Rheumatic?-A Digital Diagnostic Decision Support Tool for Individuals Suspecting Rheumatic Diseases: A Multicenter Pilot Validation Study.

Introduction: Digital diagnostic decision support tools promise to accelerate diagnosis and increase health care efficiency in rheumatology. Rheumatic? is an online tool developed by specialists in rheumatology and general medicine together with patients and patient organizations. It calculates a risk score for several rheumatic diseases. We ran a pilot study retrospectively testing Rheumatic? for its ability to differentiate symptoms from existing or emerging immune-mediated rheumatic diseases from other rheumatic and musculoskeletal complaints and disorders in patients visiting rheumatology clinics. Materials and Methods: The performance of Rheumatic? was tested using in three university rheumatology centers: (A) patients at Risk for RA (Karolinska Institutet, n = 50 individuals with musculoskeletal complaints and anti-citrullinated protein antibody positivity) (B) patients with early joint swelling [dataset B (Erlangen) n = 52]. (C) Patients with early arthritis where the clinician considered it likely to be of auto-immune origin [dataset C (Leiden) n = 73]. In dataset A we tested whether Rheumatic? could predict the development of arthritis. In dataset B and C we tested whether Rheumatic? could predict the development of an immune-mediated rheumatic diseases. We examined the discriminative power of the total score with the Wilcoxon rank test and the area-under-the-receiver-operating-characteristic curve (AUC-ROC). Next, we calculated the test characteristics for these patients passing the first or second expert-based Rheumatic? scoring threshold. Results: The total test scores differentiated between: (A) Individuals developing arthritis or not, median 245 vs. 163, P < 0.0001, AUC-ROC = 75.3; (B) patients with an immune-mediated arthritic disease or not median 191 vs. 107, P < 0.0001, AUC-ROC = 79.0; but less patients with an immune-mediated arthritic disease or not amongst those where the clinician already considered an immune mediated disease most likely (median 262 vs. 212, P < 0.0001, AUC-ROC = 53.6). Threshold-1 (advising to visit primary care doctor) was highly specific in dataset A and B (0.72, 0.87, and 0.23, respectively) and sensitive (0.67, 0.61, and 0.67). Threshold-2 (advising to visit rheumatologic care) was very specific in all three centers but not very sensitive: specificity of 1.0, 0.96, and 0.91, sensitivity 0.05, 0.07, 0.14 in dataset A, B, and C, respectively. Conclusion: Rheumatic? is a web-based patient-centered multilingual diagnostic tool capable of differentiating immune-mediated rheumatic conditions from other musculoskeletal problems. The current scoring system needs to be further optimized.

Prospective Studies on the Risk of Rheumatoid Arthritis: The European Risk RA Registry.

Background: The accumulation of risk for the development of rheumatoid arthritis (RA) is regarded as a continuum that may start with interacting environmental and genetic factors, proceed with the initiation of autoimmunity, and result in the formation of autoantibodies such as anti-citrullinated peptide antibodies (ACPA). In parallel, at-risk individuals may be asymptomatic or experience joint pain (arthralgia) that is itself non-specific or clinically suspicious for evolving RA, even in the absence of overt arthritis. Optimal strategies for the management of people at-risk of RA, both for symptom control and to delay or prevent progression to classifiable disease, remain poorly understood. Methods: To help address this, groups of stakeholders from academia, clinical rheumatology, industry and patient research partners have collaborated to advance understanding, define and study different phases of the at-risk state. In this current report we describe different European initiatives in the field and the successful effort to build a European Registry of at-risk people to facilitate observational and interventional research. Results: We outline similarities and differences between cohorts of at-risk individuals at institutions spanning several countries, and how to best combine them within the new database. Over the past 2 years, besides building the technical infrastructure, we have agreed on a core set of variables that all partners should strive to collect for harmonization purposes. Conclusion: We emphasize to address this process from different angles and touch on the biologic, epidemiologic, analytic, and regulatory aspects of collaborative studies within a meta-database of people at-risk of RA.

Polymorphic estrogen receptor binding site causes Cd2-dependent sex bias in the susceptibility to autoimmune diseases.

Complex autoimmune diseases are sexually dimorphic. An interplay between predisposing genetics and sex-related factors probably controls the sex discrepancy in the immune response, but the underlying mechanisms are unclear. Here we positionally identify a polymorphic estrogen receptor binding site that regulates Cd2 expression, leading to female-specific differences in T cell-dependent mouse models of autoimmunity. Female mice with reduced Cd2 expression have impaired autoreactive T cell responses. T cells lacking Cd2 costimulation upregulate inhibitory Lag-3. These findings help explain sexual dimorphism in human autoimmunity, as we find that CD2 polymorphisms are associated with rheumatoid arthritis and 17-ß-estradiol-regulation of CD2 is conserved in human T cells. Hormonal regulation of CD2 might have implications for CD2-targeted therapy, as anti-Cd2 treatment more potently affects T cells in female mice. These results demonstrate the relevance of sex-genotype interactions, providing strong evidence for CD2 as a sex-sensitive predisposing factor in autoimmunity.

Natural polymorphism of Ym1 regulates pneumonitis through alternative activation of macrophages.

We have positionally cloned the Ym1 gene, with a duplication and a promoter polymorphism, as a major regulator of inflammation. Mice with the RIIIS/J haplotype, with the absence of Ym1 expression, showed reduced susceptibility to mannan-enhanced collagen antibody-induced arthritis and to chronic arthritis induced by intranasal exposure of mannan. Depletion of lung macrophages alleviated arthritis, whereas intranasal supplement of Ym1 protein to Ym1-deficient mice reversed the disease, suggesting a key role of Ym1 for inflammatory activity by lung macrophages. Ym1-deficient mice with pneumonitis had less eosinophil infiltration, reduced production of type II cytokines and IgG1, and skewing of macrophages toward alternative activation due to enhanced STAT6 activation. Proteomics analysis connected Ym1 polymorphism with changed lipid metabolism. Induced PPAR-γ and lipid metabolism in Ym1-deficient macrophages contributed to cellular polarization. In conclusion, the natural polymorphism of Ym1 regulates alternative activation of macrophages associated with pulmonary inflammation.

Toward Earlier Diagnosis Using Combined eHealth Tools in Rheumatology: The Joint Pain Assessment Scoring Tool (JPAST) Project.

Outcomes of patients with inflammatory rheumatic diseases have significantly improved over the last three decades, mainly due to therapeutic innovations, more timely treatment, and a recognition of the need to monitor response to treatment and to titrate treatments accordingly. Diagnostic delay remains a major challenge for all stakeholders. The combination of electronic health (eHealth) and serologic and genetic markers holds great promise to improve the current management of patients with inflammatory rheumatic diseases by speeding up access to appropriate care. The Joint Pain Assessment Scoring Tool (JPAST) project, funded by the European Union (EU) European Institute of Innovation and Technology (EIT) Health program, is a unique European project aiming to enable and accelerate personalized precision medicine for early treatment in rheumatology, ultimately also enabling prevention. The aim of the project is to facilitate these goals while at the same time, reducing cost for society and patients.

Incidence and risk factors for adalimumab and infliximab anti-drug antibodies in rheumatoid arthritis: A European retrospective multicohort analysis.

OBJECTIVES: To evaluate the incidence of anti-drug antibody (ADA) occurrences and ADA-related risk factors under adalimumab and infliximab treatment in rheumatoid arthritis (RA) patients. METHODS: The study combined retrospective cohorts from the ABIRISK project totaling 366 RA patients treated with adalimumab (n = 240) or infliximab (n = 126), 92.4% of them anti-TNF naive (n = 328/355) and 96.6% of them co-treated with methotrexate (n = 341/353) with up to 18 months follow-up. ADA positivity was measured by enzyme-linked immunosorbent assay. The cumulative incidence of ADA was estimated, and potential bio-clinical factors were investigated using a Cox regression model on interval-censored data. RESULTS: ADAs were detected within 18 months in 19.2% (n = 46) of the adalimumab-treated patients and 29.4% (n = 37) of the infliximab-treated patients. The cumulative incidence of ADA increased over time. In the adalimumab and infliximab groups, respectively, the incidence was 15.4% (5.2-20.2) and 0% (0-5.9) at 3 months, 17.6% (11.4-26.4) and 0% (0-25.9) at 6 months, 17.7% (12.6-37.5) and 34.1% (11.4-46.3) at 12 months, 50.0% (25.9-87.5) and 37.5% (25.9-77.4) at 15 months and 50.0% (25.9-87.5) and 66.7% (37.7-100) at 18 months. Factors associated with a higher risk of ADA development were: longer disease duration (1-3 vs. < 1 year; adalimumab: HR 3.0, 95% CI 1.0-8.7; infliximab: HR 2.7, 95% CI 1.1-6.8), moderate disease activity (DAS28 3.2-5.1 vs. < 3.2; adalimumab: HR 6.6, 95% CI 1.3-33.7) and lifetime smoking (infliximab: HR 2.7, 95% CI 1.2-6.3). CONCLUSIONS: The current study focusing on patients co-treated with methotrexate for more than 95% of them found a late occurrence of ADAs not previously observed, whereby the risk continued to increase over 18 months. Disease duration, DAS28 and lifetime smoking are clinical predictors of ADA development.

Fine mapping of bone structure and strength QTLs in heterogeneous stock rat.

We previously demonstrated that skeletal structure and strength phenotypes vary considerably in heterogeneous stock (HS) rats. These phenotypes were found to be strongly heritable, suggesting that the HS rat model represents a unique genetic resource for dissecting the complex genetic etiology underlying bone fragility. The purpose of this study was to identify and localize genes associated with bone structure and strength phenotypes using 1524 adult male and female HS rats between 17 to 20 weeks of age. Structure measures included femur length, neck width, head width; femur and lumbar spine (L3-5) areas obtained by DXA; and cross-sectional areas (CSA) at the midshaft, distal femur and femoral neck, and the 5th lumbar vertebra measured by CT. In addition, measures of strength of the whole femur and femoral neck were obtained. Approximately 70,000 polymorphic SNPs distributed throughout the rat genome were selected for genotyping, with a mean linkage disequilibrium coefficient between neighboring SNPs of 0.95. Haplotypes were estimated across the entire genome for each rat using a multipoint haplotype reconstruction method, which calculates the probability of descent at each locus from each of the 8 HS founder strains. The haplotypes were then tested for association with each structure and strength phenotype via a mixed model with covariate adjustment. We identified quantitative trait loci (QTLs) for structure phenotypes on chromosomes 3, 8, 10, 12, 17 and 20, and QTLs for strength phenotypes on chromosomes 5, 10 and 11 that met a conservative genome-wide empiric significance threshold (FDR=5%; P<3×10(-6)). Importantly, most QTLs were localized to very narrow genomic regions (as small as 0.3 Mb and up to 3 Mb), each harboring a small set of candidate genes, both novel and previously shown to have roles in skeletal development and homeostasis.

Natural polymorphisms in Tap2 influence negative selection and CD4∶CD8 lineage commitment in the rat.

Genetic variation in the major histocompatibility complex (MHC) affects CD4∶CD8 lineage commitment and MHC expression. However, the contribution of specific genes in this gene-dense region has not yet been resolved. Nor has it been established whether the same genes regulate MHC expression and T cell selection. Here, we assessed the impact of natural genetic variation on MHC expression and CD4∶CD8 lineage commitment using two genetic models in the rat. First, we mapped Quantitative Trait Loci (QTLs) associated with variation in MHC class I and II protein expression and the CD4∶CD8 T cell ratio in outbred Heterogeneous Stock rats. We identified 10 QTLs across the genome and found that QTLs for the individual traits colocalized within a region spanning the MHC. To identify the genes underlying these overlapping QTLs, we generated a large panel of MHC-recombinant congenic strains, and refined the QTLs to two adjacent intervals of ∼0.25 Mb in the MHC-I and II regions, respectively. An interaction between these intervals affected MHC class I expression as well as negative selection and lineage commitment of CD8 single-positive (SP) thymocytes. We mapped this effect to the transporter associated with antigen processing 2 (Tap2) in the MHC-II region and the classical MHC class I gene(s) (RT1-A) in the MHC-I region. This interaction was revealed by a recombination between RT1-A and Tap2, which occurred in 0.2% of the rats. Variants of Tap2 have previously been shown to influence the antigenicity of MHC class I molecules by altering the MHC class I ligandome. Our results show that a restricted peptide repertoire on MHC class I molecules leads to reduced negative selection of CD8SP cells. To our knowledge, this is the first study showing how a recombination between natural alleles of genes in the MHC influences lineage commitment of T cells.

High-resolution genome screen for bone mineral density in heterogeneous stock rat.

We previously demonstrated that skeletal mass, structure, and biomechanical properties vary considerably in heterogeneous stock (HS) rat strains. In addition, we observed strong heritability for several of these skeletal phenotypes in the HS rat model, suggesting that it represents a unique genetic resource for dissecting the complex genetics underlying bone fragility. The purpose of this study was to identify and localize genes associated with bone mineral density in HS rats. We measured bone phenotypes from 1524 adult male and female HS rats between 17 and 20 weeks of age. Phenotypes included dual-energy X-ray absorptiometry (DXA) measurements for bone mineral content and areal bone mineral density (aBMD) for femur and lumbar spine (L3-L5), and volumetric BMD measurements by CT for the midshaft and distal femur, femur neck, and fifth lumbar vertebra (L5). A total of 70,000 polymorphic single-nucleotide polymorphisms (SNPs) distributed throughout the genome were selected from genotypes obtained from the Affymetrix rat custom SNPs array for the HS rat population. These SNPs spanned the HS rat genome with a mean linkage disequilibrium coefficient between neighboring SNPs of 0.95. Haplotypes were estimated across the entire genome for each rat using a multipoint haplotype reconstruction method, which calculates the probability of descent for each genotyped locus from each of the eight founder HS strains. The haplotypes were tested for association with each bone density phenotype via a mixed model with covariate adjustment. We identified quantitative trait loci (QTLs) for BMD phenotypes on chromosomes 2, 9, 10, and 13 meeting a conservative genomewide empiric significance threshold (false discovery rate [FDR] = 5%; p < 3 × 10(-6)). Importantly, most QTLs were localized to very small genomic regions (1-3 megabases [Mb]), allowing us to identify a narrow set of potential candidate genes including both novel genes and genes previously shown to have roles in skeletal development and homeostasis.

Genomes and phenomes of a population of outbred rats and its progenitors.

Finding genetic variants that contribute to phenotypic variation is one of the main challenges of modern genetics. We used an outbred population of rats (Heterogeneous Stock, HS) in a combined sequence-based and genetic mapping analysis to identify sequence variants and genes contributing to complex traits of biomedical relevance. Here we describe the sequences of the eight inbred progenitors of the HS and the variants that segregate between them. We report the genotyping of 1,407 HS rats, and the collection from 2,006 rats of 195 phenotypic measures that are relevant to models of anxiety, type 2 diabetes, hypertension and osteoporosis. We make available haplotype dosages for the 1,407 genotyped rats, since genetic mapping in the HS is best carried out by reconstructing each HS chromosome as a mosaic of the progenitor genomes. Finally, we have deposited an R object that makes it easy to incorporate our sequence data into any genetic study of HS rats. Our genetic data are available for both Rnor3.4 and Rnor5.0 rat assemblies.

Erratum: Genomes and phenomes of a population of outbred rats and its progenitors.

[This corrects the article DOI: 10.1038/sdata.2014.11.].

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

OBJECTIVE: To identify genetic factors driving pathogenic autoantibody formation in collagen-induced arthritis (CIA), a mouse model of rheumatoid arthritis (RA), in order to better understand the etiology of RA and identify possible new avenues for therapeutic intervention. METHODS: We performed a genome-wide analysis of quantitative trait loci controlling autoantibody to type II collagen (anti-CII), anti-citrullinated protein antibody (ACPA), and rheumatoid factor (RF). To identify loci controlling autoantibody production, we induced CIA in a heterogeneous stock-derived mouse cohort, with contribution of 8 inbred mouse strains backcrossed to C57BL/10.Q. Serum samples were collected from 1,640 mice before arthritis onset and at the peak of the disease. Antibody concentrations were measured by standard enzyme-linked immunosorbent assay, and linkage analysis was performed using a linear regression-based method. RESULTS: We identified loci controlling formation of anti-CII of different IgG isotypes (IgG1, IgG3), antibodies to major CII epitopes (C1, J1, U1), antibodies to a citrullinated CII peptide (citC1), and RF. The anti-CII, ACPA, and RF responses were all found to be controlled by distinct genes, one of the most important loci being the immunoglobulin heavy chain locus. CONCLUSION: This comprehensive genetic analysis of autoantibody formation in CIA demonstrates an association not only of anti-CII, but interestingly also of ACPA and RF, with arthritis development in mice. These results underscore the importance of non-major histocompatibility complex genes in controlling the formation of clinically relevant autoantibodies.

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.

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.

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.

Heterogeneous stock rat: a unique animal model for mapping genes influencing bone fragility.

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.

NANOG reporter cell lines generated by gene targeting in human embryonic stem cells.

BACKGROUND: Pluripotency and self-renewal of human embryonic stem cells (hESCs) is mediated by a complex interplay between extra- and intracellular signaling pathways, which regulate the expression of pluripotency-specific transcription factors. The homeodomain transcription factor NANOG plays a central role in maintaining hESC pluripotency, but the precise role and regulation of NANOG are not well defined. METHODOLOGY/PRINCIPAL FINDINGS: To facilitate the study of NANOG expression and regulation in viable hESC cultures, we generated fluorescent NANOG reporter cell lines by gene targeting in hESCs. In these reporter lines, the fluorescent reporter gene was co-expressed with endogenous NANOG and responded to experimental induction or repression of the NANOG promoter with appropriate changes in expression levels. Furthermore, NANOG reporter lines facilitated the separation of hESC populations based on NANOG expression levels and their subsequent characterization. Gene expression arrays on isolated hESC subpopulations revealed genes with differential expression in NANOG(high) and NANOG(low) hESCs, providing candidates for NANOG downstream targets hESCs. CONCLUSION/SIGNIFICANCE: The newly derived NANOG reporter hESC lines present novel tools to visualize NANOG expression in viable hESCs. In future applications, these reporter lines can be used to elucidate the function and regulation of NANOG in pluripotent hESCs.

FGF2 specifies hESC-derived definitive endoderm into foregut/midgut cell lineages in a concentration-dependent manner.

Fibroblast growth factor (FGF) signaling controls axis formation during endoderm development. Studies in lower vertebrates have demonstrated that FGF2 primarily patterns the ventral foregut endoderm into liver and lung, whereas FGF4 exhibits broad anterior-posterior and left-right patterning activities. Furthermore, an inductive role of FGF2 during dorsal pancreas formation has been shown. However, whether FGF2 plays a similar role during human endoderm development remains unknown. Here, we show that FGF2 specifies hESC-derived definitive endoderm (DE) into different foregut lineages in a dosage-dependent manner. Specifically, increasing concentrations of FGF2 inhibits hepatocyte differentiation, whereas intermediate concentration of FGF2 promotes differentiation toward a pancreatic cell fate. At high FGF2 levels specification of midgut endoderm into small intestinal progenitors is increased at the expense of PDX1(+) pancreatic progenitors. High FGF2 concentrations also promote differentiation toward an anterior foregut pulmonary cell fate. Finally, by dissecting the FGF receptor intracellular pathway that regulates pancreas specification, we demonstrate for the first time to the best of our knowledge that induction of PDX1(+) pancreatic progenitors relies on FGF2-mediated activation of the MAPK signaling pathway. Altogether, these observations suggest a broader gut endodermal patterning activity of FGF2 that corresponds to what has previously been advocated for FGF4, implying a functional switch from FGF4 to FGF2 during evolution. Thus, our results provide new knowledge of how cell fate specification of human DE is controlled-facts that will be of great value for future regenerative cell therapies.

Unlearned anxiety predicts learned fear: a comparison among heterogeneous rats and the Roman rat strains.

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.

High resolution mapping of expression QTLs in heterogeneous stock mice in multiple tissues.

A proportion of the genetic variants underlying complex phenotypes do so through their effects on gene expression, so an important challenge in complex trait analysis is to discover the genetic basis for the variation in transcript abundance. So far, the potential of mapping both quantitative trait loci (QTLs) and expression quantitative trait loci (eQTLs) in rodents has been limited by the low mapping resolution inherent in crosses between inbred strains. We provide a megabase resolution map of thousands of eQTLs in hippocampus, lung, and liver samples from heterogeneous stock (HS) mice in which 843 QTLs have also been mapped at megabase resolution. We exploit dense mouse SNP data to show that artifacts due to allele-specific hybridization occur in approximately 30% of the cis-acting eQTLs and, by comparison with exon expression data, we show that alternative splicing of the 3' end of the genes accounts for <1% of cis-acting eQTLs. Approximately one third of cis-acting eQTLs and one half of trans-acting eQTLs are tissue specific. We have created an important systems biology resource for the genetic analysis of complex traits in a key model organism.

FGF4 and retinoic acid direct differentiation of hESCs into PDX1-expressing foregut endoderm in a time- and concentration-dependent manner.

BACKGROUND: Retinoic acid (RA) and fibroblast growth factor 4 (FGF4) signaling control endoderm patterning and pancreas induction/expansion. Based on these findings, RA and FGFs, excluding FGF4, have frequently been used in differentiation protocols to direct differentiation of hESCs into endodermal and pancreatic cell types. In vivo, these signaling pathways act in a temporal and concentration-dependent manner. However, in vitro, the underlying basis for the time of addition of growth and differentiation factors (GDFs), including RA and FGFs, as well as the concentration is lacking. Thus, in order to develop robust and reliable differentiation protocols of ESCs into mature pancreatic cell types, including insulin-producing beta cells, it will be important to mechanistically understand each specification step. This includes differentiation of mesendoderm/definitive endoderm into foregut endoderm--the origin of pancreatic endoderm. METHODOLOGY/PRINCIPAL FINDINGS: Here, we provide data on the individual and combinatorial role of RA and FGF4 in directing differentiation of ActivinA (AA)-induced hESCs into PDX1-expressing cells. FGF4's ability to affect endoderm patterning and specification in vitro has so far not been tested. By testing out the optimal concentration and timing of addition of FGF4 and RA, we present a robust differentiation protocol that on average generates 32% PDX1(+) cells. Furthermore, we show that RA is required for converting AA-induced hESCs into PDX1(+) cells, and that part of the underlying mechanism involves FGF receptor signaling. Finally, further characterization of the PDX1(+) cells suggests that they represent foregut endoderm not yet committed to pancreatic, posterior stomach, or duodenal endoderm. CONCLUSION/SIGNIFICANCE: In conclusion, we show that RA and FGF4 jointly direct differentiation of PDX1(+) foregut endoderm in a robust and efficient manner. RA signaling mediated by the early induction of RARbeta through AA/Wnt3a is required for PDX1 expression. Part of RA's activity is mediated by FGF signaling.