Sabiha Zarin Khanam^1,2, Vishwa Raj Lal², Ariba Anwar^1,2, Quba Raza^1,2, Omama Khatoon^1,2, Nesae Akhdash^1,2, Aqusa Zaman^1,2, Nausheen Hussain^1,2, Harsimran Kaur Hora¹, Priyangulta Beck¹ and Mukesh Nitin¹*

¹Department of Tech Biosciences, Digianalix, Ranchi, Jharkhand, India
²Department of Biotechnology, Jamshedpur Women’s University, Jamshedpur, Jharkhand, India

*Corresponding Author: Shanthi Kumari, Assistant Professor, Department of Microbiology, Osmania University, Hyderabad, Telangana, India.

Received: May 28, 2024; Published: June 20, 2024

Abstract

Neurodegenerative diseases, including Alzheimer's disease (AD), pose a significant burden on healthcare systems globally. Traditional diagnostic and therapeutic strategies often lack the sensitivity and specificity required for early detection and effective intervention. However, recent advancements in multi-omics technologies offer a promising route for revolutionizing the management of these debilitating conditions. This review delves into the current landscape of multi-omics approaches in identifying neurodegenerative diseases, with a particular emphasis on AD. The integration of data from genomics, transcriptomics, proteomics, metabolomics, and epigenomics, highlighting their potential to elucidate the complex interplay of molecular mechanisms underlying neurodegeneration. Furthermore, this study examined the challenges and future prospects of translating multi-omics approaches into clinical practice, paving the way for personalized medicine and improved patient outcomes in neurodegenerative diseases.

Keywords: Neurodegenerative Diseases; Multi-omics; Alzheimer's Disease; Biomarkers; Personalized Medicine

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Citation

Citation: Mukesh Nitin.,et al. “Unveiling the Molecular Landscape of Neurodegenerative Diseases: A Multi-Omics Approach Highlighting Treatment in Alzheimer's Disease".Acta Scientific Biotechnology 5.3 (2024): 22-32.

Copyright

Copyright: © 2024 Mukesh Nitin.,et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.