Baseline Gait and Motor Function Predict Long-Term Severity of Neurological Outcomes of Viral Infection.

Neurological dysfunction following viral infection varies among individuals, largely due to differences in their genetic backgrounds. Gait patterns, which can be evaluated using measures of coordination, balance, posture, muscle function, step-to-step variability, and other factors, are also influenced by genetic background. Accordingly, to some extent gait can be characteristic of an individual, even prior to changes in neurological function. Because neuromuscular aspects of gait are under a certain degree of genetic control, the hypothesis tested was that gait parameters could be predictive of neuromuscular dysfunction following viral infection. The Collaborative Cross (CC) mouse resource was utilized to model genetically diverse populations and the DigiGait treadmill system used to provide quantitative and objective measurements of 131 gait parameters in 142 mice from 23 CC and SJL/J strains. DigiGait measurements were taken prior to infection with the neurotropic virus Theiler's Murine Encephalomyelitis Virus (TMEV). Neurological phenotypes were recorded over 90 days post-infection (d.p.i.), and the cumulative frequency of the observation of these phenotypes was statistically associated with discrete baseline DigiGait measurements. These associations represented spatial and postural aspects of gait influenced by the 90 d.p.i. phenotype score. Furthermore, associations were found between these gait parameters with sex and outcomes considered to show resistance, resilience, or susceptibility to severe neurological symptoms after long-term infection. For example, higher pre-infection measurement values for the Paw Drag parameter corresponded with greater disease severity at 90 d.p.i. Quantitative trait loci significantly associated with these DigiGait parameters revealed potential relationships between 28 differentially expressed genes (DEGs) and different aspects of gait influenced by viral infection. Thus, these potential candidate genes and genetic variations may be predictive of long-term neurological dysfunction. Overall, these findings demonstrate the predictive/prognostic value of quantitative and objective pre-infection DigiGait measurements for viral-induced neuromuscular dysfunction.

Viral Clearance and Neuroinflammation in Acute TMEV Infection Vary by Host Genetic Background.

A wide range of viruses cause neurological manifestations in their hosts. Infection by neurotropic viruses as well as the resulting immune response can irreversibly disrupt the complex structural and functional architecture of the brain, depending in part on host genetic background. The interaction between host genetic background, neurological response to viral infection, and subsequent clinical manifestations remains poorly understood. In the present study, we used the genetically diverse Collaborative Cross (CC) mouse resource to better understand how differences in genetic background drive clinical signs and neuropathological manifestations of acute Theiler's murine encephalomyelitis virus (TMEV) infection. For the first time, we characterized variations of TMEV viral tropism and load based on host genetic background, and correlated viral load with microglial/macrophage activation. For five CC strains (CC002, CC023, CC027, CC057, and CC078) infected with TMEV, we compared clinical signs, lesion distribution, microglial/macrophage response, expression, and distribution of TMEV mRNA, and identified genetic loci relevant to the early acute (4 days post-infection [dpi]) and late acute (14 dpi) timepoints. We examined brain pathology to determine possible causes of strain-specific differences in clinical signs, and found that fields CA1 and CA2 of the hippocampal formation were especially targeted by TMEV across all strains. Using Iba-1 immunolabeling, we identified and characterized strain- and timepoint-specific variation in microglial/macrophage reactivity in the hippocampal formation. Because viral clearance can influence disease outcome, we used RNA in situ hybridization to quantify viral load and TMEV mRNA distribution at both timepoints. TMEV mRNA expression was broadly distributed in the hippocampal formation at 4 dpi in all strains but varied between radiating and clustered distribution depending on the CC strain. We found a positive correlation between microglial/macrophage reactivity and TMEV mRNA expression at 4 dpi. At 14 dpi, we observed a dramatic reduction in TMEV mRNA expression, and localization to the medial portion of field CA1 and field CA2. To better understand how host genetic background can influence pathological outcomes, we identified quantitative trait loci associated with frequency of lesions in a particular brain region and with microglial/macrophage reactivity. These QTL were located near several loci of interest: lysosomal trafficking regulator (Lyst) and nidogen 1 (Nid1), and transmembrane protein 106 B (Tmem106b). Together, these results provide a novel understanding about the influences of genetic variation on the acute neuropathological and immunopathological environment and viral load, which collectively lead to variable disease outcomes. Our findings reveal possible avenues for future investigation which may lead to more effective intervention strategies and treatment regimens.

Resilience in Long-Term Viral Infection: Genetic Determinants and Interactions.

Virus-induced neurological sequelae resulting from infection by Theiler's murine encephalomyelitis virus (TMEV) are used for studying human conditions ranging from epileptic seizures to demyelinating disease. Mouse strains are typically considered susceptible or resistant to TMEV infection based on viral persistence and extreme phenotypes, such as demyelination. We have identified a broader spectrum of phenotypic outcomes by infecting strains of the genetically diverse Collaborative Cross (CC) mouse resource. We evaluated the chronic-infection gene expression profiles of hippocampi and thoracic spinal cords for 19 CC strains in relation to phenotypic severity and TMEV persistence. Strains were clustered based on similar phenotypic profiles and TMEV levels at 90 days post-infection, and we categorized distinct TMEV response profiles. The three most common profiles included "resistant" and "susceptible," as before, as well as a "resilient" TMEV response group which experienced both TMEV persistence and mild neurological phenotypes even at 90 days post-infection. Each profile had a distinct gene expression signature, allowing the identification of pathways and networks specific to each TMEV response group. CC founder haplotypes for genes involved in these pathways/networks revealed candidate response-specific alleles. These alleles demonstrated pleiotropy and epigenetic (miRNA) regulation in long-term TMEV infection, with particular relevance for resilient mouse strains.

Aberrant gene expression in humans.

Gene expression as an intermediate molecular phenotype has been a focus of research interest. In particular, studies of expression quantitative trait loci (eQTL) have offered promise for understanding gene regulation through the discovery of genetic variants that explain variation in gene expression levels. Existing eQTL methods are designed for assessing the effects of common variants, but not rare variants. Here, we address the problem by establishing a novel analytical framework for evaluating the effects of rare or private variants on gene expression. Our method starts from the identification of outlier individuals that show markedly different gene expression from the majority of a population, and then reveals the contributions of private SNPs to the aberrant gene expression in these outliers. Using population-scale mRNA sequencing data, we identify outlier individuals using a multivariate approach. We find that outlier individuals are more readily detected with respect to gene sets that include genes involved in cellular regulation and signal transduction, and less likely to be detected with respect to the gene sets with genes involved in metabolic pathways and other fundamental molecular functions. Analysis of polymorphic data suggests that private SNPs of outlier individuals are enriched in the enhancer and promoter regions of corresponding aberrantly-expressed genes, suggesting a specific regulatory role of private SNPs, while the commonly-occurring regulatory genetic variants (i.e., eQTL SNPs) show little evidence of involvement. Additional data suggest that non-genetic factors may also underlie aberrant gene expression. Taken together, our findings advance a novel viewpoint relevant to situations wherein common eQTLs fail to predict gene expression when heritable, rare inter-individual variation exists. The analytical framework we describe, taking into consideration the reality of differential phenotypic robustness, may be valuable for investigating complex traits and conditions.

Genome-wide association study to identify potential genetic modifiers in a canine model for Duchenne muscular dystrophy.

BACKGROUND: Duchenne muscular dystrophy (DMD) causes progressive muscle degeneration, cardiomyopathy and respiratory failure in approximately 1/5,000 boys. Golden Retriever muscular dystrophy (GRMD) resembles DMD both clinically and pathologically. Like DMD, GRMD exhibits remarkable phenotypic variation among affected dogs, suggesting the influence of modifiers. Understanding the role(s) of genetic modifiers of GRMD may identify genes and pathways that also modify phenotypes in DMD and reveal novel therapies. Therefore, our objective in this study was to identify genetic modifiers that affect discrete GRMD phenotypes. RESULTS: We performed a linear mixed-model (LMM) analysis using 16 variably-affected dogs from our GRMD colony (8 dystrophic, 8 non-dystrophic). All of these dogs were either full or half-siblings, and phenotyped for 19 objective, quantitative biomarkers at ages 6 and 12 months. Each biomarker was individually assessed. Gene expression profiles of 59 possible candidate genes were generated for two muscle types: the cranial tibialis and medial head of the gastrocnemius. SNPs significantly associated with GRMD biomarkers were identified on multiple chromosomes (including the X chromosome). Gene expression levels for candidate genes located near these SNPs correlated with biomarker values, suggesting possible roles as GRMD modifiers. CONCLUSIONS: The results of this study enhance our understanding of GRMD pathology and represent a first step toward the characterization of GRMD modifiers that may be relevant to DMD pathology. Such modifiers are likely to be useful for DMD treatment development based on their relationships to GRMD phenotypes.

Translating golden retriever muscular dystrophy microarray findings to novel biomarkers for cardiac/skeletal muscle function in Duchenne muscular dystrophy.

BACKGROUND: In Duchenne muscular dystrophy (DMD), abnormal cardiac function is typically preceded by a decade of skeletal muscle disease. Molecular reasons for differences in onset and progression of these muscle groups are unknown. Human biomarkers are lacking. METHODS: We analyzed cardiac and skeletal muscle microarrays from normal and golden retriever muscular dystrophy (GRMD) dogs (ages 6, 12, or 47+ mo) to gain insight into muscle dysfunction and to identify putative DMD biomarkers. These biomarkers were then measured using human DMD blood samples. RESULTS: We identified GRMD candidate genes that might contribute to the disparity between cardiac and skeletal muscle disease, focusing on brain-derived neurotropic factor (BDNF) and osteopontin (OPN/SPP1, hereafter indicated as SPP1). BDNF was elevated in cardiac muscle of younger GRMD but was unaltered in skeletal muscle, while SPP1 was increased only in GRMD skeletal muscle. In human DMD, circulating levels of BDNF were inversely correlated with ventricular function and fibrosis, while SPP1 levels correlated with skeletal muscle function. CONCLUSION: These results highlight gene expression patterns that could account for differences in cardiac and skeletal disease in GRMD. Most notably, animal model-derived data were translated to DMD and support use of BDNF and SPP1 as biomarkers for cardiac and skeletal muscle involvement, respectively.

Comparative Genomics of X-linked Muscular Dystrophies: The Golden Retriever Model.

Duchenne muscular dystrophy (DMD) is a devastating disease that dramatically decreases the lifespan and abilities of affected young people. The primary molecular cause of the disease is the absence of functional dystrophin protein, which is critical to proper muscle function. Those with DMD vary in disease presentation and dystrophin mutation; the same causal mutation may be associated with drastically different levels of disease severity. Also contributing to this variation are the influences of additional modifying genes and/or changes in functional elements governing such modifiers. This genetic heterogeneity complicates the efficacy of treatment methods and to date medical interventions are limited to treating symptoms. Animal models of DMD have been instrumental in teasing out the intricacies of DMD disease and hold great promise for advancing knowledge of its variable presentation and treatment. This review addresses the utility of comparative genomics in elucidating the complex background behind phenotypic variation in a canine model of DMD, Golden Retriever muscular dystrophy (GRMD). This knowledge can be exploited in the development of improved, more personalized treatments for DMD patients, such as therapies that can be tailor-matched to the disease course and genomic background of individual patients.

C57BL/6J mice exposed to perfluorooctanoic acid demonstrate altered immune responses and increased seizures after Theiler's murine encephalomyelitis virus infection.

Introduction: Neurological diseases can stem from environmental influences such as antecedent viral infections or exposure to potential toxicants, some of which can trigger immune responses leading to neurological symptoms. Theiler's murine encephalomyelitis virus (TMEV) is used to model human neurological conditions associated with prior viral infections, with outcomes partly attributable to improper induction and regulation of the immune response. Perfluorooctanoic acid (PFOA) can alter pathologies known to influence neurological disease such as inflammatory responses, cytokine expression, and glial activation. Co-exposure to TMEV and PFOA was used to test the hypothesis that early life exposure to the potential immunotoxicant PFOA would affect immune responses so as to render TMEV-resistant C57BL/6J (B6) mice susceptible to viral-induced neurological disease. Methods: Neonate B6 mice were exposed to different treatments: non-injected, sham-infected with PBS, and TMEV-infected, with the drinking water of each group including either 70 ppt PFOA or filtered water. The effects of PFOA were evaluated by comparing neurological symptoms and changes in immune-related cytokine and chemokine production induced by viral infection. Immune responses of 23 cytokines and chemokines were measured before and after infection to determine the effects of PFOA exposure on immune response. Results: Prior to infection, an imbalance between Th1, Th2, and Treg cytokines was observed in PFOA-exposed mice, suppressing IL-4 and IL-13 production. However, the balance was restored and characterized by an increase in pro-inflammatory cytokines in the non-infected group, and a decrease in IL-10 in the PFOA + TMEV group. Furthermore, the PFOA + TMEV group experienced an increase in seizure frequency and severity. Discussion: Overall, these findings provide insight into the complex roles of immune responses in the pathogenesis of virus-associated neurological diseases influenced by co-exposures to viruses and immunotoxic compounds.

Serum Cytokines Predict Neurological Damage in Genetically Diverse Mouse Models.

Viral infections contribute to neurological and immunological dysfunction driven by complex genetic networks. Theiler's murine encephalomyelitis virus (TMEV) causes neurological dysfunction in mice and can model human outcomes to viral infections. Here, we used genetically distinct mice from five Collaborative Cross mouse strains and C57BL/6J to demonstrate how TMEV-induced immune responses in serum may predict neurological outcomes in acute infection. To test the hypothesis that serum cytokine levels can provide biomarkers for phenotypic outcomes of acute disease, we compared cytokine levels at pre-injection, 4 days post-injection (d.p.i.), and 14 d.p.i. Each strain produced unique baseline cytokine levels and had distinct immune responses to the injection procedure itself. Thus, we eliminated the baseline responses to the injection procedure itself and identified cytokines and chemokines induced specifically by TMEV infection. Then, we identified strain-specific longitudinal cytokine profiles in serum during acute disease. Using stepwise regression analysis, we identified serum immune markers predictive for TMEV-induced neurological phenotypes of the acute phase, e.g., IL-9 for limb paralysis; and TNF-α, IL-1ß, and MIP-1ß for limb weakness. These findings indicate how temporal differences in immune responses are influenced by host genetic background and demonstrate the potential of serum biomarkers to track the neurological effects of viral infection.

Genetic and immunological contributors to virus-induced paralysis.

Infection by a single virus can evoke diverse immune responses, resulting in different neurological outcomes, depending on the host's genetic background. To study heterogenous viral response, we use Theiler's Murine Encephalomyelitis Virus (TMEV) to model virally induced neurological phenotypes and immune responses in Collaborative Cross (CC) mice. The CC resource consists of genetically distinct and reproducible mouse lines, thus providing a population model with genetic heterogeneity similar to humans. We examined different CC strains for the effect of chronic stage TMEV-induced immune responses on neurological outcomes throughout 90 days post infection (dpi), with a particular focus on limb paralysis, by measuring serum levels of 23 different cytokines and chemokines. Each CC strain demonstrated a unique set of immune responses, regardless of presence or absence of TMEV RNA. Using stepwise regression, significant associations were identified between IL-1α, RANTES, and paralysis frequency scores. To better understand these interactions, we evaluated multiple aspects of the different CC genetic backgrounds, including haplotypes of genomic regions previously linked with TMEV pathogenesis and viral clearance or persistence, individual cytokine levels, and TMEV-relevant gene expression. These results demonstrate how loci previously associated with TMEV outcomes provide incomplete information regarding TMEV-induced paralysis in the CC strains. Overall, these findings provide insight into the complex roles of immune response in the pathogenesis of virus-associated neurological diseases influenced by host genetic background.

Host genetic diversity drives variable central nervous system lesion distribution in chronic phase of Theiler's Murine Encephalomyelitis Virus (TMEV) infection.

Host genetic background is a significant driver of the variability in neurological responses to viral infection. Here, we leverage the genetically diverse Collaborative Cross (CC) mouse resource to better understand how chronic infection by Theiler's Murine Encephalomyelitis Virus (TMEV) elicits diverse clinical and morphologic changes in the central nervous system (CNS). We characterized the TMEV-induced clinical phenotype responses, and associated lesion distributions in the CNS, in six CC mouse strains over a 90 day infection period. We observed varying degrees of motor impairment in these strains, as measured by delayed righting reflex, paresis, paralysis, seizures, limb clasping, ruffling, and encephalitis phenotypes. All strains developed neuroparenchymal necrosis and mineralization in the brain, primarily localized to the hippocampal regions. Two of the six strains presented with axonal degeneration with myelin loss of the nerve roots in the lumbar spinal cord. Moreover, we statistically correlated lesion distribution with overall frequencies of clinical phenotypes and phenotype progression to better understand how and where TMEV targets the CNS, based on genetic background. Specifically, we assessed lesion distribution in relation to the clinical progression of these phenotypes from early to late TMEV disease, finding significant relationships between progression and lesion distribution. Finally, we identified quantitative trait loci associated with frequency of lesions in a particular brain region, revealing several loci of interest for future study: lysosomal trafficking regulator (Lyst) and nidogen 1 (Nid1). Together, these results indicate that the genetic background influences the type and severity of clinical phenotypes, phenotypic resilience to TMEV, and the lesion distribution across strains.

Correction: Expression profiling of disease progression in canine model of Duchenne muscular dystrophy.

[This corrects the article DOI: 10.1371/journal.pone.0194485.].

Author Correction: RNA-seq of serial kidney biopsies obtained during progression of chronic kidney disease from dogs with X-linked hereditary nephropathy.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Antecedent presentation of neurological phenotypes in the Collaborative Cross reveals four classes with complex sex-dependencies.

Antecedent viral infection may contribute to increased susceptibility to several neurological diseases, such as multiple sclerosis and Parkinson's disease. Variation in clinical presentations of these diseases is often associated with gender, genetic background, or a combination of these and other factors. The complicated etiologies of these virally influenced diseases are difficult to study in conventional laboratory mouse models, which display a very limited number of phenotypes. We have used the genetically and phenotypically diverse Collaborative Cross mouse panel to examine complex neurological phenotypes after viral infection. Female and male mice from 18 CC strains were evaluated using a multifaceted phenotyping pipeline to define their unique disease profiles following infection with Theiler's Murine Encephalomyelitis Virus, a neurotropic virus. We identified 4 distinct disease progression profiles based on limb-specific paresis and paralysis, tremors and seizures, and other clinical signs, along with separate gait profiles. We found that mice of the same strain had more similar profiles compared to those of different strains, and also identified strains and phenotypic parameters in which sex played a significant role in profile differences. These results demonstrate the value of using CC mice for studying complex disease subtypes influenced by sex and genetic background. Our findings will be useful for developing novel mouse models of virally induced neurological diseases with heterogenous presentation, an important step for designing personalized, precise treatments.

A high resolution RH map of the bovine major histocompatibility complex.

BACKGROUND: The cattle MHC is termed the bovine leukocyte antigen (BoLA) and, along with the MHCs of other ruminants, is unique in its genomic organization. Consequently, correct and reliable gene maps and sequence information are critical to the study of the BoLA region. The bovine genome sequencing project has produced two assemblies (Btau_3.1 and 4.0) that differ substantially from each other and from conventional gene maps in the BoLA region. To independently compare the accuracies of the different sequence assemblies, we have generated a high resolution map of BoLA using a 12,000rad radiation hybrid panel. Seventy-seven unique sequence tagged site (STS) markers chosen at approximately 50 kb intervals from the Btau 2.0 assembly and spanning the IIa-III-I and IIb regions of the bovine MHC were mapped on a 12,000rad bovine radiation hybrid (RH) panel to evaluate the different assemblies of the bovine genome sequence. RESULTS: Analysis of the data generated a high resolution RH map of BoLA that was significantly different from the Btau_3.1 assembly of the bovine genome but in good agreement with the Btau_4.0 assembly. Of the few discordancies between the RH map and Btau_4.0, most could be attributed to closely spaced markers that could not be precisely ordered in the RH panel. One probable incorrectly-assembled sequence and three missing sequences were noted in the Btau_4.0 assembly. The RH map of BoLA is also highly concordant with the sequence-based map of HLA (NCBI build 36) when reordered to account for the ancestral inversion in the ruminant MHC. CONCLUSION: These results strongly suggest that studies using Btau_3.1 for analyses of the BoLA region should be reevaluated in light of the Btau_4.0 assembly and indicate that additional research is needed to produce a complete assembly of the BoLA genomic sequences.

Expression profiling of disease progression in canine model of Duchenne muscular dystrophy.

Duchenne muscular dystrophy (DMD) causes progressive disability in 1 of every 5,000 boys due to the lack of functional dystrophin protein. Despite much advancement in knowledge about DMD disease presentation and progression-attributable in part to studies using mouse and canine models of the disease-current DMD treatments are not equally effective in all patients. There remains, therefore, a need for translational animal models in which novel treatment targets can be identified and evaluated. Golden Retriever muscular dystrophy (GRMD) is a phenotypically and genetically homologous animal model of DMD. As with DMD, speed of disease progression in GRMD varies substantially. However, unlike DMD, all GRMD dogs possess the same causal mutation; therefore genetic modifiers of phenotypic variation are relatively easier to identify. Furthermore, the GRMD dogs used in this study reside within the same colony, reducing the confounding effects of environment on phenotypic variation. To detect modifiers of disease progression, we developed gene expression profiles using RNA sequencing for 9 dogs: 6 GRMD dogs (3 with faster-progressing and 3 with slower-progressing disease, based on quantitative, objective biomarkers) and 3 control dogs from the same colony. All dogs were evaluated at 2 time points: early disease onset (3 months of age) and the point at which GRMD stabilizes (6 months of age) using quantitative, objective biomarkers identified as robust against the effects of relatedness/inbreeding. Across all comparisons, the most differentially expressed genes fell into 3 categories: myogenesis/muscle regeneration, metabolism, and inflammation. Our findings are largely in concordance with DMD and mouse model studies, reinforcing the utility of GRMD as a translational model. Novel findings include the strong up-regulation of chitinase 3-like 1 (CHI3L1) in faster-progressing GRMD dogs, suggesting previously unexplored mechanisms underlie progression speed in GRMD and DMD. In summary, our findings support the utility of RNA sequencing for evaluating potential biomarkers of GRMD progression speed, and are valuable for identifying new avenues of exploration in DMD research.

RNA-seq of serial kidney biopsies obtained during progression of chronic kidney disease from dogs with X-linked hereditary nephropathy.

Dogs with X-linked hereditary nephropathy (XLHN) have a glomerular basement membrane defect that leads to progressive juvenile-onset renal failure. Their disease is analogous to Alport syndrome in humans, and they also serve as a good model of progressive chronic kidney disease (CKD). However, the gene expression profile that affects progression in this disease has only been partially characterized. To help fill this gap, we used RNA sequencing to identify differentially expressed genes (DEGs), over-represented pathways, and upstream regulators that contribute to kidney disease progression. Total RNA from kidney biopsies was isolated at 3 clinical time points from 3 males with rapidly-progressing CKD, 3 males with slowly-progressing CKD, and 2 age-matched controls. We identified 70 DEGs by comparing rapid and slow groups at specific time points. Based on time course analysis, 1,947 DEGs were identified over the 3 time points revealing upregulation of inflammatory pathways: integrin signaling, T cell activation, and chemokine and cytokine signaling pathways. T cell infiltration was verified by immunohistochemistry. TGF-ß1 was identified as the primary upstream regulator. These results provide new insights into the underlying molecular mechanisms of disease progression in XLHN, and the identified DEGs can be potential biomarkers and therapeutic targets translatable to all CKDs.

Host genetic background influences diverse neurological responses to viral infection in mice.

Infection by Theiler's murine encephalomyelitis virus (TMEV) is a model for neurological outcomes caused by virus infection because it leads to diverse neurological conditions in mice, depending on the strain infected. To extend knowledge on the heterogeneous neurological outcomes caused by TMEV and identify new models of human neurological diseases associated with antecedent infections, we analyzed the phenotypic consequences of TMEV infection in the Collaborative Cross (CC) mouse population. We evaluated 5 different CC strains for outcomes of long-term infection (3 months) and acute vs. early chronic infection (7 vs. 28 days post-infection), using neurological and behavioral phenotyping tests and histology. We correlated phenotypic observations with haplotypes of genomic regions previously linked to TMEV susceptibility to test the hypothesis that genomic diversity within CC mice results in variable disease phenotypes in response to TMEV. None of the 5 strains analyzed had a response identical to that of any other CC strain or inbred strain for which prior data are available, indicating that strains of the CC can produce novel models of neurological disease. Thus, CC strains can be a powerful resource for studying how viral infection can cause different neurological outcomes depending on host genetic background.

GRMD cardiac and skeletal muscle metabolism gene profiles are distinct.

BACKGROUND: Duchenne muscular dystrophy (DMD) is caused by mutations in the DMD gene, which codes for the dystrophin protein. While progress has been made in defining the molecular basis and pathogenesis of DMD, major gaps remain in understanding mechanisms that contribute to the marked delay in cardiac compared to skeletal muscle dysfunction. METHODS: To address this question, we analyzed cardiac and skeletal muscle tissue microarrays from golden retriever muscular dystrophy (GRMD) dogs, a genetically and clinically homologous model for DMD. A total of 15 dogs, 3 each GRMD and controls at 6 and 12 months plus 3 older (47-93 months) GRMD dogs, were assessed. RESULTS: GRMD dogs exhibited tissue- and age-specific transcriptional profiles and enriched functions in skeletal but not cardiac muscle, consistent with a "metabolic crisis" seen with DMD microarray studies. Most notably, dozens of energy production-associated molecules, including all of the TCA cycle enzymes and multiple electron transport components, were down regulated. Glycolytic and glycolysis shunt pathway-associated enzymes, such as those of the anabolic pentose phosphate pathway, were also altered, in keeping with gene expression in other forms of muscle atrophy. On the other hand, GRMD cardiac muscle genes were enriched in nucleotide metabolism and pathways that are critical for neuromuscular junction maintenance, synaptic function and conduction. CONCLUSIONS: These findings suggest differential metabolic dysfunction may contribute to distinct pathological phenotypes in skeletal and cardiac muscle.

Aging Shapes the Population-Mean and -Dispersion of Gene Expression in Human Brains.

Human aging is associated with cognitive decline and an increased risk of neurodegenerative disease. Our objective for this study was to evaluate potential relationships between age and variation in gene expression across different regions of the brain. We analyzed the Genotype-Tissue Expression (GTEx) data from 54 to 101 tissue samples across 13 brain regions in post-mortem donors of European descent aged between 20 and 70 years at death. After accounting for the effects of covariates and hidden confounding factors, we identified 1446 protein-coding genes whose expression in one or more brain regions is correlated with chronological age at a false discovery rate of 5%. These genes are involved in various biological processes including apoptosis, mRNA splicing, amino acid biosynthesis, and neurotransmitter transport. The distribution of these genes among brain regions is uneven, suggesting variable regional responses to aging. We also found that the aging response of many genes, e.g., TP37 and C1QA, depends on individuals' genotypic backgrounds. Finally, using dispersion-specific analysis, we identified genes such as IL7R, MS4A4E, and TERF1/TERF2 whose expressions are differentially dispersed by aging, i.e., variances differ between age groups. Our results demonstrate that age-related gene expression is brain region-specific, genotype-dependent, and associated with both mean and dispersion changes. Our findings provide a foundation for more sophisticated gene expression modeling in the studies of age-related neurodegenerative diseases.