Gene expression profiling in human neurodegenerative disease

Nature Reviews Neurology

Volumn 8, Issue 9, 2012, Pages 518-530

  Cooper Knock, Johnathan ^a   Kirby, Janine ^a   Ferraiuolo, Laura ^a   Heath, Paul R ^a   Rattray, Magnus ^a   Shaw, Pamela J ^a  

^a UNIVERSITY OF SHEFFIELD   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL MARKER; PROTEASOME; TRANSCRIPTOME; UBIQUITIN;

ALZHEIMER DISEASE; AMYOTROPHIC LATERAL SCLEROSIS; CALCIUM SIGNALING; DATA ANALYSIS; DISORDERS OF MITOCHONDRIAL FUNCTIONS; EXON; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENE MUTATION; GENETIC SUSCEPTIBILITY; HUMAN; INTRACELLULAR SIGNALING; LASER CAPTURE MICRODISSECTION; MICROARRAY ANALYSIS; MIXED CELL CULTURE; MOLECULAR PATHOLOGY; NONHUMAN; PARKINSON DISEASE; PRIORITY JOURNAL; PROTEIN METABOLISM; REVIEW; RNA SEQUENCE; RNA SPLICING; TISSUE PREPARATION; VALIDATION PROCESS;

GENE EXPRESSION PROFILING; GENETIC PREDISPOSITION TO DISEASE; GENOMICS; HUMANS; NEURODEGENERATIVE DISEASES;

EID: 84866062627     PISSN: 17594758     EISSN: 17594766     Source Type: Journal    
DOI: 10.1038/nrneurol.2012.156     Document Type: Review

References (130)

1. Schena, M., Shalon, D., Davis, R. W. & Brown, P. O. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270, 467-470 (1995).
2. Saris, C. G. et al. Weighted gene co-expression network analysis of the peripheral blood from amyotrophic lateral sclerosis patients. BMC Genomics 10, 405 (2009).
3. Offen, D. et al. Spinal cord mRNA profile in patients with ALS: Comparison with transgenic mice expressing the human SOD 1 mutant. J. Mol. Neurosci. 38, 85-93 (2009).
4. Wang, X. S., Simmons, Z., Liu, W., Boyer, P. J. & Connor, J. R. Differential expression of genes in amyotrophic lateral sclerosis revealed by profiling the post mortem cortex. Amyotroph. Lateral Scler. 7, 201-210 (2006).
5. Lederer, C. W., Torrisi, A., Pantelidou, M., Santama, N. & Cavallaro, S. Pathways and genes differentially expressed in the motor cortex of patients with sporadic amyotrophic lateral sclerosis. BMC Genomics 8, 26 (2007).
6. Ferraiuolo, L., Kirby, J., Grierson, A. J., Sendtner, M. & Shaw, P. J. Molecular pathways of motor neuron injury in amyotrophic lateral sclerosis. Nat. Rev. Neurol. 7, 616-630 (2011).
7. Kirby, J. et al. Phosphatase and tensin homologue/protein kinase B pathway linked to motor neuron survival in human superoxide dismutase 1 related amyotrophic lateral sclerosis. Brain 134, 506-517 (2011).
8. Jiang, Y. M. et al. Gene expression profile of spinal motor neurons in sporadic amyotrophic lateral sclerosis. Ann. Neurol. 57, 236-251 (2005).
9. Rabin, S. J. et al. Sporadic ALS has compartment-specific aberrant exon splicing and altered cell-matrix adhesion biology. Hum. Mol. Genet. 19, 313-328 (2010).
10. Cox, L. E. et al. Mutations in CHMP2B in lower motor neuron predominant amyotrophic lateral sclerosis (ALS). PLoS ONE 5, e9872 (2010).
11. Hewitt, C. et al. Novel FUS/TLS mutations and pathology in familial and sporadic amyotrophic lateral sclerosis. Arch. Neurol. 67, 455-461 (2010).
12. Kirby, J. et al. Broad clinical phenotypes associated with TAR-DNA binding protein (TARDBP) mutations in amyotrophic lateral sclerosis. Neurogenetics 11, 217-225 (2010).
13. Kirby, J. et al. Mutant SOD1 alters the motor neuronal transcriptome: Implications for familial ALS. Brain 128, 1686-1706 (2005).
14. Ferraiuolo, L. et al. Microarray analysis of the cellular pathways involved in the adaptation to and progression of motor neuron injury in the SOD1 G93A mouse model of familial ALS. J. Neurosci. 27, 9201-9219 (2007).
15. Zhang, R. et al. Gene expression profiling in peripheral blood mononuclear cells from patients with sporadic amyotrophic lateral sclerosis (sALS). J. Neuroimmunol. 230, 114-123 (2011).
16. Mougeot, J. L., Li, Z., Price, A., Wright, F. & Brooks, B. Microarray analysis of peripheral blood lymphocytes from ALS patients and the SAFE detection of the KEGG ALS pathway. BMC Med. Genomics 4, 74 (2011).
17. Pradat, P. F. et al. Muscle gene expression is a marker of amyotrophic lateral sclerosis severity. Neurodegen. Dis. 9, 38-52 (2012).
18. Shtilbans, A. et al. Differential gene expression in patients with amyotrophic lateral sclerosis. Amyotroph. Lateral Scler. 12, 250-256 (2011).
19. Scherzer, C. R. et al. Molecular markers of early Parkinson's disease based on gene expression in blood. Proc. Natl Acad. Sci. USA 104, 955-960 (2007).
20. Zheng, B. et al. PGC 1α, a potential therapeutic target for early intervention in Parkinson's disease. Sci. Transl. Med. 2, 52ra73 (2010).
21. Elstner, M. et al. Expression analysis of dopaminergic neurons in Parkinson's disease and aging links transcriptional dysregulation of energy metabolism to cell death. Acta Neuropathol. 122, 75-86 (2011).
22. Shin, J. H. et al. PARIS (ZNF746) repression of PGC 1α contributes to neurodegeneration in Parkinson's disease. Cell 144, 689-702 (2011).
23. Papapetropoulos, S. et al. Multiregional gene expression profiling identifies MRPS6 as a possible candidate gene for Parkinson's disease. Gene Expr. 13, 205-215 (2006).
24. Moran, L. et al. Whole genome expression profiling of the medial and lateral substantia nigra in Parkinson's disease. Neurogenetics 7, 1-11 (2006).
25. Hauser, M. A. et al. Expression profiling of substantia nigra in Parkinson disease, progressive supranuclear palsy, and frontotemporal dementia with parkinsonism. Arch. Neurol. 62, 917-921 (2005).
26. Zhang, Y., James, M., Middleton, F. A. & Davis, R. L. Transcriptional analysis of multiple brain regions in Parkinson's disease supports the involvement of specific protein processing, energy metabolism, and signaling pathways, and suggests novel disease mechanisms. Am. J. Med. Genet. B Neuropsychiatr. Genet. 137B, 5-16 (2005).
27. Vogt, I. R. et al. Transcriptional changes in multiple system atrophy and Parkinson's disease putamen. Exp. Neurol. 199, 465-478 (2006).
28. Naydenov, A., Vassoler, F., Luksik, A., Kaczmarska, J. & Konradi, C. Mitochondrial abnormalities in the putamen in Parkinson's disease dyskinesia. Acta Neuropathol. 120, 623-631 (2010).
29. Botta-Orfila, T. et al. Microarray expression analysis in idiopathic and LRRK2-associated Parkinson's disease. Neurobiol. Dis. 45, 462-468 (2012).
30. Durrenberger, P. et al. Inflammatory pathways in Parkinson's disease; a BNE microarray study. Parkinson Dis. 2012, 214714 (2012).
31. Bossers, K. et al. Analysis of gene expression in Parkinson's disease: Possible involvement of neurotrophic support and axon guidance in dopaminergic cell death. Brain Pathol. 19, 91-107 (2009).
32. Miller, R. M. et al. Robust dysregulation of gene expression in substantia nigra and striatum in Parkinson's disease. Neurobiol. Dis. 21, 305-313 (2006).
33. Duke, D., Moran, L., Pearce, R. & Graeber, M. The medial and lateral substantia nigra in Parkinson's disease: MRNA profiles associated with higher brain tissue vulnerability. Neurogenetics 8, 83-94 (2007).
34. Fearnley, J. M. & Lees, A. J. Ageing and Parkinson's disease: Substantia nigra regional selectivity. Brain 114, 2283-2301 (1991).
35. Zhou, C., Huang, Y. & Przedborski, S. Oxidative stress in Parkinson's disease. Ann. NY Acad. Sci. 1147, 93-104 (2008).
36. Rideout, H. J., Larsen, K. E., Sulzer, D. & Stefanis, L. Proteasomal inhibition leads to formation of ubiquitin/α synuclein immunoreactive inclusions in PC12 cells. J. Neurochem. 78, 899-908 (2001).
37. Vila, M. & Przedborski, S. Targeting programmed cell death in neurodegenerative diseases. Nat. Rev. Neurosci. 4, 365-375 (2003).
38. Ved, R. et al. Similar patterns of mitochondrial vulnerability and rescue induced by genetic modification of α synuclein, parkin, and DJ 1 in Caenorhabditis elegans. J. Biol. Chem. 280, 42655-42668 (2005).
39. Dawson, T. M. & Dawson, V. L. Molecular pathways of neurodegeneration in Parkinson's disease. Science 302, 819-822 (2003).
40. Quigley, P. M., Korotkov, K., Baneyx, F. & Hol, W. G. The 1.6 Å crystal structure of the class of chaperones represented by Escherichia coli Hsp31 reveals a putative catalytic triad. Proc. Natl Acad. Sci. USA 100, 3137-3142 (2003).
41. Moran, L. et al. Analysis of alpha-synuclein, dopamine and parkin pathways in neuropathologically confirmed parkinsonian nigra. Acta Neuropathol. 113, 253-263 (2007).
42. Duke, D. et al. Transcriptome analysis reveals link between proteasomal and mitochondrial pathways in Parkinson's disease. Neurogenetics 7, 139-148 (2006).
43. Mortiboys, H., Johansen, K., Aasly, J. & Bandmann, O. Mitochondrial impairment in patients with Parkinson disease with the G2019S mutation in LRRK2. Neurology 75, 2017-2020 (2010).
44. Cantuti-Castelvetri, I. et al. Effects of gender on nigral gene expression and Parkinson disease. Neurobiol. Dis. 26, 606-614 (2007).
45. Simunovic, F. et al. Gene expression profiling of substantia nigra dopamine neurons: further insights into Parkinson's disease pathology. Brain 132, 1795-1809 (2009).
46. Stamper, C. et al. Neuronal gene expression correlates of Parkinson's disease with dementia. Mov. Disord. 23, 1588-1595 (2008).
47. Simunovic, F., Yi, M., Wang, Y., Stephens, R. & Sonntag, K. C. Evidence for gender-specific transcriptional profiles of nigral dopamine neurons in Parkinson disease. PLoS ONE 5, e8856 (2010).
48. Surmeier, D. J. Calcium, ageing, and neuronal vulnerability in Parkinson's disease. Lancet Neurol. 6, 933-938 (2007).
49. Shehadeh, L. A. et al. SRRM2, a potential blood biomarker revealing high alternative splicing in Parkinson's disease. PLoS ONE 5, e9104 (2010).
50. Mar, J. C. et al. Variance of gene expression identifies altered network constraints in neurological disease. PLoS Genet. 7, e1002207 (2011).
51. Matigian, N. et al. Disease-specific, neurosphere-derived cells as models for brain disorders. Dis. Model. Mech. 3, 785-798 (2010).
52. Mutez, E. et al. Transcriptional profile of Parkinson blood mononuclear cells with LRRK2 mutation. Neurobiol. Aging 32, 1839-1848 (2011).
53. Parachikova, A. et al. Inflammatory changes parallel the early stages of Alzheimer disease. Neurobiol. Aging 28, 1821-1833 (2007).
54. Tan, M. G. et al. Genome wide profiling of altered gene expression in the neocortex of Alzheimer's disease. J. Neurosci. Res. 88, 1157-1169 (2010).
55. Williams, C. et al. Transcriptome analysis of synaptoneurosomes identifies neuroplasticity genes overexpressed in incipient Alzheimer's disease. PLoS ONE 4, e4936 (2009).
56. Xu, P. T. et al. Differences in apolipoprotein E3/3 and E4/4 allele-specific gene expression in hippocampus in Alzheimer disease. Neurobiol. Dis. 21, 256-275 (2006).
57. Emilsson, L., Saetre, P. & Jazin, E. Alzheimer's disease: MRNA expression profiles of multiple patients show alterations of genes involved with calcium signaling. Neurobiol. Dis. 21, 618-625 (2006).
58. Haroutunian, V., Katsel, P. & Schmeidler, J. Transcriptional vulnerability of brain regions in Alzheimer's disease and dementia. Neurobiol. Aging 30, 561-573 (2009).
59. Katsel, P., Li, C. & Haroutunian, V. Gene expression alterations in the sphingolipid metabolism pathways during progression of dementia and Alzheimer's disease: A shift toward ceramide accumulation at the earliest recognizable stages of Alzheimer's disease? Neurochem. Res. 32, 845-856 (2007).
60. Katsel, P., Tan, W. & Haroutunian, V. Gain in brain immunity in the oldest-old differentiates cognitively normal from demented individuals. PLoS ONE 4, e7642 (2009).
61. Umemura, K. et al. Autotaxin expression is enhanced in frontal cortex of Alzheimer-type dementia patients. Neurosci. Lett. 400, 97-100 (2006).
62. Weeraratna, A. T. et al. Alterations in immunological and neurological gene expression patterns in Alzheimer's disease tissues. Exp. Cell Res. 313, 450-461 (2007).
63. Bronner, I. F. et al. Comprehensive mRNA expression profiling distinguishes tauopathies and identifies shared molecular pathways. PLoS ONE 4, e6826 (2009).
64. Bossers, K. et al. Concerted changes in transcripts in the prefrontal cortex precede neuropathology in Alzheimer's disease. Brain 133, 3699-3723 (2010).
65. Horesh, Y., Katsel, P., Haroutunian, V. & Domany, E. Gene expression signature is shared by patients with Alzheimer's disease and schizophrenia at the superior temporal gyrus. Eur. J. Neurol. 18, 410-424 (2011).
66. Youn, H. et al. Kalirin is under-expressed in Alzheimer's disease hippocampus. J. Alzheimers Dis. 11, 385-397 (2007).
67. Wang, S., Qaisar, U., Yin, X. & Grammas, P. Gene expression profiling in Alzheimer's disease brain microvessels. J. Alzheimers Dis. http://dx.doi.org/10.3233/JAD 2012 120454.
68. Tollervey, J. R. et al. Analysis of alternative splicing associated with aging and neurodegeneration in the human brain. Genome Res. 21, 1572-1582 (2011).
69. Kuchibhotla, K. V. et al. Aβ plaques lead to aberrant regulation of calcium homeostasis in vivo resulting in structural and functional disruption of neuronal networks. Neuron 59, 214-225 (2008).
70. Guo, Q. et al. Alzheimer's PS 1 mutation perturbs calcium homeostasis and sensitizes PC12 cells to death induced by amyloid peptide. Neuroreport 8, 379-383 (1996).
71. Camandola, S. & Mattson, M. P. Aberrant subcellular neuronal calcium regulation in aging and Alzheimer's disease. Biochim. Biophys. Acta 1813, 965-973 (2011).
72. Berchtold, N. C. et al. Gene expression changes in the course of normal brain aging are sexually dimorphic. Proc. Natl Acad. Sci. USA 105, 15605-15610 (2008).
73. Saetre, P., Jazin, E. & Emilsson, L. Age-related changes in gene expression are accelerated in Alzheimer's disease. Synapse 65, 971-974 (2011).
74. Masliah, E. et al. Altered expression of synaptic proteins occurs early during progression of Alzheimer's disease. Neurology 56, 127-129 (2001).
75. Giuditta, A. et al. Local gene expression in axons and nerve endings: The glia-neuron unit. Physiol. Rev. 88, 515-555 (2008).
76. Liang, W. S. et al. Altered neuronal gene expression in brain regions differentially affected by Alzheimer's disease: A reference data set. Physiol. Genomics 33, 240-256 (2008).
77. Liang, W. S. et al. Alzheimer's disease is associated with reduced expression of energy metabolism genes in posterior cingulate neurons. Proc. Natl Acad. Sci. USA 105, 4441-4446 (2008).
78. Dunckley, T. et al. Gene expression correlates of neurofibrillary tangles in Alzheimer's disease. Neurobiol. Aging 27, 1359-1371 (2006).
79. Alexander, G. E., Chen, K., Pietrini, P., Rapoport, S. I. & Reiman, E. M. Longitudinal PET evaluation of cerebral metabolic decline in dementia: A potential outcome measure in Alzheimer's disease treatment studies. Am. J. Psychiatry 159, 738-745 (2002).
80. Minoshima, S. et al. Metabolic reduction in the posterior cingulate cortex in very early Alzheimer's disease. Ann. Neurol. 42, 85-94 (1997).
81. Ray, M. & Zhang, W. Analysis of Alzheimer's disease severity across brain regions by topological analysis of gene co-expression networks. BMC Syst. Biol. 4, 136 (2010).
82. Liu, Z. P., Wang, Y., Zhang, X. S. & Chen, L. Identifying dysfunctional crosstalk of pathways in various regions of Alzheimer's disease brains. BMC Syst. Biol. 4, S11 (2010).
83. Ray, M., Ruan, J. & Zhang, W. Variations in the transcriptome of Alzheimer's disease reveal molecular networks involved in cardiovascular diseases. Genome Biol. 9, R148 (2008).
84. Gorelick, P. B. et al. Vascular contributions to cognitive impairment and dementia. Stroke 42, 2672-2713 (2011).
85. Helbecque, N. & Amouyel, P. Commonalities between genetics of cardiovascular disease and neurodegenerative disorders. Curr. Opin. Lipidol. 15, 121-127 (2004).
86. Simpson, J. E. et al. Microarray analysis of the astrocyte transcriptome in the aging brain: Relationship to Alzheimer's pathology and APOE genotype. Neurobiol. Aging 32, 1795-1807 (2011).
87. Strittmatter, W. J. et al. Apolipoprotein E: High-avidity binding to β-amyloid and increased frequency of type 4 allele in late-onset familial Alzheimer disease. Proc. Natl Acad. Sci. USA 90, 1977-1981 (1993).
88. Maes, O. C. et al. Transcriptional profiling of Alzheimer blood mononuclear cells by microarray. Neurobiol. Aging 28, 1795-1809 (2007).
89. Nagasaka, Y. et al. A unique gene expression signature discriminates familial Alzheimer's disease mutation carriers from their wild-type siblings. Proc. Natl Acad. Sci. USA 102, 14854-14859 (2005).
90. Calciano, M. A., Zhou, W., Snyder, P. J. & Einstein, R. Drug treatment of Alzheimer's disease patients leads to expression changes in peripheral blood cells. Alzheimers Dement. 6, 386-393 (2010).
91. Booij, B. B. et al. A gene expression pattern in blood for the early detection of Alzheimer's disease. J. Alzheimers Dis. 23, 109-119 (2011).
92. Kálmán, J. et al. Gene expression profile analysis of lymphocytes from Alzheimer's patients. Psychiatr. Genet. 15, 1-6 (2005).
93. Fehlbaum-Beurdeley, P. et al. Toward an Alzheimer's disease diagnosis via high-resolution blood gene expression. Alzheimers Dement. 6, 25-38 (2010).
94. Chen, K. D. et al. Gene expression profiling of peripheral blood leukocytes identifies and validates ABCB1 as a novel biomarker for Alzheimer's disease. Neurobiol. Dis. 43, 698-705 (2011).
95. Rye, P. D. et al. A novel blood test for the early detection of Alzheimer's disease. J. Alzheimers Dis. 23, 121-129 (2011).
96. Scherzer, C. et al. Loss of apolipoprotein E receptor LR11 in Alzheimer disease. Arch. Neurol. 61, 1200-1205 (2004).
97. Lee, J., Barral, S. & Reitz, C. The neuronal sortilin-related receptor gene SORL1 and late-onset Alzheimer's disease. Curr. Neurol. Neurosci. Rep. 8, 384-391 (2008).
98. Sutherland, G. T., Janitz, M. & Kril, J. J. Understanding the pathogenesis of Alzheimer's disease: Will RNA-Seq realize the promise of transcriptomics? J. Neurochem. 116, 937-946 (2011).
99. Emmert-Buck, M. R. et al. Laser capture microdissection. Science 274, 998-1001 (1996).
100. Sutherland, G. T. et al. A cross-study transcriptional analysis of Parkinson's disease. PLoS ONE 4, e4955 (2009).
101. Casale, V., Oneda, R., Lavezzi, A. M. & Matturri, L. Optimisation of postmortem tissue preservation and alternative protocol for serotonin transporter gene polymorphisms amplification in SIDS and SIUD cases. Exp. Mol. Pathol. 88, 202-205 (2010).
102. Durrenberger, P. F. et al. Effects of antemortem and postmortem variables on human brain mRNA quality: A BrainNet Europe study. J. Neuropathol. Exp. Neurol. 69, 70-81 (2010).
103. Strand, C., Enell, J., Hedenfalk, I. & Ferno, M. RNA quality in frozen breast cancer samples and the influence on gene expression analysis - A comparison of three evaluation methods using microcapillary electrophoresis traces. BMC Mol. Biol. 8, 38 (2007).
104. Schroeder, A. et al. The RIN: An RNA integrity number for assigning integrity values to RNA measurements. BMC Mol. Biol. 7, 3 (2006).
105. Copois, V. et al. Impact of RNA degradation on gene expression profiles: Assessment of different methods to reliably determine RNA quality. J. Biotechnol. 127, 549-559 (2007).
106. Tan, P. K., et al. Evaluation of gene expression measurements from commercial microarray platforms. Nucleic Acids Res. 31, 5676-5684 (2003).
107. MAQC Consortium et al. The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements. Nat. Biotech. 24, 1151-1161 (2006).
108. Posekany, A., Felsenstein, K. & Sykacek, P. Biological assessment of robust noise models in microarray data analysis. Bioinformatics 27, 807-814 (2011).
109. Stekel, D. Microarray Bioinformatics 110-138 (Cambridge University Press, Cambridge, UK, 2003).
110. Storey, J. D., Dai, J. Y. & Leek, J. T. The optimal discovery procedure for large-scale significance testing, with applications to comparative microarray experiments. Biostatistics 8, 414-432 (2007).
111. Hosack, D., Dennis, G., Sherman, B., Lane, H. & Lempicki, R. Identifying biological themes within lists of genes with EASE. Genome Biol. 4, R70 (2003).
112. Smyth, G. K. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat. Appl. Genet. Mol. Biol. 3, Article 3 (2004).
113. Liu, X., Milo, M., Lawrence, N. D. & Rattray, M. Probe-level measurement error improves accuracy in detecting differential gene expression. Bioinformatics 22, 2107-2113 (2006).
114. Blencowe, B. J., Ahmad, S. & Lee, L. J. Current-generation high-throughput sequencing: Deepening insights into mammalian transcriptomes. Genes Dev. 23, 1379-1386 (2009).
115. Yamamoto, M. L. et al. Alternative pre-mRNA splicing switches modulate gene expression in late erythropoiesis. Blood 113, 3363-3370 (2009).
116. Sultan, M. et al. A global view of gene activity and alternative splicing by deep sequencing of the human transcriptome. Science 321, 956-960 (2008).
117. Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L. & Wold, B. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat. Methods 5, 621-628 (2008).
118. Metzker, M. L. Sequencing technologies - The next generation. Nat. Rev. Genet. 11, 31-46 (2010).
119. Tariq, M. A., Kim, H. J., Jejelowo, O. & Pourmand, N. Whole-transcriptome RNAseq analysis from minute amount of total RNA. Nucleic Acids Res. http://dx.doi.org/10.1093/nar/gkr547.
120. Łabaj, P. P. et al. Characterization and improvement of RNA-Seq precision in quantitative transcript expression profiling. Bioinformatics 27, i383-i391 (2011).
121. Pascale, F. B. et al. Toward an Alzheimer's disease diagnosis via high-resolution blood gene expression. Alzheimers Dement. 6, 25-38 (2010).
122. Kaklamani, V. A genetic signature can predict prognosis and response to therapy in breast cancer: oncotype DX. Expert Rev. Mol. Diagn. 6, 803-809 (2006).
123. Shi, L. et al. The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models. Nat. Biotechnol. 28, 827-838 (2010).
124. Rottenberg, S. et al. Impact of intertumoral heterogeneity on predicting chemotherapy response of BRCA1-deficient mammary tumors. Cancer Res. 72, 2350-2361 (2012).
125. Ein-Dor, L., Kela, I., Getz, G., Givol, D. & Domany, E. Outcome signature genes in breast cancer: Is there a unique set? Bioinformatics 21, 171-178 (2005).
126. Ein-Dor, L., Zuk, O. & Domany, E. Thousands of samples are needed to generate a robust gene list for predicting outcome in cancer. Proc. Natl Acad. Sci. USA 103, 5923-5928 (2006).
127. Cabeza-Arvelaiz, Y. et al. Analysis of striatal transcriptome in mice overexpressing human wild-type alpha-synuclein supports synaptic dysfunction and suggests mechanisms of neuroprotection for striatal neurons. Mol. Neurodegen. 6, 83 (2011).
128. Bredesen, D. E., Rao, R. V. & Mehlen, P. Cell death in the nervous system. Nature 443, 796-802 (2006).
129. Grünblatt, E. Commonalities in the genetics of Alzheimer's disease and Parkinson's disease. Expert Rev. Neurother. 8, 1865-1877 (2008).
130. van Es, M. A. et al. Angiogenin variants in Parkinson disease and amyotrophic lateral sclerosis. Ann. Neurol. 70, 964-973 (2011).