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

MYLK and PTGS1 Genetic Variations Associated with Osteoporosis and Benign Breast Tumors in Korean Women

Osteoporosis, characterized by reduced bone mass and increased bone fragility, is a disease prevalent in women. Likewise, breast cancer is a multifactorial disease and considered the major cause of mortality in premenopausal and postmenopausal women worldwide. Our data demonstrated the association of the MYLK gene and PTGS1 gene variants with osteoporosis and benign breast tumor risk and the impact of ovariectomy on osteoporosis in Korean women. We performed a genome-wide association study (GWAS) of women with osteoporosis and benign breast tumors. There were 60 single nucleotide polymorphisms (SNPs) and 12 SNPs in the MYLK and PTGS1 genes, associated with benign breast tumors and osteoporosis. Our study showed that women with homozygous MYLK rs12163585 major alleles had an increased risk of osteoporosis following ovariectomy compared to those with minor alleles. Women carrying the minor PTGS1 rs1213265 allele and not treated via ovariectomy carried a higher risk of osteoporosis than those who underwent ovariectomy with a homozygous genotype at the major alleles. Our results suggest that both the MYLK and PTGS1 genes are genetic factors associated with the phenotypes, and these associations appear to be modulated by ovariectomy.

Osteoblastic PLEKHO1 contributes to joint inflammation in rheumatoid arthritis

Background

Osteoblasts participating in the inflammation regulation gradually obtain concerns. However, its role in joint inflammation of rheumatoid arthritis (RA) is largely unknown. Here, we investigated the role of osteoblastic pleckstrin homology domain-containing family O member 1 (PLEKHO1), a negative regulator of osteogenic lineage activity, in regulating joint inflammation in RA.

Methods

The level of osteoblastic PLEKHO1 in RA patients and collagen-induced arthritis (CIA) mice was examined. The role of osteoblastic PLEKHO1 in joint inflammation was evaluated by a CIA model and a K/BxN serum-transfer arthritis (STA) model which were induced in osteoblast-specific Plekho1 conditional knockout mice and mice expressing high Plekho1 exclusively in osteoblasts, respectively. The effect of osteoblastic PLEKHO1 inhibition was explored in a CIA mice model and a non-human primate arthritis model. The mechanism of osteoblastic PLEKHO1 in regulating joint inflammation were performed by a series of in vitro studies.

Results

PLEKHO1 was highly expressed in osteoblasts from RA patients and CIA mice. Osteoblastic Plekho1 deletion ameliorated joint inflammation, whereas overexpressing Plekho1 only within osteoblasts exacerbated local inflammation in CIA mice and STA mice. PLEKHO1 was required for TRAF2-mediated RIP1 ubiquitination to activate NF-κB for inducing inflammatory cytokines production in osteoblasts. Moreover, osteoblastic PLEKHO1 inhibition diminished joint inflammation and promoted bone formation in CIA mice and non-human primate arthritis model.

Conclusions

These data strongly suggest that the highly expressed PLEKHO1 in osteoblasts contributes to joint inflammation in RA. Targeting osteoblastic PLEKHO1 may exert dual therapeutic action of alleviating joint inflammation and promoting bone formation in RA.

PhenoRank: reducing study bias in gene prioritization through simulation

Motivation

Genome-wide association studies have identified thousands of loci associated with human disease, but identifying the causal genes at these loci is often difficult. Several methods prioritize genes most likely to be disease causing through the integration of biological data, including protein-protein interaction and phenotypic data. Data availability is not the same for all genes however, potentially influencing the performance of these methods.

Results

We demonstrate that whilst disease genes tend to be associated with greater numbers of data, this may be at least partially a result of them being better studied. With this observation we develop PhenoRank, which prioritizes disease genes whilst avoiding being biased towards genes with more available data. Bias is avoided by comparing gene scores generated for the query disease against gene scores generated using simulated sets of phenotype terms, which ensures that differences in data availability do not affect the ranking of genes. We demonstrate that whilst existing prioritization methods are biased by data availability, PhenoRank is not similarly biased. Avoiding this bias allows PhenoRank to effectively prioritize genes with fewer available data and improves its overall performance. PhenoRank outperforms three available prioritization methods in cross-validation (PhenoRank area under receiver operating characteristic curve [AUC]=0.89, DADA AUC = 0.87, EXOMISER AUC = 0.71, PRINCE AUC = 0.83, P < 2.2 × 10-16).

Availability and implementation

PhenoRank is freely available for download at https://github.com/alexjcornish/PhenoRank.

Supplementary information

Supplementary data are available at Bioinformatics online.

Heterogeneous Stock Populations for Analysis of Complex Traits

Heterogeneous Stock (HS) populations allow for fine-resolution genetic mapping of a variety of complex traits. HS mice and rats were created from breeding together eight inbred strains, followed by maintaining the colony in a manner that minimizes inbreeding. After 50 or more generations of breeding, the resulting animals' chromosomes represent a genetic mosaic of the founders' haplotypes, with the average distance between recombination events in the centiMorgan range. This allows for genetic mapping to only a few Mb, a much smaller region than what can be identified using traditional F2 intercross or backcross mapping strategies. HS animals have been used to fine-map a variety of complex traits including anxiety and fear behaviors, diabetes, asthma, and heart disease, among others. Once a quantitative trait locus (QTL) has been identified, founder sequence and expression analysis can be used to identify underlying causal genes. In the following review, we provide an overview of how HS rats and mice have been used to identify genetic loci, and in some cases the causal genes, underlying complex traits. We discuss the creation and breeding strategies for both HS rats and mice. We then discuss the statistical analyses used to identify genetic loci, as well as strategies to identify causal genes underlying these loci. We end the chapter by discussing limitations faced when using HS populations, including several statistical challenges that have not been fully resolved.

Identification of a novel gene for diabetic traits in rats, mice, and humans

The genetic basis of type 2 diabetes remains incompletely defined despite the use of multiple genetic strategies. Multiparental populations such as heterogeneous stocks (HS) facilitate gene discovery by allowing fine mapping to only a few megabases, significantly decreasing the number of potential candidate genes compared to traditional mapping strategies. In the present work, we employed expression and sequence analysis in HS rats (Rattus norvegicus) to identify Tpcn2 as a likely causal gene underlying a 3.1-Mb locus for glucose and insulin levels. Global gene expression analysis on liver identified Tpcn2 as the only gene in the region that is differentially expressed between HS rats with glucose intolerance and those with normal glucose regulation. Tpcn2 also maps as a cis-regulating expression QTL and is negatively correlated with fasting glucose levels. We used founder sequence to identify variants within this region and assessed association between 18 variants and diabetic traits by conducting a mixed-model analysis, accounting for the complex family structure of the HS. We found that two variants were significantly associated with fasting glucose levels, including a nonsynonymous coding variant within Tpcn2. Studies in Tpcn2 knockout mice demonstrated a significant decrease in fasting glucose levels and insulin response to a glucose challenge relative to those in wild-type mice. Finally, we identified variants within Tpcn2 that are associated with fasting insulin in humans. These studies indicate that Tpcn2 is a likely causal gene that may play a role in human diabetes and demonstrate the utility of multiparental populations for positionally cloning genes within complex loci.

Genome-wide mapping of gene-microbiota interactions in susceptibility to autoimmune skin blistering

Susceptibility to chronic inflammatory diseases is determined by immunogenetic and environmental risk factors. Resident microbial communities often differ between healthy and diseased states, but whether these differences are of primary aetiological importance or secondary to the altered inflammatory environment remains largely unknown. Here we provide evidence for host gene–microbiota interactions contributing to disease risk in a mouse model of epidermolysis bullosa acquisita, an autoantibody-induced inflammatory skin disease. Using an advanced intercross, we identify genetic loci contributing to skin microbiota variability, susceptibility to skin blistering and their overlap. Furthermore, by treating bacterial species abundances as covariates with disease we reveal a novel disease locus. The majority of the identified covariate taxa are characterized by reduced abundance being associated with increased disease risk, providing evidence of a primary role in protection from disease. Further characterization of these putative probiotic species or species assemblages offers promising potential for preventative and therapeutic treatment development.

The pathogenesis of inflammatory disorders afflicting the skin is multifactorial. Srinivas et al. show that diversity of the skin microbiota is a critical factor determining the susceptibility to epidermolysis bullosa acquisita, a chronic mucocutaneous autoimmune skin blistering disease.

QTL mapping in outbred populations: successes and challenges

Quantitative trait locus (QTL) mapping in animal populations has been a successful strategy for identifying genomic regions that play a role in complex diseases and traits. When conducted in an F2 intercross or backcross population, the resulting QTL is frequently large, often encompassing 30 Mb or more and containing hundreds of genes. To narrow the locus and identify candidate genes, additional strategies are needed. Congenic strains have proven useful but work less well when there are multiple tightly linked loci, frequently resulting in loss of phenotype. As an alternative, we discuss the use of highly recombinant outbred models for directly fine-mapping QTL to only a few megabases. We discuss the use of several currently available models such as the advanced intercross (AI), heterogeneous stocks (HS), the diversity outbred (DO), and commercially available outbred stocks (CO). Once a QTL has been fine-mapped, founder sequence and expression QTL mapping can be used to identify candidate genes. In this regard, the large number of alleles found in outbred stocks can be leveraged to identify causative genes and variants. We end this review by discussing some important statistical considerations when analyzing outbred populations. Fine-resolution mapping in outbred models, coupled with full genome sequence, has already led to the identification of several underlying causative genes for many complex traits and diseases. These resources will likely lead to additional successes in the coming years.

Using the emerging Collaborative Cross to probe the immune system

The Collaborative Cross (CC) is an emerging panel of recombinant inbred (RI) mouse strains. Each strain is genetically distinct but all descended from the same eight inbred founders. In 66 strains from incipient lines of the CC (pre-CC), as well as the 8 CC founders and some of their F1 offspring, we examined subsets of lymphocytes and antigen-presenting cells. We found significant variation among the founders, with even greater diversity in the pre-CC. Genome-wide association using inferred haplotypes detected highly significant loci controlling B-to-T cell ratio, CD8 T-cell numbers, CD11c and CD23 expression. Comparison of overall strain effects in the CC founders with strain effects at QTL in the pre-CC revealed sharp contrasts in the genetic architecture of two traits with significant loci: variation in CD23 can be explained largely by additive genetics at one locus, whereas variation in B-to-T ratio has a more complex etiology. For CD23, we found a strong QTL whose confidence interval contained the CD23 structural gene Fcer2a. Our data on the pre-CC demonstrate the utility of the CC for studying immunophenotypes and the value of integrating founder, CC and F1 data. The extreme immunophenotypes observed could have pleiotropic effects in other CC experiments.

Transcriptomics of wild-type mice and mice lacking ADAMTS-5 activity identifies genes involved in osteoarthritis initiation and cartilage destruction

OBJECTIVE

To identify changes in gene expression in mice with osteoarthritis (OA) in order to explore the mechanisms of the disease.

METHODS

Gene expression profiling was performed in cartilage from mice with surgically induced OA. We used wild-type (WT) mice and Adamts5Δcat mice, in which ADAMTS-5 activity is lacking and aggrecan loss and cartilage erosion are inhibited, to distinguish gene expression changes that are independent of ADAMTS-5 activity and cartilage breakdown. Mechanical instability was introduced into the knee joints of 10-week-old male mice via surgical destabilization of the medial meniscus (DMM). Cartilage from the developing lesion in the destabilized medial meniscus and corresponding regions in sham-operated joints was harvested by microdissection at 1, 2, and 6 weeks postsurgery, and RNA was extracted, amplified, and hybridized to whole-genome microarrays.

RESULTS

Several previously identified OA-related genes, including Ptgs2, Crlf1, and Inhba, and novel genes, such as Phdla2 and Il11, were up-regulated in both WT mice and Adamts5Δcat mice, indicating that they are independent of ADAMTS-5 activity. The altered expression of other genes, including Col10a1, the sentinel marker of cartilage hypertrophy, and Wnt/β-catenin pathway genes, required ADAMTS-5 activity. Cell death pathway genes were dysregulated, and Tp53, Foxo4, and Xbp1 endoplasmic reticulum-stress transcriptional networks were activated. Analysis of degradome genes identified up-regulation of many proteases, including Mmp3, Capn2, and the novel cartilage proteases Prss46 and Klk8. Comparison with other studies identified 16 genes also dysregulated in rat and human OA as priorities for study.

CONCLUSION

We have identified, for the first time, several genes that have an ADAMTS-5-independent role in OA, identifying them as possible OA initiation candidates. This work provides new insights into the sequence of gene dysregulation and the molecular basis of cartilage destruction in OA.

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.

Non-MHC risk alleles in rheumatoid arthritis and in the syntenic chromosome regions of corresponding animal models

Rheumatoid arthritis (RA) is a polygenic autoimmune disease primarily affecting the synovial joints. Numerous animal models show similarities to RA in humans; some of them not only mimic the clinical phenotypes but also demonstrate the involvement of homologous genomic regions in RA. This paper compares corresponding non-MHC genomic regions identified in rodent and human genome-wide association studies (GWAS). To date, over 30 non-MHC RA-associated loci have been identified in humans, and over 100 arthritis-associated loci have been identified in rodent models of RA. The genomic regions associated with the disease are designated by the name(s) of the gene having the most frequent and consistent RA-associated SNPs or a function suggesting their involvement in inflammatory or autoimmune processes. Animal studies on rats and mice preferentially have used single sequence length polymorphism (SSLP) markers to identify disease-associated qualitative and quantitative trait loci (QTLs) in the genome of F2 hybrids of arthritis-susceptible and arthritis-resistant rodent strains. Mouse GWAS appear to be far ahead of rat studies, and significantly more mouse QTLs correspond to human RA risk alleles.

After GWAS: mice to the rescue?

The genetic basis of human autoimmune diseases remains incompletely understood, despite significant progress from genome-wide association studies (GWAS). In this review we outline how studies in mice may help filling these knowledge gaps. Forward genetic approaches including mutagenesis screens and quantitative trait locus (QTL) mapping studies can identify candidate genes for in depth analysis in human patient populations. Reverse genetic approaches utilize genetically engineered mice to analyze the function of disease-associated genes and their variants. Inbred strains are a distinctive feature of mouse genetics and we discuss their history, advantages and disadvantages. Three factors need to be considered when comparing experimental results from studies in mice and humans: In addition to species-specific differences, phenotypes are affected by the genetic background of the mouse strain being analyzed, and by microbial factors. Despite of these complexities, mice are essential discovery tools in the post GWAS era.

ATP induces protein arginine deiminase 2-dependent citrullination in mast cells through the P2X7 purinergic receptor

Posttranslational modifications regulate physiology either by directly modulating protein function or by impacting immune recognition of self-proteins. Citrullination is a posttranslational modification formed by the conversion of arginine residues into the citrulline amino acid by protein arginine deiminase (PAD) family members. We have identified mast cells as a major source of the PAD2 enzyme. Activation of the P2X7 purinergic receptor (P2X7) by the inflammatory "danger" signal ATP induces PAD2 activity and robust protein citrullination. P2X7-mediated activation of PAD2 is sensitive to p38 MAPK and protein kinase C inhibitors, and PAD2 regulates the expression of the TNFR2, Adamts-9, and Rab6b transcripts in mast cells. Further, the PAD2 enzyme and its citrullinated substrate proteins are released from mast cells on activation with ATP. PAD2 expression is closely linked with inflammation in rheumatoid arthritis (RA) synovial tissue, and PAD2 and citrullinated proteins are found in the synovial fluid of RA patients. In addition, RA is associated with the development of autoantibodies to citrullinated self-proteins. Our results suggest that P2X7 activation of mast cells may play a role in inflammation by providing PAD2 and PAD2 substrates access to the extracellular space.

Fine-mapping diabetes-related traits, including insulin resistance, in heterogeneous stock rats

Type 2 diabetes (T2D) is a disease of relative insulin deficiency resulting from both insulin resistance and beta cell failure. We have previously used heterogeneous stock (HS) rats to fine-map a locus for glucose tolerance. We show here that glucose intolerance in the founder strains of the HS colony is mediated by different mechanisms: insulin resistance in WKY and an insulin secretion defect in ACI, and we demonstrate a high degree of variability for measures of insulin resistance and insulin secretion in HS rats. As such, our goal was to use HS rats to fine-map several diabetes-related traits within a region on rat chromosome 1. We measured blood glucose and plasma insulin levels after a glucose tolerance test in 782 male HS rats. Using 97 SSLP markers, we genotyped a 68 Mb region on rat chromosome 1 previously implicated in glucose and insulin regulation. We used linkage disequilibrium mapping by mixed model regression with inferred descent to identify a region from 198.85 to 205.9 that contains one or more quantitative trait loci (QTL) for fasting insulin and a measure of insulin resistance, the quantitative insulin sensitivity check index. This region also encompasses loci identified for fasting glucose and Insulin_AUC (area under the curve). A separate <3 Mb QTL was identified for body weight. Using a novel penalized regression method we then estimated effects of alternative haplotype pairings under each locus. These studies highlight the utility of HS rats for fine-mapping genetic loci involved in the underlying causes of T2D.

PAD4 is not essential for disease in the K/BxN murine autoantibody-mediated model of arthritis

Introduction

Both murine and human genome-wide association studies have implicated peptidyl arginine deiminase (PAD4) as a susceptibility gene in rheumatoid arthritis (RA). In addition, patients with RA commonly have autoantibodies which recognize PAD4 or and/or citrullinated peptides. This study aims to evaluate the role of PAD4 in the effector phase of arthritis.

Methods

PAD4 knock out (KO) and wild type (WT) C57BL/6J mice were injected with K/BxN sera to induce disease. Progression of disease was monitored by measuring paw and ankle swelling and clinical indexes of disease, and pathogenesis was assessed by indexing of clinical progression on paws collected from WT and PAD4 KO mice injected with K/BxN serum. PAD4 activity was determined by visualization of neutrophil extracellular traps (NETs) and immunohistological analysis of histone citrullination.

Results

PAD4 activity is readily detectable in the inflamed synovium of WT but not PAD4 deficient animals, as demonstrated by histone citrullination and NET formation. However, PAD4 WT and KO animals develop K/BxN serum transfer disease with comparable severity and kinetics, with no statistically significant differences noted in clinical scores, swelling, joint erosion or joint invasion.

Conclusions

PAD4 WT and KO mice develop disease in the K/BxN serum transfer model of arthritis with similar severity and kinetics, indicating that PAD4 is dispensable in this effector phase model of disease.

Genetic variability of transcript abundance in pig peri-mortem skeletal muscle: eQTL localized genes involved in stress response, cell death, muscle disorders and metabolism

Background

The genetics of transcript-level variation is an exciting field that has recently given rise to many studies. Genetical genomics studies have mainly focused on cell lines, blood cells or adipose tissues, from human clinical samples or mice inbred lines. Few eQTL studies have focused on animal tissues sampled from outbred populations to reflect natural genetic variation of gene expression levels in animals. In this work, we analyzed gene expression in a whole tissue, pig skeletal muscle sampled from individuals from a half sib F2 family shortly after slaughtering.

Results

QTL detection on transcriptome measurements was performed on a family structured population. The analysis identified 335 eQTLs affecting the expression of 272 transcripts. The ontologic annotation of these eQTLs revealed an over-representation of genes encoding proteins involved in processes that are expected to be induced during muscle development and metabolism, cell morphology, assembly and organization and also in stress response and apoptosis. A gene functional network approach was used to evidence existing biological relationships between all the genes whose expression levels are influenced by eQTLs. eQTLs localization revealed a significant clustered organization of about half the genes located on segments of chromosome 1, 2, 10, 13, 16, and 18. Finally, the combined expression and genetic approaches pointed to putative cis-drivers of gene expression programs in skeletal muscle as COQ4 (SSC1), LOC100513192 (SSC18) where both the gene transcription unit and the eQTL affecting its expression level were shown to be localized in the same genomic region. This suggests cis-causing genetic polymorphims affecting gene expression levels, with (e.g. COQ4) or without (e.g. LOC100513192) potential pleiotropic effects that affect the expression of other genes (cluster of trans-eQTLs).

Conclusion

Genetic analysis of transcription levels revealed dependence among molecular phenotypes as being affected by variation at the same loci. We observed the genetic variation of molecular phenotypes in a specific situation of cellular stress thus contributing to a better description of muscle physiologic response. In turn, this suggests that large amounts of genetic variation, mediated through transcriptional networks, can drive transient cell response phenotypes and contribute to organismal adaptative potential.