The DOI matches its Crossref record; 73 of the 76 references it cites were found in a registry or an index.
Gene expression profiling in the adult Down syndrome brain
Open accessAbstract
The mechanisms by which trisomy 21 leads to the characteristic Down syndrome (DS) phenotype are unclear. We used whole genome microarrays to characterize for the first time the transcriptome of human adult brain tissue (dorsolateral prefrontal cortex) from seven DS subjects and eight controls. These data were coanalyzed with a publicly available dataset from fetal DS tissue and functional profiling was performed to identify the biological processes central to DS and those that may be related to late onset pathologies, particularly Alzheimer disease neuropathology. A total of 685 probe sets were differentially expressed between adult DS and control brains at a stringent significance threshold (adjusted p value (q) < 0.005), 70% of these being up-regulated in DS. Over 25% of genes on chromosome 21 were differentially expressed in comparison to a median of 4.4% for all chromosomes. The unique profile of up-regulation on chromosome 21, consistent with primary dosage effects, was accompanied by widespread transcriptional disruption. The critical Alzheimer disease gene, APP, located on chromosome 21, was not found to be up-regulated in adult brain by microarray or QPCR analysis. However, numerous other genes functionally linked to APP processing were dysregulated. Functional profiling of genes dysregulated in both fetal and adult datasets identified categories including development (notably Notch signaling and Dlx family genes), lipid transport, and cellular proliferation. In the adult brain these processes were concomitant with cytoskeletal regulation and vesicle trafficking categories, and increased immune response and oxidative stress response, which are likely linked to the development of Alzheimer pathology in individuals with DS.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“While several reports have investigated gene expression in postmortem human DS brains or derived pluripotent stem cells (Letourneau et al., 2014; Lockstone et al., 2007; Mao et al., 2003, 2005), these studies are limited by sparse genome coverage, numbers of samples or developmental time points, and potential variances between in vitro and in vivo gene regulation.”
From Down Syndrome Developmental Brain Transcriptome Reveals Defective Oligodendrocyte Differentiation and Myelination (2016) · cites this paper as Lockstone et al., 2007
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Together, these studies demonstrate that many genes throughout the genome are altered in DS, confirming and extending previous findings that non-HSA21 genes may contribute significantly to trisomy 21 phenotypes (Letourneau et al., 2014; Lockstone et al., 2007).”
From Down Syndrome Developmental Brain Transcriptome Reveals Defective Oligodendrocyte Differentiation and Myelination (2016) · cites this paper as Lockstone et al., 2007
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Quantification of both mRNA and protein levels in brains of individuals with DS from fetal to adult stages have shown that not all trisomic genes are dysregulated or expressed at 1.5-fold (Lockstone et al., 2007; Mao et al., 2005; Mao et al., 2003).”
From Sex-specific developmental alterations in DYRK1A expression in the brain of a Down syndrome mouse model (2024) · cites this paper as Lockstone et al., 2007
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Importantly, a growing body of evidence indicates that mutations in subunits of the SNX17-Retriever-CCC-WASH recycling pathway are involved in human pathologies primarily affecting the nervous system.”
From Recruitment of the SNX17-Retriever recycling pathway regulates synaptic function and plasticity (2023) · cites this paper as Lockstone et al., 2007
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2−ΔΔCT Method
Livak, K. J., & Schmittgen, T. D. (2001) · Methods · doi:10.1006/meth.2001.1262 · Cited by 180,860
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Bioconductor: open software development for computational biology and bioinformatics
Gentleman, R. C., Carey, V. J., Bates, D. M., Bolstad, B., Dettling, M., Dudoit, S., Ellis, B., Gautier, L., Ge, Y., Gentry, J., et al. (2004) · Genome biology · doi:10.1186/gb-2004-5-10-r80 · Cited by 12,082
Exploration, normalization, and summaries of high density oligonucleotide array probe level data
Irizarry, R. A. (2003) · Biostatistics · doi:10.1093/biostatistics/4.2.249 · Cited by 10,603
limma: Linear Models for Microarray Data
Smyth, G. K. (2005) · Statistics for Biology and Health · doi:10.1007/0-387-29362-0_23 · Cited by 5,796
Genome-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
Bioinformatics and Computational Biology Solutions Using R and Bioconductor
Gentleman, R. C., Carey, V. J., Huber, W. K., Irizarry, R. A., & Dudoit, S. (2005) · Statistics in the health sciences · doi:10.1007/0-387-29362-0 · Cited by 3,470
Model-based analysis of oligonucleotide arrays: Expression index computation and outlier detection.
Li, C., & Wong, W. H. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.1.31 · Cited by 3,133
Amyloid deposition as the central event in the aetiology of Alzheimer’s disease
Hardy, J., & Allsop, D. (1991) · Trends in Pharmacological Sciences · doi:10.1016/0165-6147(91)90609-v · Cited by 2,538
Cortical inhibitory neurons and schizophrenia
Lewis, D. A., Hashimoto, T., & Volk, D. W. (2005) · Nature Reviews Neuroscience · doi:10.1038/nrn1648 · Cited by 2,297
Flagged first, then by citations
3 of the 76 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- Draghici, 2003, Global functional profiling of gene expression, Genomics, 81, 98
Cited by
Sorted by citations
Items 201–242 of 242
Gujjala, V. A., Klimek, I., Abyadeh, M., Tyshkovskiy, A., Oz, N., Castro, J. P., Gladyshev, V. N., Newton, J. C., & Kaya, A. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.04.19.590328 · Cited by 2
Complement system alteration in iPSC-derived astrocytes from individuals with Down syndromePreprint
Silva, A. L. T. E., de Oliveira, P. H. P., Yokota-Moreno, B. Y., Avila, J. P., Nakaya, H. I., Fausto, J. D. S., Sertie, A. L., & Zampieri, B. L. (2024) · Research Square · doi:10.21203/rs.3.rs-5319960/v1 · Cited by 2
Genetic Studies of Alzheimer's Disease
Blom, E. S. (2008) · KTH Publication Database DiVA (KTH Royal Institute of Technology) · Cited by 2
The cholinotrophic system in Down syndrome
Mufson, E. J., & Perez, S. E. (2025) · Handbook of clinical neurology · doi:10.1016/b978-0-443-19088-9.00017-2 · Cited by 1
Lian, G., Khabazeh, A., & Sheen, V. L. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2517953123 · Cited by 1
Skeletal Muscle Function, Morphology, and Biochemistry in Ts65Dn Mice: A Model of Down Syndrome
Cowley, P. M. (2011) · Syracuse University Libraries (Syracuse University) · Cited by 1
An overview of current knowledge about cell-free RNA in amniotic fluid
Jung, Y. W., Shin, Y. J., Shim, S. H., & Cha, D. H. (2016) · Journal of genetic medicine · doi:10.5734/jgm.2016.13.2.65 · Cited by 1
Numerical and Structural Chromosomal Abnormalities Associated with Immunodeficiency
Yarema, N., Boyarchuk, O. R., Chornomydz, I. B., & Panasiuk, Y. V. (2021) · Cytology and Genetics · doi:10.3103/s0095452721040137 · Cited by 1
Integrated Quantitative Neuro-Transcriptome Analysis of Several Brain Areas in Human Trisomy 21
Rodríguez-Ortiz, A., Montoya-Villegas, J. C., Sánchez, A., Soto, J. M. S., Mina-Paz, Y., & García‐Vallejo, F. (2022) · Genes · doi:10.3390/genes13040628 · Cited by 1
Fajardo, D., Vinasco, K., Montoya, J. C., Satizabal, J. M., Sánchez, A., & García‐Vallejo, F. (2018) · Biomedical Research - India · doi:10.4066/biomedicalresearch.29-18-690 · Cited by 1
Modeling Down Syndrome Neurodevelopment with Dosage Compensation
Czerminski, J. T. (2019) · eScholarship@UMassChan · doi:10.13028/j7xf-1q21 · Cited by 1
Degalez, F., Allain, C., Lagoutte, L., Lecerf, F., & Lagarrigue, S. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.10.03.616473 · Cited by 1
Genome Profiling and Potential Biomarkers in Neurodegenerative Disorders
Lovrečić, L., Maver, A., & Peterli, B. (2011) · InTech eBooks · doi:10.5772/28850
Functional remodeling of the cardiac glycome throughout the developing myocardium
Montpetit, M. L. (2008) · Digital Commons - University of South Florida (University of South Florida)
SigWinR; the SigWin-detector updated and ported to R
de Leeuw, W. C., Rauwerda, H., de Inda, M. A., Bruning, O., & Breit, T. M. (2009) · BMC Research Notes · doi:10.1186/1756-0500-2-205
Sharma, A. (2010) · BioData Mining · doi:10.1186/1756-0381-3-7
Changes in nitric oxide levels and erythrocyte arginase activities in patient with Down syndrome
Özbey, Ü. (2012) · African Journal of Pharmacy and Pharmacology · doi:10.5897/ajpp11.508
Generation of a panel of antibodies against proteins encoded on human chromosome 21
Wiseman, F. K., Sheppard, O., Linehan, J. M., Brandner, S., Tybulewicz, V. L. J., & Fisher, E. (2010) · Journal of Negative Results in BioMedicine · doi:10.1186/1477-5751-9-7
Fonctionnelle, U. B. (2012)
Gene expression and copy number variation in common complex diseases
Grayson, B. L. (2010)
Guo, Z., Cui, Y., Shi, X., Birchler, J. A., Albizua, I., Sherman, S. L., Qin, Z. S., & Ji, T. (2020) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqaa072
Heuristic Solutions for the $${(\alpha , \beta )}$$-k Feature Set Problem
Naeni, L. M., & Salehipour, A. (2020) · Studies in computational intelligence · doi:10.1007/978-3-030-58930-1_9
Pinto, B. G. G. (2021) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/d.95.2021.tde-18052021-171202
Vona, C. D., Barba‐Moreno, L., Ferrari, R., & de la Luna, S. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.01.21.427583
Varner, M. W., & Byrne, J. L. B. (2011) · Wiley eBooks · doi:10.1002/9781444398038.ch11
An optimization method for characterizing two groups of data
Salehipour, A. (2022) · International Transactions in Operational Research · doi:10.1111/itor.13165
Alzheimer disease and neuroinflammation in Down syndrome
Ganguly, B. B. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-90456-8.00014-4
Bartesaghi, R., Chen, X., Johnstone, A. D., Das, U., & Mobley, W. C. (2025) · Springer eBooks · doi:10.1007/978-3-031-89307-0_19
Komine, I., Chiba, Y., Sato, H., Oka, S., Yoshizaki, K., Yamada, A., & Fukumoto, S. (2025) · Pediatric Dental Journal · doi:10.1016/j.pdj.2025.100360
Rôle des ADAM dans le processus physiopathologique de la maladie d'Alzheimer
Laumet, G. O. (2010) · theses.fr (ABES) · doi:10.70675/94126786zf990z488ezb471z5f1d5686766c
Trisomy 21 Drives ADARB1 Overexpression and Premature RNA Recoding in the Developing Fetal Brain
Breen, M. S., Yang, A., Wang, X., Santos, M. R. D. L., Ran, T. A. O., Weinberger, D. R., Kleinman, J. E., Mihova, K. Y., Stancheva, G. S., Savova, S., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-70217-5
Multi-omics data integration and interactive visual data mining to explore mitochondrial dynamics
Marchianò, F. (2022) · theses.fr (ABES) · doi:10.70675/eb60a1f9zb03bz48d8z8b03zcb18fa2f49d8
Multiomics and proteomic insights into Alzheimer’s disease biology in Down syndrome
Martá-Ariza, M., & Wisniewski, T. R. (2026) · Expert Review of Neurotherapeutics · doi:10.1080/14737175.2026.2695187
Degalez, F., Allain, C., Lagoutte, L., Lecerf, F., & Lagarrigue, S. (2026) · Nucleic Acids Research · doi:10.1093/nar/gkag722 · Cited by 1
The Role of the Immunoglobulin Superfamily of Cell Adhesion Molecules in Intellectual Disability
Zaman, N., Bui, K., & Sytnyk, V. (2026) · Cells · doi:10.3390/cells15191801
Down Syndrome Early Postnatal Brain Multiome (DS-HPBM)
Bhattacharyya, A., Kumarage, P., West, N. R., Arachchilage, K. H., Knaack, S., MacGregor, S., Hosseini, M., Risgaard, R. D., Martinez, J., Zhang, S., et al. (2022) · INCLUDE Data Hub · doi:10.71738/an79-4v78
DS-HPBM Human Postnatal Basal Forebrain snRNA-seq
Bhattacharyya, A., Kumarage, P., West, N. R., Arachchilage, K. H., Knaack, S., MacGregor, S., Hosseini, M., Risgaard, R. D., Martinez, J., Zhang, S., et al. (2022) · INCLUDE Data Hub · doi:10.71738/543y-5019
DS-HPBM Human Postnatal Basal Forebrain snATAC-seq
Bhattacharyya, A., Kumarage, P., West, N. R., Arachchilage, K. H., Knaack, S., MacGregor, S., Hosseini, M., Risgaard, R. D., Martinez, J., Zhang, S., et al. (2022) · INCLUDE Data Hub · doi:10.71738/0cbf-8c55
Potier, M., & Rivals, I. (2012) · Springer eBooks · doi:10.1007/978-94-007-3858-4_1
Metadata
- Authors
- Lockstone, H. E., Harris, L. W., Swatton, J. E., Wayland, M. T., Holland, A. J., & Bahn, S.
- Affiliations
- University of Cambridge (GB)
- Corresponding author
- Bahn, S.
- Venue
- Genomics
- Publisher
- Elsevier BV
- Published
- 2007-12
- Volume
- 90
- Issue
- 6
- Pages
- 647-660
- ISSN
- 0888-7543 (ISSN-L)
- OpenAlex
- W2010597204
- Cited by
- 240
- References
- 76
- Citations by year
- 2026: 6 · 2025: 14 · 2024: 10 · 2023: 8 · 2022: 13 · 2021: 20 · 2020: 12 · 2019: 14 · 2018: 15 · 2017: 14 · 2016: 15 · 2015: 11 · 2014: 16 · 2013: 15 · 2012: 19
- FWCI
- 9.30
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Genomics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Stanley Medical Research Institute
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Down syndrome and intellectual disability research
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Keywords
- Down syndrome, dorsolateral prefrontal cortex, gene expression profiling, APP processing, Notch signaling, Dlx genes, lipid transport, cell proliferation, cytoskeleton regulation, vesicle trafficking, immune response, oxidative stress response
- MeSH terms
- Adult, Aged, Alzheimer Disease, Chromosomes, Human, Pair 21, Down Syndrome, Female, Fetus, Humans, Male, Middle Aged, Receptors, Cell Surface, Up-Regulation, Case-Control Studies, Polymerase Chain Reaction, Amyloid beta-Protein Precursor, Prefrontal Cortex, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, Databases, Genetic, Proteomics, Protease Nexins
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
