Cited by 14

The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.

A Map of Transcriptomic Signatures of Different Brain Areas in Alzheimer’s Disease

Ferrari, Riccardo Rocco, Fantini, Valentina, Garofalo, Maria, Di Gerlando, Rosalinda, Dragoni, Francesca, Rizzo, Bartolo, Spina, Erica, Rossi, Michele, Calatozzolo, Chiara, Profka, Xhulja, Ceroni, Mauro, Guaita, Antonio, Davin, Annalisa, Gagliardi, Stella, Poloni, Tino Emanuele·2024·International Journal of Molecular Sciences

Abstract

Alzheimer’s disease (AD) is a neurodegenerative disorder that progressively involves brain regions with an often-predictable pattern. Damage to the brain appears to spread and worsen with time, but the molecular mechanisms underlying the region-specific distribution of AD pathology at different stages of the disease are still under-investigated. In this study, a whole-transcriptome analysis was carried out on brain samples from the hippocampus (HI), temporal and parietal cortices (TC and PC, respectively), cingulate cortex (CG), and substantia nigra (SN) of six subjects with a definite AD diagnosis and three healthy age-matched controls in duplicate. The transcriptomic results showed a greater number of differentially expressed genes (DEGs) in the TC (1571) and CG (1210) and a smaller number of DEGs in the HI (206), PC (109), and SN (60). Furthermore, the GSEA showed a difference between the group of brain areas affected early (HI and TC) and the group of areas that were subsequently involved (PC, CG, and SN). Notably, in the HI and TC, there was a significant downregulation of shared DEGs primarily involved in synaptic transmission, while in the PC, CG, and SN, there was a significant downregulation of genes primarily involved in protein folding and trafficking. The course of AD could follow a definite time- and severity-related pattern that arises from protein misfolding, as observed in the PC, CG, and SN, and leads to synaptic impairment, as observed in the HI and TC. Therefore, a map of the molecular and biological processes involved in AD pathogenesis may be traced. This could aid in the discovery of novel biological targets in order to develop effective and well-timed therapeutic approaches.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3390/ijms252011117

Cites

13 of 13 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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?

  • Previous transcriptomic studies and investigations into cortical synaptic density in AD have underscored the link between synaptic transmission and AD pathogenesis, demonstrating that disruptions in synaptic integrity contribute to cortical thinning in AD.

    “Other previous transcriptomic studies and investigations into cortical synaptic density in AD have underscored the link between synaptic transmission and AD pathogenesis, demonstrating that disruptions in synaptic integrity contribute to cortical thinning in AD [74, 75].”
  • Our findings reinforce the connection between synaptic dysfunction and AD pathogenesis, suggesting that disruptions in synaptic integrity contribute to cortical thinning and cognitive decline.

    “Our findings, consistent with previous studies [72, 74–76], reinforce the connection between synaptic dysfunction and AD pathogenesis, suggesting that disruptions in synaptic integrity contribute to cortical thinning and cognitive decline.”

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

Flagged first, then by citations

Research works printed but not linked: 80

  1. Scheltens, 2021, Alzheimer’s disease, Lancet, 397, 1577, 10.1016/S0140-6736(20)32205-4 · DOI · Paper page
  2. Querfurth, 2010, Alzheimer’s disease, N. Engl. J. Med., 362, 329, 10.1056/NEJMra0909142 · DOI · Paper page
  3. Braak, 2006, Staging of Alzheimer disease-associated neurofibrillary pathology using paraffin sections and immunocytochemistry, Acta Neuropathol., 112, 389, 10.1007/s00401-006-0127-z · DOI · Paper page
  4. Mirra, 1991, The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD); Part II. Standardization of the neuropathologic assessment of Alzheimer’s disease, Neurology, 41, 479, 10.1212/WNL.41.4.479 · DOI · Paper page
  5. Thal, 2002, Phases of A beta-deposition in the human brain and its relevance for the development of AD, Neurology, 58, 1791, 10.1212/WNL.58.12.1791 · DOI · Paper page
  6. Fjell, A.M., McEvoy, L., Holland, D., Dale, A.M., and Walhovd, K.B. (2014). What is normal in normal aging? Effects of Aging, Amyloid and Alzheimer’s Disease on the Cerebral Cortex and the Hippocampus. Prog. Neurobiol., 117. · DOI · Paper page
  7. Swanson, 2023, Lecanemab in Early Alzheimer’s Disease, N. Engl. J. Med., 388, 9, 10.1056/NEJMoa2212948 · DOI · Paper page
  8. Swerdlow, 2023, The Alzheimer’s Disease Mitochondrial Cascade Hypothesis: A Current Overview, J. Alzheimers Dis., 92, 751, 10.3233/JAD-221286 · DOI
  9. Cozachenco, 2023, Defective proteostasis in Alzheimer’s disease, Ageing Res. Rev., 85, 101862, 10.1016/j.arr.2023.101862 · DOI
  10. Annese, A., Manzari, C., Lionetti, C., Picardi, E., Horner, D.S., Chiara, M., Caratozzolo, M.F., Tullo, A., Fosso, B., and Pesole, G. (2018). Whole transcriptome profiling of Late-Onset Alzheimer’s Disease patients provides insights into the molecular changes involved in the disease. Sci. Rep., 8. · DOI
  11. Fantini, 2024, Functional analysis and transcriptome profile of meninges and skin fibroblasts from human-aged donors, Cell Prolif., 57, e13627, 10.1111/cpr.13627 · DOI
  12. Bagyinszky, E., Giau, V.V., and An, S.A. (2020). Transcriptomics in alzheimer’s disease: Aspects and challenges. Int. J. Mol. Sci., 21. · DOI
  13. Mei, T., Li, Y., Orduña Dolado, A., Li, Z., Andersson, R., Berliocchi, L., and Rasmussen, L.J. (2023). Pooled analysis of frontal lobe transcriptomic data identifies key mitophagy gene changes in Alzheimer’s disease brain. Front. Aging Neurosci., 15. · DOI
  14. Amro, Z., Ryan, M., Collins-Praino, L.E., and Yool, A.J. (2023). Unexpected Classes of Aquaporin Channels Detected by Transcriptomic Analysis in Human Brain Are Associated with Both Patient Age and Alzheimer’s Disease Status. Biomedicines, 11. · DOI
  15. Rahayel, 2023, Mitochondrial function-associated genes underlie cortical atrophy in prodromal synucleinopathies, Brain, 146, 3301, 10.1093/brain/awad044 · DOI
  16. Huang, Z., Chen, Q., Mu, X., An, Z., and Xu, Y. (2024). Elucidating the Functional Roles of Long Non-Coding RNAs in Alzheimer’s Disease. Int. J. Mol. Sci., 25. · DOI
  17. Liu, 2024, Profiling of long non-coding RNAs in hippocampal-entorhinal system subfields: Impact of RN7SL1 on neuroimmune response modulation in Alzheimer’s disease, J. Neuroinflamm., 21, 84, 10.1186/s12974-024-03083-x · DOI
  18. Caldwell, 2022, Transcriptomic profiling of sporadic Alzheimer’s disease patients, Mol. Brain, 15, 83, 10.1186/s13041-022-00963-2 · DOI
  19. Guaita, A., Colombo, M., Vaccaro, R., Fossi, S., Vitali, S.F., Forloni, G., Polito, L., Davin, A., Ferretti, V.V., and Villani, S. (2013). Brain aging and dementia during the transition from late adulthood to old age: Design and methodology of the “invece.Ab” population-based study. BMC Geriatr., 13. · DOI
  20. Gagliardi, S., Truffi, M., Tinelli, V., Garofalo, M., Pandini, C., Cotta Ramusino, M., Perini, G., Costa, A., Negri, S., and Mazzucchelli, S. (2022). Bisdemethoxycurcumin (BDC)-Loaded H-Ferritin-Nanocages Mediate the Regulation of Inflammation in Alzheimer’s Disease Patients. Int. J. Mol. Sci., 23. · DOI
  21. Guo, 2009, Expression and Distribution of Cystic Fibrosis Transmembrane Conductance Regulator in Neurons of the Human Brain, J. Histochem. Cytochem., 57, 1113, 10.1369/jhc.2009.953455 · DOI
  22. Bukau, 1998, The Hsp70 and Hsp60 chaperone machines, Cell, 92, 351, 10.1016/S0092-8674(00)80928-9 · DOI
  23. Esquivel, A.R., Hill, S.E., and Blair, L.J. (2023). DnaJs are enriched in tau regulators. Int. J. Biol. Macromol., 253. · DOI
  24. Nachman, 2020, Disassembly of Tau fibrils by the human Hsp70 disaggregation machinery generates small seeding-competent species, J. Biol. Chem., 295, 9676, 10.1074/jbc.RA120.013478 · DOI
  25. Urabe, 2020, miR-26a regulates extracellular vesicle secretion from prostate cancer cells via targeting SHC4, PFDN4, and CHORDC1, Sci. Adv., 6, eaay3051, 10.1126/sciadv.aay3051 · DOI
  26. Wang, Z., Zhang, H., and Cheng, Q. (2020). PDIA4: The basic characteristics, functions and its potential connection with cancer. Biomed. Pharmacother., 122. · DOI
  27. Xia, Y.J., Chen, J., Liu, G., Huang WBin Wei, X.J., Wei, Z.W., and He, Y.L. (2021). STIP1 knockdown suppresses colorectal cancer cell proliferation, migration and invasion by inhibiting STAT3 pathway. Chem. Biol. Interact., 341. · DOI
  28. Zong, 2021, FKBP4 integrates FKBP4/Hsp90/IKK with FKBP4/Hsp70/RelA complex to promote lung adenocarcinoma progression via IKK/NF-κB signaling, Cell Death Dis., 12, 602, 10.1038/s41419-021-03857-8 · DOI
  29. Voss, 1996, Piccolo, a novel 420 kDa protein associated with the presynaptic cytomatrix, Eur. J. Cell Biol., 69, 214
  30. Schoch, 2006, Molecular organization of the presynaptic active zone, Cell Tissue Res., 326, 379, 10.1007/s00441-006-0244-y · DOI
  31. Mukherjee, 2010, Piccolo and bassoon maintain synaptic vesicle clustering without directly participating in vesicle exocytosis, Proc. Natl. Acad. Sci. USA, 107, 6504, 10.1073/pnas.1002307107 · DOI · Paper page
  32. Kiyonaka, 2012, Physical and functional interaction of the active zone protein CAST/ERC2 and the β-subunit of the voltage-dependent Ca2+ channel, J. Biochem., 152, 149, 10.1093/jb/mvs054 · DOI
  33. Shah, K., and Rossie, S. (2018). Tale of the Good and the Bad Cdk5: Remodeling of the Actin Cytoskeleton in the Brain. Mol. Neurobiol., 55. · DOI
  34. Spiering, 2011, Dynamics of the Rho-family small GTPases in actin regulation and motility, Cell Adhes. Migr., 5, 170, 10.4161/cam.5.2.14403 · DOI
  35. Dagda, 2015, Role of protein kinase A in regulating mitochondrial function and neuronal development: Implications to neurodegenerative diseases, Rev. Neurosci., 26, 359, 10.1515/revneuro-2014-0085 · DOI
  36. Wu, 1995, Altered behavior and long-term potentiation in type I adenylyl cyclase mutant mice, Proc. Natl. Acad. Sci. USA, 92, 220, 10.1073/pnas.92.1.220 · DOI · Paper page
  37. Moriguchi, 2018, Reduced expression of Na+/Ca2+ exchangers is associated with cognitive deficits seen in Alzheimer’s disease model mice, Neuropharmacology, 131, 291, 10.1016/j.neuropharm.2017.12.037 · DOI
  38. Barthet, 2018, Presenilin-mediated cleavage of APP regulates synaptotagmin-7 and presynaptic plasticity, Nat. Commun., 9, 4780, 10.1038/s41467-018-06813-x · DOI
  39. Sun, 2021, Association of neurogranin gene expression with Alzheimer’s disease pathology in the perirhinal cortex, Alzheimer’s Dement. Transl. Res. Clin. Interv., 7, e12162, 10.1002/trc2.12162 · DOI
  40. Repalli, 2015, Screening strategies to identify HSP70 modulators to treat Alzheimer’s disease, Drug Des. Devel. Ther., 9, 321, 10.2147/DDDT.S72165 · DOI
  41. Venediktov, A.A., Bushueva, O.Y., Kudryavtseva, V.A., Kuzmin, E.A., Moiseeva, A.V., Baldycheva, A., Meglinski, I., and Piavchenko, G.A. (2023). Closest horizons of Hsp70 engagement to manage neurodegeneration. Front. Mol. Neurosci., 16. · DOI
  42. Chambraud, 2021, Decrease of neuronal FKBP4/FKBP52 modulates perinuclear lysosomal positioning and MAPT/Tau behavior during MAPT/Tau-induced proteotoxic stress, Autophagy, 17, 3491, 10.1080/15548627.2021.1875611 · DOI
  43. Tan, J.S.Y., Lee, B., Lim, J., Ma, D.R., Goh, J.X., Goh, S.Y., Gulam, M.Y., Koh, S.M., Lee, W.W., and Feng, L. (2022). Parkinson’s Disease-Specific Autoantibodies against the Neuroprotective Co-Chaperone STIP1. Cells, 11. · DOI
  44. Pulido, 2023, DNA Methylation Description of Hippocampus, Cortex, Amygdala, and Blood of Drug-Resistant Temporal Lobe Epilepsy, Mol. Neurobiol., 60, 2070, 10.1007/s12035-022-03180-z · DOI
  45. Mathys, 2019, Single-cell transcriptomic analysis of Alzheimer’s disease, Nature, 570, 332, 10.1038/s41586-019-1195-2 · DOI · Paper page
  46. Noori, A., Mezlini, A.M., Hyman, B.T., Serrano-Pozo, A., and Das, S. (2021). Systematic review and meta-analysis of human transcriptomics reveals neuroinflammation, deficient energy metabolism, and proteostasis failure across neurodegeneration. Neurobiol. Dis., 149. · DOI · Paper page
  47. Wang, 2010, Deposition of lactoferrin in fibrillar-type senile plaques in the brains of transgenic mouse models of Alzheimer’s disease, Neurosci. Lett., 481, 164, 10.1016/j.neulet.2010.06.079 · DOI
  48. Tsatsanis, 2021, The acute phase protein lactoferrin is a key feature of Alzheimer’s disease and predictor of Aβ burden through induction of APP amyloidogenic processing, Mol. Psychiatry, 26, 5516, 10.1038/s41380-021-01248-1 · DOI
  49. Mungas, 2001, MRI predictors of cognition in subcortical ischemic vascular disease and Alzheimer’s disease, Neurology, 57, 2229, 10.1212/WNL.57.12.2229 · DOI · Paper page
  50. Pereira, 2018, ABC Transporters Are Key Players in Alzheimer’s Disease, J. Alzheimers Dis., 61, 463, 10.3233/JAD-170639 · DOI
  51. Lahousse, 2003, Reduced expression of the cystic fibrosis transmembrane conductance regulator gene in the hypothalamus of patients with Alzheimer’s disease, J. Alzheimer’s Dis., 5, 455, 10.3233/JAD-2003-5605 · DOI
  52. Dahimene, 2022, Biallelic CACNA2D1 loss-of-function variants cause early-onset developmental epileptic encephalopathy, Brain, 145, 2721, 10.1093/brain/awac081 · DOI
  53. Bonaguro, 2020, CRELD1 modulates homeostasis of the immune system in mice and humans, Nat. Immunol., 21, 1517, 10.1038/s41590-020-00811-2 · DOI
  54. Wang, 2022, Activation of Wnt/β-catenin pathway mitigates blood–brain barrier dysfunction in Alzheimer’s disease, Brain, 145, 4474, 10.1093/brain/awac236 · DOI
  55. Brown, 2016, Neuronal Hemoglobin Expression and Its Relevance to Multiple Sclerosis Neuropathology, J. Mol. Neurosci., 59, 1, 10.1007/s12031-015-0711-6 · DOI
  56. Richter, 2009, Neurons express hemoglobin alpha- and beta-chains in rat and human brains, J. Comp. Neurol., 515, 538, 10.1002/cne.22062 · DOI
  57. Goitre, L., De Luca, E., Braggion, S., Trapani, E., Guglielmotto, M., Biasi, F., Forni, M., Moglia, A., Trabalzini, L., and Retta, S.F. (2014). KRIT1 loss of function causes a ROS-dependent upregulation of c-Jun. Free Radic. Biol. Med., 68. · DOI
  58. Tief, 1996, Tyrosinase, the Key Enzyme in Melanin Synthesis, is Expressed in Murine Brain, Eur. J. Biochem., 241, 12, 10.1111/j.1432-1033.1996.0012t.x · DOI
  59. Wang, 2006, Regulation of tyrosinase trafficking and processing by presenilins: Partial loss of function by familial Alzheimer’s disease mutation, Proc. Natl. Acad. Sci. USA, 103, 353, 10.1073/pnas.0509822102 · DOI
  60. Goebeler, 2008, Annexin A8 regulates late endosome organization and function, Mol. Biol. Cell, 19, 5267, 10.1091/mbc.e08-04-0383 · DOI
  61. Chang, 2006, Molecular network and chromosomal clustering of genes involved in synaptic plasticity in the hippocampus, J. Biol. Chem., 281, 30195, 10.1074/jbc.M605876200 · DOI
  62. McArthur, 2010, Annexin A1: A central player in the anti-inflammatory and neuroprotective role of microglia, J. Immunol., 185, 6317, 10.4049/jimmunol.1001095 · DOI
  63. Bedrood, 2009, Annexin A5 directly interacts with amyloidogenic proteins and reduces their toxicity, Biochemistry, 48, 10568, 10.1021/bi900608m · DOI
  64. Barbisin, M., Vanni, S., Schmädicke, A.C., Montag, J., Motzkus, D., Opitz, L., Salinas-Riester, G., and Legname, G. (2014). Gene expression profiling of brains from bovine spongiform encephalopathy (BSE)-infected cynomolgus macaques. BMC Genom., 15. · DOI
  65. Ferrer, 2011, Neuronal hemoglobin is reduced in Alzheimer’s disease, argyrophilic grain disease, Parkinson’s disease, and dementia with Lewy bodies, J. Alzheimers Dis., 23, 537, 10.3233/JAD-2010-101485 · DOI
  66. Vanni, S., Zattoni, M., Moda, F., Giaccone, G., Tagliavini, F., Haïk, S., Deslys, J.P., Zanusso, G., Ironside, J.W., and Carmona, M. (2018). Hemoglobin mRNA changes in the frontal cortex of patients with neurodegenerative diseases. Front. Neurosci., 12. · DOI
  67. Schmeisser, 2012, IκB kinase/nuclear factor κB-dependent insulin-like growth factor 2 (Igf2) expression regulates synapse formation and spine maturation via Igf2 receptor signaling, J. Neurosci., 32, 5688, 10.1523/JNEUROSCI.0111-12.2012 · DOI
  68. Stern, 2014, Enhancement of Memories by Systemic Administration of Insulin-Like Growth Factor II, Neuropsychopharmacology, 39, 2179, 10.1038/npp.2014.69 · DOI
  69. Martin, 1999, Molecular basis of the neurodegenerative disorders, N. Engl. J. Med., 340, 1970, 10.1056/NEJM199906243402507 · DOI
  70. Berron, 2020, Medial temporal lobe connectivity and its associations with cognition in early Alzheimer’s disease, Brain, 143, 1233, 10.1093/brain/awaa068 · DOI
  71. Chen, 2018, Assessing Synaptic Density in Alzheimer Disease with Synaptic Vesicle Glycoprotein 2A Positron Emission Tomographic Imaging, JAMA Neurol., 75, 1215, 10.1001/jamaneurol.2018.1836 · DOI · Paper page
  72. Brinkmalm, 2014, SNAP-25 is a promising novel cerebrospinal fluid biomarker for synapse degeneration in Alzheimer’s disease, Mol. Neurodegener., 9, 53, 10.1186/1750-1326-9-53 · DOI · Paper page
  73. Hartl, 2011, Molecular chaperones in protein folding and proteostasis, Nature, 475, 324, 10.1038/nature10317 · DOI · Paper page
  74. Mizushima, 2008, Autophagy fights disease through cellular self-digestion, Nature, 451, 1069, 10.1038/nature06639 · DOI · Paper page
  75. Chen, 2012, Quantitative proteomic analysis of human substantia nigra in alzheimer’s disease, huntington’s disease and multiple sclerosis, Neurochem. Res., 37, 2805, 10.1007/s11064-012-0874-2 · DOI
  76. Kumari, A., Rahaman, A., Zeng, X.A., Farooq, M.A., Huang, Y., Yao, R., Ali, M., Ishrat, R., and Ali, R. (2022). Temporal Cortex Microarray Analysis Revealed Impaired Ribosomal Biogenesis and Hyperactivity of the Glutamatergic System: An Early Signature of Asymptomatic Alzheimer’s Disease. Front. Neurosci., 16. · DOI
  77. Blennow, 2018, Biomarkers for Alzheimer’s disease: Current status and prospects for the future, J. Intern. Med., 284, 643, 10.1111/joim.12816 · DOI · Paper page
  78. Wu, 2017, RNA sequencing in post-mortem human brains of neuropsychiatric disorders, Psychiatry Clin. Neurosci., 71, 663, 10.1111/pcn.12550 · DOI
  79. Poloni, 2020, Abbiategrasso brain bank protocol for collecting, processing and characterizing aging brains, J. Vis. Exp., 2020, e60296
  80. Kuleshov, 2016, Enrichr: A comprehensive gene set enrichment analysis web server 2016 update, Nucleic Acids Res., 44, W90, 10.1093/nar/gkw377 · DOI · Paper page

Cited by

Sorted by citations

Metadata

Authors
Ferrari, R. R., Fantini, V., Garofalo, M., Di Gerlando, R., Dragoni, F., Rizzo, B., Spina, E., Rossi, M., Calatozzolo, C., Profka, X., Ceroni, M., Guaita, A., Davin, A., Gagliardi, S., & Poloni, T. E.
Affiliations
  • Department of Brain and Behavioral Sciences, University of Pavia, Viale Golgi 19, 27100 Pavia, Italy
  • Laboratory of Neurobiology and Neurogenetics, Golgi Cenci Foundation, Corso San Martino 10, 20081 Abbiategrasso, Italy
  • Molecular Biology and Transcriptomic Unit, IRCCS Mondino Foundation, Via Mondino 2, 27100 Pavia, Italy
  • Unity of Biostatistics, Golgi Cenci Foundation, Corso San Martino 10, 20081 Abbiategrasso, Italy
  • Department of Neurology and Neuropathology, Golgi Cenci Foundation, Corso San Martino 10, 20081 Abbiategrasso, Italy
Venue
International Journal of Molecular Sciences
Publisher
MDPI AG
Published
2024-10-16
Volume
25
Issue
20
Pages
11117
ISSN
1422-0067
Cited by
14
References
13
Language
en
Funders
  • Serpero Foundation (20129, 20081)
  • Golgi Cenci Foundation (20129, 20081)

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