Incipient Alzheimer's disease: Microarray correlation analyses reveal major transcriptional and tumor suppressor responses
Open accessAbstract
The pathogenesis of incipient Alzheimer's disease (AD) has been resistant to analysis because of the complexity of AD and the overlap of its early-stage markers with normal aging. Gene microarrays provide new tools for addressing complexity because they allow overviews of the simultaneous activity of multiple cellular pathways. However, microarray data interpretation is often hindered by low statistical power, high false positives or false negatives, and by uncertain relevance to functional endpoints. Here, we analyzed hippocampal gene expression of nine control and 22 AD subjects of varying severity on 31 separate microarrays. We then tested the correlation of each gene's expression with MiniMental Status Examination (MMSE) and neurofibrillary tangle (NFT) scores across all 31 subjects regardless of diagnosis. These well powered tests revealed a major transcriptional response comprising thousands of genes significantly correlated with AD markers. Several hundred of these genes were also correlated with AD markers across only control and incipient AD subjects (MMSE > 20). Biological process categories associated with incipient AD-correlated genes were identified statistically ( ease program) and revealed up-regulation of many transcription factor/signaling genes regulating proliferation and differentiation, including tumor suppressors, oligodendrocyte growth factors, and protein kinase A modulators. In addition, up-regulation of adhesion, apoptosis, lipid metabolism, and initial inflammation processes occurred, and down-regulation of protein folding/metabolism/transport and some energy metabolism and signaling pathways took place. These findings suggest a new model of AD pathogenesis in which a genomically orchestrated up-regulation of tumor suppressor-mediated differentiation and involution processes induces the spread of pathology along myelinated axons.
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Early transcriptomic studies utilizing microarrays revealed alterations in synaptic, immune, and metabolic pathways that appear even before clinical symptoms.
“Early transcriptomic studies utilizing microarrays revealed alterations in synaptic, immune, and metabolic pathways that appear even before clinical symptoms, underscoring the potential for pre-symptomatic intervention120,125,161.”
From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [120]
Significant deviations (Welsh's P < 0.05) of 74 AD-related signatures from previous studies and GO pathways, including pathways related to Aβ, oxidative stress, tau NFT, and synaptic function, are observed across the five AD subtypes and controls.
“As shown in Fig. 1E, we highlight significant deviations (Welsh’s P < 0.05) of 74 AD-related signatures from previous studies and GO pathways (17, 28), including pathways related to Aβ, oxidative stress, tau NFT, and synaptic function, across the five AD subtypes and controls.”
From Molecular subtyping of Alzheimer’s disease using RNA sequencing data reveals novel mechanisms and targets (2021) · cites this paper as [17]
Intersection of the microglia signature gene list with 46 publicly available data sets for differentially regulated genes in neurodegenerative and behavioral disorders revealed significant enrichment or depletion of microglia signature genes in 28 of the 46 data sets.
“We then intersected this gene list with 46 publicly available data sets for differentially regulated genes in neurodegenerative and behavioral disorders derived from microarray or RNA-seq analysis of intact tissue (39–53). Two-sided Fisher’s exact tests revealed significant enrichment or depletion of microglia signature genes in 28 of the 46 data sets (Table S3).”
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The first large transcriptomic study (188 controls and 176 Alzheimer disease cases) connected genetic variation to expression changes using eQTL analysis and supported pathway-level findings related to transcriptional regulation and energy metabolism.
“The first large transcriptomic study (involving 188 controls and 176 individuals with Alzheimer disease)147 connected genetic variation to expression changes by using expression quantitative trait locus analysis (eQTL analysis) in controls and Alzheimer disease, and further supported the pathway-level findings related to transcriptional regulation and energy metabolism in Alzheimer disease140,148.”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [140]
Large transcriptomic studies using quantitative severity metrics and differentially vulnerable regions identified pathway-level changes in transcriptional regulation, apoptosis, cell proliferation, energy metabolism, and synaptic transmission in Alzheimer disease.
“Large studies using quantitative metrics of severity140 and differentially vulnerable regions144 have identified pathway-level changes in transcriptional regulation, apoptosis, cell proliferation, energy metabolism and synaptic transmission.”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [140]
Reduced expression of genes involved in mitochondrial energy metabolism may become more pronounced in humans with cognitive decline and Alzheimer's disease.
“Furthermore, reduced expression of genes involved in mitochondrial energy metabolism may become more pronounced in humans with cognitive decline and Alzheimer’s disease (20–22).”
From Neural mechanisms of ageing and cognitive decline (2010) · cites this paper as [20]
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Hoerndli, F. J., Pelech, S., Papassotiropoulos, A., & Götz, J. (2007) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2007.05618.x · Cited by 34 · see citing works
Expression profiling of drug response - from genes to pathways
Herwig, R., & Lehrach, H. (2006) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2006.8.3/rherwig · Cited by 14 · see citing works
Technology Insight: querying the genome with microarrays—progress and hope for neurological disease
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“(C) TSC1 knockdown signatures significantly overlapped with known human AD gene signatures including (1) Avramopoulos, signature detected in the temporal lobe from Avramopoulos et al 2011 [25]; (2) Blalock, signature detected in the hippocampus from Blalock et al 2004 [26]; (3) Colangelo, signature detected in the hip…”
Background
- Authors
- Blalock, E. M., Geddes, J. W., Chen, K. C., Porter, N. M., Markesbery, W. R., & Landfield, P. W.
- Affiliations
- University of Kentucky (US)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2004-02-09
- Volume
- 101
- Issue
- 7
- Pages
- 2173-2178
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC357071
- OpenAlex
- W2114729479
- Cited by
- 1,025
- References
- 9
- Citations by year
- 2026: 20 · 2025: 25 · 2024: 43 · 2023: 30 · 2022: 44 · 2021: 43 · 2020: 52 · 2019: 56 · 2018: 40 · 2017: 46 · 2016: 43 · 2015: 61 · 2014: 52 · 2013: 56 · 2012: 80
- FWCI
- 27.41
- 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 Institute on Aging (P50AG005144, AG-05144, P01AG010836, AG 10836)
- Topics
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- hippocampal gene expression, transcriptional response, tumor suppressor, neurofibrillary tangles, Mini-Mental State Examination, protein kinase A, apoptosis, inflammation, lipid metabolism, energy metabolism, Alzheimer's disease pathogenesis
- MeSH terms
- Algorithms, Alzheimer Disease, Female, Hippocampus, Humans, Male, Transcription Factors, Transcription, Genetic, Genes, Tumor Suppressor, Cyclic AMP-Dependent Protein Kinases, Disease Progression, Calcium Signaling, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling
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 ›
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