. Integrative gene-tissue microarray-based approach for identification of human disease biomarkers: application to amyotrophic lateral sclerosis. Hum Mol Genet. 2010 Aug 15;19(16):3233-53. PubMed.


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  1. We have read the very interesting article by Kudo et al. These scientists have performed a careful analysis to identify transcripts (in motor neurons and surrounding cells) that are differentially expressed between control mice and two different mouse models displaying motor neuron degeneration; the mutant SOD1G93A mouse model of familial ALS (fALS) and the mutant TauP301L mouse. They analyzed gene expression differences, using microarrays, in motor neurons, and in cells surrounding the motor neurons, isolated using laser capture microdissection. Their goal was to analyze pre-symptomatic animals in order to avoid studying events downstream of degeneration. The hypothesis was that identification of common molecular targets in the two genetically distinct disease models could represent general markers of neuronal vulnerability, instead of gene-specific effects. Commonly regulated genes could then perhaps translate not only to familiar ALS (fALS), but also to sporadic ALS (sALS).

    Using this strategy, 251 transcripts with altered gene expression were identified. Of these, only 12 transcripts were differentially regulated in both animal models. The microarray data was carefully confirmed using RT-PCR and immunohistochemical analysis. Importantly, of the 12 genes with differential regulation in both animal models, five genes (CNGA3, CRB1, OTUB2, MMP14, and RSPO2) were consistently differentially expressed also in sporadic ALS (sALS) patient material compared to control tissue (as analyzed by custom made tissue microarrays). It would be very interesting to find out if the remaining genes that were not differentially expressed in sALS patient postmortem material could be in fALS patient material. However, if these genes were not regulated similarly in fALS patients as in the disease models, it might reflect discrepancies between the animal models and the human disease(s) or, as suggested by the authors, an issue of comparing pre-symptomatic/early disease in the animal with end-stage of disease in the patients.

    Furthermore, to analyze if any differentially expressed genes could be identified in peripheral blood, and thereby be potential biomarkers of disease, a custom microarray harboring genes that were initially identified as differentially expressed was developed and 13 genes were identified in peripheral blood of the SOD1G93A mice.

    This study shows an example of a very stringent analysis and subsequent confirmation of microarray data on both RNA and protein level. Furthermore, mouse data was compared to sporadic ALS patient data to identify clinical relevance. It will be very interesting to see if the differential gene targets in common between the mutant SOD1 and tau models of motor neuron disease and sALS patient can be used to modulate neuronal vulnerability in vivo. Furthermore, if the markers identified in peripheral blood in the SOD1G93A transgenic mouse can also be inferred to ALS patient material that would be a big step forward in the early diagnosis of ALS (and subsequent future early treatment).

    In the present study, the SOD1G93A mice were analyzed at eight weeks of age in order to analyze pre-symptomatic animals. Paralysis, in general, begins at three months of age in this model of fALS (1,2). It should, however, be noted that the electrical properties of lumbar motor neurons and axonopathy already start during the first and second month of age in this model (3,4), long before onset of symptoms and loss of motor neuron cell bodies. Therefore, the motor neurons that were analyzed in this study were most likely already going through early molecular changes characteristic of their forthcoming demise. Perhaps a complementary analysis of even younger animals, four weeks old, could provide more common targets genes between the two disease models.

    Data from fALS models indicate that factors intrinsic to motor neurons are crucial for initiation of degeneration, while non-cell-autonomous events are instrumental for disease progression (1-9). A careful gene expression analysis of motor neurons and surrounding cells could therefore give clues to intrinsic and extrinsic mechanisms of motor neuron degeneration in ALS. In the present study, the isolation of cell types that were subsequently analyzed by microarrays was based on staining of spinal cord tissue with Cresyl violet. Motor neurons were clearly identified based on size, while punctuate staining of Cresyl violet was used for collection of surrounding cells, defined as glial cells. However, the surrounding cells isolated will be a mixture of astrocytes, oligodendrocytes, microglial cells, and small interneurons that surround (and innervate) motor neurons in the ventral horn. While it has been demonstrated that astrocytes and microglia can drive disease progression in mutant SOD1 mouse models of fALS (1,4), it is still unknown what role interneurons might play (9). While, oligodendrocytes don’t appear to drive initiation of disease in fALS models (10), the specific role of these cells in disease progression remains to be further characterized. In the present study, the microarray analysis of the likely mixture of cells isolated might be less informative than a selective analysis of the individual glial cell types (astrocytes versus microglial cells versus oligodendrocytes) and neuronal populations surrounding (and influencing) motor neurons.

    We have also aimed to identify targets of neuronal vulnerability, but using a different strategy (Hedlund et al., in press). Based on the differential loss of specific motor neuron subpopulations in motor neuron diseases, we isolated individual motor neurons from the oculomotor/trochlear complex (these do not degenerate in ALS), hypoglossal nucleus (show vulnerability in ALS), and from the ventral horn of the cervical spinal cord (degenerate in ALS) using laser capture microdissection in wild-type rats. We hypothesized that dissecting the intrinsic molecular code underlying the normal physiology of motor neurons that display differential vulnerability to disease could provide a basis for revealing why one motor neuron subpopulation is more vulnerable to degeneration than another. Our findings also support the use of gene profiling of vulnerable versus resistant cell populations to understand which molecules and pathways can be modified to protect against disease processes in vivo.


    . Onset and progression in inherited ALS determined by motor neurons and microglia. Science. 2006 Jun 2;312(5778):1389-92. PubMed.

    . Wild-type microglia extend survival in PU.1 knockout mice with familial amyotrophic lateral sclerosis. Proc Natl Acad Sci U S A. 2006 Oct 24;103(43):16021-6. PubMed.

    . Recovery from paralysis in adult rats using embryonic stem cells. Ann Neurol. 2006 Jul;60(1):32-44. PubMed.

    . Astrocytes as determinants of disease progression in inherited amyotrophic lateral sclerosis. Nat Neurosci. 2008 Mar;11(3):251-3. PubMed.

    . Astrocytes expressing ALS-linked mutated SOD1 release factors selectively toxic to motor neurons. Nat Neurosci. 2007 May;10(5):615-22. PubMed.

    . Non-cell autonomous effect of glia on motor neurons in an embryonic stem cell-based ALS model. Nat Neurosci. 2007 May;10(5):608-14. PubMed.

    . Human embryonic stem cell-derived motor neurons are sensitive to the toxic effect of glial cells carrying an ALS-causing mutation. Cell Stem Cell. 2008 Dec 4;3(6):637-48. PubMed.

    . Non-cell-autonomous effect of human SOD1 G37R astrocytes on motor neurons derived from human embryonic stem cells. Cell Stem Cell. 2008 Dec 4;3(6):649-57. PubMed.

    . ALS model glia can mediate toxicity to motor neurons derived from human embryonic stem cells. Cell Stem Cell. 2008 Dec 4;3(6):575-6. PubMed.

    . Mutant SOD1 in cell types other than motor neurons and oligodendrocytes accelerates onset of disease in ALS mice. Proc Natl Acad Sci U S A. 2008 May 27;105(21):7594-9. PubMed.

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  1. ALS Gene Expression and Biomarkers: A Better Way to Microarray?