Findings and advancements of next-generation sequencing in Alzheimer’s disease

Main Article Content

Guilherme Nobre Nogueira
https://orcid.org/0000-0002-6294-4934
Rafaela Fernandes Gonçalves
https://orcid.org/0000-0003-0603-0633
Joel Lavinsky
https://orcid.org/0000-0002-0377-5704
Gustavo Rassier Isolan
https://orcid.org/0000-0002-7863-0112

Abstract

Introduction: Next-generation sequencing (NGS) has revolutionized the understanding of Alzheimer’s disease (AD), uncovering genetic and transcriptomic biomarkers that enhance the ATN (Amyloid-beta, Tau, Neurodegeneration) framework. These advancements have illuminated the roles of reactive astrocytes, amyloid deposition, and tau phosphorylation, linking neurodegeneration to specific molecular pathways.


Objective: To evaluate NGS’s impact on identifying biomarkers, understanding AD pathogenesis, and advancing personalized diagnostics and treatments.


Method: A narrative review was conducted using terms like “Alzheimer’s disease,” “nextgeneration sequencing,” “ATN framework,” and “transcriptomics.” Studies published in English, focusing on NGS in AD diagnosis or management, were included.


Result: NGS has identified genes such as APP, TREM2, and PLD3, along with epigenetic modifications linked to AD. Transcriptomic studies highlighted pathways related to inflammation, synaptic dysfunction, and neurodegeneration. Moreover, reactive astrocytes were shown to mediate beta-amyloid accumulation and tau progression.


Conclusion: While NGS has transformed AD research, challenges such as data interpretation and protocol standardization limit its clinical application. Nonetheless, its integration into the ATN model and personalized diagnostics offers promising avenues for early detection and targeted therapies.

Article Details

Section

Review Article

References

Dubois B, Villain N, Schneider L, Fox N, Campbell N, Galasko D, et al. Alzheimer disease as a clinical-biological construct—an international working group recommendation. JAMA Neurol. 2024;81(12):1304-11. https://doi.org/10.1001/jamaneurol.2024.3770

Jack CR Jr, Andrews JS, Beach TG, Buracchio T, Dunn B, Graf A, et al. Revised criteria for diagnosis and staging of Alzheimer disease: Alzheimer’s Association Workgroup. Alzheimers Dement. 2024;20(8):5143–69. https://doi.org/10.1002/alz.13859

Dubois B, Feldman HH, Jacova C, Dekosky ST, Barberger-Gateau P, Cummings J, et al. Research criteria for the diagnosis of Alzheimer disease: revising the NINCDS-ADRDA criteria. Lancet Neurol. 2007;6(8):734–46. https://doi.org/10.1016/S1474-4422(07)70178-3

Nitrini R. What is “biological Alzheimer’s disease”? Dement Neuropsychol. 2024;18:e2024E001. https://doi.org/10.1590/1980-5764-DN-2024-E001

Villain N, Michalon R. What is Alzheimer’s disease? An analysis of nosological perspectives from the 20th and 21st centuries. Eur J Neurol. 2024;31(11):e16302. https://doi.org/10.1111/ene.16302

Schindler SE, Petersen KK, Saef B, Tosun D, Shaw LM, Zetterberg H, et al. Head-to-head comparison of leading blood tests for Alzheimer’s disease pathology. Alzheimers Dement. 2024;20(11):8074–96. https://doi.org/10.1002/alz.14315

Chen Y, Yu Y. Tau and neuroinflammation in Alzheimer’s disease: interplay mechanisms and clinical translation. J Neuroinflammation. 2023;20(1):165. https://doi.org/10.1186/s12974-023-02853-3

Novoa C, Salazar P, Cisternas P, Gherardelli C, Vera-Salazar R, Zolezzi JM, et al. Inflammation context in Alzheimer’s disease, a relationship intricate to define. Biol Res. 2022;55(1):39. https://doi.org/10.1186/s40659-022-00404-3

Jonsson T, Stefansson H, Steinberg S, Jonsdottir I, Jonsson PV, Snaedal J, et al. Variant of TREM2 associated with the risk of Alzheimer’s disease. N Engl J Med. 2012;368(2):107–16. https://doi.org/10.1056/NEJMoa1211103

Düz E, İlgün A, Bozkurt FB, Çakır T. Integration of genomic and transcriptomic layers in RNA-Seq data leads to protein interaction modules with improved Alzheimer’s disease associations. Eur J Neurosci. 2024;60(11):6891-08. https://doi.org/10.1111/ejn.16600

Dai Z, Pang X, Chen N, Fan X, Liu W, Chen Z, et al. Network medicine approach unravels endophenotype signature in Alzheimer’s disease through large-scale comparative proteomics analysis: vascular dysfunction as a prime example. J Chem Inf Model. 2024;64(19):7758–71. https://doi.org/10.1021/acs.jcim.4c01344

Sforzini L, Marizzoni M, Bottanelli C, Kunšteková V, Zonca V, Saleri S, et al. Transcriptomic profiles in major depressive disorder: the role of immunometabolic and cell-cycle-related pathways in depression with different levels of inflammation. Mol Psychiatry. 2024;30(4):1308-1. https://doi.org/10.1038/s41380-024-02736-w