Stock Mice Research Articles

Genetic control of antibody production during collagen induced arthritis development in heterogeneous stock mice (171.44)

Abstract The aim of this study was to identify genetic factors driving pathogenic autoantibody formation in collagen induced arthritis (CIA), a mouse model for rheumatoid arthritis (RA) in order to understand the etiology of the disease and improve possibilities for therapeutic intervention. To this end we made a genome wide analysis of quantitative trait loci (QTL) controlling autoantibodies towards type II collagen (AC2A), anti-citrullinated protein antibodies (ACPA) and rheumatoid factors (RF). To identify loci controlling autoantibody production, we induced CIA in a heterogeneous stock (HS) derived mouse cohort. Serum samples of 1843 mice were collected before onset and at peak of the disease. All antibody concentrations were measured by ELISA and linkage analysis was performed using a linear regression based method. We identified loci controlling formation of AC2A of different IgG isotypes, antibodies to major type II collagen (CII) epitopes, to a citrullinated CII peptide and RF. The AC2A, ACPA and RF responses were all found to be controlled by distinct genes, one of the most important loci being the Immunoglobulin heavy chain (IgH) locus. Here, we provide a comprehensive genetic analysis of autoantibody formation in CIA. Our study demonstrates that not only AC2A, but interestingly also ACPA and RF are associated with arthritis development in mice. These results underscore the importance of non-MHC genes controlling the formation of clinically relevant autoantibodies.

Effects of a high maternal sodium intake on offspring of genetically diverse (CCHS) mice

The present study sought to determine whether a high maternal salt intake during pregnancy and lactation affected offspring blood pressure (BP), heart rate (HR), or locomotor activity in a genetically diverse stock of mice (Collaborative Cross Heterozygous Stock, CCHS). Dams were fed a low or high salt diet (0.25% NaCl (LS) vs 5% NaCl (HS)) from before conception through weaning, and telemetry studies were performed in 10 month old male offspring raised on either the LS or HS diet. A maternal HS diet was associated with significantly smaller litter sizes (P=0.03, data from groups of 34 and 37 litters), but offspring weight was not affected at any time between the day of birth (data from 22 and 24 litters) and 10 months of age (group sizes ≥ 11). Telemetry studies revealed no effects of maternal HS on mean BP or HR. However, maternal HS was associated with increased circadian variation in BP, increased percentage of time spent active during the 12h light period, and a tendency towards increased pulse pressure (P=0.03, 0.04, 0.06, respectively, group sizes of 8 – 14). Our results indicate that a maternal high salt diet does not affect offspring mean BP level in 10 month old male CCHS mice, but does reduce litter size and has subtle effects on activity and blood pressure cycles. Supported by the Canadian Institutes of Health Research (#91547).

A Bayesian Antedependence Model for Whole Genome Prediction

Hierarchical mixed effects models have been demonstrated to be powerful for predicting genomic merit of livestock and plants, on the basis of high-density single-nucleotide polymorphism (SNP) marker panels, and their use is being increasingly advocated for genomic predictions in human health. Two particularly popular approaches, labeled BayesA and BayesB, are based on specifying all SNP-associated effects to be independent of each other. BayesB extends BayesA by allowing a large proportion of SNP markers to be associated with null effects. We further extend these two models to specify SNP effects as being spatially correlated due to the chromosomally proximal effects of causal variants. These two models, that we respectively dub as ante-BayesA and ante-BayesB, are based on a first-order nonstationary antedependence specification between SNP effects. In a simulation study involving 20 replicate data sets, each analyzed at six different SNP marker densities with average LD levels ranging from r(2) = 0.15 to 0.31, the antedependence methods had significantly (P < 0.01) higher accuracies than their corresponding classical counterparts at higher LD levels (r(2) > 0. 24) with differences exceeding 3%. A cross-validation study was also conducted on the heterogeneous stock mice data resource (http://mus.well.ox.ac.uk/mouse/HS/) using 6-week body weights as the phenotype. The antedependence methods increased cross-validation prediction accuracies by up to 3.6% compared to their classical counterparts (P < 0.001). Finally, we applied our method to other benchmark data sets and demonstrated that the antedependence methods were more accurate than their classical counterparts for genomic predictions, even for individuals several generations beyond the training data.

Genetic influence of specific anticollagen antibody production in a mouse model of rheumatoid arthritis

Backgroundand objectivesRheumatoid arthritis (RA) is an autoimmune disease affecting about 1% of the population. Though of unknown aetiology, it is considered to have a strong genetic influence, resulting in the...

Identification of arthritis promoting non-obese diabetic genes in the Cia9 locus using different genetic strategies

BackgroundIn the gene segregation experiment between susceptible B10.Q and protective NOD.Q mice strains, two strong loci associated with collagen-induced arthritis (CIA) were found, disease-promoting locus on chromosome 1 named Cia9...

Genetic control of antibody production during collagen induced arthritis development in heterogeneous stock mice

ObjectivesThe genetic factors that drive pathogenic autoantibody formation in rheumatoid arthritis (RA) and its experimental models need to be elucidated in order to understand the aetiology of the disease and...

Genomic Mixing to Elucidate the Genetic System of Complex Traits

Understanding the genetic basis of complex traits has become one of the major issues in genetics, but recent advances in this field are still faced with a difficulty, the so-called "missing heritability." It is speculated that missing heritability mainly stems from a large number of variants of small effect that are poorly detected by currently available methods. In order to overcome this problem, many recent genetic studies of complex traits have actively used outbred stocks of mice. However, most of the available outbred stocks have a limited amount of genetic variation, because many stocks originate from Swiss mouse colonies. We have repeatedly shown that wild-derived strains are a useful mouse resource since there is a large genetic diversity among these strains. Here, we give an overview of mouse resources produced by crossing different founder mice. Finally, we propose an advantage of new attempts to conduct selective breeding using heterogeneous stocks created by mixing genomes of wild-derived inbred strains of mice when studying complex traits.

Experimental infection of three laboratory mouse stocks with a shrew origin Bartonella elizabethae strain: an evaluation of bacterial host switching potential

Background: Bartonella elizabethae has been reported as a causative agent of human illnesses and strains of this bacterium are commonly isolated from commensal small mammals in Asia.Methods: Since the zoonotic potential of a pathogen is often related to its host switching ability, we explored the capacity of a B. elizabethae strain to host switch by subcutaneously inoculating groups of Swiss Webster, BALB/c, and C57BL/6 mice with the bacteria at a range of doses.Results: A low number of mice in each of the three groups showed susceptibility to infection at high doses (105 and 106 bacteria), and developed bacteremias of 6–8 weeks duration.Conclusion: The capacity of this B. elizabethae strain to switch hosts can have important public health consequences for humans in areas of Asia where many small mammal populations have high bartonellae infection prevalences and live as commensals with humans.

A comparison of statistical methods for genomic selection in a mice population

BackgroundThe availability of high-density panels of SNP markers has opened new perspectives for marker-assisted selection strategies, such that genotypes for these markers are used to predict the genetic merit of selection candidates. Because the number of markers is often much larger than the number of phenotypes, marker effect estimation is not a trivial task. The objective of this research was to compare the predictive performance of ten different statistical methods employed in genomic selection, by analyzing data from a heterogeneous stock mice population.ResultsFor the five traits analyzed (W6W: weight at six weeks, WGS: growth slope, BL: body length, %CD8+: percentage of CD8+ cells, CD4+/ CD8+: ratio between CD4+ and CD8+ cells), within-family predictions were more accurate than across-family predictions, although this superiority in accuracy varied markedly across traits. For within-family prediction, two kernel methods, Reproducing Kernel Hilbert Spaces Regression (RKHS) and Support Vector Regression (SVR), were the most accurate for W6W, while a polygenic model also had comparable performance. A form of ridge regression assuming that all markers contribute to the additive variance (RR_GBLUP) figured among the most accurate for WGS and BL, while two variable selection methods ( LASSO and Random Forest, RF) had the greatest predictive abilities for %CD8+ and CD4+/ CD8+. RF, RKHS, SVR and RR_GBLUP outperformed the remainder methods in terms of bias and inflation of predictions.ConclusionsMethods with large conceptual differences reached very similar predictive abilities and a clear re-ranking of methods was observed in function of the trait analyzed. Variable selection methods were more accurate than the remainder in the case of %CD8+ and CD4+/CD8+ and these traits are likely to be influenced by a smaller number of QTL than the remainder. Judged by their overall performance across traits and computational requirements, RR_GBLUP, RKHS and SVR are particularly appealing for application in genomic selection.

A large scale genome simulation model incorporating patterns of linkage disequilibrium

Evaluation of multiple hypotheses is a common problem, especially in genome wide association studies. False Discovery Rate control is often used to correct for multiple comparisons. However, this approach is influenced by linkage disequilibrium and needs to be evaluated. For such evaluation, first a model needs to be developed with a simulated linkage disequilibrium pattern that matches as closely as possible the observed linkage disequilibrium structure. This paper outlines the steps involved in the development of such a model, using mouse genome data as an example. References http://gscan.well.ox.ac.uk/ K. G. Ardlie, L. Kruglyak, and M. Seielstad. Patterns of linkage disequilibrium in the human genome. Nature Reviews Genetics, 3(4):299--309, 2002. doi:10.1038/nrg777 J. C. Barrett, B. Fry, J. Maller, and M. J. Daly. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics, 21(2):263, 2005. doi:10.1093/bioinformatics/bth457 Y. Benjamini and Y. Hochberg. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), 57(1):289--300, 1995. http://www.jstor.org/pss/2346101 M. S. Khatkar, F. W. Nicholas, A. R. Collins, K. R. Zenger, J. A. L. Cavanagh, W. Barris, R. D. Schnabel, J. F. Taylor, and H. W. Raadsma. Extent of genome-wide linkage disequilibrium in Australian Holstein--Friesian cattle based on a high-density SNP panel. BMC genomics, 9(1):187, 2008. doi:10.1186/1471-2164-9-187 L. Kruglyak. Prospects for whole-genome linkage disequilibrium mapping of common disease genes. Nature genetics, 22:139--144, 1999. doi:10.1038/9642 C. C. Laurie, D. A. Nickerson, A. D. Anderson, B. S. Weir, R. J. Livingston, M. D. Dean, K. L. Smith, E. E. Schadt, and M. W. Nachman. Linkage disequilibrium in wild mice. PLoS Genetics, 3(8):e144, 2007. doi:10.1371/journal.pgen.0030144 W. Valdar, L. C. Solberg, D. Gauguier, S. Burnett, P. Klenerman, W. O. Cookson, M. S. Taylor, J. N. P. Rawlins, R. Mott, and J. Flint. Genome-wide genetic association of complex traits in heterogeneous stock mice. Nature genetics, 38(8):879--887, 2006. doi:10.1038/ng1840

Abstract B10: Diversity Outbred: A new, highly diverse mouse stock for toxicology and cancer.

Abstract The Diversity Outbred (J:DO) stock is a new heterogeneous, highly diverse mouse resource designed for complex trait analysis and toxicology studies as well as to facilitate rapid mapping with single gene resolution. This stock was derived from crossing partially-inbred Collaborative Cross strains, which are a mixture of eight genetically well-defined JAX® Mice inbred strains, including three wild-derived. Subsequent maintenance follows a randomized outcross non-sibling mating scheme to retain maximum genetic diversity. Each Diversity Outbred mouse is genetically unique, representing a novel combination of alleles present in the founder strains. To determine the extent to which this genetic variation leads to phenotypic variation, over 50 metabolic measurements including plasma glucose, insulin, triglycerides, cholesterol, and body composition were collected, under both standard chow and high fat diet conditions. The Diversity Outbred animals displayed a wide spectrum of metabolic phenotypes, home cage nesting behavior and aggressiveness. Mouse-to-mouse variation is demonstrated by fold-differences in plasma triglycerides and creatine kinase levels, both as high as 11–12. Plasma glucose, free fatty acids, thyroxine, and percentage of fat all showed differences of 3-fold or greater. These fold-changes are comparable to the variation among unique inbred mouse strains, and mimic the diversity within human populations. The J:DO stock represents a new powerful tool for rapid gene mapping, toxicology/pharmacogenomic screens and compound evaluation for a wide variety of human diseases, including cancer and metabolic diseases. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr B10.

Genome‐wide and species‐wide dissection of the genetics of arthritis severity in heterogeneous stock mice

Susceptibility to inflammatory arthritis is determined by a complex set of environmental and genetic factors, but only a portion of the genetic effect can be explained. Conventional genome-wide screens of arthritis models using crosses between inbred mice have been hampered by the low resolution of results and by the restricted range of natural genetic variation sampled. The aim of this study was to address these limitations by performing a genome-wide screen for determinants of arthritis severity using a genetically heterogeneous cohort of mice. Heterogeneous stock (HS) mice derive from 8 founder inbred strains by serial intercrossing (n>60), resulting in fine-grained genetic variation. With a cohort of 570 HS mice, we performed a genome-wide screen for determinants of arthritis severity in the K/BxN serum-transfer model. We mapped regions on chromosomes 1, 2, 4, 6, 7, and 15 that contain quantitative trait loci influencing arthritis severity at a resolution of a few megabases. In several instances, these regions proved to contain 2 quantitative trait loci: the region on chromosome 2 included the C5 fraction of complement known to be required for K/BxN serum-transfer arthritis but also contained a second adjacent quantitative trait locus, for which an intriguing candidate is Ptgs1 (Cox1). Interesting candidates on chromosome 4 included the Padi family, encoding the peptidyl arginine deiminases responsible for citrulline protein modification; suggestively, Padi2 and Padi4 RNA expression was correlated with arthritis severity in HS mice. These results provide a broad overview of the genetic variation that controls the severity of K/BxN serum-transfer arthritis and suggest intriguing candidate genes for further study.

Prioritization and Association Analysis of Murine-Derived Candidate Genes in Anxiety-Spectrum Disorders

Anxiety disorders are common psychiatric conditions that are highly comorbid with each other and related phenotypes such as depression, likely due to a shared genetic basis. Fear-related behaviors in mice have long been investigated as potential models of anxiety disorders, making integration of information from both murine and human genetic data a powerful strategy for identifying potential susceptibility genes for these conditions. We combined genome-wide association analysis of fear-related behaviors with strain distribution pattern analysis in heterogeneous stock mice to identify a preliminary list of 52 novel candidate genes. We ranked these according to three complementary sources of prior anxiety-related genetic data: 1) extant linkage and knockout studies in mice, 2) a meta-analysis of human linkage scans, and 3) a preliminary human genome-wide association study. We genotyped tagging single nucleotide polymorphisms covering the nine top-ranked regions in a two-stage association study of 1316 subjects from the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders chosen for high or low genetic loading for anxiety-spectrum phenotypes (anxiety disorders, neuroticism, and major depression). Multiple single nucleotide polymorphisms in the PPARGC1A gene demonstrated association in both stages that survived gene-wise correction for multiple testing. Integration of genetic data across human and murine studies suggests PPARGC1A as a potential susceptibility gene for anxiety-related disorders.

Methods to Assess Beta Cell Death Mediated by Cytotoxic T Lymphocytes

Type 1 diabetes (T1D) is a T cell mediated autoimmune disease. During the pathogenesis, patients become progressively more insulinopenic as insulin production is lost, presumably this results from the destruction of pancreatic beta cells by T cells. Understanding the mechanisms of beta cell death during the development of T1D will provide insights to generate an effective cure for this disease. Cell-mediated lymphocytotoxicity (CML) assays have historically used the radionuclide Chromium 51 ((51)Cr) to label target cells. These targets are then exposed to effector cells and the release of (51)Cr from target cells is read as an indication of lymphocyte-mediated cell death. Inhibitors of cell death result in decreased release of (51)Cr. As effector cells, we used an activated autoreactive clonal population of CD8(+) Cytotoxic T lymphocytes (CTL) isolated from a mouse stock transgenic for both the alpha and beta chains of the AI4 T cell receptor (TCR). Activated AI4 T cells were co-cultured with (51)Cr labeled target NIT cells for 16 hours, release of (51)Cr was recorded to calculate specific lysis Mitochondria participate in many important physiological events, such as energy production, regulation of signaling transduction, and apoptosis. The study of beta cell mitochondrial functional changes during the development of T1D is a novel area of research. Using the mitochondrial membrane potential dye Tetramethyl Rhodamine Methyl Ester (TMRM) and confocal microscopic live cell imaging, we monitored mitochondrial membrane potential over time in the beta cell line NIT-1. For imaging studies, effector AI4 T cells were labeled with the fluorescent nuclear staining dye Picogreen. NIT-1 cells and T cells were co-cultured in chambered coverglass and mounted on the microscope stage equipped with a live cell chamber, controlled at 37°C, with 5% CO(2;), and humidified. During these experiments images were taken of each cluster every 3 minutes for 400 minutes. Over a course of 400 minutes, we observed the dissipation of mitochondrial membrane potential in NIT-1 cell clusters where AI4 T cells were attached. In the simultaneous control experiment where NIT-1 cells were co-cultured with MHC mis-matched human lymphocyte Jurkat cells, mitochondrial membrane potential remained intact. This technique can be used to observe real-time changes in mitochondrial membrane potential in cells under attack of cytotoxic lymphocytes, cytokines, or other cytotoxic reagents.

Variation in stress reactivity affects cage-induced stereotypies in female CD-1 (ICR) mice

Stereotypies in captive animals typically occur under conditions that are stressful for the animals, and there is some anecdotal evidence that stress levels during early stereotypy development predict later stereotypy levels. Based on this and on the involvement of stress in the behavioural sensitization to psychostimulant drugs, it has been hypothesized that stereotypy development might be causally related to stress. To address this question further, we used mice of the commercial outbred stock CD-1 (ICR) and mice of two lines derived from the outbred CD-1 (ICR) strain by selective breeding for high (HR) and low (LR) stress reactivity, respectively, and examined whether genetically driven variation in stress reactivity is associated with variation in the expression of cage-induced stereotypies. From 21 days of age, 10 females of each line were housed in pairs under standard laboratory conditions until they were video recorded for stereotypic behaviour and tested for corticosterone responses in a stress reactivity test (SRT) at 12 weeks of age. As expected, HR females showed a significantly stronger corticosterone response in the SRT than LR females, while ICR females were intermediate. Unexpectedly, however, both HR and LR females showed very low levels of stereotypic behaviour, while ICR females developed the high levels of stereotypies typical for this strain of mouse. Consequently, there was no significant relationship between measures of acute corticosterone reactivity and stereotypy performance, but a trend for reduced recovery of the corticosterone response in the ICR line suggests that variation in recovery rather than the acute response might predict stereotypy levels in these mice.

High-resolution mapping of a complex disease, a model for rheumatoid arthritis, using heterogeneous stock mice

Resolving the genetic basis of complex diseases like rheumatoid arthritis will require knowledge of the corresponding diseases in experimental animals to enable translational functional studies. Mapping of quantitative trait loci in mouse models of arthritis, such as collagen-induced arthritis (CIA), using F(2) crosses has been successful, but can resolve loci only to large chromosomal regions. Using an inbred-outbred cross design, we identified and fine-mapped CIA loci on a genome-wide scale. Heterogeneous stock mice were first intercrossed with an inbred strain, B10.Q, to introduce an arthritis permitting MHCII haplotype. Homozygous H2(q) mice were then selected to set up an F(3) generation with fixed major histocompatibility complex that was used for arthritis experiments. We identified 26 loci, 18 of which are novel, controlling arthritis traits such as incidence of disease, severity and time of onset and fine-mapped a number of previously mapped loci.

Abstract 4303: The Jackson Laboratory Repository: resource for mouse strains modeling cancer

Abstract The Jackson Laboratory Repository is an established resource for the importation, cryopreservation, development, and distribution of mouse strains vital to biomedical research. More than 500 new strains are added annually to the approximately 5,000 strains and stocks of mice currently held in the Repository collection. Newly acquired or developed strains include a model of malignant melanoma and metastasis; a xenotransplant model that provides continuous circulation of human growth factors; a targeted mutation strain for studying myeloproliferative diseases such as chronic myelomonocytic leukemia and Chronic Familial Myelocytic Leukemia-Like Syndrome; and a knock-in strain that mimics the t(9;11)(p22;q23) translocation identified in acute myeloid leukemia. Also under development are a transgenic/targeted mutation strain with increased mammary gland tumor incidence and three targeted mutation strains with increased sensitivity to carcinogens or radiation. The Repository's inducible and conditional mutation mouse strains allow researchers to generate temporal and/or tissue-specific tools for modeling human cancer. New additions to the Repository collection include strains with Cre recombinase expression specific to the colon and rectum, as well as a transgenic strain that can be used as part of a bitransgenic system utilizing the tetracycline-inducible expression of a gene of interest in blood vessel endothelial cells. For non-invasive in-vivo imaging studies, the Repository distributes a xenograft/transplant host with widespread expression of firefly luciferase and enhanced green fluorescence protein. The Repository maintains a searchable on-line resource (www.jax.org) for each strain. Researchers can submit their strains to be considered for inclusion in the Repository by using the on-line form available at The Jackson Laboratory website: http://www.jax.org/grc/index.html. The Jackson Laboratory Repository is supported by the NCRR, The Howard Hughes Medical Institute, The Ellison Medical Foundation and donations from private charitable foundations. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4303. doi:10.1158/1538-7445.AM2011-4303

Abstract 4387: Diversity Outbred: a new, highly diverse mouse stock for toxicology and cancer

Abstract The Diversity Outbred (J:DO) stock is a new heterogeneous, highly diverse mouse resource designed for complex trait analysis and toxicology studies as well as to facilitate rapid mapping with single gene resolution. This stock was derived from crossing partially-inbred Collaborative Cross strains, which are a mixture of eight genetically well-defined JAX® Mice inbred strains, including three wild-derived. Subsequent maintenance follows a randomized outcross non-sibling mating scheme to retain maximum genetic diversity. Each Diversity Outbred mouse is genetically unique, representing a novel combination of alleles present in the founder strains. To determine the extent to which this genetic variation leads to phenotypic variation, over 50 metabolic measurements including plasma glucose, insulin, triglycerides, cholesterol, and body composition were collected, under both standard chow and high fat diet conditions. The Diversity Outbred animals displayed a wide spectrum of metabolic phenotypes, home cage nesting behavior and aggressiveness. Mouse-to-mouse variation is demonstrated by fold-differences in plasma triglycerides and creatine kinase levels, both as high as 11-12. Plasma glucose, free fatty acids, thyroxine, and percentage of fat all showed differences of 3-fold or greater. These fold-changes are comparable to the variation among unique inbred mouse strains, and mimic the diversity within human populations. The J:DO stock represents a new powerful tool for rapid gene mapping, toxicology/pharmacogenomic screens and compound evaluation for a wide variety of human diseases, including cancer and metabolic diseases. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4387. doi:10.1158/1538-7445.AM2011-4387

A genetic and functional relationship between T cells and cellular proliferation in the adult hippocampus.

Author SummaryIn adult mice new neurons are produced in the hippocampus, where they are thought to influence learning, memory, and emotional regulation. The mechanisms and functions of this neurogenesis, however, remain unclear. Here we report that in different strains of mice, variation in cellular proliferation in the hippocampus (an index of neurogenesis) correlates with variation in the relative proportions of the ratio of CD4+ to CD8+ T cells (an immunology phenotype). We also show that T cells can influence neurogenesis (but that neurogenesis does not influence T cells) by analyzing knockouts, depleting mice of T cells, and repopulating alymphoid animals. The strong genetic correlation between T cells and cellular proliferation in the hippocampus contrasts with the weak, often non-significant, correlation with behavioral phenotypes. Of significance, the findings here suggest that modulation of the functions of the hippocampus to influence behavior is not the primary role of neurogenesis.

The Retinoic Acid Receptor Beta (Rarb) Region of Mmu14 Is Associated with Prion Disease Incubation Time in Mouse

In neurodegenerative conditions such as Alzheimer's and prion disease it has been shown that host genetic background can have a significant effect on susceptibility. Indeed, human genome-wide association studies (GWAS) have implicated several candidate genes. Understanding such genetic susceptibility is relevant to risks of developing variant CJD (vCJD) in populations exposed to bovine spongiform encephalopathy (BSE) and understanding mechanisms of neurodegeneration. In mice, aspects of prion disease susceptibility can be modelled by examining the incubation period following experimental inoculation. Quantitative trait linkage studies have already identified multiple candidate genes; however, it is also possible to take an individual candidate gene approach. Rarb and Stmn2 were selected as candidates based on the known association with vCJD. Because of the increasing overlap described between prion and Alzheimer's diseases we also chose Clu, Picalm and Cr1, which were identified as part of Alzheimer's disease GWAS. Clusterin (Clu) was considered to be of particular interest as it has already been implicated in prion disease. Approximately 1,000 heterogeneous stock (HS) mice were inoculated intra-cerebrally with Chandler/RML prions and incubation times were recorded. Candidate genes were evaluated by sequencing the whole transcript including exon-intron boundaries and potential promoters in the parental lines of the HS mice. Representative SNPs were genotyped in the HS mice. No SNPs were identified in Cr1 and no statistical association with incubation time was seen for Clu (P = 0.96) and Picalm (P = 0.91). Significant associations were seen for both Stmn2 (P = 0.04) and Rarb (P = 0.0005), however, this was only highly significant for Rarb. This data provides significant further support for a role for the Rarb region of Mmu14 and Stmn2 in prion disease.