The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.
Divergence of human and mouse brain transcriptome highlights Alzheimer disease pathways
Open accessAbstract
Because mouse models play a crucial role in biomedical research related to the human nervous system, understanding the similarities and differences between mouse and human brain is of fundamental importance. Studies comparing transcription in human and mouse have come to varied conclusions, in part because of their relatively small sample sizes or underpowered methodologies. To better characterize gene expression differences between mouse and human, we took a systems-biology approach by using weighted gene coexpression network analysis on more than 1,000 microarrays from brain. We find that global network properties of the brain transcriptome are highly preserved between species. Furthermore, all modules of highly coexpressed genes identified in mouse were identified in human, with those related to conserved cellular functions showing the strongest between-species preservation. Modules corresponding to glial and neuronal cells were sufficiently preserved between mouse and human to permit identification of cross species cell-class marker genes. We also identify several robust human-specific modules, including one strongly correlated with measures of Alzheimer disease progression across multiple data sets, whose hubs are poorly-characterized genes likely involved in Alzheimer disease. We present multiple lines of evidence suggesting links between neurodegenerative disease and glial cell types in human, including human-specific correlation of presenilin-1 with oligodendrocyte markers, and significant enrichment for known neurodegenerative disease genes in microglial modules. Together, this work identifies convergent and divergent pathways in mouse and human, and provides a systematic framework that will be useful for understanding the applicability of mouse models for human brain disorders.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“This work also found major differences in dementia susceptibility genes between humans and mice, potentially identifying why some mouse models might not recapitulate human neuropathology.”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [150]
In the citing paper
“They subsequently150 incorporated more than 1,000 microarrays from mouse models of Alzheimer disease and human patients with Alzheimer disease from public databases to reproduce and extend these results, identifying additional co-expression modules that are related to mitochondrial dysfunction and synaptic plasticity.”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [150]
In the citing paper
“Applied to the entire 911 sample set from Brain 1, genes were grouped into well-defined co-expression modules with specific anatomical distributions (Fig. 3a, b), consistent with previous studies in brain tissues18, 19.”
From An anatomically comprehensive atlas of the adult human brain transcriptome (2012) · cites this paper as [19]
In the citing paper
“Modules corresponding to broad neural cell types also showed highly significant preservation compared to a previous study using human brain samples (ref. 19 and data not shown).”
From An anatomically comprehensive atlas of the adult human brain transcriptome (2012) · cites this paper as [19]
In the citing paper
“a number of important studies have compared gene expression in microglia from mice and humans, and while they have shown a significant overlap between the transcriptomes of the two species, they have also seen a number of genes are expressed selectively more abundantly in human microglia”
From Genetic variability in response to amyloid beta deposition influences Alzheimer’s disease risk (2019) · cites this paper as Miller et al., 2010
In the citing paper
“a meta-analysis of microarray studies which showed better preservation of neuronal gene co-expression compared to glial and disease-related genes36”
From Canonical genetic signatures of the adult human brain (2015) · cites this paper as [36]
In the citing paper
“Microarray studies have also revealed distinct gene expression profiles and coexpression networks associated with different human brain regions, major cell types, and cellular processes (Johnson et al., 2009; Miller et al., 2010; Oldham et al., 2006; Oldham et al., 2008).”
From Large-Scale Cellular-Resolution Gene Profiling in Human Neocortex Reveals Species-Specific Molecular Signatures (2012) · cites this paper as Miller et al., 2010
Citations
Cites
WGCNA: an R package for weighted correlation network analysis
Langfelder, P., & Horvath, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-559 · Cited by 27,252
Self-citationGene Expression Omnibus: NCBI gene expression and hybridization array data repository
Edgar, R. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.1.207 · Cited by 13,288
A General Framework for Weighted Gene Co-Expression Network Analysis
Zhang, B., & Horvath, S. (2005) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1128 · Cited by 5,684
Self-citationGenome-wide atlas of gene expression in the adult mouse brain
Lein, E. S., Hawrylycz, M. J., Ao, N., Ayres, M., Bensinger, A., Bernard, A., Boe, A. F., Boguski, M. S., Brockway, K. S., Byrnes, E. J., et al. (2007) · Nature · doi:10.1038/nature05453 · Cited by 5,572
Hierarchical Organization of Modularity in Metabolic Networks
Ravasz, E., Somera, A. L., Mongru, D. A., Oltvai, Z. N., & Barabási, A.-L. (2002) · Science · doi:10.1126/science.1073374 · Cited by 4,224
Triple-Transgenic Model of Alzheimer’s Disease with Plaques and Tangles
Oddo, S., Caccamo, A., Shepherd, J. D., Murphy, M. P., Golde, T. E., Kayed, R., Metherate, R., Mattson, M. P., Akbari, Y., & LaFerla, F. M. (2003) · Neuron · doi:10.1016/s0896-6273(03)00434-3 · Cited by 4,126
A gene atlas of the mouse and human protein-encoding transcriptomes
Su, A. I., Wiltshire, T., Batalov, S., Lapp, H., Ching, K. A., Block, D., Zhang, J., Soden, R., Hayakawa, M., Kreiman, G., et al. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0400782101 · Cited by 3,475
Human Protein Reference Database--2009 update
Prasad, T. S. K., Goel, R., Kandasamy, K., Keerthikumar, S., Kumar, S., Mathivanan, S., Telikicherla, D., Raju, R., Shafreen, R. B., Venugopal, A., et al. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn892 · Cited by 3,252
Cahoy, J. D., Emery, B., Kaushal, A., Foo, L. C., Zamanian, J. L., Christopherson, K. S., Xing, Y., Lubischer, J. L., Krieg, P. A., Krupenko, S. A., et al. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.4178-07.2008 · Cited by 3,129
King, M.-C., & Wilson, A. C. (1975) · Science · doi:10.1126/science.1090005 · Cited by 2,815
Lee, V. M.-Y., Goedert, M., & Trojanowski, J. Q. (2001) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.24.1.1121 · Cited by 2,480
A Gene-Coexpression Network for Global Discovery of Conserved Genetic Modules
Stuart, J. M., Segal, E., Koller, D., & Kim, S. K. (2003) · Science · doi:10.1126/science.1087447 · Cited by 2,274
Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R
Langfelder, P., Zhang, B., & Horvath, S. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btm563 · Cited by 1,892
Self-citationSystematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database
Bertram, L., McQueen, M. B., Mullin, K., Blacker, D., & Tanzi, R. E. (2007) · Nature Genetics · doi:10.1038/ng1934 · Cited by 1,857
White matter in learning, cognition, and psychiatric disorders
Fields, R. D. (2008) · Trends in Neurosciences · doi:10.1016/j.tins.2008.04.001 · Cited by 1,337
Activation of microglial cells by β-amyloid protein and interferon-γ
Meda, L., Cassatella, M. A., Szendrei, G. I., Otvos, L., Baron, P., Villalba, M., Ferrari, D., & Rossi, F. (1995) · Nature · doi:10.1038/374647a0 · Cited by 1,314
Age-related myelin breakdown: a developmental model of cognitive decline and Alzheimer’s disease
Bartzokis, G. (2004) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2003.03.001 · Cited by 968
Eigengene networks for studying the relationships between co-expression modules
Langfelder, P., & Horvath, S. (2007) · BMC Systems Biology · doi:10.1186/1752-0509-1-54 · Cited by 867
Self-citationGeometric Interpretation of Gene Coexpression Network Analysis
Horvath, S., & Dong, J. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000117 · Cited by 867
Self-citationCoexpression Analysis of Human Genes Across Many Microarray Data Sets
Lee, H. K., Hsu, A. K., Sajdak, J., Qin, J., & Pavlidis, P. (2004) · Genome Research · doi:10.1101/gr.1910904 · Cited by 770
Functional organization of the transcriptome in human brain
Oldham, M. C., Konopka, G., Iwamoto, K., Langfelder, P., Kato, T., Horvath, S., & Geschwind, D. H. (2008) · Nature Neuroscience · doi:10.1038/nn.2207 · Cited by 752 · cited 10×
“These markerswere comparedwith publishedmouse (20–22) and human (3, 23) marker genes for each cell type, and validated by showing highly significant overlap (P < 10 for each cell type).”
BackgroundMethodResultInfluentialSelf-citationAstrocytic complexity distinguishes the human brain
Oberheim, N. A., Wang, X., Goldman, S., & Nedergaard, M. (2006) · Trends in Neurosciences · doi:10.1016/j.tins.2006.08.004 · Cited by 739
Analysis of oncogenic signaling networks in glioblastoma identifies ASPM as a molecular target
Horvath, S., Zhang, B., Carlson, M., Lu, K. V., Zhu, S., Felciano, R. M., Laurance, M. F., Zhao, W., Qi, S., Chen, Z., et al. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0608396103 · Cited by 641
Self-citationGene expression changes in the course of normal brain aging are sexually dimorphic
Berchtold, N. C., Cribbs, D. H., Coleman, P. D., Rogers, J., Head, E., Kim, R., Beach, T., Miller, C., Troncoso, J., Trojanowski, J. Q., et al. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0806883105 · Cited by 626
Neurological abnormalities in a knock-in mouse model of Huntington's disease
Lin, C. (2001) · Human Molecular Genetics · doi:10.1093/hmg/10.2.137 · Cited by 592
Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae
Ge, H., Liu, Z., Church, G. M., & Vidal, M. (2001) · Nature Genetics · doi:10.1038/ng776 · Cited by 575
Conservation and evolution of gene coexpression networks in human and chimpanzee brains
Oldham, M. C., Horvath, S., & Geschwind, D. H. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0605938103 · Cited by 566
Self-citationThe Mouse Genome Database (MGD): mouse biology and model systems
Bult, C. J., Eppig, J. T., Kadin, J. A., Richardson, J. E., Blake, J. A., & the Mouse Genome Database Group (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm961 · Cited by 415
Human-specific transcriptional regulation of CNS development genes by FOXP2
Konopka, G., Bomar, J. M., Winden, K., Coppola, G., Jonsson, Z. O., Gao, F., Peng, S., Preuss, T. M., Wohlschlegel, J. A., & Geschwind, D. H. (2009) · Nature · doi:10.1038/nature08549 · Cited by 390
Self-citationA Systems Level Analysis of Transcriptional Changes in Alzheimer's Disease and Normal Aging
Miller, J. A., Oldham, M. C., & Geschwind, D. H. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.4098-07.2008 · Cited by 385
Self-citationSimilarities and Differences in Genome-Wide Expression Data of Six Organisms
Bergmann, S., Ihmels, J., & Barkai, N. (2003) · PLoS Biology · doi:10.1371/journal.pbio.0020009 · Cited by 353
Evolution of primate gene expression
Khaitovich, P., Enard, W., Lachmann, M., & Pääbo, S. (2006) · Nature Reviews Genetics · doi:10.1038/nrg1940 · Cited by 341
Genetic Control of Human Brain Transcript Expression in Alzheimer Disease
Webster, J. A., Gibbs, J. R., Clarke, J., Ray, M., Zhang, W., Holmans, P., Rohrer, K., Zhao, A., Marlowe, L., Kaleem, M., et al. (2009) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2009.03.011 · Cited by 304
Ringman, J. M., O'Neill, J., Geschwind, D., Medina, L., Apostolova, L. G., Rodriguez, Y., Schaffer, B., Varpetian, A., Tseng, B., Ortiz, F., et al. (2007) · Brain · doi:10.1093/brain/awm102 · Cited by 290
Self-citationImproved human disease candidate gene prioritization using mouse phenotype
Chen, J., Xu, H., Aronow, B. J., & Jegga, A. G. (2007) · BMC Bioinformatics · doi:10.1186/1471-2105-8-392 · Cited by 284
VisANT: an online visualization and analysis tool for biological interaction data
Hu, Z., Mellor, J. C., Wu, J., & DeLisi, C. (2004) · BMC Bioinformatics · doi:10.1186/1471-2105-5-17 · Cited by 261
Takahashi, K., Sugi, Y., Hosono, A., & Kaminogawa, S. (2009) · The Journal of Immunology · doi:10.4049/jimmunol.0901271 · Cited by 182
Genetic advances in autism: heterogeneity and convergence on shared pathways
Bill, B. R., & Geschwind, D. H. (2009) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2009.04.004 · Cited by 164
Self-citationCross-species analysis of biological networks by Bayesian alignment
Berg, J., & Lässig, M. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0602294103 · Cited by 146
Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis
Ala, U., Piro, R. M., Grassi, E., Damasco, C., Silengo, L., Oti, M., Provero, P., & Di Cunto, F. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000043 · Cited by 134 · cited 1×
“Between-species coexpression preservation has been shown to prioritize DG selection under genetic disease loci (40) and to categorize the function of poorlycharacterized genes better than coexpression in a single species (11).”
BackgroundYanai, I., Graur, D., & Ophir, R. (2004) · OMICS A Journal of Integrative Biology · doi:10.1089/153623104773547462 · Cited by 132
Gan, L., Ye, S., Chu, A., Anton, K., Yi, S.-L., Vincent, V. A. M., von Schack, D., Chin, D. J., Murray, J. C., Lohr, S., et al. (2004) · Journal of Biological Chemistry · doi:10.1074/jbc.m306183200 · Cited by 130
Tau Phosphorylation, Tangles, and Neurodegeneration
Geschwind, D. H. (2003) · Neuron · doi:10.1016/s0896-6273(03)00681-0 · Cited by 129
Self-citationMethodological considerations for gene expression profiling of human brain
Atz, M. E., Walsh, D. M. A., Cartagena, P. M., Li, J. Z., Evans, S. J., Choudary, P. V., Overman, K., Stein, R., Tomita, H., Potkin, S. G., et al. (2007) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2007.03.022 · Cited by 115
The organization of the transcriptional network in specific neuronal classes
Winden, K. D., Oldham, M. C., Mirnics, K., Ebert, P. J., Swan, C. H., Levitt, P., Rubenstein, J. L., Horvath, S., & Geschwind, D. H. (2009) · Molecular Systems Biology · doi:10.1038/msb.2009.46 · Cited by 112
Self-citationConservation of Regional Gene Expression in Mouse and Human Brain
Strand, A. D., Aragaki, A. K., Baquet, Z. C., Hodges, A., Cunningham, P., Holmans, P., Jones, K. R., Jones, L., Kooperberg, C. L., & Olson, J. M. (2007) · PLoS Genetics · doi:10.1371/journal.pgen.0030059 · Cited by 106
Global similarity and local divergence in human and mouse gene co-expression networks
Tsaparas, P., Mariño‐Ramírez, L., Bodenreider, O., Koonin, E. V., & Jordan, I. K. (2006) · BMC Evolutionary Biology · doi:10.1186/1471-2148-6-70 · Cited by 79
Celsius: a community resource for Affymetrix microarray data
Day, A., Carlson, M. R. J., Dong, J., O’Connor, B. D., & Nelson, S. F. (2007) · Genome biology · doi:10.1186/gb-2007-8-6-r112 · Cited by 63
Albright, A. V., & González‐Scarano, F. (2004) · Journal of Neuroimmunology · doi:10.1016/j.jneuroim.2004.09.007 · Cited by 57
Assessing the Conservation of Mammalian Gene Expression Using High-Density Exon Arrays
Xing, Y., Ouyang, Z., Kapur, K., Scott, M. P., & Wong, W. H. (2007) · Molecular Biology and Evolution · doi:10.1093/molbev/msm061 · Cited by 52
TBP, a polyglutamine tract containing protein, accumulates in Alzheimer's disease.
Reid, S., van Roon-Mom, W. V., Wood, P. C., Rees, M., Owen, M., Faull, R., Dragunow, M., & Snell, R. (2004) · Brain Research. Molecular Brain Research · doi:10.1016/j.molbrainres.2004.03.018 · Cited by 30
Pao, S.-Y., Lin, W.-L., & Hwang, M. (2006) · BMC Genomics · doi:10.1186/1471-2164-7-86 · Cited by 25
Cited by
Sorted by citations
An anatomically comprehensive atlas of the adult human brain transcriptome
Hawrylycz, M. J., Lein, E. S., Guillozet-Bongaarts, A. L., Shen, E. H., Ng, L., Miller, J. A., van de Lagemaat, L. N., Smith, K. A., Ebbert, A., Riley, Z. L., et al. (2012) · Nature · doi:10.1038/nature11405 · Cited by 3,083
Self-citationThe Cellular Phase of Alzheimer’s Disease
De Strooper, B., & Karran, E. (2016) · Cell · doi:10.1016/j.cell.2015.12.056 · Cited by 1,990
Transcriptomic Analysis of Autistic Brain Reveals Convergent Molecular Pathology
Voineagu, I., Wang, X., Johnston, P., Lowe, J. K., Tian, Y., Horvath, S., Mill, J., Cantor, R. M., Blencowe, B. J., & Geschwind, D. H. (2011) · Nature · doi:10.1038/nature10110 · Cited by 1,874
Self-citationAlzheimer Mechanisms and Therapeutic Strategies
Huang, Y., & Mucke, L. (2012) · Cell · doi:10.1016/j.cell.2012.02.040 · Cited by 1,758
Gene expression elucidates functional impact of polygenic risk for schizophrenia
Fromer, M., Roussos, P., Sieberts, S. K., Johnson, J. S., Kavanagh, D. H., Perumal, T. M., Ruderfer, D. M., Oh, E. C., Topol, A., Shah, H. R., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4399 · Cited by 1,091
Metadata
- Authors
- Miller, J. A., Horvath, S., & Geschwind, D. H.
- Affiliations
- University of California, Los Angeles (US)
- Departments of cHuman Genetics and
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2010-06-25
- Volume
- 107
- Issue
- 28
- Pages
- 12698-12703
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC2906579
- OpenAlex
- W2139511828
- Cited by
- 480
- References
- 52
- Citations by year
- 2026: 10 · 2025: 12 · 2024: 27 · 2023: 20 · 2022: 35 · 2021: 31 · 2020: 34 · 2019: 47 · 2018: 35 · 2017: 39 · 2016: 35 · 2015: 36 · 2014: 26 · 2013: 35 · 2012: 33
- FWCI
- 11.99
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (HL028481)
- National Institute on Aging (F31AG031649, U01AG016976, R01 AG26938-05, R01AG026938)
- National Heart, Lung, and Blood Institute (P01HL028481)
- National Institute of Mental Health (R37MH060233, R37 MH 60233-09S1)
- National Institute of Allergy and Infectious Diseases (U19AI063603)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- Alzheimer's disease, gene co-expression network, cell type markers, glial cells, microglia, oligodendrocytes, presenilin 1, network hubs
- MeSH terms
- Alzheimer Disease, Animals, Brain, Humans, Male, Gene Expression Profiling, Systems Biology, Mice, Gene Regulatory Networks, Presenilin-1
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
