACs in Pancreatic Neuroendocrine Tumor Models. Cells 2021;10:1408.10.3390/cells10061408822803334204116 Search in Google Scholar

332. Grayson DR, Guidotti A. DNA Methylation in Animal Models of Psychosis. Prog Mol Biol Transl Sci 2018;157:105–132.10.1016/bs.pmbts.2017.12.012793913029933947 Search in Google Scholar

333. Monacelli F, Acquarone E, Giannotti C, et al. Vitamin C, Aging and Alzheimer’s Disease. Nutrients 2017;9:E670.10.3390/nu9070670553778528654021 Search in Google Scholar

334. Horsburgh S, Robson-Ansley P, Adams R, et al. Exercise and inflammation-related epigenetic modifications: focus on DNA methylation. Exerc Immunol Rev 2015;21:26–41. Search in Google Scholar

335. Cabezudo D, Baekelandt V, Lobbestael E. Multiple-Hit Hypothesis in Parkinson’s Disease: LRRK2 and Inflammation. Front Neurosci 2020;14:376.10.3389/fnins.2020.00376719938432410948 Search in Google Scholar

336. Patrick KL, Bell SL, Weindel CG, et al. Exploring the “Multiple-Hit Hypothesis” of Neurodegenerative Disease: Bacterial Infection Comes Up to Bat. Front Cell Infect Microbiol 2019;9:138.10.3389/fcimb.2019.00138654688531192157 Search in Google Scholar

337. Persico AM, Bourgeron T. Searching for ways out of the autism maze: genetic, epigenetic and environmental clues. Trends Neurosci 2006;29:349–358.10.1016/j.tins.2006.05.01016808981 Search in Google Scholar

338. Arnold AP, Chen X. What does the “four core genotypes” mouse model tell us about sex differences in the brain and other tissues? Front Neuroendocrinol 2009;30:1–9. Search in Google Scholar

339. Arnold AP, McCarthy MM. Sexual Differentiation of the Brain and Behavior: A Primer. In: Pfaff DW, Volkow ND (eds) Neuroscience in the 21st Century: From Basic to Clinical. New York, NY: Springer:2016;2139–2168.10.1007/978-1-4939-3474-4_141 Search in Google Scholar

340. Walker DM, Gore AC. Epigenetic impacts of endocrine disruptors in the brain. Front Neuroendocrinol 2017;44:1–26.10.1016/j.yfrne.2016.09.002542981927663243 Search in Google Scholar

341. Schug TT, Blawas AM, Gray K, et al. Elucidating the Links Between Endocrine Disruptors and Neurodevelopment. Endocrinology 2015;156:1941–1951.10.1210/en.2014-1734539334025714811 Search in Google Scholar

342. Kuehner JN, Bruggeman EC, Wen Z, et al. Epigenetic Regulations in Neuropsychiatric Disorders. Front Genet 2019;10:268.10.3389/fgene.2019.00268645825131019524 Search in Google Scholar

343. Repouskou A, Papadopoulou A-K, Panagiotidou E, et al. Long term transcriptional and behavioral effects in mice developmentally exposed to a mixture of endocrine disruptors associated with delayed human neurodevelopment. Sci Rep 2020;10:9367.10.1038/s41598-020-66379-x728333132518293 Search in Google Scholar

344. Tan Q, Zoghbi HY. Mouse models as a tool for discovering new neurological diseases. Neurobiol Learn Mem 2019;165:106902.10.1016/j.nlm.2018.07.00630030131 Search in Google Scholar

345. Armstrong RA. What causes alzheimer’s disease? Folia Neuropathol 2013;51:169–188. Search in Google Scholar

346. Armstrong RA. Risk factors for Alzheimer’s disease. Folia Neuropathol 2019;57:87–105.10.5114/fn.2019.8592931556570 Search in Google Scholar

347. Adams JD. Probable Causes of Alzheimer’s Disease. Sci 2021;3:16.10.3390/sci3010016 Search in Google Scholar

348. Fertan E, Stover KRJ, Brant MG, et al. Effects of the Novel IDO Inhibitor DWG-1036 on the Behavior of Male and Female 3xTg-AD Mice. Front Pharmacol 2019;10:1044.10.3389/fphar.2019.01044677397931607909 Search in Google Scholar

349. Sorgdrager FJH, Vermeiren Y, Van Faassen M, et al. Age- and disease-specific changes of the kynurenine pathway in Parkinson’s and Alzheimer’s disease. J Neurochem 2019;151:656–668.10.1111/jnc.14843689986231376341 Search in Google Scholar

350. Willette AA, Pappas C, Hoth N, et al. Inflammation, negative affect, and amyloid burden in Alzheimer’s disease: Insights from the kynurenine pathway. Brain Behav Immun 2021;95:216–225.10.1016/j.bbi.2021.03.019818728333775832 Search in Google Scholar

351. Sharma VK, Singh TG, Prabhakar NK, et al. Kynurenine Metabolism and Alzheimer’s Disease: The Potential Targets and Approaches. Neurochem Res. Epub ahead of print February 8, 2022. DOI: 10.1007/s11064-022-03546-8.10.1007/s11064-022-03546-835133568 Search in Google Scholar

352. Breijyeh Z, Karaman R. Comprehensive Review on Alzheimer’s Disease: Causes and Treatment. Mol Basel Switz 2020;25:E5789.10.3390/molecules25245789776410633302541 Search in Google Scholar

353. Fertan E, Rodrigues GJ, Wheeler RV, et al. Cognitive Decline, Cerebral-Spleen Tryptophan Metabolism, Oxidative Stress, Cytokine Production, and Regulation of the Txnip Gene in a Triple Transgenic Mouse Model of Alzheimer Disease. Am J Pathol 2019;189:1435–1450.10.1016/j.ajpath.2019.03.00630980800 Search in Google Scholar

354. Tsubaki H, Tooyama I, Walker DG. Thioredoxin-Interacting Protein (TXNIP) with Focus on Brain and Neurodegenerative Diseases. Int J Mol Sci 2020;21:E9357.10.3390/ijms21249357776458033302545 Search in Google Scholar

355. Oblak AL, Forner S, Territo PR, et al. Model organism development and evaluation for late-onset Alzheimer’s disease: MODEL-AD. Alzheimers Dement N Y N 2020;6:e12110.10.1002/trc2.12110768395833283040 Search in Google Scholar

356. Baglietto-Vargas D, Forner S, Cai L, et al. Generation of a humanized Aβ expressing mouse demonstrating aspects of Alzheimer’s disease-like pathology. Nat Commun 2021;12:2421.10.1038/s41467-021-22624-z806516233893290 Search in Google Scholar

357. Kotredes KP, Oblak A, Pandey RS, et al. APOEe4.Trem2*R47H Mice Show Changes in Alzheimer’s Disease-Relevant Processes in the Absence of Amyloid Plaques. 2021; DOI:10.21203/rs.3.rs-580913/v1.10.21203/rs.3.rs-580913/v1 Search in Google Scholar

358. Mehder RH, Bennett BM, Andrew RD. Morphometric Analysis of Hippocampal and Neocortical Pyramidal Neurons in a Mouse Model of Late Onset Alzheimer’s Disease. J Alzheimers Dis JAD 2020;74:1069–1083.10.3233/JAD-191067724283832144984 Search in Google Scholar

359. Ochiishi T, Kaku M, Kiyosue K, et al. New Alzheimer’s disease model mouse specialized for analyzing the function and toxicity of intraneuronal Amyloid β oligomers. Sci Rep 2019;9:17368.10.1038/s41598-019-53415-8687455631757975 Search in Google Scholar

360. Wong P, Ho WY, Yen Y-C, et al. The vulnerability of motor and frontal cortex-dependent behaviors in mice expressing ALS-linked mutation in TDP-43. Neurobiol Aging 2020;92:43–60.10.1016/j.neurobiolaging.2020.03.01932422502 Search in Google Scholar

361. Murava AL, Meadows S, Palaguachi F, et al. Dementia-linked TDP-43 dysregulation in astrocytes impairs memory, antiviral signaling, and chemokine-mediated astrocytic-neuronal interactions. Alzheimers Dement 2021;17:e058562.10.1002/alz.058562 Search in Google Scholar

362. Nackenoff AG, Hohman TJ, Neuner SM, et al. PLD3 is a neuronal lysosomal phospholipase D associated with β-amyloid plaques and cognitive function in Alzheimer’s disease. PLoS Genet 2021;17:e1009406.10.1371/journal.pgen.1009406803139633830999 Search in Google Scholar

363. Rosene MJ, Hsu S, Martinez R, et al. Defining the role of PLD3 in Alzheimer’s disease pathology. Alzheimers Dement 2021;17:e058730.10.1002/alz.058730 Search in Google Scholar

364. Nagu P, Parashar A, Behl T, et al. Gut Microbiota Composition and Epigenetic Molecular Changes Connected to the Pathogenesis of Alzheimer’s Disease. J Mol Neurosci 2021;71:1436–1455.10.1007/s12031-021-01829-333829390 Search in Google Scholar

365. Shen G, Hu S, Zhao Z, et al. Antenatal Hypoxia Accelerates the Onset of Alzheimer’s Disease Pathology in 5xFAD Mouse Model. Front Aging Neurosci 2020;12:251.10.3389/fnagi.2020.00251747263932973487 Search in Google Scholar

366. Wang M, Lv J, Huang X, et al. High-fat diet-induced atherosclerosis promotes neurodegeneration in the triple transgenic (3 × Tg) mouse model of Alzheimer’s disease associated with chronic platelet activation. Alzheimers Res Ther 2021;13:144.10.1186/s13195-021-00890-9840341834454596 Search in Google Scholar

367. Peterman JL, White JD, Calcagno A, et al. Prolonged isolation stress accelerates the onset of Alzheimer’s disease-related pathology in 5xFAD mice despite running wheels and environmental enrichment. Behav Brain Res 2020;379:112366.10.1016/j.bbr.2019.11236631743728 Search in Google Scholar

368. Liang F, Yang S, Zhang Y, et al. Social housing promotes cognitive function through enhancing synaptic plasticity in APP/PS1 mice. Behav Brain Res 2019;368:111910.10.1016/j.bbr.2019.11191031034995 Search in Google Scholar

369. Zhu X, Lee H, Perry G, et al. Alzheimer disease, the two-hit hypothesis: an update. Biochim Biophys Acta 2007;1772:494–502.10.1016/j.bbadis.2006.10.01417142016 Search in Google Scholar

370. Hawkes CH, Del Tredici K, Braak H. Parkinson’s disease: a dual-hit hypothesis. Neuropathol Appl Neurobiol 2007;33:599–614.10.1111/j.1365-2990.2007.00874.x719430817961138 Search in Google Scholar

371. Feigenson KA, Kusnecov AW, Silverstein SM. Inflammation and the two-hit hypothesis of schizophrenia. Neurosci Biobehav Rev 2014;38:72–93.10.1016/j.neubiorev.2013.11.006389692224247023 Search in Google Scholar

372. Fang Y-L, Chen H, Wang C-L, et al. Pathogenesis of non-alcoholic fatty liver disease in children and adolescence: From “two hit theory” to “multiple hit model.” World J Gastroenterol 2018;24:2974–2983.10.3748/wjg.v24.i27.2974605495030038464 Search in Google Scholar

373. Bouayed J, Bohn T. The link between microglia and the severity of COVID-19: The “two-hit” hypothesis. J Med Virol 2021;93:4111–4113.10.1002/jmv.26984825088633788265 Search in Google Scholar

374. Baranov SV, Jauhari A, Carlisle DL, et al. Two hit mitochondrial-driven model of synapse loss in neurodegeneration. Neurobiol Dis 2021;158:105451.10.1016/j.nbd.2021.10545134298088 Search in Google Scholar

375. Möller M, Swanepoel T, Harvey BH. Neurodevelopmental Animal Models Reveal the Convergent Role of Neurotransmitter Systems, Inflammation, and Oxidative Stress as Biomarkers of Schizophrenia: Implications for Novel Drug Development. ACS Chem Neurosci 2015;6:987–1016.10.1021/cn500336825794269 Search in Google Scholar

376. Bouet V, Percelay S, Leroux E, et al. A new 3-hit mouse model of schizophrenia built on genetic, early and late factors. Schizophr Res 2021;228:519–528.10.1016/j.schres.2020.11.04333298334 Search in Google Scholar

377. Hansen J, Baum A, Pascal KE, et al. Studies in humanized mice and convalescent humans yield a SARS-CoV-2 antibody cocktail. Science 2020;369:1010–1014.10.1126/science.abd0827729928432540901 Search in Google Scholar

378. Netland J, Meyerholz DK, Moore S, et al. Severe acute respiratory syndrome coronavirus infection causes neuronal death in the absence of encephalitis in mice transgenic for human ACE2. J Virol 2008;82:7264–7275.10.1128/JVI.00737-08249332618495771 Search in Google Scholar

379. Sefik E, Israelow B, Mirza H, et al. A humanized mouse model of chronic COVID-19. Nat Biotechnol 2021;1–15.10.1038/s41587-021-01155-434921308 Search in Google Scholar

Articles recommandés par Trend MD

Planifiez votre conférence à distance avec Sciendo