Collaborative Cross Lines Research Articles

Host Genetics Background Affects Intestinal Cancer Development Associated with High-Fat Diet-Induced Obesity and Type 2 Diabetes

Background: Obesity and type 2 diabetes (T2D) promote inflammation, increasing the risk of colorectal cancer (CRC). High-fat diet (HFD)-induced obesity is key to these diseases through biological mechanisms. This study examined the impact of genetic background on the multimorbidity of intestinal cancer, T2D, and inflammation due to HFD-induced obesity. Methods: A cohort of 357 Collaborative Cross (CC) mice from 15 lines was fed either a control chow diet (CHD) or HFD for 12 weeks. Body weight was tracked biweekly, and blood glucose was assessed at weeks 6 and 12 via intraperitoneal glucose tolerance tests (IPGTT). At the study’s endpoint, intestinal polyps were counted, and cytokine profiles were analyzed to evaluate the inflammatory response. Results: HFD significantly increased blood glucose levels and body weight, with males showing higher susceptibility to T2D and obesity. Genetic variation across CC lines influenced glucose metabolism, body weight, and polyp development. Mice on HFD developed more intestinal polyps, with males showing higher counts than females. Cytokine analysis revealed diet-induced variations in pro-inflammatory markers like IL-6, IL-17A, and TNF-α, differing by genetic background and sex. Conclusions: Host genetics plays a crucial role in susceptibility to HFD-induced obesity, T2D, CRC, and inflammation. Genetic differences across CC lines contributed to variability in disease outcomes, providing insight into the genetic underpinnings of multimorbidity. This study supports gene-mapping efforts to develop personalized prevention and treatment strategies for these diseases.

The collaborative cross mouse for studying the effect of host genetic background on memory impairments due to obesity and diabetes.

Over the past few decades, a threefold increase in obesity and type 2 diabetes (T2D) has placed a heavy burden on the health-care system and society. Previous studies have shown correlations between obesity, T2D, and neurodegenerative diseases, including dementia. It is imperative to further understand the relationship between obesity, T2D, and cognitive deficits. This investigation tested and evaluated the cognitive impact of obesity and T2D induced by high-fat diet (HFD) and the effect of the host genetic background on the severity of cognitive decline caused by obesity and T2D in collaborative cross (CC) mice. The CC mice are a genetically diverse panel derived from eight inbred strains. Our findings demonstrated significant variations in the recorded phenotypes across different CC lines compared to the reference mouse line, C57BL/6J. CC037 line exhibited a substantial increase in body weight on HFD, whereas line CC005 exhibited differing responses based on sex. Glucose tolerance tests revealed significant variations, with some lines like CC005 showing a marked increase in area under the curve (AUC) values on HFD. Organ weights, including brain, spleen, liver, and kidney, varied significantly among the lines and sexes in response to HFD. Behavioral tests using the Morris water maze indicated that cognitive performance was differentially affected by diet and genetic background. Our study establishes a foundation for future quantitative trait loci mapping using CC lines and identifying genes underlying the comorbidity of Alzheimer's disease (AD), caused by obesity and T2D. The genetic components may offer new tools for early prediction and prevention.

Host Genetic Background Effect on Body Weight Changes Influenced by Heterozygous Smad4 Knockout Using Collaborative Cross Mouse Population.

Obesity and its attendant conditions have become major health problems worldwide, and obesity is currently ranked as the fifth most common cause of death globally. Complex environmental and genetic factors are causes of the current obesity epidemic. Diet, lifestyle, chemical exposure, and other confounding factors are difficult to manage in humans. The mice model is helpful in researching genetic BW gain because genetic and environmental risk factors can be controlled in mice. Studies in mouse strains with various genetic backgrounds and established genetic structures provide unparalleled opportunities to find and analyze trait-related genomic loci. In this study, we used the Collaborative Cross (CC), a large panel of recombinant inbred mouse strains, to present a predictive study using heterozygous Smad4 knockout profiles of CC mice to understand and effectively identify predispositions to body weight gain. Male C57Bl/6J Smad4+/- mice were mated with female mice from 10 different CC lines to create F1 mice (Smad4+/-x CC). Body weight (BW) was measured weekly until week 16 and then monthly until the end of the study (week 48). The heritability (H2) of the assessed traits was estimated and presented. Comparative analysis of various machine learning algorithms for predicting the BW changes and genotype of mice was conducted. Our data showed that the body weight records of F1 mice with different CC lines differed between wild-type and mutant Smad4 mice during the experiment. Genetic background affects weight gain and some lines gained more weight in the presence of heterozygous Smad4 knockout, while others gained less, but, in general, the mutation caused overweight mice, except for a few lines. In both control and mutant groups, female %BW had a higher heritability (H2) value than males. Additionally, both sexes with wild-type genotypes showed higher heritability values than the mutant group. Logistic regression provides the most accurate mouse genotype predictions using machine learning. We plan to validate the proposed method on more CC lines and mice per line to expand the literature on machine learning for BW prediction.

A study of the influence of genetic variance and sex on the density and thickness of the calvarial bone in collaborative cross mice.

Bone microarchitecture is affected by multiple genes, each having a small effect on the external appearance. It is thus challenging to characterize the genes and their specific effect on bone thickness and porosity. The purpose of this study was to assess the heritability and the genetic variation effect, as well as the sex effect on the calvarial bone thickness (Ca.Th) and calvarial porosity (%PoV) using the Collaborative Cross (CC) mouse population. In the study we examined the parietal bones of 56 mice from 9 lines of CC mice. Morphometric parameters were evaluated using microcomputed tomography (μCT) and included Ca.Th and %PoV. We then evaluated heritability, genetic versus environmental variance and the sex effect for these parameters. Our morphometric analysis showed that Ca.Th and %PoV are both significantly different among the CC lines with a broad sense heritability of 0.78 and 0.90, respectively. The sex effect within the lines was significant in line IL111 and showed higher values of Ca.Th and %PoV in females compared to males. In line IL19 there was a borderline sex effect in Ca.Th in which males showed higher values than females. These results stress the complexity of sex and genotype interactions controlling Ca.Th and %PoV, as the skeletal sexual dimorphism was dependent on the genetic background. This study also shows that the CC population is a powerful tool for establishing the genetic effect on these traits.

High-fat diet and oral infection induced type 2 diabetes and obesity development under different genetic backgrounds.

Type 2 diabetes (T2D) is an adult-onset and obese form of diabetes caused by an interplay between genetic, epigenetic, and environmental components. Here, we have assessed a cohort of 11 genetically different collaborative cross (CC) mouse lines comprised of both sexes for T2D and obesity developments in response to oral infection and high-fat diet (HFD) challenges. Mice were fed with either the HFD or the standard chow diet (control group) for 12 weeks starting at the age of 8 weeks. At week 5 of the experiment, half of the mice of each diet group were infected with Porphyromonas gingivalis and Fusobacterium nucleatum bacteria strains. Throughout the 12-week experimental period, body weight (BW) was recorded biweekly, and intraperitoneal glucose tolerance tests were performed at weeks 6 and 12 of the experiment to evaluate the glucose tolerance status of mice. Statistical analysis has shown the significance of phenotypic variations between the CC lines, which have different genetic backgrounds and sex effects in different experimental groups. The heritability of the studied phenotypes was estimated and ranged between 0.45 and 0.85. We applied machine learning methods to make an early call for T2D and its prognosis. The results showed that classification with random forest could reach the highest accuracy classification(ACC=0.91) when all the attributes were used. Using sex, diet, infection status, initial BW, and area under the curve (AUC) at week 6, we could classify the final phenotypes/outcomes at the end stage of the experiment (at 12 weeks).

Studying the Pharmagenomic effect of Portulaca oleracea extract on anti-diabetic therapy using the Collaborative Cross mice

BackgroundPortulaca oleracea L. (PO) is a herb widely used in folk medicine as antioxidant and mainly as an anti-diabetic. However, scientific evidence of its effects remains very limited. Here we aim to unravel the effect of the host genetic background on the PO treatment in the development of obesity and type 2 diabetes (T2D) using the genetically diverse Collaborative Cross (CC) mouse model, which could contribute to better understand and design personalized medical treatment. ResultsWe have studied the PO treatments efficacy on reduction of body weight (BW) and glucose tolerance ability in 221 mice of 13 different CC lines as a response to two different diets: the control match diet (CMD – 10% fat) as a control group and the high-fat diet (HFD – 60% fat) as the experiment group. Glucose tolerance ability was determined by a 180 minutes Intraperitoneal Glucose Tolerance Test (IPGTT) and the calculation of the area under the curve (AUC) was made. PO treatments started in week 12 of the dietary challenge and lasted for 4 weeks. PO was given to the mice every other day by intraperitoneal (IP) injection at concentration of 200mg/kg. The results showed significant sex effect across the different lines and assessed traits; therefore, male and female mice data was analyzed separately. Sex differences among lines were analyzed by ANOVA and shown to be significant (P <0.05) for BW and IPGTT-AUC in three time points: initial time point, after three months of dietary challenge and when PO treatment completed. Additionally, the results showed a significant increase in BW for both female and males maintained on HFD and CMD for 12 weeks period. Furthermore, significant increase in Total AUC values for both sexes maintained on HFD was showed while mice maintained on CMD did not develop any insulin resistance keeping their glucose levels slightly lower than the initial time point. Thenceforth, a four weeks of PO treatment showed a significant decrease in glucose levels in the HFD group, presenting that male mice were more sensitive to the treatment than females. Furthermore, PO treatment seemed to affect female mice fed with CMD rather than male mice maintained on the same diet. ConclusionsOur findings confirm the effect of PO treatment as an antidiabetic agent due to its significant effect in reducing glucose levels in CC mice that developed T2D induced by HFD. Additionally, a stabilizing effect on body weight as a response to PO treatment was shown. Variations among the different CC lines might be explained by differences in host genetics. Further studies can provide a base for a pharmacogenetics approach to treat T2D.

Genetically diverse mouse models of Alzheimer’s Disease reveal an association between amyloid deposition and glycan metabolism in the brain

AbstractBackgroundVarying degrees of cerebral amyloid angiopathy (CAA) co‐occur with parenchymal amyloid deposition in majority of Alzheimer’s Disease (AD) cases. However, common mouse models of familial AD generated on a single inbred strain do not recapitulate the spectrum of parenchymal and vascular amyloid pathogenesis in the brain. To better represent phenotypic diversity in AD, we generated a panel of genetically diverse Collaborative Cross (CC) mouse strains harboring APOE4 allele and amyloidogenic mutations.MethodFive CC strains (CC002, CC006, CC013, CC037 and CC041) were selected for maximal genetic and transcriptional variation in AD‐relevant genes. Selected CC strains were crossed to C57BL/6J (B6J) mice homozygous for humanized APOE4 allele and carrying mutant APP and PS1 alleles (APPswe , PS1de9 ). Cohorts of male and female B6JCCnF1.APOE4.APP/PS1 mice and controls were aged to 8 months, and brain hemispheres were processed for RNA‐Seq transcriptomics and neuropathological assessment. Weighted Gene Co‐Expression Networks Analysis (WGCNA) and gene set enrichment analysis were performed to identify gene modules and biological pathways associated with plaque deposition and CAA in CC strains.ResultNeuropathological assessment revealed significant strain and sex‐dependent differences in both parenchymal and vascular amyloid pathology. Highest levels of plaque deposition in cortex and hippocampus was observed in female CC002 mice. Female mice had higher plaque load compared to male mice in all strains, whereas CAA score was higher in males and in CC037 strain. CC006 represented lowest levels of plaque deposition and CAA at comparable levels with B6J mice. RNA‐Seq data revealed a common microglia/neuroinflammation related transcriptional response observed in all strains and both sexes. On the other hand, gene expression signatures associated with varying levels of plaque deposition and CAA revealed alterations in metabolic pathways, in particular glucose, lipid and glycan metabolisms.ConclusionOur results suggest that major genetic diversity modulates distinctive parenchymal and vascular amyloid phenotypes, and differentially impacts transcriptomic signatures in the mouse brain. Overall, CC lines mouse models better represent the spectrum of neuropathological and molecular phenotypes associated with AD.

Incorporating genetic diversity to improve alignment of mouse models to human Alzheimer’s disease

Previous work by our labs, and others, reveal the benefits of incorporating diverse mouse strains to better model human Alzheimer's disease (AD). For instance, mouse models of AD on genetically distinct wild-derived mouse strains demonstrated robust differences in immune response to amyloid and neurodegeneration, better representing the phenotypic spectrum of AD than previous models. To further investigate the importance of genetic diversity, as part of MODEL-AD, we generated AD-relevant mouse models on Collaborative Cross (CC) lines background, a recombinant inbred mouse panel created from eight highly diverse founder strains.C57BL/6J (B6J) mice homozygous for humanized APOE4 allele and carrying mutant APP and PS1 alleles (APPswe , PS1de9 ) were crossed to five CC strains that were selected based on variation in AD-relevant genes. Cohorts of male and female B6JCCnF1.APOE4.APP/PS1 mice and controls were aged to 8 months (a mid-point for amyloid deposition in B6.APP/PS1 mice) and brain hemispheres processed for RNA-Seq and neuropathological assessment. Expectation Maximization for Allele Specific Expression (EMASE) tool was used to quantify transcriptome-wide expression at allelic level. Differential expression and KEGG pathway enrichment analysis were performed to determine altered molecular processes in CC strains. Strain specific transcriptional signatures were mapped to co-expression gene modules of human Late-Onset AD (LOAD) from the AMP-AD consortium. Neuropathological assessment included characterization of plaque deposition, Tau pathology, glial activation, neurodegeneration and cerebrovascular health.RNA-Seq analysis revealed up-regulation of neuroinflammation related pathways (lysosome, complement and coagulation cascades) in all CC strains as an effect of mutant APP and PS1 transgenes in presence of APOE4 allele. On the other hand, we observed significant CC strain and sex specific variation in immune (Fc gamma R-mediated phagocytosis) and metabolic (glycosphingolipid biosynthesis) response to amyloid pathogenesis. Alignment with human LOAD signatures revealed high strain and sex specific variation in correlation with synaptic signaling, cell cycle and DNA repair related gene modules. Overall, novel AD mouse models that incorporated CC lines demonstrated increased alignment to human AD-like transcriptomic signatures compared to B6J.This work builds on previous work highlighting the strengths of including multiple diverse mouse strains to better model complex neurodegenerative disorders such as AD and related dementias.

Genetic mapping of novel modifiers for ApcMin induced intestinal polyps\u2019 development using the genetic architecture power of the collaborative cross mice

BackgroundFamilial adenomatous polyposis is an inherited genetic disease, characterized by colorectal polyps. It is caused by inactivating mutations in the Adenomatous polyposis coli (Apc) gene. Mice carrying a nonsense mutation in the Apc gene at R850, which is designated ApcMin/+ (Multiple intestinal neoplasia), develop intestinal adenomas. Several genetic modifier loci of Min (Mom) were previously mapped, but so far, most of the underlying genes have not been identified. To identify novel modifier loci associated with ApcMin/+, we performed quantitative trait loci (QTL) analysis for polyp development using 49 F1 crosses between different Collaborative Cross (CC) lines and C57BL/6 J-ApcMin/+mice. The CC population is a genetic reference panel of recombinant inbred lines, each line independently descended from eight genetically diverse founder strains. C57BL/6 J-ApcMin/+ males were mated with females from 49 CC lines. F1 offspring were terminated at 23 weeks and polyp counts from three sub-regions (SB1–3) of small intestinal and colon were recorded.ResultsThe number of polyps in all these sub-regions and colon varied significantly between the different CC lines. At 95% genome-wide significance, we mapped nine novel QTL for variation in polyp number, with distinct QTL associated with each intestinal sub-region. QTL confidence intervals varied in width between 2.63–17.79 Mb. We extracted all genes in the mapped QTL at 90 and 95% CI levels using the BioInfoMiner online platform to extract, significantly enriched pathways and key linker genes, that act as regulatory and orchestrators of the phenotypic landscape associated with the ApcMin/+ mutation.ConclusionsGenomic structure of the CC lines has allowed us to identify novel modifiers and confirmed some of the previously mapped modifiers. Key genes involved mainly in metabolic and immunological processes were identified. Future steps in this analysis will be to identify regulatory elements – and possible epistatic effects – located in the mapped QTL.

The First Immunocompetent Mouse Model of Strictly Human Pathogen, Borrelia recurrentis.

The spirochetal bacterium Borrelia recurrentis causes louse-borne relapsing fever (LBRF). B. recurrentis is unique because, as opposed to other Borrelia spirochetes, this strictly human pathogen is transmitted by lice. Despite the high mortality and historically proven epidemic potential and current outbreaks in African countries and Western Europe, research on LBRF has been obstructed by the lack of suitable animal models. The previously used grivet monkey model is associated with ethical concerns, among other issues. An existing immunodeficient mouse model does not limit bacteremia due to its impaired immune system. In this study, we used genetically diverse Collaborative Cross (CC) lines to develop the first LBRF immunocompetent mouse model. Out of 12 CC lines tested, CC046 mice consistently developed B. recurrentis-induced spirochetemia during the first 3 days postchallenge as concordantly detected by dark-field microscopy, culture, and quantitative PCR. However, spirochetemia was not detected from day 4 through day 10 postchallenge. The high-level spirochetemia (>107 cells/ml of blood) observed in CC046 mice was similar to that recorded in LBRF patients as well as immunocompetent mouse strains experimentally infected by tick-borne relapsing fever (RF) spirochetes, Borrelia hermsii and Borrelia persica. In contrast to the Old World and New World RF spirochetes, which develop multiple relapses (n = 3 to 9), B. recurrentis produced only single culture-detectable spirochetemia in CC046 mice. The lack of relapses may not be surprising, as LBRF patients and the grivet monkey model usually develop no or only 1 to 2 spirochetemic relapses. The novel model will now allow scientists to study B. recurrentis in the context of intact immunity.

Studying host genetic background effects on multimorbidity of intestinal cancer development, type 2 diabetes and obesity in response to oral bacterial infection and high-fat diet using the collaborative cross (CC) lines.

BackgroundMultimorbidity of intestinal cancer (IC), type 2 diabetes (T2D) and obesity is a complex set of diseases, affected by environmental and genetic risk factors. High‐fat diet (HFD) and oral bacterial infection play important roles in the etiology of these diseases through inflammation and various biological mechanisms.MethodsTo study the complexity of this multimorbidity, we used the collaborative cross (CC) mouse genetics reference population. We aimed to study the multimorbidity of IC, T2D, and obesity using CC lines, measuring their responses to HFD and oral bacterial infection. The study used 63 mice of both sexes generated from two CC lines (IL557 and IL711). For 12 weeks, experimental mice were maintained on specific dietary regimes combined with co‐infection with oral bacteria Porphyromonas gingivalis and Fusobacterium nucleatum, while control groups were not infected. Body weight (BW) and results of a intraperitoneal glucose tolerance test (IPGTT) were recorded at the end of 12 weeks, after which length and size of the intestines were assessed for polyp counts.ResultsPolyp counts ranged between 2 and 10 per CC line. The combination of HFD and infection significantly reduced (P < .01) the colon polyp size of IL557 females to 2.5 cm2, compared to the other groups. Comparing BW gain, IL557 males on HFD gained 18 g, while the females gained 10 g under the same conditions and showed the highest area under curve (AUC) values of 40 000‐45 000 (min mg/dL) in the IPGTT.ConclusionThe results show that mice from different genetic backgrounds respond differently to a high fat diet and oral infection in terms of polyp development and glucose tolerance, and this effect is gender related.

Studying the pharmacogenomic effect of cranberry extract on reducing body weight using collaborative cross mice.

The non-dialyzable material (NDM) of polyphenol-rich cranberry extract (CRE) powder (NDM-CRE) was studied for its effect of inducing body weight (BW) loss in 13 different mouse lines with well-defined genetically diverse backgrounds, named the collaborative cross (CC). From the age of 8 weeks, the mice were maintained on a high-fat diet (HFD) for 18 weeks, to induce obesity, and BW was measured biweekly. From week 12, CRE was injected intraperitoneally (IP) (50 mg kg-1) 3 times a week per mouse for a 6 week period. Statistical analysis results have shown a significant increase in body weight between week 0 and week 12; the increase in BW of 13 lines of mice on HFD was in the range of 10.41% to 68.65% for males and 9.78% to 64.74% for females. After injecting NDM-CRE extract, our analysis has shown an induced change in BW between week 12 and week 18. In males, NDM-CRE caused a significant decrease in BW of 5 out of the 13 lines in the range of -5.68% to -16.69% and a significant increase of 8.31% in BW of one male line, whereas in seven lines there was no significant decrease (-2.14% to -4.09%). In females, NDM-CRE caused a significant decrease in BW of 5 out of the 13 lines in the range of -3.90% to -11.83%, whereas in eight lines there were no significant changes in BW and it ranged between -1.50% and 4.90%. The broad-sense heritability (H2) and genetic coefficient of variation (CVg) were estimated and found to be between 0.71 and 0.81 for H2, and 0.18 and 0.24 for CVg of females and males, respectively, with respect to the efficacy of NDM-CRE on body weight reduction. Our results have shown that hosts with different genetic backgrounds respond differently to body weight increase, as well as to NDM-CRE treatment for body weight reduction. These results provide a platform for assessing more CC lines and mapping genes underlying the efficacy of the NDM-CRE treatment as a way of understanding pharmacogenomics.

Mapping the Effects of Genetic Variation on Chromatin State and Gene Expression Reveals Loci That Control Ground State Pluripotency.

Mouse embryonic stem cells (mESCs) cultured in the presence of LIF occupy a ground state with highly active pluripotency-associated transcriptional and epigenetic circuitry. However, ground state pluripotency in some inbred strain backgrounds is unstable in the absence of ERK1/2 and GSK3 inhibition. Using an unbiased genetic approach, we dissect the basis of this divergent response to extracellular cues by profiling gene expression and chromatin accessibility in 170 genetically heterogeneous mESCs. We map thousands of loci affecting chromatin accessibility and/or transcript abundance, including 10 QTL hotspots where genetic variation at a single locus coordinates the regulation of genes throughout the genome. For one hotspot, we identify a single enhancer variant ∼10 kb upstream of Lifr associated with chromatin accessibility and mediating a cascade of molecular events affecting pluripotency. We validate causation through reciprocal allele swaps, demonstrating the functional consequences of noncoding variation in gene regulatory networks that stabilize pluripotent states invitro.

Assessing the host genetic background effects on type 2 diabetes and obesity development in response to mixed-oral bacteria and high-fat diet using the collaborative cross mouse model.

BackgroundHost genetic background and sex, play central roles in defining the pathogenesis of type 2 diabetes (T2D), obesity and infectious diseases. Our previous studies demonstrated the utilization of genetically highly diverse inbred mouse lines, namely collaborative cross (CC), for dissecting host susceptibility for the development of T2D and obesity, showing significant variations following high‐fat (42% fat) diet (HFD). Here, we aimed to assessing the host genetic background and sex effects on T2D and obesity development in response to oral‐mixed bacterial infection and HFD using the CC lines.Materials and MethodsStudy cohort consists of 97 mice from 2 CC lines (both sexes), maintained on either HFD or Standard diet (CHD) for 12 weeks. At week 5 a group of mice from each diet were infected with Porphyromonas gingivalis (Pg) and Fusobacterium nucleatum (Fn) bacteria (control groups without infection). Body weight (BW) and glucose tolerance ability were assessed at the end time point of the experiment.ResultsThe CC lines varied (P < .05) at their BW gain and glucose tolerance ability (with sex effect) in response to diets and/or infection, showing opposite responses despite sharing the same environmental conditions. The combination of diet and infection enhances BW accumulation for IL1912, while restraints it for IL72. As for glucose tolerance ability, only females (both lines) were deteriorated in response to infection.ConclusionsThis study emphasizes the power of the CC mouse population for the characterization of host genetic makeup for defining the susceptibility of the individual to development of obesity and/or impaired glucose tolerance.

Translation of mouse model to human gives insights into periodontitis etiology

To suggest candidate genes involved in periodontitis, we combined gene expression data of periodontal biopsies from Collaborative Cross (CC) mouse lines, with previous reported quantitative trait loci (QTL) in mouse and with human genome-wide association studies (GWAS) associated with periodontitis. Periodontal samples from two susceptible, two resistant and two lines that showed bone formation after periodontal infection were collected during infection and naïve status. Differential expressed genes (DEGs) were analyzed in a case-control and case-only design. After infection, eleven protein-coding genes were significantly stronger expressed in resistant CC lines compared to susceptible ones. Of these, the most upregulated genes were MMP20 (P = 0.001), RSPO4 (P = 0.032), CALB1 (P = 1.06×10−4), and AMTN (P = 0.05). In addition, human orthologous of candidate genes were tested for their association in a case-controls samples of aggressive (AgP) and chronic (CP) periodontitis (5,095 cases, 9,908 controls). In this analysis, variants at two loci, TTLL11/PTGS1 (rs9695213, P = 5.77×10−5) and RNASE2 (rs2771342, P = 2.84×10−5) suggested association with both AgP and CP. In the association analysis with AgP only, the most significant associations were located at the HLA loci HLA-DQH1 (rs9271850, P = 2.52×10−14) and HLA-DPA1 (rs17214512, P = 5.14×10−5). This study demonstrates the utility of the CC RIL populations as a suitable model to investigate the mechanism of periodontal disease.

Transcriptional Correlates of Tolerance and Lethality in Mice Predict Ebola Virus Disease Patient Outcomes

Host response to infection is a major determinant of disease severity in Ebola virus disease (EVD), but gene expression programs associated with outcome are poorly characterized. Collaborative Cross (CC) mice develop strain-dependent EVD phenotypes of differential severity, ranging from tolerance to lethality. We screen 10 CC lines and identify clinical, virologic, and transcriptomic features that distinguish tolerant from lethal outcomes. Tolerance is associated with tightly regulated induction of immune and inflammatory responses shortly following infection, as well as reduced inflammatory macrophages and increased antigen-presenting cells, B-1 cells, and γδ Tcells. Lethal disease is characterized by suppressed early gene expression and reduced lymphocytes, followed by uncontrolled inflammatory signaling, leading to death. We apply machine learning to predict outcomes with 99% accuracy in mice using transcriptomic profiles. This signature predicts outcomes in a cohort of EVD patients from western Africa with 75% accuracy, demonstrating potential clinical utility.

Designing a QTL Mapping Study for Implementation in the Realized Collaborative Cross Genetic Reference Population.

The Collaborative Cross (CC) mouse resource is a next-generation mouse genetic reference population (GRP) designed for high-resolution mapping of quantitative trait loci (QTL) of large effect affecting complex traits during health and disease. The CC resource consists of a set of 72 recombinant inbred lines (RILs) generated by reciprocal crossing of five classical and three wild-derived mouse founder strains. Complex traits are controlled by variations within multiple genes and environmental factors, and their mutual interactions. These traits are observed at multiple levels of the animals' systems, including metabolism, body weight, immune profile, and susceptibility or resistance to the development and progress of infectious or chronic diseases. Herein, we present general guidelines for design of QTL mapping experiments using the CC resource-along with full step-by-step protocols and methods that were implemented in our lab for the phenotypic and genotypic characterization of the different CC lines-for mapping the genes underlying host response to infectious and chronic diseases. © 2019 by John Wiley & Sons, Inc. Basic Protocol 1: CC lines for whole body mass index (BMI) Basic Protocol 2: A detailed assessment of the power to detect effect sizes based on the number of lines used, and the number of replicates per line Basic Protocol 3: Obtaining power for QTL with given target effect by interpolating in Table 1 of Keele etal. (2019).

Identification of Candidate Risk Factor Genes for Human Idelalisib Toxicity Using a Collaborative Cross Approach.

Idelalisib is a phosphatidylinositol 3-kinase inhibitor highly selective for the delta isoform that has shown good efficacy in treating chronic lymphocytic leukemia and follicular lymphoma. In clinical trials, however, idelalisib was associated with rare, but potentially serious liver and lung toxicities. In this study, we used the Collaborative Cross (CC) mouse population to identify genetic factors associated with the drug response that may inform risk management strategies for idelalisib in humans. Eight male mice (4 matched pairs) from 50 CC lines were treated once daily for 14 days by oral gavage with either vehicle or idelalisib at a dose selected to achieve clinically relevant peak plasma concentrations (150 mg/kg/day). The drug was well tolerated across all CC lines, and there were no observations of overt liver injury. Differences across CC lines were seen in drug concentration in plasma samples collected at the approximate Tmax on study Days 1, 7, and 14. There were also small but statistically significant treatment-induced alterations in plasma total bile acids and microRNA-122, and these may indicate early hepatocellular stress required for immune-mediated hepatotoxicity in humans. Idelalisib treatment further induced significant elevations in the total cell count of terminal bronchoalveolar lavage fluid, which may be analogous to pneumonitis observed in the clinic. Genetic mapping identified loci associated with interim plasma idelalisib concentration and the other 3 treatment-related endpoints. Thirteen priority candidate quantitative trait genes identified in CC mice may now guide interrogation of risk factors for adverse drug responses associated with idelalisib in humans.

Efficient protocols and methods for high-throughput utilization of the Collaborative Cross mouse model for dissecting the genetic basis of complex traits.

The Collaborative Cross (CC) mouse model is a next‐generation mouse genetic reference population (GRP) designated for a high‐resolution quantitative trait loci (QTL) mapping of complex traits during health and disease. The CC lines were generated from reciprocal crosses of eight divergent mouse founder strains composed of five classical and three wild‐derived strains. Complex traits are defined to be controlled by variations within multiple genes and the gene/environment interactions. In this article, we introduce and present variety of protocols and results of studying the host response to infectious and chronic diseases, including type 2 diabetes and metabolic diseases, body composition, immune response, colorectal cancer, susceptibility to Aspergillus fumigatus, Klebsiella pneumoniae, Pseudomonas aeruginosa, sepsis, and mixed infections of Porphyromonas gingivalis and Fusobacterium nucleatum, which were conducted at our laboratory using the CC mouse population. These traits are observed at multiple levels of the body systems, including metabolism, body weight, immune profile, susceptibility or resistance to the development and progress of infectious or chronic diseases. Herein, we present full protocols and step‐by‐step methods, implemented in our laboratory for the phenotypic and genotypic characterization of the different CC lines, mapping the gene underlying the host response to these infections and chronic diseases. The CC mouse model is a unique and powerful GRP for dissecting the host genetic architectures underlying complex traits, including chronic and infectious diseases.

Transcriptional Correlates of Tolerance and Lethality in Mice Predict Ebola Virus Disease Patient Outcomes

Host response to infection is a major determinant of disease severity in Ebola virus disease (EVD), but gene expression programs associated with clinical outcome are poorly characterized. Using the Collaborative Cross (CC) mouse model of genetic diversity, we developed a model of differential EVD severity. CC mice develop a strain-dependent spectrum of distinct EVD phenotypes, ranging from tolerance (mild, transient disease with full recovery) to lethality (severe disease that may include hemorrhagic syndrome). We performed a screen of 10 CC lines with differential phenotypes and identified clinical, virologic, and transcriptomic features that distinguish tolerant from lethal outcomes. Tolerance is associated with tightly regulated induction of immune and inflammatory responses early following infection, as well as reduced numbers of inflammatory macrophages and increased numbers of mature antigen-presenting cells, B-1 cells, and γδ T cells, allowing for control of viral replication and subsequent recovery. Lethal disease is characterized by broad suppression of early gene expression and reduced quantitiesof lymphocytes, followed by uncontrolled inflammatory signaling leading to death. Using machine learning classification, we developed and trained a transcriptomic signature that predicted outcome in CC mice at any time point post-infection with 99% accuracy. This signature predicted outcome in a cohort of EVD patients from West Africa with 75% accuracy, demonstrating its utility as a prognostic tool to guide EVD patient treatment in future outbreaks.