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Human Molecular Genetics, 2003, Vol. 12, No. 15 1813-1821
DOI: 10.1093/hmg/ddg197
© 2003 Oxford University Press

Dissection of temporal gene expression signatures of affected and spared muscle groups in dystrophin-deficient (mdx) mice

John D. Porter1,2,3,*, Anita P. Merriam1, Patrick Leahy4, Bendi Gong1 and Sangeeta Khanna1

1Department of Ophthalmology, 2Department of Neurology and 3Department of Neurosciences and 4The Comprehensive Cancer Center, Case Western Reserve University and University Hospitals of Cleveland, Cleveland, OH 44106, USA

Received April 3, 2003; Accepted June 1, 2003


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESULTS
 DISCUSSION
 CONCLUSIONS
 MATERIALS AND METHODS
 SUPPLEMENTARY MATERIAL
 REFERENCES
 
Although dystrophin mutations are the proximate cause of Duchenne muscular dystrophy (DMD), interactions among heterogeneous downstream mechanisms may be key phenotypic determinants. Temporal gene expression profiling was used to identify and correlate diverse transcriptional patterns to one another and to the disease course, for both affected and spared muscle groups, in postnatal day 7–112 dystrophin-deficient (mdx) mice. While 719 transcripts were differentially expressed at one or more ages in leg muscle, only 56 genes were altered in the spared extraocular muscles (EOM). Contrasting molecular signatures of affected versus spared muscles provide compelling evidence that the absence of dystrophin alone is necessary but not sufficient to cause the patterned fibrosis, inflammation and failure of muscle regeneration characteristic of dystrophinopathy. Dystrophic and adaptive changes in the microarray profiles were further quantified using an aggregate disease load index (DLI) to measure stage-dependent transcriptional impact in both muscles. DLI analysis highlighted the divergent responses of EOM and leg muscle groups. Cellular process-specific DLIs in leg muscle identified positively correlated temporal expression profiles for some gene classes, and the independence of others, that are linked to major disease components. Data also showed a previously unrecognized transient and selective developmental delay in pre-necrotic mdx skeletal muscle that was confirmed by qPCR. Taken together, validation and targeting of signaling pathways responsible for the coordination of the fibrotic, proteolytic and inflammatory mechanisms shown here for mdx muscle may yield new therapeutic means of mitigating the devastating consequences of DMD.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESULTS
 DISCUSSION
 CONCLUSIONS
 MATERIALS AND METHODS
 SUPPLEMENTARY MATERIAL
 REFERENCES
 
Although the proximate cause of Duchenne muscular dystrophy (DMD) is inherited mutations of dystrophin (1), its pathogenesis is not yet fully understood. Dystrophin is the key to membrane localization of an oligomeric dystrophin–glycoprotein complex (DGC); truncated or absent dystrophin displaces the other DGC components (2). It is generally accepted that dystrophinopathy breaks the DGC-mediated mechanical linkage between the myofiber cytoskeleton and extracellular matrix (ECM) that stabilizes the sarcolemma during the transfer of force from contractile myofilaments to tendon, making muscle fibers susceptible to necrosis (3–5). This simple mechanical model for DMD is complicated by data that individual DGC components have cell signaling roles and collectively comprise a scaffold for membrane localization of signal transduction elements needed for myofiber homeostasis (6). The latent period between birth and disease onset and the selective sparing of some muscle groups argue for interactive mechanisms as determinants of the progression of dystrophinopathy.

Despite the primacy of the mechanical model, secondary events in dystrophin-deficient muscle (fibrosis, inflammation, muscle regeneration failure) may actively contribute toward the pathogenesis of DMD (4,7–10). A multifactorial model of DMD requires an understanding of the myriad cell autonomous and non-cell autonomous events among interrelated muscular, vascular, connective and immune tissues. Gene expression profiling has clarified mechanisms downstream from the dystrophin mutation in DMD (9–13) and its mdx mouse model (8,14–17), but has largely been restricted to single disease stages. While confirming established features of DMD, DNA microarray allows unbiased discovery of previously unrecognized changes in the transcriptomes of cellular participants in disease (18). We previously showed that inflammation-related transcripts dominate the signature of 8-week-old mdx leg muscle (8) and have since demonstrated early production of pro-inflammatory chemoattractants by mononuclear cells and dystrophic muscle fibers proper (19). These and other data lend support to the notion that the muscle response to dystrophinopathy is conditioned by downstream mechanisms and further suggest that understanding of mdx temporal expression signatures may lead to comprehensive disease models and identification of new treatment strategies for DMD.

Here, we used oligonucleotide microarrays to dissect progressive transcriptional changes in muscles that are spared (extraocular muscle, EOM) or targeted (leg) in mdx mice. Mdx EOM showed no consistent pathologic or adaptive transcriptional changes, supporting the notion that its sparing mechanism lies in the broad constitutive differences from other skeletal muscle (20,21). By contrast, the mdx leg transcriptome showed broad-based, progressive alterations. Dystrophic and adaptive changes in mdx skeletal muscle were quantified by an aggregate disease load index (DLI) to represent the total impact of transcriptional changes in pre-necrotic and pathologic stages. Similarly, biologic process- and cell type-specific DLIs identified both temporal correlations and independence among the diverse mechanisms participating in muscular dystrophy. Collectively, data provide insight into the identity and temporal patterns of individual transcript and transcript functional class expression patterns, and will contribute toward a comprehensive model of the pathogenesis of dystrophinopathy.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
DISCUSSION
 CONCLUSIONS
 MATERIALS AND METHODS
 SUPPLEMENTARY MATERIAL
 REFERENCES
 
Overall temporal expression profile of mdx hindlimb muscle
Transcriptional profiles were determined for mdx versus age-matched control leg muscles by DNA microarray at six ages (P7–P112) selected to correspond with recognized morphopathologic stages. Mdx muscle is pre-necrotic at P7 and P14, disease onset is by P21, pathology peaks by P56, and disease processes slow by P112 (22–24). There is no consensus as to the best approach to microarray data analysis. Methods in current use are known to generate overlapping but often very different gene lists from the same data set (18). Prior studies by ourselves and others have demonstrated the effectiveness of the Affymetrix MAS algorithm when applying the stringent criteria that are used here, including the requirement for consistent calls across all replicates.

Using this approach, 719 transcripts passed a stringent significance filter for differential regulation in mdx leg (Fig. 1A and Supplementary Table 1). Figure 1B shows the number of up-/down-regulated transcripts by age. With the exception of P7, gene induction predominated in mdx leg (Fig. 1A and B). An early pattern of down-regulation in P7 mdx leg muscle (nine transcripts increased/28 decreased) was reversed by P14. Only one gene (Edr) was differentially expressed in mdx at both P7 and P14 (Supplementary Table 1). Moreover, only 51% of the transcripts differentially expressed at P7 were also changed at one or more of the later stages; often the changes were reversed in sign at the later age(s). Patterned suppression of transcripts at P7 was confirmed by qPCR (Table 1).



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  		Figure 1. Relative expression levels in mdx muscle compared to control. (A) Eisen expression plot of mdx/wild-type expression ratios for 719 transcripts differentially expressed in leg muscle at one or more ages between P7 and P112 (replicate samples normalized to wild type at each age). Transcripts more highly expressed in mdx are indicated in red; those expressed in mdx at levels lower than wild type are indicated in green. (B) Number of differentially regulated genes (red=up-regulated, green=down-regulated) by age in mdx leg. (C) Number of differentially regulated genes at each age in mdx EOM (coded as in C). (D) Eisen expression plot of the mdx/wild type expression ratios for 56 transcripts differentially expressed in EOM at one or more ages between P14 and P112 (coded as in A). (E) Venn diagram of the correspondence between genes differentially regulated in mdx EOM and leg muscles.

 

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  		Table 1. qPCR analysis of mdx hindlimb muscle and comparative fold change data for DNA microarray versus qPCRa
 
Consistent with the onset of pathologic alterations in 3-week mdx leg, the number of differentially regulated genes increased by >17-fold from P14 to P23 (at P14, 16 increased/three decreased; at P23, 263 increased/66 decreased). After a drop in number of transcripts between P23 and P28, dystrophinopathy-associated expression changes peaked at P56, when 76% of genes altered at any stage of mdx skeletal muscle were differentially expressed, and then the number of transcripts dropped by ~2.3-fold between P56 and P112 (Fig. 1B). While dystrophin expression was reduced in mdx, we observed no changes in expression of the other DGC components.

The 719 genes that were differentially expressed in mdx leg at one or more stages were further evaluated to determine which also changed in expression across the time course of the study. A total of 364 transcripts also showed significant modulation of expression levels across when assessed by an independent measure (P<=0.01; Welch t-test/Welch ANOVA, with multiple testing correction; Fig. 2A and Supplementary Table 1). Genes meeting this additional criterion are more likely to dynamically contribute toward the pathogenesis of dystrophinopathy. Of these, 290 were up-regulated and 74 down-regulated during the disease course.



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  		Figure 2. Gene expression patterns in mdx leg and EOM. (A) Hierarchical cluster plot of 364 transcripts meeting criteria for differential expression at one or more age and modulation of expression between P7 and P112 in mdx leg (P<=0.01; Welch t-test/Welch ANOVA parametric statistic, with multiple testing correction). These genes represent a subset of those in Figure 1A. (B) Aggregate DLI plots for mdx leg and EOM, illustrating disease progression by summing the absolute values of fold changes of differentially regulated transcripts at each age. (C) Functional distribution of differentially regulated transcripts detected at any age for mdx leg and EOM.

 
Overall temporal expression profile of mdx EOM
Unlike most skeletal muscles, EOM shows no detectable pathology in DMD or its animal models (25–30), nor does it adapt by any mechanism predicted from existing pathogenic models (21). Based upon expression profiling, mdx EOM showed few alterations at any of four postnatal ages examined. Pooling data across all ages, only 56 transcripts total were differentially expressed in EOM (Fig. 1D and Supplementary Table 2). There was no consistent pattern in the temporal expression profiles, as most genes (84%) induced or repressed in EOM were functionally unrelated and limited to one age. Only Myla, Tnnt2, Edf, H2-T17, Cebpd, Dmd and three ESTs were differentially regulated at more than one age. In contrast to leg, the mdx EOM expression profile was not dominated by up-regulated transcripts (54 versus 70% for leg; Fig. 1A–D). The EOM transcriptional response also was very different from that of other muscles; only 3.9% of the transcripts identified in mdx leg muscle data were also differentially regulated in EOM (Fig. 1E).

Aggregate DLI analysis and functional characterization of differentially regulated transcripts
The global impact of dystrophin-deficiency on leg and EOM was quantified using an aggregate DLI (Fig. 2B). Up-regulated and down-regulated transcripts contribute to the disease process and summing their absolute fold change values provides a single transcriptional index of dystrophinopathy. The higher number of induced/repressed transcripts in mdx leg at P7 versus P14, and the disease progression from P14 to P112 (Fig. 1B), were reflected in the DLI plot (Fig. 2B). The aggregate DLI for EOM was substantially lower than leg at all ages.

All genes differentially expressed in mdx leg or EOM were functionally classified. To account for functional role diversity, some genes were placed in up to two major categories (Fig. 2C and Supplementary Tables 1 and 2). Overall, leg transcripts represent several classes previously linked to the pathogenesis of dystrophinopathy, including inflammation (21.2% of transcripts identified at one or more ages), ECM/fibrosis (6.8%) and muscle/muscle regeneration (5.9%). The large proportion of transcripts in the other/unknown (25.4%) and EST (18.1%) categories suggests involvement of as yet unknown mechanisms in dystrophin-deficient muscle. The functional distribution of transcripts differentially regulated in mdx EOMs is shown in Figure 2C.

Temporal dissection of disease processes in mdx hindlimb
To dissect temporal gene expression signatures in mdx leg, we constructed DLI plots for major functional categories of genes (Fig. 3A and B). Similar to the aggregate DLI above, the absolute values of fold changes were summed for all differentially regulated transcripts by functional category. DLIs for three related mechanisms—inflammation, proteolysis and fibrotic changes in the ECM—exhibited a striking correlation (Fig. 3A). The DLI for each was elevated at P7, and dropped by P14 to then rise and plateau after P28. Moreover, the character of the gene expression profile at P7 was very different from that at other stages. Most transcripts down-regulated at P7 that were linked to inflammation (Anxa1, Cd24a, Cfh, Cnlp, Lyl1, Ngp, S100a8, S100a9, Spp1 and Tnc), proteolysis (Acp5, Ctsk, Mmp9, Mmp13 and Timp1) and ECM (Alkp2, Bglap1, Col11a1, Dmp1, Ibsp, Spp1 and Tnc) were either unchanged or up-regulated at P14–P112 (Supplementary Table 1).



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  		Figure 3. Functional category-specific DLI plots calculated for mdx leg muscle. (A) High correlation of DLIs for inflammation-, proteolysis- and ECM-related transcripts; note differential regulation at P7 that partially resolves by P14 before onset of the morphopathological signs of muscular dystrophy. (B) DLIs for cytoskeletal-, muscle/muscle regeneration- and metabolism-related transcripts exhibit different temporal patterns from those in A. (C) To profile the patterned temporal involvement of inflammatory cell markers, fold change values for up-regulated transcripts that could be associated with specific cell types were plotted. (D) Chemoattractant (cytokines and chemokines) transcripts and transcripts associated with the vascular response in inflammation were separately plotted. The chemokine DLI shows a pattern early induction, substantial upregulation, and suppression that mirrors the time course of pathology in mdx skeletal muscle. (E) Additional events in inflammation, including induction of major histocompatibility complex transcripts, complement, and interferon-related genes followed patterns similar to that of chemokine transcripts. (F) Transcripts associated with ECM signaling- and processing-led changes in ECM components that contribute to the fibrotic response and the up-regulation of proteoglycans/glycoproteins in mdx muscle.

 
By contrast, muscle/muscle regeneration, cytoskeleton and metabolism DLIs generally did not follow the same pattern of differential regulation at P7 followed by a reversal at P14 (Fig. 3B). Instead, muscle-related transcripts showed a rise from P7 to P23 and the index leveled-off thereafter. After a slight drop between P7 and P14, the metabolism DLI exhibited a nearly identical pattern to that of muscle transcripts. Differential regulation of cytoskeletal mRNAs was not first detected until after disease onset (P23), and the cytoskeletal DLI subsequently followed a fluctuating pattern, reaching a low at P112. Most of the differentially regulated transcripts in the muscle-specific (80%; e.g. Chrna1, Crap, Igf2, Myh3, Myog and Tnnt2) and cytoskeletal (93%; e.g. Tmsb10, Tuba2, Tuba6 and Tubb2) categories were induced in mdx, while the majority of transcripts contributing to the metabolism DLI (59%) were repressed (e.g. Amd1, Ckmt2, Ldh2, Mod1, Nnt, Oxct, Scd1 and Suclg1; Supplementary Table 1).

Temporal patterns of inflammation and ECM transcripts in mdx hindlimb
To further dissect interactive mechanisms contributing to DMD, we classified all 719 differentially regulated transcripts into 28 functional classes, allowing each to appear in five or fewer categories (Supplementary Table 1, Fig. 3; all of the individual functional class patterns are shown in Supplementary Figs 1–3). Transcripts identified with specific inflammatory cell types yielded information on both the patterned activation of resident cells and infiltration of circulating mononuclear cells in dystrophic skeletal muscle (Fig. 3C). No markers that could be specifically linked to macrophages, T-lymphocytes, B-lymphocytes, natural killer cells, neutrophils or mast cells were up-regulated in P7 leg, and only two transcripts associated with macrophages (Lyzs and Lzp-s) were detected at P14. Multiple macrophage and T-lymphocyte markers were induced by P23 and, based upon expression profiles, these remained as the dominant inflammatory cell types in dystrophic muscle throughout the time course studied here.

Inflammation- and ECM/fibrosis-related genes (collectively, 28% of all differentially regulated transcripts in leg) may be of particular importance in dystrophin-deficient muscle (Fig. 3D–F). Cytokines have multiple roles in cell growth/differentiation and as inflammation chemoattractants, but have been inconsistently reported in dystrophinopathy (7,31–33). Here, the cytokine-specific DLI showed a weak correlation with pathogenic events in mdx muscle (Fig. 3D). By contrast, chemokine temporal expression patterns closely mirrored the overall transcriptional and morphopathologic patterns in mdx. Likewise, markers identified with interferon-mediated events, complement response and the major histocompatibility response (Fig. 3E) closely correlated with other cellular/molecular events in dystrophic muscle. Among ECM transcripts, genes related to ECM signaling and processing were differentially regulated early (P7) and most were restored to wild-type values by P14, but the ECM signaling/processing DLI then rose rapidly and remained elevated through P56. ECM transcriptional changes at P7 reflected repressed genes (Mmp9, Mmp13 and Spp1). While Spp1 was repressed by 22.4-fold in P7 mdx muscle, it was induced by 2.4- to 74.1-fold at all later stages (confirmed by qPCR, Table 1). Similarly, Mmp9 and Mmp13 were down-regulated by 34.5- and 14.1-fold, respectively, at P7 but thereafter were unchanged. The increased ECM signaling/processing DLI at P23–P112 resulted from more consistent patterns of gene induction (e.g. Mmp12, Ctgf and Lox). Induction of ECM component collagen (e.g. Col1a2, Col3a1, Col5a2 and Col8a1) and proteoglycan/glycoprotein (e.g. Lum, Fbn1 and Bgn) transcripts followed the increase in ECM signaling (Fig. 3F).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
CONCLUSIONS
 MATERIALS AND METHODS
 SUPPLEMENTARY MATERIAL
 REFERENCES
 
Expression profiling of mdx skeletal muscle was used to identify genes differentially expressed in dystrophinopathy and to gain insight into temporal relationships among mechanisms operating downstream from the primary dystrophin defect. Dystrophin mutations condition skeletal muscle toward the likelihood of necrosis, but the sparing of EOM (21,25–30) establishes that myofiber necrosis is not an inevitable consequence. Absence of deleterious or adaptive alterations in the mdx EOM transcriptome lends considerable support to the notion that events secondary to dystrophin deficiency and sarcolemmal displacement of the DGC determine the ultimate fate of a muscle class. DLI analysis allowed comprehensive dissection of key downstream mechanisms in dystrophinopathy. This approach revealed a previously unappreciated developmental delay in pre-necrotic mdx leg along with a high degree of coordination among the inflammatory, proteolytic and ECM responses to the disease.

EOM is constitutively spared in muscular dystrophy
While a total of 56 genes were differentially regulated in mdx EOM, detection was inconsistent across ages and 50% of the EOM response was not shared with leg. Only dystrophin and an EST (AW125272) were differentially regulated in EOM at all four ages. The aggregate DLI for EOM was one to two orders of magnitude lower than that for leg at most ages. Although the EOM DLI showed a slight rise by P112, its aggregate value was still low and it is unlikely that this is a long-term trend since EOM is morphologically normal even in mdx mice older than P250 (27). While genes linked to the inflammatory response were detected, total numbers (nine genes versus 163 in leg) were substantially less than in leg, and differential regulation was found in only a few genes/category (e.g. chemokines, Ccl9; interferon-related, Ifit1, proteolysis, Ctss, Lyzs, Lzp-s), often at one age only. Given the paucity of interstitial mononuclear cells in mdx EOM (19) and the presence of these same inflammation transcripts in leg, this inconsistent pattern is probably a bystander effect of systemically elevated mononuclear cells.

Likewise, evidence for EOM transcriptional changes in ECM included only two genes (versus 52 in leg): induction of Igf2 (1.59-fold) and lumican (2.9-fold), both positive regulators of collagen synthesis (34,35), was modest and limited to P56 and P112 mice, respectively. Limited changes were observed in muscle-specific transcripts (e.g. Tncc, Tnnt2, Myla, Igf2 and Mef2c). Expression of the cardiac contractile protein isoforms (Tncc, Tnnt2 and Myla) in mdx EOM has been reported as potentially adaptive in DMD (12), but again induction of these transcripts was modest and, except for Myla, temporally inconsistent. Taken together, little in the mdx EOM expression pattern could be linked to pathogenic or adaptive processes. These findings reinforce the concept that its novel expression signature and phenotype (20,36,37) play constitutive roles in conditioning EOM protection in dystrophinopathy (21,25).

Mdx hindlimb experiences an early developmental delay in gene expression
In contrast to all other ages, the majority of transcripts (76%) differentially expressed in P7 mdx leg muscle were down-regulated. Many of these genes were confirmed by qPCR (Table 1). That the pattern was virtually reversed by P14, when only one of the 28 genes remained repressed, is suggestive of a transient developmental delay in neonatal mdx leg muscle. Transcripts exhibiting this behavior were generally restricted to specific functions (proteolysis/lysosomal, cytokines, ECM signaling/processing, ECM—other and neutrophil markers; Supplementary Fig. 1), while only two myofiber-related transcripts exhibited similar behavior (Myh3, decreased by 1.5-fold at P7, unchanged at P14, and increased by >6-fold thereafter; and Grb10, decreased by 3.3-fold at P7 and unchanged thereafter). Myh3 (embryonic myosin heavy chain) repression at P7 may be associated with a modest delay in myofiber development; subsequent induction probably reflects myofiber regeneration following disease onset. Grb10 is an insulin- and Igf1 binding protein highly expressed in skeletal muscle; the significance of repression in P7 mdx leg is unclear. Down-regulation of transcripts related to inflammation and ECM predominated at P7, although many of these transcripts also are linked to general cell proliferation and growth processes (e.g. Cd24a, Gadd45b, Hemgn, Mmp9, Mmp13, Spp1 and Timp1). We interpret these findings as a mild developmental delay in dystrophin-deficient skeletal muscle, likely affecting multiple tissue types as a consequence of a primary muscle mutation, but only modestly involving the myofibers proper.

DLI analysis shows that secondary events in mdx hindlimb muscle are tightly correlated
Our implementation of the aggregate DLI measure allows weighting of transcripts that are differentially expressed at more than one age and therefore accurately reflects their total genetic contribution toward muscular dystrophy. The temporal pattern of the aggregate DLI closely follows morphopathologic staging in mdx muscle and the predominant pattern was differential regulation by P23, peak values by P56, and returns toward baseline by P112 (Supplementary Figs 2 and 3). Progressive increase and maintenance of elevated levels through P112 was observed for only three functional classes (glycoprotein/proteoglycan, collagen and metabolism; Supplementary Fig. 1).

Here, we show that inflammation, proteolysis and ECM up-regulation/fibrosis are initiated very early in the course of the disease, represent a substantial component of the transcriptional response, and their DLIs were tightly coordinated (Pearson correlation coefficients: inflammation versus proteolysis, r=0.95; inflammation versus ECM, r=0.75; ECM versus proteolysis, r=0.90). The coordinated drop in the DLIs for all three processes between P56 and P112 may reflect, or actively contribute toward, the observed stabilization of histopathology in mdx mice of these ages. These data support the concept of co-regulation of contributing mechanisms in dystrophinopathy, potentially via multifunctional transcripts such as Spp1 (osteopontin), which originates from macrophages, is up-regulated 2.4-fold in pre-necrotic (P14) leg, maintains high expression levels throughout the disease course, and exerts signaling roles in both fibrosis and inflammation (8,38–43). These data, plus osteopontin protein detection in mdx (8) and gene up-regulation in DMD patients (11), suggest that it may be a viable therapeutic target in the absence of a primary cure.

Detection of macrophage markers by P14 and the involvement of macrophages and T-lymphocytes between P23 and P112, based on inflammatory cell expression marker analysis (Fig. 3C), were consistent with prior histologic findings in DMD and mdx (44–48). These data add to the compelling argument of Spencer and Tidball (7) that inflammation is not simply a consequence of dystrophinopathy, but rather an active participant in myofiber necrosis. Likewise, our data suggest the involvement of complement, interferon-related transcripts, and major histocompatibility complex molecules in dystrophic muscle, although few studies have addressed these putative mechanisms in any dystrophin-deficient muscle model (49–52). The rapid induction and sustained expression of CC class chemokines (Ccl2, Ccl6, Ccl7, Ccl8 and Ccl9) and corresponding chemokine receptors (Ccr2 and Ccr5; Fig. 3D) in mdx leg provides a selective mechanism for macrophage and T-cell recruitment. These chemokines specifically target the predominant mononuclear cell types identified in mdx muscle and all CC chemokines identified here have been seen previously in P56 mdx leg by transcript and/or protein assays (8,19). Moreover, the protein products of Ccl2 and Ccl6 are produced by mdx myofibers proper (19), suggestive of a pathogenic cycle involving dystrophin deficiency, myofiber-mediated pro-inflammatory chemotaxis, additional chemotaxis by recruited mononuclear cells and muscle damage amplification via inflammation.

Correlation with prior expression profiling studies
The majority of differentially regulated transcripts in mdx leg can be linked with known histopathologic features of the disease. Several prior studies used profiling techniques to evaluate mdx skeletal muscle at single ages (8,14,16,17). In the only prior temporal series (15), mdx data at all ages were compared with 12-week wild-type only, instead of to age-matched controls, using 1082-probe cDNA arrays. In that study, developmental- and disease-related changes are then intermingled and it is difficult to compare these data with our study of ~12 500 transcripts. We, however, compared our data with all other mdx profiling studies and with available data from DMD patients (9–13) (Supplementary Table 1). Forty three percent of the 719 transcripts that we detected in P7–P112 mdx muscle were previously reported in advanced stage (P56, P84, P84–105 or P112) mdx mice or in diagnostic biopsies from DMD patients, and 98% of these were altered in the same direction as in all prior studies. Our mdx data showed the highest correspondence with DMD studies for ECM and muscle/muscle regeneration transcript classes (29% also detected in DMD for both), consistent with the established importance of these mechanisms in all models of dystrophinopathy. By contrast, we observed only weak correspondence of mdx and DMD data for inflammation (8%) and metabolism (10%) transcripts. The paucity of correspondence in inflammation markers may relate either to the disease stage at the time of DMD biopsies or to an intrinsic difference in mdx versus DMD. Metabolism data are consistent with prior assertions that the energy metabolism crisis documented in DMD patients does not occur in mdx (8,9,16).


   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 CONCLUSIONS
MATERIALS AND METHODS
 SUPPLEMENTARY MATERIAL
 REFERENCES
 
Collectively, our data establish that several pathogenic pathways in mdx skeletal muscles are tightly inter-related and share features with DMD. The contrasting expression signatures of muscle groups that are targeted or spared in mdx show that downstream mechanisms are likely determinants of disease outcomes. DLI analysis identified a novel developmental delay and potentially broad co-regulation of select mechanisms secondary to the dystrophin mutation. Possible candidates for coordinated regulation of a wide variety of transcripts include transcription factor networks and co-activators that could simultaneously link multiple transcriptional pathways. Early recruitment of T-cells and macrophages by chemokines originating from muscle fibers proper (19) and the subsequent coordination of inflammation and fibrosis by the macrophage product, Spp1, is a compelling candidate mechanism. Subsequent validation of this and/or other signal transduction pathways responsible for the tight coordination of ECM, proteolysis and inflammation transcripts in mdx may yield new therapeutic means to mitigate the devastating consequences of DMD.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 CONCLUSIONS
 MATERIALS AND METHODS
SUPPLEMENTARY MATERIAL
 REFERENCES
 
Animals
Control (C57BL/10SnJ) and mdx (C57BL/10ScSn-Dmdmdx/J) mice (Jackson Laboratory, Bar Harbor, ME, USA) were bred to obtain a time series of pooled gastrocnemius/soleus muscles [postnatal day (P) 7, P14, P23, P28, P56, and P112] and EOMs (P14, P28, P56, and P112). Muscles from two to 10 (mean=5.5) male mice were pooled for each of three independent replicate analyses per muscle group, age and strain.

DNA microarray
DNA microarray was performed as described (8,20). Total RNA was extracted using Trizol (GibcoBRL, Rockville, MD, USA) and RNA pellets resuspended at 1 µg RNA/µl DEPC-treated water. Eight micrograms of RNA then were used in a reverse transcription reaction (SuperScript II; Life Technologies, Rockville, MD, USA) to generate first-strand cDNA. Double strand cDNA was synthesized and used in an in vitro transcription (IVT) reaction to generate biotinylated cRNA. Fifteen micrograms of purified and fragmented cRNA were used in a 300 µl hybridization cocktail containing spiked IVT controls; 200 µl of cocktail were hybridized onto Affymetrix (Santa Clara, CA, USA) MG-U74Av2 microarrays for 16 h at 45°C. Standard post-hybridization wash, double-stain and scanning protocols used an Affymetrix GeneChip Fluidics Station 400 and a Hewlett Packard Gene Array scanner.

Data analysis
Microarrays were scaled to the same target intensity and analyzed by Affymetrix Microarray Suite (MAS version 5.0). Pairwise comparisons were made between age-matched wild-type and mdx samples processed concurrently. Transcripts defined as differentially regulated met the criteria of: (a) consistent increase/decrease call in mdx versus wild-type in all replicates at one or more ages, based upon Wilcoxon's signed rank test (algorithm assesses probe pair saturation, calculates a P-value and determines increase, decrease or no change calls) and (b) absolute value of the average fold difference >=1.5. Silicon Genetics GeneSpring (version 4.2.1; Redwood City, CA, USA) was used for data normalization for hierarchical clustering.

To track stage-dependent changes in mdx mice, we used an aggregate measure designated as the DLI. The DLI is a unit-less measure, representing the sum of the fold change absolute values of all differentially regulated transcripts at a given age and muscle type. Transcripts were assigned to one or two of 11 major functional classes and to as many as five of 28 subclasses using NCBI LocusLink, Jackson Laboratory Mouse Genome Informatics, and Weizmann Institute of Science GeneCards. Major classes show overall trends for pathogenic processes (e.g. inflammation), while subclasses show trends for specific sets of transcripts contained within these processes (e.g. chemokines, complement). This approach allowed calculation of DLIs for both specific disease processes and classes of molecules.

Quantitative PCR (qPCR)
Select genes were verified by qPCR using SYBR green reagent and an Applied Biosystems (Foster City, CA, USA) 7000 instrument. Primers used and methodological details are in Table 1.


   SUPPLEMENTARY MATERIAL
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 CONCLUSIONS
 MATERIALS AND METHODS
 SUPPLEMENTARY MATERIAL
REFERENCES
 
Supplementary Material is available at HMG Online.


   ACKNOWLEDGEMENTS
 
We thank Scott Shnider, Clarence Williamson Jr, Jason Feuerman and Pat Porter for assistance with data management. These studies were supported by grants from the Muscular Dystrophy Association USA and NIH R01 EY09834 and R01 EY12779. Microarray and bioinformatics core support were from P30 CA43703 and P30 EY11371, respectively. J.D.P. received general laboratory support as the Carl F. Asseff, MD Professor of Ophthalmology.


   FOOTNOTES
 
* To whom correspondence should be addressed at: Department of Ophthalmology, Case Western Reserve University, 11100 Euclid Avenue, Cleveland, OH 44106-5068, USA. Tel: +1 2168447053; Fax: +1 2168444792; Email: jdp7{at}po.cwru.edu Back


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 CONCLUSIONS
 MATERIALS AND METHODS
 SUPPLEMENTARY MATERIAL
 REFERENCES
 

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