Recent research has shifted focus from amyloid-beta to soluble tau as a significant contributor to cognitive decline in Alzheimer's disease (AD). A study demonstrated that high-molecular-weight soluble tau impairs burst firing in hippocampal neurons, linking it to neuronal dysfunction and suggesting it as a potential therapeutic target (ref: Lopes doi.org/10.1016/j.cell.2025.06.016/). Additionally, a novel cell-type-directed network-correcting combination therapy was proposed, utilizing human data and single-cell transcriptomics to address the heterogeneous molecular changes in AD, which complicate treatment development (ref: Li doi.org/10.1016/j.cell.2025.06.035/). The role of mast cells in regulating cerebrospinal fluid dynamics was also highlighted, indicating their potential impact on neurodegenerative diseases (ref: Mamuladze doi.org/10.1016/j.cell.2025.06.046/). Furthermore, the integrated stress response (ISR) was identified as a therapeutic target, with an optogenetic platform developed to discover compounds that modulate ISR without toxicity (ref: Wong doi.org/10.1016/j.cell.2025.06.024/). In terms of biomarkers, a study analyzed tau PET positivity across age groups, revealing significant variations linked to amyloid-beta status and APOE genotype (ref: Ossenkoppele doi.org/10.1038/s41593-025-02000-6/). The Global Neurodegeneration Proteomics Consortium provided insights into shared and disease-specific pathways across neurodegenerative diseases, identifying numerous proteins associated with AD, PD, and FTD (ref: Ali doi.org/10.1038/s41591-025-03833-1/).

Neuroinflammation plays a crucial role in neurodegenerative diseases, with studies revealing the impact of immune responses on disease progression. The APOE ε4 allele was shown to correlate with immune-related proteomic changes across various neurodegenerative diseases, emphasizing its role as a genetic risk factor (ref: Shvetcov doi.org/10.1038/s41591-025-03835-z/). The Global Neurodegeneration Proteomics Consortium's findings highlighted the necessity for novel biomarkers to improve early detection and treatment strategies (ref: Imam doi.org/10.1038/s41591-025-03834-0/). Additionally, research on selective autophagy mechanisms has unveiled how transmembrane cargo receptors initiate autophagosome biogenesis, which is critical for maintaining cellular homeostasis (ref: Adriaenssens doi.org/10.1038/s41556-025-01712-y/). The study of aging in the killifish brain revealed altered translation elongation as a contributor to neurodegeneration, linking cellular aging processes to neuroinflammatory responses (ref: Di Fraia doi.org/10.1126/science.adk3079/). These findings collectively underscore the intricate relationship between neuroinflammation, immune responses, and neurodegenerative disease mechanisms.

Genetic and epigenetic factors significantly influence the risk and progression of neurodegenerative diseases. A novel framework, scPRS, was introduced to compute single-cell polygenic risk scores, enhancing the understanding of genetic risks associated with complex diseases, including Alzheimer's disease (ref: Zhang doi.org/10.1038/s41587-025-02725-6/). Furthermore, a combined approach of single-cell profiling of chromatin and transcriptome revealed insights into splicing and chromatin accessibility across brain cell types, shedding light on the molecular underpinnings of neurodegeneration (ref: Hu doi.org/10.1038/s41587-025-02734-5/). The identification of intersectin and endophilin condensates in synaptic vesicle replenishment highlighted the importance of genetic factors in synaptic function and neurodegenerative disease (ref: Ogunmowo doi.org/10.1038/s41593-025-02002-4/). Additionally, machine learning techniques applied to genome-wide data have shown promise in discovering novel genetic loci associated with Alzheimer's disease, demonstrating the potential of advanced computational methods in genetic research (ref: Bracher-Smith doi.org/10.1038/s41467-025-61650-z/).

Proteomics has emerged as a powerful tool for identifying biomarkers and understanding the pathophysiology of neurodegenerative diseases. A comprehensive analysis of plasma samples revealed both shared and disease-specific proteomic signatures across Alzheimer's disease, Parkinson's disease, and frontotemporal dementia, highlighting the complexity of neurodegenerative processes (ref: Ali doi.org/10.1038/s41591-025-03833-1/). The disruption of cerebrospinal fluid-plasma protein balance was associated with cognitive impairment, emphasizing the role of protein transport mechanisms in neurodegeneration (ref: Farinas doi.org/10.1038/s41591-025-03831-3/). Additionally, the Global Neurodegeneration Proteomics Consortium's efforts to identify biomarkers for early detection and treatment of neurodegenerative diseases have underscored the importance of proteomic profiling in clinical settings (ref: Imam doi.org/10.1038/s41591-025-03834-0/). The spatial proteomics study of microglial states in Alzheimer's disease provided insights into the cellular dynamics and interactions that contribute to disease progression (ref: Mrdjen doi.org/10.1038/s41590-025-02203-w/).

The intersection of neurodegeneration and aging has been a focal point of recent research, revealing how aging processes contribute to the onset and progression of neurodegenerative diseases. A plasma proteomics study linked organ aging with healthspan and longevity, demonstrating that biological age estimates derived from plasma proteins can predict the onset of diseases, including Alzheimer's disease (ref: Oh doi.org/10.1038/s41591-025-03798-1/). Furthermore, the development of MultiVINE-seq has provided insights into how genetic variants in brain vascular cells influence disease risk, highlighting the role of cerebrovascular dysfunction in neurodegeneration (ref: Reid doi.org/10.1016/j.neuron.2025.07.001/). Dietary patterns were also shown to influence multimorbidity trajectories in older adults, suggesting that lifestyle factors can mitigate the effects of aging on health (ref: Abbad-Gomez doi.org/10.1038/s43587-025-00929-8/). Collectively, these findings emphasize the need for a holistic approach to understanding the aging process in the context of neurodegenerative diseases.

Research into neurodegenerative disease models has provided critical insights into the mechanisms underlying diseases such as Alzheimer's and progressive supranuclear palsy. Evidence for trans-synaptic propagation of oligomeric tau in progressive supranuclear palsy suggests that tau pathology may spread through synaptic connections, contributing to synapse loss (ref: McGeachan doi.org/10.1038/s41593-025-01992-5/). Additionally, studies on microglial states in mouse models of Alzheimer's disease have revealed distinct contributions of microglial dynamics to disease progression, indicating potential targets for therapeutic intervention (ref: Ardura-Fabregat doi.org/10.1038/s41593-025-02006-0/). The development of human stem cell-derived GABAergic interneurons has opened avenues for treating neurological disorders, showcasing the potential of stem cell technology in understanding and addressing neurodegenerative diseases (ref: Bershteyn doi.org/10.1016/j.neuron.2025.06.010/). These models and mechanisms are crucial for developing effective therapies and understanding the complex interactions involved in neurodegeneration.

Recent clinical trials have explored various therapeutic strategies for neurodegenerative diseases, with mixed results. A randomized clinical trial of ambroxol for Parkinson's disease dementia indicated potential benefits, although the results necessitate further investigation (ref: Silveira doi.org/10.1001/jamaneurol.2025.1687/). The relationship between amyloid-beta pathology and cognitive performance in centenarians revealed that high amyloid loads do not necessarily correlate with cognitive decline, suggesting that amyloid pathology may not be a definitive marker of cognitive health (ref: Rohde doi.org/10.1001/jamaneurol.2025.1734/). Additionally, the impact of TET2-mutant myeloid cells on Alzheimer's disease progression demonstrated a protective effect against cognitive decline, highlighting the potential for targeting hematopoietic mutations in therapeutic strategies (ref: Matatall doi.org/10.1016/j.stem.2025.06.006/). The concordance between amyloid-PET quantification and real-world visual reads underscores the importance of accurate diagnostic tools in clinical settings (ref: Zeltzer doi.org/10.1001/jamaneurol.2025.2218/). These findings collectively inform ongoing efforts to develop effective treatments for neurodegenerative diseases.

Genetic factors play a pivotal role in the susceptibility and progression of neurodegenerative diseases. A multi-ancestry genome-wide meta-analysis identified novel risk loci for Alzheimer's disease, emphasizing the importance of diverse genetic backgrounds in understanding disease mechanisms (ref: Rajabli doi.org/10.1186/s13059-025-03564-z/). Machine learning approaches have been applied to genetic data to enhance the identification of risk factors and predict individual susceptibility to Alzheimer's disease, showcasing the potential of advanced computational techniques in genetic research (ref: Bracher-Smith doi.org/10.1038/s41467-025-61650-z/). The spatial proteomics study of microglial states in Alzheimer's disease provided insights into the cellular dynamics and interactions that contribute to disease progression, further linking genetic factors to disease mechanisms (ref: Mrdjen doi.org/10.1038/s41590-025-02203-w/). These studies highlight the complex interplay between genetics, epigenetics, and neurodegenerative disease, underscoring the need for continued research in this area.