Genes: APP, PSEN1
Mutations: APP KM670/671NL (Swedish), APP I716V (Florida), APP V717I (London), PSEN1 M146L (A>C), PSEN1 L286V
Modification: APP: Transgenic; PSEN1: Transgenic
Disease Relevance: Alzheimer's Disease
Strain Name: (B6.Cg-Tg(APPSwFlLon,PSEN1*M146L*L286V)6799Vas/Mmjax x BXD[strain number]
Genetic Background: C57BL/6J X BXD[strain number]
Availability: Individual AD-BXD strains are available as F1 hybrids from The Jackson Laboratory (each strain has its own stock number).
“AD-BXD” refers to a panel of transgenic mouse strains, created to model the genetic diversity seen in human populations. These mice represent a unique resource for scientists seeking to identify genetic factors that influence resilience or vulnerability to AD, examining the interactions between genetic and environment factors, or wishing to conduct preclinical studies in an animal population that incorporates genetic heterogeneity that better reflects human populations.
AD-BXD mice were generated by crossing female 5XFAD mice to male members of the BXD genetic reference panel (Neuner et al., 2019). 5XFAD mice carry human APP and PSEN1 transgenes with a total of five mutations linked to AD; the 5XFAD females used for these crosses were hemizygous for the transgenes on an inbred C57BL/6J background. The BXD genetic reference panel is a set of recombinant inbred mouse strains derived from crossing two inbred strains—C57BL/6J and DBA/2J—that differ at approximately 5 million sites in their genomes (Peirce et al., 2004; Wang et al., 2016). In all, 27 distinct, reproducible F1 AD-BXD strains were created. Within each strain, approximately half of the mice will carry the APP and PSEN1 transgenes and half will not, but the mice are otherwise genetically identical. Overall, there is substantial genetic diversity between strains.
Expression of the APP and PSEN1 transgenes did not vary between AD-BXD strains, nor did the expression of endogenous mouse App or Psen1. However, levels of Aβ42 and the amount of amyloid plaque pathology were strain-dependent. Cognitive function, measured using a contextual fear-conditioning test, also varied between strains, although cognitive impairment did not correlate with amyloid pathology. Age of onset of cognitive impairment—the age at which carriers of the APP and PSEN1 transgenes differed in performance from their non-transgenic littermates—varied between strains; in the AD-BXD population as a whole, transgenic mice were cognitively normal at 6 months, but impaired at 14 months.
The nucleotide sequences of several genes reported to be associated with the risk of sporadic, late-onset AD (LOAD) differ somewhat between C57BL/6J and DBA/2J mice. When a genetic risk score was assigned to each AD-BXD strain, based on polymorphisms in 21 LOAD-associated genes, this score was found to correlate with cognitive function in 14-month-old transgenic AD-BXD mice, but not their non-transgenic littermates. This suggests that some of the same genetic mechanisms modulating AD risk in human populations also regulate susceptibility to cognitive decline in the AD-BXDs.
Balance, coordination, vestibular function, and muscle strength vary across strains (O’Connell et al., 2019). Both transgenic and non-transgenic mice show age-related deterioration of sensorimotor function, but the presence of the transgenes exacerbates this decline.
Sex did not affect transgene expression or amyloid pathology in the AD-BXD population (Neuner et al., 2019), in contrast to greater APP expression in 5XFAD females on a B6SJL background (Sadleir et al., 2015; Sadleir et al., 2018). However, in the AD-BXD population as a whole, females showed greater transgene-related impairments of motor function compared with males (O’Connell et al., 2019).
Transcriptomic analyses revealed that the presence of the APP and PSEN1 transgenes altered the expression of the mouse homologues of several genes associated with LOAD risk in humans—including Bin1, Clu, Cd33, Trem2, and C1qa—and that the expression of these genes varied between AD-BXD strains (Neuner et al., 2019). More broadly, genes related to neuronal activity, structure, and function were downregulated in transgenic mice, while genes related to immune responses were upregulated. There was significant overlap between genes upregulated in the brains of 14-month AD-BXD mice and upregulated genes associated with AD in lists generated using samples from the Harvard Brain Tissue Resource Center (Zhang et al., 2013) and the International Genomics of Alzheimer’s Project (IGAP, 2015).
The AD-BXD panel is being used to identify transcriptional networks that confer resilience to AD-related cognitive decline (Neuner et al., 2019). Networks have been identified in 6-month mice that predicted cognitive decline at 14 months; these networks are related to neuroinflammation, cerebral vasculature, extracellular matrix organization, and synaptic communication.
5XFAD transgenic mice were made by co-injecting two vectors encoding APP (with Swedish [K670N/M671L], Florida [I716V], and London [V717I] mutations) and PSEN1 (with M146L and L286V mutations), each driven by the mouse Thy1 promoter. The transgenes inserted at a single locus, Chr3:6297836 (Build GRCm38/mm10), where they did not affect any known genes (Goodwin et al., 2019). Mice on the original hybrid B6SJL background were backcrossed to C57BL/6J mice using a speed congenic approach.
When visualized, these models will distributed over a 18 month timeline demarcated at the following intervals: 1mo, 3mo, 6mo, 9mo, 12mo, 15mo, 18mo+.
- Neuronal Loss
- Synaptic Loss
- Changes in LTP/LTD
Transgenic AD-BXD mice develop amyloid plaques by 6 months of age, the earliest age examined. The extent of plaque deposition is strain-dependent.
Strain-dependent gliosis by 6 months.
Changes in LTP/LTD
In the AD-BXD population as a whole, transgenic mice performed similarly to non-transgenic littermates in a contextual fear-conditioning test at 6 months, but were impaired at 14 months. The age of onset and severity of impairment are strain-dependent.
Last Updated: 20 Sep 2019
Research Models Citations
- Neuner SM, Heuer SE, Huentelman MJ, O'Connell KM, Kaczorowski CC. Harnessing Genetic Complexity to Enhance Translatability of Alzheimer's Disease Mouse Models: A Path toward Precision Medicine. Neuron. 2019 Feb 6;101(3):399-411.e5. Epub 2018 Dec 27 PubMed.
- 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 Apr 29;5:7. PubMed.
- Wang X, Pandey AK, Mulligan MK, Williams EG, Mozhui K, Li Z, Jovaisaite V, Quarles LD, Xiao Z, Huang J, Capra JA, Chen Z, Taylor WL, Bastarache L, Niu X, Pollard KS, Ciobanu DC, Reznik AO, Tishkov AV, Zhulin IB, Peng J, Nelson SF, Denny JC, Auwerx J, Lu L, Williams RW. Joint mouse-human phenome-wide association to test gene function and disease risk. Nat Commun. 2016 Feb 2;7:10464. PubMed.
- O'Connell KM, Ouellette AR, Neuner SM, Dunn AR, Kaczorowski CC. Genetic background modifies CNS-mediated sensorimotor decline in the AD-BXD mouse model of genetic diversity in Alzheimer's disease. Genes Brain Behav. 2019 Nov;18(8):e12603. Epub 2019 Aug 19 PubMed.
- Sadleir KR, Eimer WA, Cole SL, Vassar R. Aβ reduction in BACE1 heterozygous null 5XFAD mice is associated with transgenic APP level. Mol Neurodegener. 2015 Jan 7;10:1. PubMed.
- Sadleir KR, Popovic J, Vassar R. ER stress is not elevated in the 5XFAD mouse model of Alzheimer's disease. J Biol Chem. 2018 Nov 30;293(48):18434-18443. Epub 2018 Oct 12 PubMed.
- Zhang B, Gaiteri C, Bodea LG, Wang Z, McElwee J, Podtelezhnikov AA, Zhang C, Xie T, Tran L, Dobrin R, Fluder E, Clurman B, Melquist S, Narayanan M, Suver C, Shah H, Mahajan M, Gillis T, Mysore J, MacDonald ME, Lamb JR, Bennett DA, Molony C, Stone DJ, Gudnason V, Myers AJ, Schadt EE, Neumann H, Zhu J, Emilsson V. Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimer's disease. Cell. 2013 Apr 25;153(3):707-20. PubMed.
- International Genomics of Alzheimer's Disease Consortium (IGAP). Convergent genetic and expression data implicate immunity in Alzheimer's disease. Alzheimers Dement. 2015 Jun;11(6):658-71. Epub 2014 Dec 20 PubMed.
- Neuner SM, Heuer SE, Zhang JG, Philip VM, Kaczorowski CC. Identification of Pre-symptomatic Gene Signatures That Predict Resilience to Cognitive Decline in the Genetically Diverse AD-BXD Model. Front Genet. 2019;10:35. Epub 2019 Feb 6 PubMed.
- Goodwin LO, Splinter E, Davis TL, Urban R, He H, Braun RE, Chesler EJ, Kumar V, van Min M, Ndukum J, Philip VM, Reinholdt LG, Svenson K, White JK, Sasner M, Lutz C, Murray SA. Large-scale discovery of mouse transgenic integration sites reveals frequent structural variation and insertional mutagenesis. Genome Res. 2019 Mar;29(3):494-505. Epub 2019 Jan 18 PubMed.
- Dunn AR, O'Connell KM, Kaczorowski CC. Gene-by-environment interactions in Alzheimer's disease and Parkinson's disease. Neurosci Biobehav Rev. 2019 Aug;103:73-80. Epub 2019 Jun 14 PubMed.
- Raw data characterizing the phenotypes of the AD-BXD panel can be found at the AMP-AD Knowledge Portal
- RNA-Seq data from the hippocampi of a subset of AD-BXD strains is available on Gene Expression Omnibus (GEO)
- RNA-Seq data from Neuner et al., 2019 is available on Gene Expression Omnibus (GEO)
- Genetic information and phenotyping data for the BXD panel