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Brain & Heart Alzheimer’s disease: Gene and protein network analysis

a comprehensive picture of the molecular landscape of AD, study design, potentially leading to biased or misleading
underlining the complexity of the disease. The identified results. In addition, our study has not independently
genes, pathways, and hub proteins collectively place the validated the findings through experimental or additional
spotlight on the ribosomal protein pathway associated with computational methods, which is an evident limitation in
AD pathogenesis. Prior proteomic analyses of AD donors affirming the reliability of our conclusions.
revealed that 28 ribosomal proteins were significantly
upregulated in AD samples, among which RPL12, RPL15, 5. Conclusion
RPL18, RPL27, RPL35, and RPS16 overlapped with the hub Our multifaceted analyses provide precious insights into
genes identified in our study. This prior study also exhibited the molecular complexity of AD. The identified genes,
that ribosomal proteins were upregulated only in the brain pathways, and hub proteins related to ribosomal function
capillaries but not in the brain parenchyma, signifying the form the basis for future mechanistic studies and the search
40
functional impairment of the blood-brain barrier (BBB). for therapeutic targets.
The relationship between the functional impairment of the
BBB and neuroinflammation in AD was also demonstrated Acknowledgments
in our previous study. In addition to their canonical roles None.
41
in protein synthesis, ribosomal proteins, including hub
genes in our study (such as RPL12, RPL15, RPL18, RPL19, Funding
and RPL27), have been implicated in a variety of extra-
ribosomal functions responsible for cellular homeostasis None.
and stress responses. Of note, several ribosomal proteins Conflict of interest
have been demonstrated to interact with MDM2 protein,
a key regulator of the tumor suppressor p53. Under The authors declare that they have no competing interests.
conditions of cellular stress, such interactions can stabilize
and activate p53, thereby initiating a cascade of events that Author contributions
can cause cell cycle arrest, DNA repair, or apoptosis. Our Conceptualization: Shan Luo
bioinformatic analysis also demonstrated the presence of Investigation: Shan Luo
ribosomal pathway abnormalities in the entorhinal cortex. Methodology: Shan Luo, Yifei Wang
Our findings are concordant with previous studies that Project administration: Kohji Fukunaga
have underscored the importance of neuroinflammation, Supervision: Kohji Fukunaga
synaptic dysfunction, and protein synthesis dysregulation Writing – original draft: Shan Luo
in AD. 42,43 Innovatively, our study offered a novel Writing – review & editing: Yifei Wang
perspective by spotlighting specific genes and pathways Ethics approval and consent to participate
among these factors. Importantly, our results unravel
that ribosomal proteins, traditionally associated with Not applicable.
protein synthesis, may exert multifaceted effects on AD by
potentially mediating neuroinflammation and maintaining Consent for publication
synaptic integrity. This finding opens a new avenue for Not applicable.
probing the crosstalk between these two processes and
their contribution to disease progression. Nevertheless, the Availability of data
detailed mechanisms by which ribosomal proteins influence Data used in the study can be obtained from the GSE4757
AD remain unclear. Accordingly, further molecular dataset in the GEO database (https://www.ncbi.nlm.nih.
biological studies are warranted to analyze the involvement gov/geo/query/acc.cgi?acc=GSE4757).
and sequence of events of ribosomal proteins in AD and to
examine potential differences in the expression patterns of References
specific proteins among the identified hub genes and their
implications in AD pathology. 1. Hutton M, Hardy J. The presenilins and Alzheimer’s disease.
Hum Mol Genet. 1997;6(10):1639-1646.
As the samples and sequencing data utilized in this doi: 10.1093/hmg/6.10.1639
study were not originally prepared by the authors, there
is a potential for biases that could influence the results. 2. Bush AI. The metallobiology of Alzheimer’s disease. Trends
These gaps, due to the reliance on pre-existing data sets, Neurosci. 2003;26(4):207-214.
may introduce variables that are not accounted for in our doi: 10.1016/S0166-2236(03)00067-5

Volume 2 Issue 4 (2024) 9 doi: 10.36922/bh.2906