The human genome project reached a major milestone earlier this year, with the completion
of a rough draft of the sequence (Pennisi 2000). An accessible catalog of all human
genes could greatly accelerate the pace of breakthroughs in medical research by allowing
global analyses of gene expression changes in a variety of developmental and pathological
states. However, it has never been clear whether these types of analyses could be
efficiently performed, or whether significant sets of important data would emerge
from the study of large sets of genes. Many diseases arise from single gene mutations
in which the corresponding protein products are known. Would knowledge of global gene
expression changes add to our existing understanding of these monogenic disorders
or lead to the development of treatments? A paper in this issue provides a test of
these questions and suggests that large scale gene expression profiling can contribute
greatly to an understanding of monogenic disease mechanisms, may simplify diagnosis
of genetic diseases, and could eventually provide important clues to assist with the
development of novel molecular therapies.
Chen et al. 2000 report a survey of gene expression changes in two types of muscular
dystrophy whose primary gene defect was known (Chen et al. 2000). The results demonstrate
both the power and value of this type of analysis while providing a number of interesting
insights into the underlying disease pathologies. This work also serves as a model
for the application of this approach to other monogenic disorders. Chen et al. have
carefully considered approaches to overcoming many of the inherent difficulties in
analyzing gene expression changes from diseased tissues, and provide a preliminary
check of some of the more intriguing observations of altered mRNA levels by immunolocalization
studies of the corresponding proteins. Together, these observations have confirmed
some previously known features of muscular dystrophies, have uncovered several novel
alterations that may contribute to disease pathology, and have revealed interesting
differences between two similar forms of dystrophy that may be as important to understanding
the disease pathogenesis as is knowledge of the primary defects that initiate muscle
cell degeneration.
The focus of the work by Chen et al. 2000 was on two related diseases, Duchenne and
limb–girdle muscular dystrophies (DMD and LGMD). DMD is the most common form of the
disease and arises from defects in the dystrophin gene (Monaco et al. 1986). Dystrophin
is an enormous cytoskeletal protein that links the muscle cytoskeleton to the extracellular
matrix (Koenig et al. 1988; Ervasti and Campbell 1993). This linkage facilitates force
transduction from the contractile apparatus to the connective tissue surrounding muscle
fibers, stabilizing the sarcolemma and minimizing contraction induced injuries (Petrof
et al. 1993; Lynch et al. 2000). Dystrophin works by interacting with a large number
of integral and peripheral membrane proteins known as the dystrophin glycoprotein
complex (DGC), which includes four members encoded by the sarcoglycan gene family
(Ibraghimov-Beskrovnaya et al. 1992; Ozawa et al. 1995). Mutations in any of the sarcoglycan
genes lead to different types of LGMD, which are distinct, yet similar diseases to
DMD (Bönnemann et al. 1995; Bushby 1999).
Most models for the function of the DGC imply that mutation of either dystrophin or
one of the sarcoglycans should render the DGC nonfunctional and lead to essentially
identical phenotypes, yet a surprising number of differences have been observed. Some
groups have speculated that the sarcoglycans and other DGC members such as the syntrophin
and dystrobrevin family members could play auxiliary roles in maintaining normal muscle
function by regulating or localizing signal transduction molecules. These signaling
pathways would presumably help muscle cells adapt to the myriad forms of stress imposed
by muscle activity. However, despite extensive analysis in transgenic mice and induced
knockout models for the sarcoglycans, the nature and importance of these signals remains
obscure (Hack et al. 1998; Grady et al. 1999; Crawford et al. 2000).
Understanding the precise function of the DGC may facilitate development of an efficient
therapy for the muscular dystrophies. Despite knowledge of the primary genetic defects,
the mechanisms that lead to muscle cell dysfunction and death in the muscular dystrophies
are poorly understood. For example, how does the absence of dystrophin lead to instability
of the sarcolemma? Why do different disruptions of the DGC lead to different manifestations
of the dystrophic process? The overall phenotypic manifestations of these diseases
presumably result from a combination of muscle fiber necrosis, incomplete regeneration,
infiltration of damaged muscle with immune effector cells, perturbed metabolic capacity,
reduced blood supply to exercising muscle, activation of apoptotic pathways, and many
other unknown processes. Developing a compete understanding of these multiple pathological
events could help guide new types of therapies, as well as provide reference points
for assessing the effectiveness of therapeutic intervention. For these reasons, the
global gene expression analysis of Chen et al. 2000 plays an especially important
role, by providing the first overall picture of the gene expression state of dystrophic
muscle tissue.
Chen et al. 2000 provide a significant amount of clarity to the overall pattern of
gene expression in dystrophic muscle because of their elaborate and well controlled
approach. A direct comparison between a dystrophic and a normal muscle sample is difficult
to interpret due to phenotypic variations within an individual muscle biopsy, as well
as patient-specific differences arising from genetic variability. In addition, comparison
of samples only from DMD patients and normal controls might reveal both specific and
nonspecific alterations, making it difficult to identify the most important differences.
Chen et al. 2000 solved some of these dilemmas by analyzing pooled samples from multiple
controls in parallel with pooled samples from multiple patients that had either DMD,
or LGMD resulting from mutations in the alpha-sarcoglycan gene. To reduce the problems
that might arise from variations within a given biopsy and provide independent confirmation
of the data sets, each muscle specimen was divided in half before preparing pooled
sets for parallel processing. Pooled probes made from the sample sets were analyzed
for gene expression by hybridization to the Affymetrix HuGeneFL microarray that contains
sequences from ∼6,000 human genes. Sophisticated data analysis tools were then used
to compare each result and identify trends. The authors focused on several types of
changes. Initially, genes whose expression was consistently elevated or reduced in
either type of dystrophy were identified. Next, genes whose expression was consistently
altered only in one of the two types of dystrophy were identified. As a result, the
authors derived a list of genes whose products were likely to be altered in any general
dystrophic process and those that might contribute to specific features of a single
form of muscular dystrophy. Finally, a select subset of the more interesting and accessible
alterations was confirmed by immunologic analysis of muscle biopsies. While this enormous
data set will require a great deal of further analysis, a variety of interesting and
novel trends have already emerged.
An initial observation from the data sets is that many secondary features of the disease,
which had been hinted at in earlier studies were confirmed and extended, such as a
generalized metabolic crisis manifested by a significant reduction in the expression
of many nuclear-encoded mitochondrial genes. Upregulated gene expression was also
observed for many cell surface and extracellular proteins, perhaps reflecting the
widespread fibrosis and mononuclear cell infiltrates seen in dystrophies. In addition,
a number of calcium-regulated signaling molecules were downregulated, potentially
providing new insights into pathways affected by the altered calcium homeostasis that
results from ruptures in the sarcolemma membrane. Perhaps more importantly, a number
of novel observations were apparent that should inspire increased efforts to examine
the consequence of these changes on the dystrophies. A few examples of the many novel
observations from the gene expression analysis include reduced levels of the protein
kinase ERK6 and the protein phosphatase pTPH1 in DMD, but not in LGMD. The expression
of numerous genes involved in cell growth and signaling was also upregulated. Intriguingly,
several markers for activated dendritic cells were elevated in dystrophic samples,
supporting a role for immune effector cells altering the microenvironment of dystrophic
muscle.
One of the more striking observations made by Chen et al. (2000) is that dystrophic
muscle may exist in a generalized state of incomplete differentiation. Widespread
elevated levels of embryonic muscle isoforms for both myosin heavy chain and alpha-actin
support the idea of a generalized state of incomplete differentiation, and the observed
changes can not be accounted for solely by the number of actively regenerating fibers.
Reduced mRNA levels for the alpha subunit of the acetylcholine receptor could contribute
to neuromuscular junction structural abnormalities seen in DMD and may inhibit complete
muscle maturation by contributing to a functional denervation of the muscle (Rafael
et al. 2000). The authors also provide evidence for a process by which cells in dystrophic
muscle tissue might be undergoing a dedifferentiation into alternate lineages such
as bone and connective tissue precursors.
Despite the enormous wealth of information produced by Chen et al. 2000, it is clear
that many additional observations remain to be mined from these data sets. Further
interpretation of the emerging trends will also be aided by additional studies on
biopsies obtained at different stages of disease progression and from additional forms
of muscular dystrophy. However, the present data have already provided numerous new
insights that will immediately aid studies of the disease pathogenesis. These data
should also lead to a variety of new targets to treat secondary pathological features
of the diseases, and may well provide a generalized method to monitor the efficacy
of such interventions, which might be used either singly or in combination with cell
and gene based therapies (Hartigan-O'Connor and Chamberlain 2000). Finally, as Chen
et al. 2000 note, these approaches may also serve as a basis for differential diagnosis
of the many types of muscular dystrophy by enabling test of specific molecule signatures
associated with each individual primary genetic defect. This convergence of the human
genome project and molecular medicine may well be a critical factor in finding a cure
for muscular dystrophy.