Alzheimer's disease affects more than 35 million people worldwide but there is no known cure. Age is the strongest risk factor for Alzheimer's disease but it is not clear how age-related changes impact the disease. Here, we used a mouse model of Alzheimer's disease to identify age-specific changes that occur prior to and at the onset of traditional Alzheimer-related phenotypes including amyloid plaque formation. To identify these early events we used transcriptional profiling of mouse brains combined with computational approaches including singular value decomposition and hierarchical clustering.

The tandem duplicator phenotype (TDP) is a genome-wide instability configuration primarily observed in breast, ovarian, and endometrial carcinomas. Here, we stratify TDP tumors by classifying their tandem duplications (TDs) into three span intervals, with modal values of 11 kb, 231 kb, and 1.7 Mb, respectively. TDPs with ∼11 kb TDs feature loss of TP53 and BRCA1. TDPs with ∼231 kb and ∼1.7 Mb TDs associate with CCNE1 pathway activation and CDK12 disruptions, respectively. We demonstrate that p53 and BRCA1 conjoint abrogation drives TDP induction by generating short-span TDP mammary tumors in genetically modified mice lacking them. Lastly, we show how TDs in TDP tumors disrupt heterogeneous combinations of tumor suppressors and chromatin topologically associating domains while duplicating oncogenes and super-enhancers.

Genome-wide association studies (GWAS) for late onset Alzheimer's disease (AD) may miss genetic variants relevant for delineating disease stages when using clinically defined case/control as a phenotype due to its loose definition and heterogeneity.

Hyperexcitability and epileptiform activity are commonplace in Alzheimer's disease (AD) patients and associated with impaired cognitive function. The anti-seizure drug levetiracetam (LEV) is currently being evaluated in clinical trials for ability to reduce epileptiform activity and improve cognitive function in AD. The purpose of our studies was to establish a pharmacokinetic/pharmacodynamic (PK/PD) relationship with LEV in an amyloidogenic mouse model of AD to enable predictive preclinical to clinical translation, using the rigorous preclinical testing pipeline of the Model Organism Development and Evaluation for Late-Onset Alzheimer's Disease Preclinical Testing Core.

Mutations in the apicobasal polarity gene CRB1 lead to diverse retinal diseases, such as Leber congenital amaurosis, cone-rod dystrophy, retinitis pigmentosa (with and without Coats-like vasculopathy), foveal retinoschisis, macular dystrophy, and pigmented paravenous chorioretinal atrophy. Limited correlation between disease phenotypes and CRB1 alleles, and evidence that patients sharing the same alleles often present with different disease features, suggest that genetic modifiers contribute to clinical variation. Similarly, the retinal phenotype of mice bearing the Crb1 retinal degeneration 8 (rd8) allele varies with genetic background. Here, we initiated a sensitized chemical mutagenesis screen in B6.Cg-Crb1rd8/Pjn, a strain with a mild clinical presentation, to identify genetic modifiers that cause a more severe disease phenotype. Two models from this screen, Tvrm266 and Tvrm323, exhibited increased retinal dysplasia. Genetic mapping with high-throughput exome and candidate-gene sequencing identified causative mutations in Arhgef12 and Prkci, respectively. Epistasis analysis of both strains indicated that the increased dysplastic phenotype required homozygosity of the Crb1rd8 allele. Retinal dysplastic lesions in Tvrm266 mice were smaller and caused less photoreceptor degeneration than those in Tvrm323 mice, which developed an early, large diffuse lesion phenotype. At one month of age, Müller glia and microglia mislocalization at dysplastic lesions in both modifier strains was similar to that in B6.Cg-Crb1rd8/Pjn mice but photoreceptor cell mislocalization was more extensive. External limiting membrane disruption was comparable in Tvrm266 and B6.Cg-Crb1rd8/Pjn mice but milder in Tvrm323 mice. Immunohistological analysis of mice at postnatal day 0 indicated a normal distribution of mitotic cells in Tvrm266 and Tvrm323 mice, suggesting normal early development. Aberrant electroretinography responses were observed in both models but functional decline was significant only in Tvrm323 mice. These results identify Arhgef12 and Prkci as modifier genes that differentially shape Crb1-associated retinal disease, which may be relevant to understanding clinical variability and underlying disease mechanisms in humans.

Restrictions on existing APOE mouse models have impacted research toward understanding the strongest genetic risk factor contributing to Alzheimer's disease (AD) and dementia, APOEε4 , by hindering observation of a key, common genotype in humans - APOEε3/ε4 . Human studies are typically underpowered to address APOEε4 allele risk as the APOEε4/ε4 genotype is rare, which leaves human and mouse research unsupported to evaluate the APOEε3/ε4 genotype on molecular and pathological risk for AD and dementia.

Obesity is recognized as a significant risk factor for Alzheimer's disease (AD). Studies have supported the notion that obesity accelerates AD-related pathophysiology in mouse models of AD. The majority of studies, to date, have focused on the use of early-onset AD models. Here, we evaluate the impact of genetic risk factors on late-onset AD (LOAD) in mice fed with a high fat/high sugar diet (HFD). We focused on three mouse models created through the IU/JAX/PITT MODEL-AD Center. These included a combined risk model with APOE4 and a variant in triggering receptor expressed on myeloid cells 2 (Trem2R47H ). We have termed this model, LOAD1. Additional variants including the M28L variant in phospholipase C Gamma 2 (Plcg2M28L ) and the 677C > T variant in methylenetetrahydrofolate reductase (Mthfr 677C > T ) were engineered by CRISPR onto LOAD1 to generate LOAD1.Plcg2M28L and LOAD1.Mthfr 677C > T . At 2 months of age, animals were placed on an HFD that induces obesity or a control diet (CD), until 12 months of age. Throughout the study, blood was collected to assess the levels of cholesterol and glucose. Positron emission tomography/computed tomography (PET/CT) was completed prior to sacrifice to image for glucose utilization and brain perfusion. After the completion of the study, blood and brains were collected for analysis. As expected, animals fed a HFD, showed a significant increase in body weight compared to those fed a CD. Glucose increased as a function of HFD in females only with cholesterol increasing in both sexes. Interestingly, LOAD1.Plcg2M28L demonstrated an increase in microglia density and alterations in regional brain glucose and perfusion on HFD. These changes were not observed in LOAD1 or LOAD1.Mthfr 677C > T animals fed with HFD. Furthermore, LOAD1.Plcg2M28L but not LOAD1.Mthfr 677C > T or LOAD1 animals showed transcriptomics correlations with human AD modules. Our results show that HFD affects the brain in a genotype-specific manner. Further insight into this process may have significant implications for the development of lifestyle interventions for the treatment of AD.

RNA sequencing and genetic data support spleen tyrosine kinase (SYK) and high affinity immunoglobulin epsilon receptor subunit gamma (FCER1G) as putative targets to be modulated for Alzheimer's disease (AD) therapy. FCER1G is a component of Fc receptor complexes that contain an immunoreceptor tyrosine-based activation motif (ITAM). SYK interacts with the Fc receptor by binding to doubly phosphorylated ITAM (p-ITAM) via its two tandem SH2 domains (SYK-tSH2). Interaction of the FCER1G p-ITAM with SYK-tSH2 enables SYK activation via phosphorylation. Since SYK activation is reported to exacerbate AD pathology, we hypothesized that disruption of this interaction would be beneficial for AD patients. Herein, we developed biochemical and biophysical assays to enable the discovery of small molecules that perturb the interaction between the FCER1G p-ITAM and SYK-tSH2. We identified two distinct chemotypes using a high-throughput screen (HTS) and orthogonally assessed their binding. Both chemotypes covalently modify SYK-tSH2 and inhibit its interaction with FCER1G p-ITAM, however, these compounds lack selectivity and this limits their utility as chemical tools.

Contemporary genetic studies are revealing the genetic complexity of many traits in humans and model organisms. Two hallmarks of this complexity are epistasis, meaning gene-gene interaction, and pleiotropy, in which one gene affects multiple phenotypes. Understanding the genetic architecture of complex traits requires addressing these phenomena, but interpreting the biological significance of epistasis and pleiotropy is often difficult. While epistasis reveals dependencies between genetic variants, it is often unclear how the activity of one variant is specifically modifying the other. Epistasis found in one phenotypic context may disappear in another context, rendering the genetic interaction ambiguous. Pleiotropy can suggest either redundant phenotype measures or gene variants that affect multiple biological processes. Here we present an R package, R/cape, which addresses these interpretation ambiguities by implementing a novel method to generate predictive and interpretable genetic networks that influence quantitative phenotypes. R/cape integrates information from multiple related phenotypes to constrain models of epistasis, thereby enhancing the detection of interactions that simultaneously describe all phenotypes. The networks inferred by R/cape are readily interpretable in terms of directed influences that indicate suppressive and enhancing effects of individual genetic variants on other variants, which in turn account for the variance in quantitative traits. We demonstrate the utility of R/cape by analyzing a mouse backcross, thereby discovering novel epistatic interactions influencing phenotypes related to obesity and diabetes. R/cape is an easy-to-use, platform-independent R package and can be applied to data from both genetic screens and a variety of segregating populations including backcrosses, intercrosses, and natural populations. The package is freely available under the GPL-3 license at http://cran.r-project.org/web/packages/cape.

Liposarcoma is an often fatal cancer of fat cells. Mechanisms of liposarcoma development are incompletely understood. The cleavage of fatty acids from acylglycerols (lipolysis) has been implicated in cancer. We generated mice with adipose tissue deficiency of two major enzymes of lipolysis, adipose triglyceride lipase (ATGL) and hormone-sensitive lipase (HSL), encoded respectively by Pnpla2 and Lipe. Adipocytes from double adipose knockout (DAKO) mice, deficient in both ATGL and HSL, showed near-complete deficiency of lipolysis. All DAKO mice developed liposarcoma between 11 and 14 months of age. No tumors occurred in single knockout or control mice. The transcriptome of DAKO adipose tissue showed marked differences from single knockout and normal controls as early as 3 months. Gpnmb and G0s2 were among the most highly dysregulated genes in premalignant and malignant DAKO adipose tissue, suggesting a potential utility as early markers of the disease. Similar changes of GPNMB and G0S2 expression were present in a human liposarcoma database. These results show that a previously-unknown, fully penetrant epistatic interaction between Pnpla2 and Lipe can cause liposarcoma in mice. DAKO mice provide a promising model for studying early premalignant changes that lead to late-onset malignant disease.

Scleroderma, or systemic sclerosis (SSc), is an autoimmune disease characterized by progressive fibrosis of the skin and internal organs. The most common cause of death in people with SSc is lung disease, but the pathogenesis of lung disease in SSc is insufficiently understood to devise specific treatment strategies. Developing targeted treatments requires not only the identification of molecular processes involved in SSc-associated lung disease, but also understanding of how these processes interact to drive pathology. One potentially powerful approach is to identify alleles that interact genetically to influence lung outcomes in patients with SSc. Analysis of interactions, rather than individual allele effects, has the potential to delineate molecular interactions that are important in SSc-related lung pathology. However, detecting genetic interactions, or epistasis, in human cohorts is challenging. Large numbers of variants with low minor allele frequencies, paired with heterogeneous disease presentation, reduce power to detect epistasis. Here we present an analysis that increases power to detect epistasis in human genome-wide association studies (GWAS). We tested for genetic interactions influencing lung function and autoantibody status in a cohort of 416 SSc patients. Using Matrix Epistasis to filter SNPs followed by the Combined Analysis of Pleiotropy and Epistasis (CAPE), we identified a network of interacting alleles influencing lung function in patients with SSc. In particular, we identified a three-gene network comprising WNT5A, RBMS3, and MSI2, which in combination influenced multiple pulmonary pathology measures. The associations of these genes with lung outcomes in SSc are novel and high-confidence. Furthermore, gene coexpression analysis suggested that the interactions we identified are tissue-specific, thus differentiating SSc-related pathogenic processes in lung from those in skin.

The continuous and non-synchronous nature of postnatal male germ-cell development has impeded stage-specific resolution of molecular events of mammalian meiotic prophase in the testis. Here the juvenile onset of spermatogenesis in mice is analyzed by combining cytological and transcriptomic data in a novel computational analysis that allows decomposition of the transcriptional programs of spermatogonia and meiotic prophase substages.

Late-onset Alzheimer's disease (LOAD) is the most common form of dementia worldwide. To date, animal models of Alzheimer's have focused on rare familial mutations, due to a lack of frank neuropathology from models based on common disease genes. Recent multi-cohort studies of postmortem human brain transcriptomes have identified a set of 30 gene co-expression modules associated with LOAD, providing a molecular catalog of relevant endophenotypes.

Adipor1tm1Dgen and Mfrprd6 mutant mice share similar eye disease characteristics. Previously, studies established a functional relationship of ADIPOR1 and MFRP proteins in maintaining retinal lipidome homeostasis and visual function. However, the independent and/or interactive contribution of both genes to similar disease phenotypes, including fundus spots, decreased axial length, and photoreceptor degeneration has yet to be examined. We performed a gene-interaction study where homozygous Adipor1tm1Dgen and Mfrprd6 mice were bred together and the resulting doubly heterozygous F1 offspring were intercrossed to produce 210 F2 progeny. Four-month-old mice from all nine genotypic combinations obtained in the F2 generation were assessed for white spots by fundus photo documentation, for axial length by caliper measurements, and for photoreceptor degeneration by histology. Two-way factorial ANOVA was performed to study individual as well as gene interaction effects on each phenotype. Here, we report the first observation of reduced axial length in Adipor1tmlDgen homozygotes. We show that while Adipor1 and Mfrp interact to affect spotting and degeneration, they act independently to control axial length, highlighting the complex functional association between these two genes. Further examination of the molecular basis of this interaction may help in uncovering mechanisms by which these genes perturb ocular homeostasis.

It is well understood that variation in relatedness among individuals, or kinship, can lead to false genetic associations. Multiple methods have been developed to adjust for kinship while maintaining power to detect true associations. However, relatively unstudied are the effects of kinship on genetic interaction test statistics. Here, we performed a survey of kinship effects on studies of six commonly used mouse populations. We measured inflation of main effect test statistics, genetic interaction test statistics, and interaction test statistics reparametrized by the Combined Analysis of Pleiotropy and Epistasis (CAPE). We also performed linear mixed model (LMM) kinship corrections using two types of kinship matrix: an overall kinship matrix calculated from the full set of genotyped markers, and a reduced kinship matrix, which left out markers on the chromosome(s) being tested. We found that test statistic inflation varied across populations and was driven largely by linkage disequilibrium. In contrast, there was no observable inflation in the genetic interaction test statistics. CAPE statistics were inflated at a level in between that of the main effects and the interaction effects. The overall kinship matrix overcorrected the inflation of main effect statistics relative to the reduced kinship matrix. The two types of kinship matrices had similar effects on the interaction statistics and CAPE statistics, although the overall kinship matrix trended toward a more severe correction. In conclusion, we recommend using an LMM kinship correction for both main effects and genetic interactions and further recommend that the kinship matrix be calculated from a reduced set of markers in which the chromosomes being tested are omitted from the calculation. This is particularly important in populations with substantial population structure, such as recombinant inbred lines in which genomic replicates are used.

Genome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimer's disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action.

Cell differentiation is driven by changes in gene expression that manifest as changes in cellular phenotype or function. Altered cellular phenotypes, stemming from genetic mutations or other perturbations, are widely assumed to directly correspond to changes in the transcriptome and vice versa. Here, we exploited the cytologically well-defined Prdm9 mutant mouse as a model of developmental arrest to test whether parallel programs of cellular differentiation and gene expression are tightly coordinated, or can be disassociated. By comparing cytological phenotype markers and transcriptomes in wild-type and mutant spermatocytes, we identified multiple instances of cellular and molecular uncoupling in Prdm9-/- mutants. Most notably, although Prdm9-/- germ cells undergo cytological arrest in a late-leptotene/zygotene stage, they nevertheless develop gene expression signatures characteristic of later developmental substages. These findings suggest that transcriptomic changes may not reliably map to cellular phenotypes in developmentally perturbed systems.

The extent and strength of epistasis is commonly unresolved in genetic studies, and observed epistasis is often difficult to interpret in terms of biological consequences or overall genetic architecture. We investigated the prevalence and consequences of epistasis by analyzing four body composition phenotypes--body weight, body fat percentage, femoral density, and femoral circumference--in a large F2 intercross of B6-lit/lit and C3.B6-lit/lit mice. We used Combined Analysis of Pleiotropy and Epistasis (CAPE) to examine interactions for the four phenotypes simultaneously, which revealed an extensive directed network of genetic loci interacting with each other, circulating IGF1, and sex to influence these phenotypes. The majority of epistatic interactions had small effects relative to additive effects of individual loci, and tended to stabilize phenotypes towards the mean of the population rather than extremes. Interactive effects of two alleles inherited from one parental strain commonly resulted in phenotypes closer to the population mean than the additive effects from the two loci, and often much closer to the mean than either single-locus model. Alternatively, combinations of alleles inherited from different parent strains contribute to more extreme phenotypes not observed in either parental strain. This class of phenotype-stabilizing interactions has effects that are close to additive and are thus difficult to detect except in very large intercrosses. Nevertheless, we found these interactions to be useful in generating hypotheses for functional relationships between genetic loci. Our findings suggest that while epistasis is often weak and unlikely to account for a large proportion of heritable variance, even small-effect genetic interactions can facilitate hypotheses of underlying biology in well-powered studies.

Recent technical and methodological advances have greatly enhanced genome-wide association studies (GWAS). The advent of low-cost, whole-genome sequencing facilitates high-resolution variant identification, and the development of linear mixed models (LMM) allows improved identification of putatively causal variants. While essential for correcting false positive associations due to sample relatedness and population stratification, LMMs have commonly been restricted to quantitative variables. However, phenotypic traits in association studies are often categorical, coded as binary case-control or ordered variables describing disease stages. To address these issues, we have devised a method for genomic association studies that implements a generalized LMM (GLMM) in a Bayesian framework, called Bayes-GLMM Bayes-GLMM has four major features: (1) support of categorical, binary, and quantitative variables; (2) cohesive integration of previous GWAS results for related traits; (3) correction for sample relatedness by mixed modeling; and (4) model estimation by both Markov chain Monte Carlo sampling and maximal likelihood estimation. We applied Bayes-GLMM to the whole-genome sequencing cohort of the Alzheimer's Disease Sequencing Project. This study contains 570 individuals from 111 families, each with Alzheimer's disease diagnosed at one of four confidence levels. Using Bayes-GLMM we identified four variants in three loci significantly associated with Alzheimer's disease. Two variants, rs140233081 and rs149372995, lie between PRKAR1B and PDGFA The coded proteins are localized to the glial-vascular unit, and PDGFA transcript levels are associated with Alzheimer's disease-related neuropathology. In summary, this work provides implementation of a flexible, generalized mixed-model approach in a Bayesian framework for association studies.

Interleukin 21 (IL-21) plays key roles in humoral immunity and autoimmune diseases. It is known to function in mature CD4+ T follicular B cell helper (TFH) cells, but its potential involvement in early T cell ontogeny is unclear. Here, we find that a significant population of newly activated thymic and peripheral CD4+ T cells functionally expresses IL-21 soon after birth. This naturally occurring population, termed natural (n)TH21 cells, exhibits considerable similarity to mature TFH cells. nTH21 cells originating and activated in the thymus are strictly dependent on autoimmune regulator (AIRE) and express high levels of NUR77, consistent with a bias toward self-reactivity. Their activation/expansion in the periphery requires gut microbiota and is held in check by FoxP3+ TREG cells. nTH21 cells are the major thymic and peripheral populations of IL-21+ cells to expand in an IL-21-dependent humoral autoimmune disease. These studies link IL-21 to T cell ontogeny, self-reactivity, and humoral autoimmunity.