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Research experience
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Jan 2011–
Dec 2012Research: Karolinska Institutet
Karolinska Institutet · Institutionen för medicinsk biokemi och biofysikSweden · Solna -
Jan 2006–
Apr 2010Research: Wellcome Trust Center for Human Genetics
Wellcome TrustUnited Kingdom · Oxford -
Jan 2001–
Dec 2011Research: Lund University
Lund University · Department of Experimental Medical ScienceSweden · Lund
Publications (27) View all
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Article: Genetic control of antibody production during collagen induced arthritis development in heterogeneous stock mice.
Michael Förster, Bruno Raposo, Diana Ekman, Dorota Klaczkowska, Marjan Popovic, Kutty S Nandakumar, Therese Lindvall, Malin Hultqvist, Ivanka Teneva, Martina Johannesson, Emma Ahlqvist, Rikard Holmdahl[show abstract] [hide abstract]
ABSTRACT: OBJECTIVE: 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). METHODS: To identify loci controlling autoantibody production, we induced CIA in a heterogeneous stock (HS) derived mouse cohort, with contribution of 8 inbred mouse strains backcrossed to C57BL/10.Q (BQ). Serum samples of 1640 mice were collected before onset and at peak of the disease. Antibody concentrations were measured by standard ELISA and linkage analysis was performed using a linear regression based method. RESULTS: We identified loci controlling formation of AC2A of different IgG isotypes (IgG1, IgG3), antibodies to major type II collagen (CII) epitopes (C1, J1, U1), to a citrullinated CII peptide (CitC1) 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. CONCLUSION: 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. © 2012 American College of Rheumatology.Arthritis & Rheumatism 08/2012; · 7.87 Impact Factor -
SourceAvailable from: Martina Johannesson
Article: Effects of environmental and physiological covariates on sex differences in unconditioned and conditioned anxiety and fear in a large sample of genetically heterogeneous (N/Nih-HS) rats.
Regina López-Aumatell, Esther Martínez-Membrives, Elia Vicens-Costa, Toni Cañete, Gloria Blázquez, Carme Mont-Cardona, Martina Johannesson, Jonathan Flint, Adolf Tobeña, Alberto Fernández-Teruel[show abstract] [hide abstract]
ABSTRACT: Physiological and environmental variables, or covariates, can account for an important portion of the variability observed in behavioural/physiological results from different laboratories even when using the same type of animals and phenotyping procedures. We present the results of a behavioural study with a sample of 1456 genetically heterogeneous N/Nih-HS rats, including males and females, which are part of a larger genome-wide fine-mapping QTL (Quantitative Trait Loci) study. N/Nih-HS rats have been derived from 8 inbred strains and provide very small distance between genetic recombinations, which makes them a unique tool for fine-mapping QTL studies. The behavioural test battery comprised the elevated zero-maze test for anxiety, novel-cage (open-field like) activity, two-way active avoidance acquisition (related to conditioned anxiety) and context-conditioned freezing (i.e. classically conditioned fear). Using factorial analyses of variance (ANOVAs) we aimed to analyse sex differences in anxiety and fear in this N/Nih-HS rat sample, as well as to assess the effects of (and interactions with) other independent factors, such as batch, season, coat colour and experimenter. Body weight was taken as a quantitative covariate and analysed by covariance analysis (ANCOVA). Obliquely-rotated factor analyses were also performed separately for each sex, in order to evaluate associations among the most relevant variables from each behavioural test and the common dimensions (i.e. factors) underlying the different behavioural responses. ANOVA analyses showed a consistent pattern of sex effects, with females showing less signs of anxiety and fear than males across all tests. There were also significant main effects of batch, season, colour and experimenter on almost all behavioural variables, as well as "sex × batch", "sex × season" and "sex × experimenter" interactions. Body weight showed significant effects in the ANCOVAs of most behavioural measures, but sex effects were still present in spite of (and after controlling for) these "body weight" effects. Factor analyses of relevant variables from each test showed a two-fold factor structure in both sexes, with the first factor mainly representing anxiety and conditioned fear in males, while in females the first factor was dominated by loadings of activity measures. Thus, besides showing consistent sex differences in anxiety-, fear- and activity-related responses in N/Nih-HS rats, the present study shows that females' behaviour is predominantly influenced by activity while males are more influenced by anxiety. Moreover, the results point out that, besides "sex" effects, physiological variables such as colour and body weight, and environmental factors as batch/season or "experimenter", have to be taken into account in both behavioural and quantitative genetic studies because of their demonstrated influences on phenotypic outcomes.Behavioral and Brain Functions 11/2011; 7:48. · 2.13 Impact Factor -
SourceAvailable from: Martina Johannesson
Article: High-resolution mapping of a complex disease, a model for rheumatoid arthritis, using heterogeneous stock mice.
Emma Ahlqvist, Diana Ekman, Therese Lindvall, Marjan Popovic, Michael Förster, Malin Hultqvist, Dorota Klaczkowska, Ivanka Teneva, Martina Johannesson, Jonathan Flint, William Valdar, Kutty Selva Nandakumar, Rikard Holmdahl[show abstract] [hide abstract]
ABSTRACT: 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.Human Molecular Genetics 05/2011; 20(15):3031-41. · 7.64 Impact Factor -
SourceAvailable from: Sira Díaz-Morán
Article: Heterogeneous stock rat: a unique animal model for mapping genes influencing bone fragility.
Imranul Alam, Daniel L Koller, Qiwei Sun, Ryan K Roeder, Toni Cañete, Gloria Blázquez, Regina López-Aumatell, Esther Martínez-Membrives, Elia Vicens-Costa, Carme Mont, [......], Adolf Tobeña, Alberto Fernández-Teruel, Adam Whitley, Pernilla Strid, Margarita Diez, Martina Johannesson, Jonathan Flint, Michael J Econs, Charles H Turner, Tatiana Foroud[show abstract] [hide abstract]
ABSTRACT: Previously, we demonstrated that skeletal mass, structure and biomechanical properties vary considerably among 11 different inbred rat strains. Subsequently, we performed quantitative trait loci (QTL) analysis in four inbred rat strains (F344, LEW, COP and DA) for different bone phenotypes and identified several candidate genes influencing various bone traits. The standard approach to narrowing QTL intervals down to a few candidate genes typically employs the generation of congenic lines, which is time consuming and often not successful. A potential alternative approach is to use a highly genetically informative animal model resource capable of delivering very high resolution gene mapping such as Heterogeneous stock (HS) rat. HS rat was derived from eight inbred progenitors: ACI/N, BN/SsN, BUF/N, F344/N, M520/N, MR/N, WKY/N and WN/N. The genetic recombination pattern generated across 50 generations in these rats has been shown to deliver ultra-high even gene-level resolution for complex genetic studies. The purpose of this study is to investigate the usefulness of the HS rat model for fine mapping and identification of genes underlying bone fragility phenotypes. We compared bone geometry, density and strength phenotypes at multiple skeletal sites in HS rats with those obtained from five of the eight progenitor inbred strains. In addition, we estimated the heritability for different bone phenotypes in these rats and employed principal component analysis to explore relationships among bone phenotypes in the HS rats. Our study demonstrates that significant variability exists for different skeletal phenotypes in HS rats compared with their inbred progenitors. In addition, we estimated high heritability for several bone phenotypes and biologically interpretable factors explaining significant overall variability, suggesting that the HS rat model could be a unique genetic resource for rapid and efficient discovery of the genetic determinants of bone fragility.Bone 02/2011; 48(5):1169-77. · 4.02 Impact Factor -
Article: Unlearned anxiety predicts learned fear: a comparison among heterogeneous rats and the Roman rat strains.
Regina López-Aumatell, Elia Vicens-Costa, Marc Guitart-Masip, Esther Martínez-Membrives, William Valdar, Martina Johannesson, Toni Cañete, Gloria Blázquez, Peter Driscoll, Jonathan Flint, Adolf Tobeña, Alberto Fernández-Teruel[show abstract] [hide abstract]
ABSTRACT: Anxiety-related behaviors were evaluated across five tests in a sample of 277 rats from a genetically heterogeneous stock (N/Nih-HS rats), derived from an eight-way cross of inbred strains, and compared with the performance of RLA-I (high anxious) and RHA-I (low anxious) rats in the same tests. These tests either evoke unlearned (novel-cage activity (NACT), elevated "zero" maze (ZM), baseline acoustic startle response (BAS)) or learned (fear-potentiated startle (FPS), two-way active-shuttle box-avoidance acquisition (SHAV)) anxious/fearful responses. The results overall showed that unlearned anxiety responses/behaviors were predictive of behavior in learned fear (i.e. fear-potentiated startle) and conflict (i.e. two-way active avoidance acquisition) situations. Moreover, it was found that N/Nih-HS rats either resemble RLA-I rat anxiety/fear scores or fall in between those of the RLA-I (high anxious) and the RHA-I (low anxious) rat strains. An additional regression analysis (of N/Nih-HS rat data) showed significant positive influences of (unlearned) baseline startle response, risk assessment (i.e. stretch-attend) behavior and activity (5min) in a novel cage on SHAV acquisition, while baseline startle and entries into the open section of the elevated 'zero' maze test of anxiety were the main variables influencing FPS. This indicates that startle responses may have a facilitating role in the rat's active responses in the two-way active (shuttlebox) avoidance acquisition. The results of this behavioral evaluation of N/Nih-HS rats show that unconditioned anxiety (e.g. in the ZM test) predicts learned fear-related responses (e.g. FPS and SHAV) to some extent, while a positive association is also observed between BAS and SHAV. These findings are discussed in terms of their potential usefulness for present and future neurobehavioral and genetic studies of fearfulness/anxiety.Behavioural brain research 09/2009; 202(1):92-101. · 3.22 Impact Factor