Molecular Advances in Parkinson’s Disease: Current Insights and Future Directions
A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Neurobiology".
Deadline for manuscript submissions: 30 November 2026 | Viewed by 11
Special Issue Editor
Special Issue Information
Dear Colleagues,
We are pleased to invite you to contribute to this Special Issue entitled “Molecular Advances in Parkinson’s Disease: Current Insights and Future Directions.”
Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by the selective loss of dopaminergic neurons and the accumulation of misfolded alpha-synuclein in the form of Lewy bodies. Although the neuropathological features of PD are well established, the molecular mechanisms underlying disease onset and progression are complex and involve multiple interconnected pathways.
Current evidence indicates that several molecular processes contribute to PD pathogenesis, including protein aggregation, neuroinflammation, immune dysregulation, mitochondrial dysfunction, oxidative stress, impaired autophagy, and lysosomal dysfunction. In addition, alterations to cellular signaling pathways and protein homeostasis mechanisms play a critical role in neuronal survival and degeneration. These processes arise from a complex interplay between genetic susceptibility, environmental exposures, and systemic biological factors. Environmental contributors such as toxins, pollutants, and infections promote oxidative stress, mitochondrial impairment, and chronic inflammation. Emerging evidence also implicates gut microbiota dysbiosis in disease onset and progression through the gut–brain axis, influencing intestinal permeability, immune activation, and microbial metabolite production. Aging remains the most significant risk factor, amplifying vulnerability to cellular stress and reducing compensatory mechanisms. Furthermore, epigenetic modifications, metabolic disturbances, and alterations to both innate and adaptive immune responses contribute to disease progression. Together, these factors converge on shared pathogenic pathways that ultimately drive dopaminergic neuronal degeneration.
Recent advances in molecular biology techniques have enabled the identification of new molecular pathways and regulatory mechanisms involved in neurodegeneration. Furthermore, the identification of molecular biomarkers has become a major research priority, as they may contribute to early diagnosis, disease monitoring, and the development of targeted therapies. Complementary approaches such as omics technologies and artificial intelligence are increasingly being used to analyze complex molecular datasets and identify disease-associated molecular patterns.
This Special Issue will highlight recent advances in the molecular understanding of Parkinson’s disease and promote research focused on molecular pathways, biomarkers, and potential therapeutic targets.
Led by Prof. Dr. Laura Virginia Adalid Peralta, with the assistance of Dr. Gloria Erandi Pérez-Figueroa (Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico), we will showcase recent advances in this field, and we are delighted to invite you to contribute.
This Special Issue will platform high-quality original research and review articles focused on the molecular mechanisms underlying Parkinson’s disease, including cellular signaling pathways, protein aggregation, neuroinflammation, immune dysregulation, and molecular biomarkers. Particular emphasis will be placed on the interplay between genetic susceptibility, environmental exposures, aging, and gut microbiota in shaping disease onset and progression. This Special Issue will also highlight studies employing omics technologies and computational approaches to advance the understanding of molecular and systemic mechanisms in Parkinson’s disease.
This topic is fully aligned with the scope of the International Journal of Molecular Sciences, which publishes research on molecular biology, molecular medicine, and the cellular and biochemical basis of disease. The proposed Special Issue will provide a focused and integrative collection of articles addressing molecular and translational aspects of Parkinson’s disease, bridging mechanistic insights and emerging analytical approaches.
Our aim is to gather at least 20 high-quality articles that advance the understanding of Parkinson’s disease pathogenesis, including the identification of biomarkers, risk-modifying factors, and potential therapeutic targets. Once this number of accepted articles is reached, the Special Issue may be published in book form.
For this Special Issue, original research and review articles are welcome. Research areas may include, but are not limited to, the following:
- Molecular mechanisms of Parkinson’s disease;
- Alpha-synuclein biology, aggregation, and toxicity;
- Molecular signaling pathways in neurodegeneration;
- Neuroinflammation, immune response, and immune dysregulation;
- Neuroimmune interactions and systemic inflammation;
- Genetic susceptibility and epigenetic regulation;
- Environmental risk factors and toxin exposure;
- Gut microbiota and the gut–brain axis;
- Protein homeostasis and degradation pathways;
- Autophagy and lysosomal dysfunction;
- Mitochondrial dysfunction and oxidative stress;
- Aging-related mechanisms in neurodegeneration;
- Cell death pathways in Parkinson’s disease;
- Molecular biomarkers for diagnosis and disease progression;
- Experimental and preclinical molecular models;
- Translational research and therapeutic targets;
- Omics approaches (genomics, proteomics, metabolomics, etc.);
- Bioinformatics and artificial intelligence applied to molecular data.
We look forward to receiving your contributions.
Dr. Laura Adalid-Peralta
Guest Editor
Manuscript Submission Information
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Keywords
- Parkinson’s disease
- neurodegenerative mechanisms
- genetic susceptibility
- alpha-synuclein aggregation
- neuroinflammation
- mitochondrial dysfunction
- oxidative stress
- autophagy–lysosomal pathway
- gut–brain axis
- microbiome dysbiosis
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