February 4, 2004 - BETHESDA, MD -- Amyotrophic lateral sclerosis (ALS) may be better known to some as "Lou Gehrig's disease," a reference to the great New York Yankees hitter and teammate of Babe Ruth who was struck down by the disease. Some 30,000 Americans now suffer from this disabling, almost invariably fatal, disease that is caused by the degeneration of the body's motor neurons, muscle atrophy and weakness.
No one knows what causes the process of terminal neurodegernation to begin. However, using a two-step process to analyze 6,800 genes, scientists have now found an ALS-specific "signature" in spinal cord gray matter taken from ALS patients. The researchers were also able to distinguish familial ALS (FALS) from sporadic ALS (SALS). They believe their approach can reveal some of the distinct changes that underlie the terminal stages in the disease.
A New Study
The new study is entitled "The Molecular Signature of Late-Stage Human ALS Revealed By Expression Profiling of Post-Mortem Spinal Cord Gray Matter." The authors are Fernando Dangond and Sandra Camelo, Laboratory of Transcriptional and Immune Regulation, Center for Neurologic Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Daehee Hwang, Gregory Stephanopoulos and George Stephanopoulos, of the Bioinformatics and Metabolic Engineering Laboratory, Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA; Piera Pasinelli and Robert H. Brown, Jr., of the Day Neuromuscular Research Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston, MA; Matthew P. Frosch, from the C.S. Kubik, Laboratory of Neuropathology, Department of Neuropathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; and Steven R. Gullans of the Laboratory of Functional Genomics, Department of Neurology, Harvard Medical School, Boston, MA. Their findings are published in the January 2004 edition of Physiological Genomics. The journal is one of 14 scientific journals published monthly by the American Physiological Society (APS) (www.the-aps.org).
Postmortem gray matter tissues from the lumbar spinal cord were obtained from tissue banks. Samples from 11 individuals were used, including 7 with ALS and 4 normal controls. The 7 ALS spinal cords were obtained from five individuals with sporadic ALS and 2 with familial ALS. All samples were frozen and frozen tissues were dissected to separate gray and white matter and isolate total RNA.
DNA microanalysis was performed with the microarrays representing approximately 6,800 human genes. Scanned image files were converted to mRNA expression levels using software programs. To generate a discriminatory gene list, all genes with maximum intensities below a value of 1500 across all samples were excluded. Thus, the analysis was designed to obtain the genes with highest statistical significance.
To discriminate gray matters of ALS from gray matters of normal spinal cord, the leave-one-out cross-validation (LOOCV) procedure, coupled with Wilks' lambda, was used to identify a robust set of discriminatory genes. A Fisher Discriminant Analysis (FDA) was also used in the analyses.
Relative quantitation with real-time, one-step quantitative reverse-transcriptase polymerase chain reaction (QRT-PCR) was performed multiple times on RNA isolated from whole spinal cord tissue.
Highlights of the results include the following:
a final set of informative discriminatory genes could be identified as the top 93 genes in ALS;
microarray data combined with the statistical analyses provided a characteristic signature of the gray matter components of ALS pathology;
a distinct signature for familial ALS and sporadic ALS spinal cord gray matter gene expression was discerned (also demonstrating that global transcriptional profiling can capture the prominent molecular phenotypes of various forms of ALS, when compared to normal spinal cords); and
genes significantly altered in ALS uncovered a pro-inflammatory terminal state.
It is apparent from these findings that DNA microrray analysis and appropriate bioinformatics can provide a window into the late stages of the molecular pathophysiology of human neurodegeneration.
Source: Eurekalert & othersLast reviewed: By John M. Grohol, Psy.D. on 21 Feb 2009
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