Advancing Metabolite Biomarkers in Neurodegenerative Disease: Discovery, Integration, and Therapeutic Potential
A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Cell Metabolism".
Deadline for manuscript submissions: 31 May 2025 | Viewed by 133
Special Issue Editor
Interests: Parkinson’s disease; senolytics and senescence; glia; early diagnosis strategies; bioinformatics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Biomarkers are essential tools in the fight against neurodegenerative diseases. They play a pivotal role in establishing an early diagnosis, prognosis, in treatment monitoring, and the identification of therapeutic targets. Advancements in biomarker research refine our ability to diagnose and treat neurodegenerative conditions and enhance our understanding of the complex biological processes underlying these diseases.
Biomarker categories are quite diverse. They can include genetic markers, proteomic signatures, imaging, and cellular characteristics. However, metabolites are particularly attractive for their relative ease of clinical access and analysis. Furthermore, when integrated with multi-omics data, metabolic biomarkers offer unique insights into disease mechanisms and therapeutic possibilities. Additionally, machine learning and other computational approaches are transforming how we analyze and interpret these rich datasets, leading to the discovery of novel biomarkers and improving our ability to translate findings into clinical practice.
This Special Issue welcomes submissions exploring all facets of metabolomic biomarker research in neurodegenerative diseases. We encourage a broad range of contributions, including but not limited to the following:
- Discovery of novel metabolite biomarkers of neurodegeneration.
- New insights into established metabolic biomarkers of neurodegeneration.
- Methodological advances in metabolomic data collection, integration, and analysis.
- Applications of machine learning and/or bioinformatics in metabolomic biomarker discovery.
- Translational studies leveraging metabolomic biomarkers for therapeutic development or precision medicine.
- Cross-disciplinary approaches integrating metabolomics with other omics data to address critical challenges in neurodegeneration research.
By welcoming a wide variety of studies, we aim to capture the diversity and innovation in this important and dynamic field.
Dr. Robert Logan
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- biomarkers
- neurodegeneration
- metabolites
- metabolic pathways
- metabolomic
- Alzheimer’s disease
- Parkinson’s disease
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