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Neurodegenerative diseases encompass a range of disorders characterized by the progressive degeneration of the nervous system, affecting millions of individuals globally. Conditions such as Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, and multiple sclerosis are among the most prevalent and debilitating. These diseases not only impact the quality of life of affected individuals but also place a significant burden on healthcare systems. Understanding the underlying mechanisms, identifying biomarkers for early diagnosis, and developing effective therapies are crucial for improving patient outcomes and guiding clinical care. The importance of studying these conditions is underscored by the need for innovative approaches that integrate clinical, preclinical, and translational research.
Current research in neurodegenerative diseases is multifaceted, focusing on diverse areas such as disease pathophysiology, the role of genetics, the impact of environmental factors, and the integration of epidemiological studies. Advances in imaging techniques have enhanced our ability to visualize disease progression, while the identification of potential biomarkers holds promise for early diagnostic and prognostic assessments. Additionally, the application of machine learning approaches is revolutionizing data analysis, enhancing our understanding of disease mechanisms, and aiding in more personalized care. Therapeutic strategies, including pharmacological interventions and lifestyle modifications, are under investigation for their potential to alter disease trajectories. This Collection aims to bring together research from various domains related to neurodegenerative conditions, encompassing novel insights into disease pathophysiology, diagnostics, therapeutic developments, and care strategies.
We welcome the submission of all papers relevant to advances in neurodegenerative disease. This is a joint Collection across Nature Communications, Nature Neuroscience, Communications Medicine, Communications Biology, and Scientific Reports. We encourage authors to choose which journal to submit to according to their own preference. However, before any decision is taken, the relevant journal webpages should be checked to ensure the submission is within the journal’s scope. Each journal will apply its standard editorial criteria for scope and advance. Where submissions are more suitable for another participating journal, editors will recommend a transfer to a more appropriate alternative journal. Seamless transfers within the Nature Portfolio help ensure a smooth and timely experience for all authors. Note that Nature Communications and Scientific Reports will only consider original research Articles.
MINT is a Python toolbox for multimodal data integration and community detection, offering cross-validation and modality selection optimization to identify biologically relevant subgroups and predict Alzheimer’s progression.
Saman Sarraf
Bárbara Avelar-Pereira
for the Alzheimer’s Disease Neuroimaging Initiative
Gao et al. examine if napping patterns can predict individuals at risk for cognitive impairment. They find that among older adults, more morning naps are linked to a higher Alzheimer’s risk, while more early afternoon naps and less variability in nap duration are linked to lower levels of Alzheimer’s pathology.
This study characterised the landscapes and changes of RNA m6A in brains of individuals with or without Alzheimer’s disease, and revealed roles of a promoter antisense RNA next to MAPT in neuronal gene regulation that promote neuronal survival.
BPAN is a rare neurodegenerative disease caused by WDR45 mutations. Here, the authors discover that WDR45 can competitively displace G3BP1 from Caprin-1 to promote stress granule disassembly, a function that is disrupted by BPAN-associated WDR45 mutations.
Early expression of intraneuronal amyloid-β (not phospho-tau) and inflammatory and glycosylation pathway transcripts distinguish neocortical RORB+ and GAD1+ neurons selectively vulnerable to neurodegeneration in Alzheimer’s disease.
WM dysfunction observed in AD and MCI spatially correlates with specific genes enriched in biological processes related to synaptic function and development, mostly active in neurons and astrocytes.
Ex vivo stimulation of isolated monocytes and T cells from peripheral blood immune cells reveals distinct signatures of immune activation across different stages of Parkinson’s disease, including the prodromal stage.
Kverneng et al. assess the mitochondrial respiratory chain in skeletal muscle from persons with Parkinson’s disease. Their findings suggest the existence of a subpopulation with complex I deficiency and support the potential of extra-neural biomarkers for patient stratification.
Feizpour et al. assess the utility of a high-performing Alzheimer’s disease (AD) blood test to discriminate AD disease stages. The blood test reliably detects Intermediate and Advanced stages of disease, and while the test is less effective at distinguishing Advanced stage alone, it may reduce reliance on expensive brain scans.
Nunes et al. predict Huntington’s disease score by applying deep learning to readings from a wrist-worn sensor obtained over a 7 day period. Differences are seen in goal-directed movement that correlate with clinical score.