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Turning strains into strengths for understanding psychiatric disorders

Abstract

There is a paucity in the development of new mechanistic insights and therapeutic approaches for treating psychiatric disease. One of the major challenges is reflected in the growing consensus that risk for these diseases is not determined by a single gene, but rather is polygenic, arising from the action and interaction of multiple genes. Canonically, experimental models in mice have been designed to ascertain the relative contribution of a single gene to a disease by systematic manipulation (e.g., mutation or deletion) of a known candidate gene. Because these studies have been largely carried out using inbred isogenic mouse strains, in which there is no (or very little) genetic diversity among subjects, it is difficult to identify unique allelic variants, gene modifiers, and epigenetic factors that strongly affect the nature and severity of these diseases. Here, we review various methods that take advantage of existing genetic diversity or that increase genetic variance in mouse models to (1) strengthen conclusions of single-gene function; (2) model diversity among human populations; and (3) dissect complex phenotypes that arise from the actions of multiple genes.

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Fig. 1: Experimental strategies for leveraging genetic tractability and diversity to understand complex phenotypes.
Fig. 2: Effects of modifier genes.

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References

  1. Collins PY, Patel V, Joestl SS, March D, Insel TR, Daar AS, et al. Grand challenges in global mental health. Nature. 2011;475:27–30.

    CAS  PubMed  PubMed Central  Google Scholar 

  2. Crimmins EM. Trends in the health of the elderly. Annu Rev Public Health. 2004;25:79–98.

    PubMed  Google Scholar 

  3. Murray CJL, Lopez AD. Measuring the global burden of disease. N. Engl J Med. 2013;369:448–57.

    CAS  PubMed  Google Scholar 

  4. Trautmann S, Rehm J, Wittchen HU. The economic costs of mental disorders: do our societies react appropriately to the burden of mental disorders? EMBO Rep. 2016;17:1245–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Josselyn SA, Frankland PW. Memory allocation: mechanisms and function. Annu Rev Neurosci. 2018;41:389–413.

    CAS  PubMed  Google Scholar 

  6. Glineburg MR, Todd PK, Charlet-Berguerand N, Sellier C. Repeat-associated non-AUG (RAN) translation and other molecular mechanisms in Fragile X Tremor Ataxia Syndrome. Brain Res. 2018;1693:43–54.

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Schizophrenia Working Group of the Psychiatric Genomics Consortium, Sekar A, Bialas AR, de Rivera H, Davis A, Hammond TR, et al. Schizophrenia risk from complex variation of complement component 4. Nature. 2016;530:177–83.

    PubMed Central  Google Scholar 

  8. Bailey SJ, Toth M. Variability in the benzodiazepine response of serotonin 5-HT1A receptor null mice displaying anxiety-like phenotype: evidence for genetic modifiers in the 5-HT-mediated regulation of GABA(A) receptors. J Neurosci. 2004;24:6343–51.

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Dominguez-Salazar E, Bateman HL, Rissman EF. Background matters: the effects of estrogen receptor alpha gene disruption on male sexual behavior are modified by background strain. Horm Behav. 2004;46:482–90.

    CAS  PubMed  Google Scholar 

  10. Errijgers V, Kooy RF. Genetic modifiers in mice: the example of the fragile X mouse model. Cytogenet Genome Res. 2004;105:448–54.

    CAS  PubMed  Google Scholar 

  11. Bruening S, Oh E, Hetzenauer A, Escobar-Alvarez S, Westphalen RI, Hemmings HC, et al. The anxiety-like phenotype of 5-HT receptor null mice is associated with genetic background-specific perturbations in the prefrontal cortex GABA-glutamate system. J Neurochem. 2006;99:892–9.

    CAS  PubMed  Google Scholar 

  12. van den Buuse M, Martin S, Holgate J, Matthaei K, Hendry I. Mice deficient in the alpha subunit of G(z) show changes in pre-pulse inhibition, anxiety and responses to 5-HT(1A) receptor stimulation, which are strongly dependent on the genetic background. Psychopharmacology. 2007;195:273–83.

    PubMed  Google Scholar 

  13. Petkau TL, Hill A, Leavitt BR. Core neuropathological abnormalities in progranulin-deficient mice are penetrant on multiple genetic backgrounds. Neuroscience. 2016;315:175–95.

    CAS  PubMed  Google Scholar 

  14. Crawley JN, Belknap JK, Collins A, Crabbe JC, Frankel W, Henderson N, et al. Behavioral phenotypes of inbred mouse strains: implications and recommendations for molecular studies. Psychopharmacology. 1997;132:107–24.

    CAS  PubMed  Google Scholar 

  15. Silva AJ, Simpson EM, Takahashi JS, Lipp H-P, Nakanishi S, Wehner JM, et al. Mutant mice and neuroscience: recommendations concerning genetic background. Neuron. 1997;19:755–9.

    Google Scholar 

  16. Frankel WN. Mouse strain backgrounds: more than black and white. Neuron. 1998;20:183.

    CAS  PubMed  Google Scholar 

  17. Miller RA, Austad S, Burke D, Chrisp C, Dysko R, Galecki A, et al. Exotic mice as models for aging research: polemic and prospectus. Neurobiol Aging. 1999;20:217–31.

    CAS  PubMed  Google Scholar 

  18. Riordan JD, Nadeau JH. From peas to disease: modifier genes, network resilience, and the genetics of health. Am J Hum Genet. 2017;101:177–91.

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Ellenbroek B, Youn J. Rodent models in neuroscience research: is it a rat race? Dis Model Mech. 2016;9:1079–87.

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Beck JA, Lloyd S, Hafezparast M, Lennon-Pierce M, Eppig JT, Festing MF, et al. Genealogies of mouse inbred strains. Nat Genet. 2000;24:23–25.

    CAS  PubMed  Google Scholar 

  21. Castle WE, Little CC. The peculiar inheritance of pink eyes among colored mice. Science. 1909;30:313–4.

    CAS  PubMed  Google Scholar 

  22. Sullivan PF, Daly MJ, O’Donovan M. Genetic architectures of psychiatric disorders: the emerging picture and its implications. Nat Rev Genet. 2012;13:537–51.

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Meisler MH, Kearney JA. Sodium channel mutations in epilepsy and other neurological disorders. J Clin Invest. 2005;115:2010–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Miller AR, Hawkins NA, McCollom CE, Kearney JA. Mapping genetic modifiers of survival in a mouse model of Dravet syndrome. Genes, Brain Behav. 2014;13:163–72.

    CAS  Google Scholar 

  25. Yu FH, Mantegazza M, Westenbroek RE, Robbins CA, Kalume F, Burton KA, et al. Reduced sodium current in GABAergic interneurons in a mouse model of severe myoclonic epilepsy in infancy. Nat Neurosci. 2006;9:1142–9.

    CAS  PubMed  Google Scholar 

  26. Nadeau JH. Modifier genes in mice and humans. Nat Rev Genet. 2001;2:165–74.

    CAS  PubMed  Google Scholar 

  27. Stein RE, Kaplan JS, Li J, Catterall WA. Hippocampal deletion of NaV1.1 channels in mice causes thermal seizures and cognitive deficit characteristic of Dravet Syndrome. Proc Natl Acad Sci USA. 2019;116:16571–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Gunduz-Cinar O, Brockway E, Lederle L, Wilcox T, Halladay LR, Ding Y, et al. Identification of a novel gene regulating amygdala-mediated fear extinction. Mol Psychiatry. 2018;36:1.

    Google Scholar 

  29. Lenselink AM, Rotaru DC, Li KW, van Nierop P, Rao-Ruiz P, Loos M, et al. Strain differences in presynaptic function proteomics, ultrastructure, and physiology of hippocampal synapses in DBA/2 J and C57Bl/6 J mice. J Biol Chem. 2015;290:15635–45.

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Moore SJ, Throesch BT, Murphy GG. Of mice and intrinsic excitability: genetic background affects the size of the postburst afterhyperpolarization in CA1 pyramidal neurons. J Neurophysiol. 2011;106:1570–80.

    PubMed  PubMed Central  Google Scholar 

  31. Sandberg R, Yasuda R, Pankratz DG, Carter TA, Del Rio JA, Wodicka L, et al. Regional and strain-specific gene expression mapping in the adult mouse brain. Proc Natl Acad Sci USA. 2000;97:11038–43.

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Woo-Hyun Cho J-SH. Differences in the flexibility of switching learning strategies and CREB phosphorylation levels in prefrontal cortex, dorsal striatum and hippocampus in two inbred strains of mice. Front Behav Neurosci. 2016;10:9.

    Google Scholar 

  33. Kim CK, Adhikari A, Deisseroth K. Integration of optogenetics with complementary methodologies in systems neuroscience. Nat Rev Neurosci. 2017;18:222–35.

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Lin MZ, Schnitzer MJ. Genetically encoded indicators of neuronal activity. Nat Neurosci. 2016;19:1142–53.

    PubMed  PubMed Central  Google Scholar 

  35. Hefner K, Whittle N, Juhasz J, Norcross M, Karlsson R-M, Saksida LM, et al. Impaired fear extinction learning and cortico-amygdala circuit abnormalities in a common genetic mouse strain. J Neurosci. 2008;28:8074–85.

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Muigg P, Scheiber S, Salchner P, Bunck M, Landgraf R, Singewald N. Differential stress-induced neuronal activation patterns in mouse lines selectively bred for high, normal or low anxiety. PLoS One. 2009;4:e5346.

    PubMed  PubMed Central  Google Scholar 

  37. Fenster RJ, Lebois LAM, Ressler KJ, Suh J. Brain circuit dysfunction in post-traumatic stress disorder: from mouse to man. Nat Rev Neurosci. 2018;69:516.

    Google Scholar 

  38. Smoller JW. The genetics of stress-related disorders: PTSD, depression, and anxiety disorders. Neuropsychopharmacology. 2016;41:297–319.

    CAS  PubMed  Google Scholar 

  39. Rescorla RA. Pavlovian conditioning It’s not what you think it is. Am Psychol. 1988;43:151–60.

    CAS  PubMed  Google Scholar 

  40. Camp M, Norcross M, Whittle N, Feyder M, D’Hanis W, Yilmazer-Hanke D, et al. Impaired Pavlovian fear extinction is a common phenotype across genetic lineages of the 129 inbred mouse strain. Genes, Brain Behav. 2009;8:744–52.

    CAS  Google Scholar 

  41. Camp MC, MacPherson KP, Lederle L, Graybeal C, Gaburro S, DeBrouse LM, et al. Genetic strain differences in learned fear inhibition associated with variation in neuroendocrine, autonomic, and amygdala dendritic phenotypes. Neuropsychopharmacology. 2012;37:1534–47.

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Temme SJ, Bell RZ, Pahumi R, Murphy GG. Comparison of inbred mouse substrains reveals segregation of maladaptive fear phenotypes. Front Behav Neurosci. 2014;8:282.

    PubMed  PubMed Central  Google Scholar 

  43. Fitzgerald PJ, Whittle N, Flynn SM, Graybeal C, Pinard CR, Gunduz-Cinar O, et al. Prefrontal single-unit firing associated with deficient extinction in mice. Neurobiol Learn Mem. 2014;113:69–81.

    CAS  PubMed  Google Scholar 

  44. Flores Á, Valls-Comamala V, Costa G, Saravia R, Maldonado R, Berrendero F. The hypocretin/orexin system mediates the extinction of fear memories. Neuropsychopharmacology. 2014;39:2732–41.

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Daviu N, Füzesi T, Rosenegger DG, Rasiah NP, Sterley T-L, Peringod G, et al. Paraventricular nucleus CRH neurons encode stress controllability and regulate defensive behavior selection. Nat Neurosci. 2020;23:398–410.

    CAS  PubMed  Google Scholar 

  46. Futch HS, McFarland KN, Moore BD, Kuhn MZ, Giasson BI, Ladd TB, et al. An anti-CRF antibody suppresses the HPA axis and reverses stress-induced phenotypes. J Exp Med. 2019;216:2479–91.

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Zorn JV, Schür RR, Boks MP, Kahn RS, Joëls M, Vinkers CH. Cortisol stress reactivity across psychiatric disorders: A systematic review and meta-analysis. Psychoneuroendocrinology. 2017;77:25–36.

    CAS  PubMed  Google Scholar 

  48. Wichmann S, Kirschbaum C, Böhme C, Petrowski K. Cortisol stress response in post-traumatic stress disorder, panic disorder, and major depressive disorder patients. Psychoneuroendocrinology. 2017;83:135–41.

    CAS  PubMed  Google Scholar 

  49. Yehuda R, Halligan SL, Bierer LM. Cortisol levels in adult offspring of Holocaust survivors: relation to PTSD symptom severity in the parent and child. Psychoneuroendocrinology. 2002;27:171–80.

    CAS  PubMed  Google Scholar 

  50. Sapolsky RM. Glucocorticoids and hippocampal atrophy in neuropsychiatric disorders. Arch Gen Psychiatry. 2000;57:925–35.

    CAS  PubMed  Google Scholar 

  51. Le-Niculescu H, Roseberry K, Levey DF, Rogers J, Kosary K, Prabha S, et al. Towards precision medicine for stress disorders: diagnostic biomarkers and targeted drugs. Mol Psychiatry. 2019;376:1.

    Google Scholar 

  52. Holmes SE, Girgenti MJ, Davis MT, Pietrzak RH, DellaGioia N, Nabulsi N, et al. Altered metabotropic glutamate receptor 5 markers in PTSD: In vivo and postmortem evidence. Proc Natl Acad Sci USA. 2017;114:8390–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Yehuda R, Cai G, Golier JA, Sarapas C, Galea S, Ising M, et al. Gene expression patterns associated with posttraumatic stress disorder following exposure to the World Trade Center attacks. Biol Psychiatry. 2009;66:708–11.

    CAS  PubMed  Google Scholar 

  54. Binder EB, Bradley RG, Liu W, Epstein MP, Deveau TC, Mercer KB, et al. Association of FKBP5 polymorphisms and childhood abuse with risk of posttraumatic stress disorder symptoms in adults. JAMA. 2008;299:1291–305.

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Kessler RC, Sonnega A, Bromet E, Hughes M, Nelson CB. Posttraumatic stress disorder in the National Comorbidity Survey. Arch Gen Psychiatry. 1995;52:1048–60.

    CAS  PubMed  Google Scholar 

  56. Ressler KJ. Translating across circuits and genetics toward progress in fear- and anxiety-related disorders. Am J Psychiatry. 2020;177:214–22.

    PubMed  PubMed Central  Google Scholar 

  57. Roy-Byrne P. Treatment-refractory anxiety; definition, risk factors, and treatment challenges. Dialogues Clin Neurosci. 2015;17:191–206.

    PubMed  PubMed Central  Google Scholar 

  58. Whittle N, Hauschild M, Lubec G, Holmes A, Singewald N. Rescue of impaired fear extinction and normalization of cortico-amygdala circuit dysfunction in a genetic mouse model by dietary zinc restriction. J Neurosci. 2010;30:13586–96.

    CAS  PubMed  PubMed Central  Google Scholar 

  59. Whittle N, Schmuckermair C, Gunduz-Cinar O, Hauschild M, Ferraguti F, Holmes A, et al. Deep brain stimulation, histone deacetylase inhibitors and glutamatergic drugs rescue resistance to fear extinction in a genetic mouse model. Neuropharmacology. 2013;64:414–23.

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Whittle N, Maurer V, Murphy C, Rainer J, Bindreither D, Hauschild M, et al. Enhancing dopaminergic signaling and histone acetylation promotes long-term rescue of deficient fear extinction. Transl Psychiatry. 2016;6:e974–e974.

    CAS  PubMed  PubMed Central  Google Scholar 

  61. Cazares VA, Rodriguez G, Parent R, Ouillette L, Glanowska KM, Moore SJ, et al. Environmental variables that ameliorate extinction learning deficits in the 129S1/SvlmJ mouse strain. Genes, Brain Behav. 2019;19:e12575.

    Google Scholar 

  62. Murphy CP, Li X, Maurer V, Oberhauser M, Gstir R, Wearick-Silva LE, et al. MicroRNA-mediated rescue of fear extinction memory by miR-144-3p in extinction-impaired mice. Biol Psychiatry. 2017;81:979–89.

    CAS  PubMed  Google Scholar 

  63. Dunsmoor JE, Campese VD, Ceceli AO, LeDoux JE, Phelps EA. Novelty-facilitated extinction: providing a novel outcome in place of an expected threat diminishes recovery of defensive responses. Biol Psychiatry. 2015;78:203–9.

    PubMed  Google Scholar 

  64. Dunsmoor JE, Kroes MCW, Li J, Daw ND, Simpson HB, Phelps EA. Role of human ventromedial prefrontal cortex in learning and recall of enhanced extinction. J Neurosci. 2019;39:3264–76.

    CAS  PubMed  PubMed Central  Google Scholar 

  65. Hermann A, Stark R, Müller EA, Kruse O, Wolf OT, Merz CJ. Multiple extinction contexts modulate the neural correlates of context-dependent extinction learning and retrieval. Neurobiol Learn Mem. 2020;168:107150.

    CAS  PubMed  Google Scholar 

  66. de Jong R, Lommen M, de Jong PJ, Nauta MH. Using multiple contexts and retrieval cues in exposure-based therapy to prevent relapse in anxiety disorders. Cogn Behav Pr. 2019;26:156–65.

    Google Scholar 

  67. Duncan LE, Ratanatharathorn A, Aiello AE, Almli LM, Amstadter AB, Ashley-Koch AE, et al. Largest GWAS of PTSD (N = 20 070) yields genetic overlap with schizophrenia and sex differences in heritability. Mol Psychiatry. 2018;23:666–73.

    CAS  PubMed  Google Scholar 

  68. McLean SA, Ressler K, Koenen KC, Neylan T, Germine L, Jovanovic T, et al. The AURORA Study: a longitudinal, multimodal library of brain biology and function after traumatic stress exposure. Mol Psychiatry. 2020;25:283–96.

    PubMed  Google Scholar 

  69. Grewe BF, Gründemann J, Kitch LJ, Lecoq JA, Parker JG, Marshall JD, et al. Neural ensemble dynamics underlying a long-term associative memory. Nature. 2017;543:670–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  70. Sartori SB, Maurer V, Murphy C, Schmuckermair C, Muigg P, Neumann ID, et al. Combined neuropeptide S and D-cycloserine augmentation prevents the return of fear in extinction-impaired rodents: advantage of dual versus single drug approaches. Int J Neuropsychopharmacol. 2016;19:pyv128.

    PubMed  Google Scholar 

  71. Swallow JG, Garland T. Selection experiments as a tool in evolutionary and comparative physiology: insights into complex traits-an introduction to the symposium. Integr Comp Biol. 2005;45:387–90.

    PubMed  Google Scholar 

  72. Zhang P, Rhodes JS, Garland T, Perez SD, Southey BR, Rodriguez-Zas SL. Brain region-dependent gene networks associated with selective breeding for increased voluntary wheel-running behavior. PLoS One. 2018;13:e0201773.

    PubMed  PubMed Central  Google Scholar 

  73. Kolb EM, Rezende EL, Holness L, Radtke A, Lee SK, Obenaus A, et al. Mice selectively bred for high voluntary wheel running have larger midbrains: support for the mosaic model of brain evolution. J Exp Biol. 2013;216:515–23.

    CAS  PubMed  Google Scholar 

  74. Koch LG, Britton SL. Artificial selection for intrinsic aerobic endurance running capacity in rats. Physiol Genomics. 2001;5:45–52.

    CAS  PubMed  Google Scholar 

  75. Thompson Z, Argueta D, Garland T Jr., DiPatrizio N. Circulating levels of endocannabinoids respond acutely to voluntary exercise, are altered in mice selectively bred for high voluntary wheel running, and differ between the sexes. Physiol Behav. 2017;170:141–50.

    CAS  PubMed  Google Scholar 

  76. Stead JDH, Clinton S, Neal C, Schneider J, Jama A, Miller S, et al. Selective breeding for divergence in novelty-seeking traits: heritability and enrichment in spontaneous anxiety-related behaviors. Behav Genet. 2006;36:697–712.

    PubMed  Google Scholar 

  77. de Fiebre NC, Dawson R, de Fiebre CM. The selectively bred high alcohol sensitivity (HAS) and low alcohol sensitivity (LAS) rats differ in sensitivity to nicotine. Alcohol: Clin Exp Res. 2002;26:765–72.

    Google Scholar 

  78. Thiele TE, Miura GI, Marsh DJ, Bernstein IL, Palmiter RD. Neurobiological responses to ethanol in mutant mice lacking neuropeptide Y or the Y5 receptor. Pharmacol Biochem Behav. 2000;67:683–91.

    CAS  PubMed  Google Scholar 

  79. Gariépy J-L, Bauer DJ, Cairns RB. Selective breeding for differential aggression in mice provides evidence for heterochrony in social behaviours. Anim Behav. 2001;61:933–47.

    Google Scholar 

  80. Slattery DA, Naik RR, Grund T, Yen YC, Sartori SB, Fuchsl A, et al. Selective breeding for high anxiety introduces a synonymous SNP that increases neuropeptide S receptor activity. J Neurosci. 2015;35:4599–613.

    CAS  PubMed  PubMed Central  Google Scholar 

  81. Clinton SM, Vazquez DM, Kabbaj M, Kabbaj M-H, Watson SJ, Akil H. Individual differences in novelty-seeking and emotional reactivity correlate with variation in maternal behavior. Horm Behav. 2007;51:655–64.

    PubMed  PubMed Central  Google Scholar 

  82. Perez JA, Clinton SM, Turner CA, Watson SJ, Akil H. A new role for FGF2 as an endogenous inhibitor of anxiety. J Neurosci. 2009;29:6379–87.

    CAS  PubMed  PubMed Central  Google Scholar 

  83. Turner CA, Clinton SM, Thompson RC, Watson SJ, Akil H. Fibroblast growth factor-2 (FGF2) augmentation early in life alters hippocampal development and rescues the anxiety phenotype in vulnerable animals. Proc Natl Acad Sci USA. 2011;108:8021–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  84. Flagel SB, Robinson TE, Clark JJ, Clinton SM, Watson SJ, Seeman P, et al. An animal model of genetic vulnerability to behavioral disinhibition and responsiveness to reward-related cues: implications for addiction. Neuropsychopharmacology. 2010;35:388–400.

    PubMed  Google Scholar 

  85. Garofalo S, di Pellegrino G. Individual differences in the influence of task-irrelevant Pavlovian cues on human behavior. Front Behav Neurosci. 2015;9:163.

    PubMed  PubMed Central  Google Scholar 

  86. Warner HR, Ingram D, Miller RA, Nadon NL, Richardson AG. Program for testing biological interventions to promote healthy aging. Mech Ageing Dev. 2000;155:199–207.

    Google Scholar 

  87. Miller RA, Burke D, Nadon N. Announcement: four-way cross mouse stocks: a new, genetically heterogeneous resource for aging research. J Gerontol A Biol Sci Med Sci. 1999;54:B358–60.

    CAS  PubMed  Google Scholar 

  88. Grabowska W, Sikora E, Bielak-Zmijewska A. Sirtuins, a promising target in slowing down the ageing process. Biogerontology. 2017;18:447–76.

    CAS  PubMed  PubMed Central  Google Scholar 

  89. Wood JG, Rogina B, Lavu S, Howitz K, Helfand SL, Tatar M, et al. Sirtuin activators mimic caloric restriction and delay ageing in metazoans. Nature. 2004;430:686–9.

    CAS  PubMed  Google Scholar 

  90. Viswanathan M, Kim SK, Berdichevsky A, Guarente L. A role for SIR-2.1 regulation of ER stress response genes in determining C. elegans life span. Dev Cell. 2005;9:605–15.

    CAS  PubMed  Google Scholar 

  91. Bass TM, Weinkove D, Houthoofd K, Gems D, Partridge L. Effects of resveratrol on lifespan in Drosophila melanogaster and Caenorhabditis elegans. Mechanisms Ageing Dev. 2007;128:546–52.

    CAS  Google Scholar 

  92. Baur JA, Pearson KJ, Price NL, Jamieson HA, Lerin C, Kalra A, et al. Resveratrol improves health and survival of mice on a high-calorie diet. Nature. 2006;444:337–42.

    CAS  PubMed  PubMed Central  Google Scholar 

  93. Pearson KJ, Baur JA, Lewis KN, Peshkin L, Price NL, Labinskyy N, et al. Resveratrol delays age-related deterioration and mimics transcriptional aspects of dietary restriction without extending life span. Cell Metab. 2008;8:157–68.

    CAS  PubMed  PubMed Central  Google Scholar 

  94. Miller RA, Harrison DE, Astle CM, Baur JA, Boyd AR, de Cabo R, et al. Rapamycin, but not resveratrol or simvastatin, extends life span of genetically heterogeneous mice. J Gerontol A Biol Sci Med Sci. 2011;66:191–201.

    PubMed  Google Scholar 

  95. Strong R, Miller RA, Astle CM, Baur JA, de Cabo R, Fernandez E, et al. Evaluation of resveratrol, green tea extract, curcumin, oxaloacetic acid, and medium-chain triglyceride oil on life span of genetically heterogeneous mice. J Gerontol A Biol Sci Med Sci. 2013;68:6–16.

    CAS  PubMed  Google Scholar 

  96. Nadon NL, Strong R, Miller RA, Harrison DE. NIA interventions testing program: investigating putative aging intervention agents in a genetically heterogeneous mouse model. EBioMedicine. 2017;21:3–4.

    PubMed  Google Scholar 

  97. Harrison DE, Strong R, Sharp ZD, Nelson JF, Astle CM, Flurkey K, et al. Rapamycin fed late in life extends lifespan in genetically heterogeneous mice. Nature. 2009;460:392–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  98. Wilkinson JE, Burmeister L, Brooks SV, Chan C-C, Friedline S, Harrison DE, et al. Rapamycin slows aging in mice. Aging Cell. 2012;11:675–82.

    CAS  PubMed  Google Scholar 

  99. Harrison DE, Strong R, Allison DB, Ames BN, Astle CM, Atamna H, et al. Acarbose, 17-α-estradiol, and nordihydroguaiaretic acid extend mouse lifespan preferentially in males. Aging Cell. 2014;13:273–82.

    CAS  PubMed  Google Scholar 

  100. Harrison DE, Strong R, Alavez S, Astle CM, DiGiovanni J, Fernandez E, et al. Acarbose improves health and lifespan in aging HET3 mice. Aging Cell. 2019;18:e12898.

    PubMed  PubMed Central  Google Scholar 

  101. Reid JJ, Linden MA, Peelor FF, Miller RA, Hamilton KL, Miller BF. Brain protein synthesis rates in the UM-HET3 mouse following treatment with rapamycin or rapamycin with metformin. J Gerontol A Biol Sci Med Sci. 2020;75:40–49.

    CAS  PubMed  Google Scholar 

  102. Drake JC, Peelor FF, Biela LM, Watkins MK, Miller RA, Hamilton KL, et al. Assessment of mitochondrial biogenesis and mTORC1 signaling during chronic rapamycin feeding in male and female mice. J Gerontol A Biol Sci Med Sci. 2013;68:1493–501.

    CAS  PubMed  PubMed Central  Google Scholar 

  103. Sadagurski M, Cady G, Miller RA. Anti-aging drugs reduce hypothalamic inflammation in a sex-specific manner. Aging Cell. 2017;16:652–60.

    CAS  PubMed  PubMed Central  Google Scholar 

  104. Zaseck LW, Miller RA, Brooks SV. Rapamycin attenuates age-associated changes in tibialis anterior tendon viscoelastic properties. J Gerontol A Biol Sci Med Sci. 2016;71:858–65.

    CAS  PubMed  PubMed Central  Google Scholar 

  105. Altschuler RA, Kanicki A, Martin C, Kohrman DC, Miller RA. Rapamycin but not acarbose decreases age-related loss of outer hair cells in the mouse Cochlea. Hearing Res. 2018;370:11–15.

    CAS  Google Scholar 

  106. Stoyanov D, Telles-Correia D, Cuthbert BN. The Research Domain Criteria (RDoC) and the historical roots of psychopathology: a viewpoint. Eur Psychiatry. 2019;57:58–60.

    PubMed  Google Scholar 

  107. Mackay TF. The genetic architecture of quantitative traits. Annu Rev Genet. 2001;35:303–39.

    CAS  PubMed  Google Scholar 

  108. Zhou Z, Blandino P, Yuan Q, Shen P-H, Hodgkinson CA, Virkkunen M, et al. Exploratory locomotion, a predictor of addiction vulnerability, is oligogenic in rats selected for this phenotype. Proc Natl Acad Sci USA. 2019;116:13107–15.

    CAS  PubMed  PubMed Central  Google Scholar 

  109. Muller CL, Anacker AMJ, Veenstra-VanderWeele J. The serotonin system in autism spectrum disorder: From biomarker to animal models. Neuroscience. 2016;321:24–41.

    CAS  PubMed  Google Scholar 

  110. 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. 2019;101:399–411.e5.

    CAS  PubMed  Google Scholar 

  111. Taylor BA. Recombinant inbred strains: use in gene mapping. In: H. C. Morse iii, editor. Origins of inbred mice. NY; 1978. p 423–438.

  112. Peirce JL, Lu L, Gu J, Silver LM, Williams RW. A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet. 2004;5:7.

    PubMed  PubMed Central  Google Scholar 

  113. Ashbrook DG, Arends D, Prins P, Mulligan MK, Roy S, Williams EG, et al. The expanded BXD family of mice: a cohort for experimental systems genetics and precision medicine. Preprint at biorxiv 2019; https://doi.org/10.1101/672097.

  114. International HapMap Consortium, Daly MJ. The International HapMap Project. Nature. 2003;426:789–96.

    Google Scholar 

  115. Chintalapudi SR, Maria D, Di Wang X, Bailey JNC, NEIGHBORHOOD consortium, International Glaucoma Genetics consortium, et al. Systems genetics identifies a role for Cacna2d1 regulation in elevated intraocular pressure and glaucoma susceptibility. Nat Commun. 2017;8:1755.

    PubMed  PubMed Central  Google Scholar 

  116. Neuner SM, Garfinkel BP, Wilmott LA, Ignatowska-Jankowska BM, Citri A, Orly J, et al. Systems genetics identifies Hp1bp3 as a novel modulator of cognitive aging. Neurobiol Aging. 2016;46:58–67.

    CAS  PubMed  PubMed Central  Google Scholar 

  117. Philip VM, Duvvuru S, Gomero B, Ansah TA, Blaha CD, Cook MN, et al. High-throughput behavioral phenotyping in the expanded panel of BXD recombinant inbred strains. Genes, Brain Behav. 2010;9:129–59.

    CAS  Google Scholar 

  118. Neuner SM, Ding S, Kaczorowski CC. Knockdown of heterochromatin protein 1 binding protein 3 recapitulates phenotypic, cellular, and molecular features of aging. Aging Cell. 2019;18:e12886.

    PubMed  Google Scholar 

  119. Schain RJ, Freedman DX. Studies on 5-hydroxyindole metabolism in autistic and other mentally retarded children. J Pediatrics. 1961;58:315–20.

    CAS  Google Scholar 

  120. Piven J, Tsai GC, Nehme E, Coyle JT, Chase GA, Folstein SE. Platelet serotonin, a possible marker for familial autism. J Autism Dev Disord. 1991;21:51–59.

    CAS  PubMed  Google Scholar 

  121. Mulder EJ, Anderson GM, Kema IP, de Bildt A, van Lang ND, Boer den JA, et al. Platelet serotonin levels in pervasive developmental disorders and mental retardation: diagnostic group differences, within-group distribution, and behavioral correlates. J Am Acad Child Adolesc Psychiatry. 2004;43:491–9.

    PubMed  Google Scholar 

  122. Sutcliffe JS, Delahanty RJ, Prasad HC, McCauley JL, Han Q, Jiang L, et al. Allelic heterogeneity at the serotonin transporter locus (SLC6A4) confers susceptibility to autism and rigid-compulsive behaviors. Am J Hum Genet. 2005;77:265–79.

    CAS  PubMed  PubMed Central  Google Scholar 

  123. International Molecular Genetic Study of Autism Consortium (IMGSAC). A genomewide screen for autism: strong evidence for linkage to chromosomes 2q, 7q, and 16p. Am J Hum Genet. 2001;69:570–81.

    Google Scholar 

  124. Cantor RM, Kono N, Duvall JA, Alvarez-Retuerto A, Stone JL, Alarcón M, et al. Replication of autism linkage: fine-mapping peak at 17q21. Am J Hum Genet. 2005;76:1050–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  125. Carneiro AMD, Airey DC, Thompson B, Zhu C-B, Lu L, Chesler EJ, et al. Functional coding variation in recombinant inbred mouse lines reveals multiple serotonin transporter-associated phenotypes. Proc Natl Acad Sci USA. 2009;106:2047–52.

    CAS  PubMed  PubMed Central  Google Scholar 

  126. Ellegood J, Yee Y, Kerr TM, Muller CL, Blakely RD, Henkelman RM, et al. Analysis of neuroanatomical differences in mice with genetically modified serotonin transporters assessed by structural magnetic resonance imaging. Mol Autism. 2018;9:24.

    PubMed  PubMed Central  Google Scholar 

  127. Ye R, Carneiro AMD, Airey D, Bush ES, Williams RW, Lu L, et al. Evaluation of heritable determinants of blood and brain serotonin homeostasis using recombinant inbred mice. Genes, Brain Behav. 2014;13:247–60.

    CAS  Google Scholar 

  128. Veenstra-VanderWeele J, Muller CL, Iwamoto H, Sauer JE, Owens WA, Shah CR, et al. Autism gene variant causes hyperserotonemia, serotonin receptor hypersensitivity, social impairment and repetitive behavior. Proc Natl Acad Sci USA. 2012;109:5469–74.

    CAS  PubMed  PubMed Central  Google Scholar 

  129. Kerr TM, Muller CL, Miah M, Jetter CS, Pfeiffer R, Shah C, et al. Genetic background modulates phenotypes of serotonin transporter Ala56 knock-in mice. Molecular Autism 2013 4:1 2013; 4.

  130. Geschwind DH, Flint J. Genetics and genomics of psychiatric disease. Science. 2015;349:1489–94.

    CAS  PubMed  PubMed Central  Google Scholar 

  131. Holmans PA, Massey TH, Jones L. Genetic modifiers of Mendelian disease: Huntington’s disease and the trinucleotide repeat disorders. Hum Mol Genet. 2017;26:R83–90.

    CAS  PubMed  Google Scholar 

  132. Welter D, MacArthur J, Morales J, Burdett T, Hall P, Junkins H, et al. The NHGRI GWAS Catalog, a curated resource of SNP-trait associations. Nucleic Acids Res. 2014;42:D1001–6.

    CAS  PubMed  Google Scholar 

  133. Duncan LE, Ostacher M, Ballon J. How genome-wide association studies (GWAS) made traditional candidate gene studies obsolete. Neuropsychopharmacology. 2019;44:1518–23.

    PubMed  PubMed Central  Google Scholar 

  134. Colom-Lapetina J, Begley SL, Johnson ME, Bean KJ, Kuwamoto WN, Shansky RM. Strain-dependent sex differences in a long-term forced swim paradigm. Behav Neurosci. 2017;131:428–36.

    PubMed  Google Scholar 

  135. Graybeal C, Bachu M, Mozhui K, Saksida LM, Bussey TJ, Sagalyn E, et al. Strains and stressors: an analysis of touchscreen learning in genetically diverse mouse strains. PLoS One. 2014;9:e87745.

    PubMed  PubMed Central  Google Scholar 

  136. Manahan-Vaughan D, Schwegler H. Strain-dependent variations in spatial learning and in hippocampal synaptic plasticity in the dentate gyrus of freely behaving rats. Front Behav Neurosci. 2011;5 https://doi.org/10.3389/fnbeh.2011.00007.

  137. Turner KM, Simpson CG, Burne THJ. BALB/c Mice can learn touchscreen visual discrimination and reversal tasks faster than C57BL/6 Mice. Front Behav Neurosci. 2017;11:141.

    Google Scholar 

  138. Whitehouse CM, Curry-Pochy LS, Shafer R, Rudy J, Lewis MH. Reversal learning in C58 mice: Modeling higher order repetitive behavior. Behav Brain Res. 2017;332:372–8.

    PubMed  PubMed Central  Google Scholar 

  139. Kessler S, Elliott GR, Orenberg EK, Barchas JD. A genetic analysis of aggressive behavior in two strains of mice. Behav Genet 1977;7:313–21.

    CAS  PubMed  Google Scholar 

  140. Takahashi A, Sugimoto H, Kato S, Shiroishi T, Koide T. Mapping of genetic factors that elicit intermale aggressive behavior on mouse chromosome 15: intruder effects and the complex genetic basis. PLoS One. 2015;10:e0137764.

    PubMed  PubMed Central  Google Scholar 

  141. Keum S, Park J, Kim A, Park J, Kim KK, Jeong J, et al. Variability in empathic fear response among 11 inbred strains of mice. Genes Brain Behav. 2016;15:231–42

    CAS  PubMed  Google Scholar 

  142. Mitra S, Bastos CP, Chesworth S, Frye C, Bult-Ito A. Strain and sex based characterization of behavioral expressions in non-induced compulsive-like mice. Physiol Behav. 2017;168: 103–11.

    CAS  PubMed  Google Scholar 

  143. Podhorna J, Brown RE. Strain differences in activity and emotionality do not account for differences in learning and memory performance between C57BL/6 and DBA/2 mice. Genes Brain Behav. 2002;1:96–110.

    CAS  PubMed  Google Scholar 

  144. Carola V, Frazzetto G, Gross C. Identifying interactions between genes and early environment in the mouse. Genes Brain Behav. 2006;5:189–99.

    CAS  PubMed  Google Scholar 

  145. Chourbaji S, Hoyer C, Richter SH, Brandwein C, Pfeiffer N, Vogt MA, et al. Differences in mouse maternal care behavior – is there a genetic impact of the glucocorticoid receptor? PLoS One. 2011;6:e19218.

    CAS  PubMed  PubMed Central  Google Scholar 

  146. Mattapallil MJ, Wawrousek EF, Chan C-C, Zhao H, Roychoudhury J, Ferguson TA, et al. The Rd8 mutation of the Crb1 gene is present in vendor lines of C57BL/6N mice and embryonic stem cells, and confounds ocular induced mutant phenotypes. Invest Ophthalmol Vis Sci. 2012;53:2921–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  147. Mehalow AK, Kameya S, Smith RS, Hawes NL, Denegre JM, Young JA, et al. CRB1 is essential for external limiting membrane integrity and photoreceptor morphogenesis in the mammalian retina. Hum Mol Genet 2003;12:2179–89.

    CAS  PubMed  Google Scholar 

  148. Turner JG, Parrish JL, Hughes LF, Toth LA, Caspary DM. Hearing in laboratory animals: strain differences and nonauditory effects of noise. Comp Med 2005;55:12–23.

    CAS  PubMed  Google Scholar 

  149. Zheng QY, Johnson KR, Erway LC. Assessment of hearing in 80 inbred strains of mice by ABR threshold analyses. Hearing research 1999;130:94–107.

    CAS  PubMed  PubMed Central  Google Scholar 

  150. Crabbe JC, Schlumbohm JP, Hack W, Barkley-Levenson AM, Metten P, Lattal KM. Fear conditioning in mouse lines genetically selected for binge-like ethanol drinking. Alcohol 2016;52:25–32.

    CAS  PubMed  PubMed Central  Google Scholar 

  151. Dockstader CL, van der Kooy D. Mouse strain differences in opiate reward learning are explained by differences in anxiety, not reward or learning. J Neurosci. 2001;21:9077–81.

    CAS  PubMed  PubMed Central  Google Scholar 

  152. Holtz NA, Radke AK, Zlebnik NE, Harris AC, Carroll ME. Intracranial self-stimulation reward thresholds during morphine withdrawal in rats bred for high (HiS) and low (LoS) saccharin intake. Brain Res. 2015;1602:119–26.

    CAS  PubMed  PubMed Central  Google Scholar 

  153. Mulligan MK, Ponomarev I, Boehm SL, Owen JA, Levin PS, Berman AE, et al. Alcohol trait and transcriptional genomic analysis of C57BL/6 substrains. Genes Brain Behav. 2008;7:677–89.

    CAS  PubMed  Google Scholar 

  154. Surget A, Van Nieuwenhuijzen PS, Heinzmann J-M, Knapman A, McIlwrick S, Westphal W-P, et al. Antidepressant treatment differentially affects the phenotype of high and low stress reactive mice. Neuropharmacology 2016;110:37–47.

    CAS  PubMed  Google Scholar 

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Moore, S.J., Murphy, G.G. & Cazares, V.A. Turning strains into strengths for understanding psychiatric disorders. Mol Psychiatry 25, 3164–3177 (2020). https://doi.org/10.1038/s41380-020-0772-y

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