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Ageing is the primary risk factor for most neurodegenerative diseases, including Alzheimer disease (AD) and Parkinson disease (PD). One in ten individuals aged ≥65 years has AD and its prevalence continues to increase with increasing age. Few or no effective treatments are available for ageing-related neurodegenerative diseases, which tend to progress in an irreversible manner and are associated with large socioeconomic and personal costs. This Review discusses the pathogenesis of AD, PD and other neurodegenerative diseases, and describes their associations with the nine biological hallmarks of ageing: genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, mitochondrial dysfunction, cellular senescence, deregulated nutrient sensing, stem cell exhaustion and altered intercellular communication. The central biological mechanisms of ageing and their potential as targets of novel therapies for neurodegenerative diseases are also discussed, with potential therapies including NAD+ precursors, mitophagy inducers and inhibitors of cellular senescence.

There are currently no effective biomarkers for diagnosing Parkinson’s disease (PD) or tracking its progression. Here, we developed an artificial intelligence (AI) model to detect PD and track its progression from nocturnal breathing signals. The model was evaluated on a large dataset comprising 7,671 individuals, using data from several hospitals in the United States, as well as multiple public datasets. The AI model can detect PD with an area-under-the-curve of 0.90 and 0.85 on held-out and external test sets, respectively. The AI model can also estimate PD severity and progression in accordance with the Movement Disorder Society Unified Parkinson’s Disease Rating Scale ( R  = 0.94, P  = 3.6 × 10 –25 ). The AI model uses an attention layer that allows for interpreting its predictions with respect to sleep and electroencephalogram. Moreover, the model can assess PD in the home setting in a touchless manner, by extracting breathing from radio waves that bounce off a person’s body during sleep. Our study demonstrates the feasibility of objective, noninvasive, at-home assessment of PD, and also provides initial evidence that this AI model may be useful for risk assessment before clinical diagnosis. Using a neural network-based model, Parkinson’s disease can be diagnosed and its severity monitored based on breathing patterns while someone is asleep, with the potential for at-home touchless monitoring.

Key Points Many neurodegenerative diseases involve the accumulation of protein aggregates Endoplasmic reticulum (ER) stress triggers activation of the unfolded protein response (UPR), an adaptive reaction that restores cellular protein homeostasis, known as proteostasis Dysfunction of proteostasis is associated with abnormal levels of ER stress and is associated with neuronal degeneration in human post-mortem brain tissue Targeting the UPR can have distinct and even opposite effects on disease progression, depending on the disease context and the signalling branch that is analysed Gene therapy and pharmacological strategies to attenuate ER stress alleviates degeneration in various disease models Chronic ER stress not only results in neuronal loss, but also represses the synthesis of synaptic proteins, with implications for cognition and memory, and possibly autism spectrum disorder Accumulation of misfolded protein in neurons is a common feature of many neurodegenerative diseases. In this Review, Hetz and Saxena discuss the latest advances in our understanding about the mechanisms by which protein misfolding causes neurodegeneration, and look at novel insights into the role of cellular responses to protein misfolding in synaptic function and in inflammatory and mechanical injury in the nervous system. The clinical manifestation of neurodegenerative diseases is initiated by the selective alteration in the functionality of distinct neuronal populations. The pathology of many neurodegenerative diseases includes accumulation of misfolded proteins in the brain. In physiological conditions, the proteostasis network maintains normal protein folding, trafficking and degradation; alterations in this network — particularly disturbances to the function of endoplasmic reticulum (ER) — are thought to contribute to abnormal protein aggregation. ER stress triggers a signalling reaction known as the unfolded protein response (UPR), which induces adaptive programmes that improve protein folding and promote quality control mechanisms and degradative pathways or can activate apoptosis when damage is irreversible. In this Review, we discuss the latest advances in defining the functional contribution of ER stress to brain diseases, including novel evidence that relates the UPR to synaptic function, which has implications for cognition and memory. A complex concept is emerging wherein the consequences of ER stress can differ drastically depending on the disease context and the UPR signalling pathway that is altered. Strategies to target specific components of the UPR using small molecules and gene therapy are in development, and promise interesting avenues for future interventions to delay or stop neurodegeneration.

Existing therapeutic strategies for managing Parkinson disease (PD), which focus on addressing the loss of dopamine and dopaminergic function linked with degeneration of dopaminergic neurons, are limited by side effects and lack of long-term efficacy. In recent decades, research into PD pathophysiology and pharmacology has focused on understanding and tackling the neurodegenerative processes and symptomology of PD. In this Review, we discuss the challenges associated with the development of novel therapies for PD, highlighting emerging agents that aim to target cell death, as well as new targets offering a symptomatic approach to managing features and progression of the disease.

Genome-wide association studies of neurological diseases have identified thousands of variants associated with disease phenotypes. However, most of these variants do not alter coding sequences, making it difficult to assign their function. Here, we present a multi-omic epigenetic atlas of the adult human brain through profiling of single-cell chromatin accessibility landscapes and three-dimensional chromatin interactions of diverse adult brain regions across a cohort of cognitively healthy individuals. We developed a machine-learning classifier to integrate this multi-omic framework and predict dozens of functional SNPs for Alzheimer’s and Parkinson’s diseases, nominating target genes and cell types for previously orphaned loci from genome-wide association studies. Moreover, we dissected the complex inverted haplotype of the MAPT (encoding tau) Parkinson’s disease risk locus, identifying putative ectopic regulatory interactions in neurons that may mediate this disease association. This work expands understanding of inherited variation and provides a roadmap for the epigenomic dissection of causal regulatory variation in disease. Single-cell chromatin profiling of different brain regions identifies cell-type-specific regulatory elements, and helps to predict functional SNPs for Alzheimer’s and Parkinson’s diseases.

Robert Graham and colleagues carried out a GWAS meta-analysis for Parkinson's disease (PD) and report 17 new risk loci. Their analyses support a key role for autophagy and lysosomal biology in PD risk. Common variant genome-wide association studies (GWASs) have, to date, identified >24 risk loci for Parkinson's disease (PD). To discover additional loci, we carried out a GWAS comparing 6,476 PD cases with 302,042 controls, followed by a meta-analysis with a recent study of over 13,000 PD cases and 95,000 controls at 9,830 overlapping variants. We then tested 35 loci ( P < 1 × 10 −6 ) in a replication cohort of 5,851 cases and 5,866 controls. We identified 17 novel risk loci ( P < 5 × 10 −8 ) in a joint analysis of 26,035 cases and 403,190 controls. We used a neurocentric strategy to assign candidate risk genes to the loci. We identified protein-altering or cis –expression quantitative trait locus ( cis -eQTL) variants in linkage disequilibrium with the index variant in 29 of the 41 PD loci. These results indicate a key role for autophagy and lysosomal biology in PD risk, and suggest potential new drug targets for PD.

Andrew Singleton and colleagues report a large-scale meta-analysis of genome-wide association data in Parkinson's disease using over 13,000 cases and 95,000 controls plus additional samples for replication. They identify 6 new risk loci and replicate 28 independent risk variants for Parkinson's disease across 24 loci. We conducted a meta-analysis of Parkinson's disease genome-wide association studies using a common set of 7,893,274 variants across 13,708 cases and 95,282 controls. Twenty-six loci were identified as having genome-wide significant association; these and 6 additional previously reported loci were then tested in an independent set of 5,353 cases and 5,551 controls. Of the 32 tested SNPs, 24 replicated, including 6 newly identified loci. Conditional analyses within loci showed that four loci, including GBA , GAK - DGKQ , SNCA and the HLA region, contain a secondary independent risk variant. In total, we identified and replicated 28 independent risk variants for Parkinson's disease across 24 loci. Although the effect of each individual locus was small, risk profile analysis showed substantial cumulative risk in a comparison of the highest and lowest quintiles of genetic risk (odds ratio (OR) = 3.31, 95% confidence interval (CI) = 2.55–4.30; P = 2 × 10 −16 ). We also show six risk loci associated with proximal gene expression or DNA methylation.

Subthalamic deep brain stimulation (DBS) for Parkinson disease (PD) currently requires laborious open-loop programming, which can mitigate the benefits of this treatment. Experimental closed-loop DBS systems are emerging that can sense the electrophysiological surrogates of PD motor signs and respond with delivery of an automatically adapted stimulation. Such biomarker-based neural interfaces constitute a major advance towards improving the outcomes of patients treated with DBS and enhancing our understanding of the pathophysiological mechanisms underlying PD. In this Perspectives article, we argue that closed-loop DBS, in addition to offering advantages in patients with PD, might extend the current indications for DBS to include selected psychiatric disorders in which the symptoms are similarly driven by pathological brain circuit activity. The success of closed-loop DBS in such settings will depend on the identification of symptom-specific biomarkers, which ideally should reflect causal mechanisms of the underlying pathology.Here, Bouthour et al. argue that the success of closed-loop deep brain stimulation based on electrophysiological biomarkers in patients with Parkinson disease could inspire novel treatments for other neuropsychiatric disorders in which symptoms are driven by pathological activity in motor, cognitive and limbic brain networks.

In 1912, Fritz Heinrich Lewy identified the intracellular inclusions that are characteristic of Parkinson disease (PD). Here, Goedert and colleagues present an overview of Lewy's life, including the events leading up to the discovery of the inclusion bodies that now bear his name. They go on to discuss the central role of Lewy pathology in PD and other neurodegenerative disorders, and the research that has elucidated the mechanisms through which α-synuclein aggregation causes neuronal dysfunction and death. In 1817, James Parkinson described the symptoms of the shaking palsy, a disease that was subsequently defined in greater detail, and named after Parkinson, by Jean-Martin Charcot. Parkinson expected that the publication of his monograph would lead to a rapid elucidation of the anatomical substrate of the shaking palsy; in the event, this process took almost a century. In 1912, Fritz Heinrich Lewy identified the protein aggregates that define Parkinson disease (PD) in some brain regions outside the substantia nigra. In 1919, Konstantin Nikolaevich Tretiakoff found similar aggregates in the substantia nigra and named them after Lewy. In the 1990s, α-synuclein was identified as the main constituent of the Lewy pathology, and its aggregation was shown to be central to PD, dementia with Lewy bodies, and multiple system atrophy. In 2003, a staging scheme for idiopathic PD was introduced, according to which α-synuclein pathology originates in the dorsal motor nucleus of the vagal nerve and progresses from there to other brain regions, including the substantia nigra. In this article, we review the relevance of Lewy's discovery 100 years ago for the current understanding of PD and related disorders. Key Points 100 years ago, Fritz Heinrich Lewy used light microscopy to describe the nerve cell inclusions that are characteristic of Parkinson disease (PD) The Lewy pathology consists of the protein α-synuclein in an insoluble form Missense and gene dosage mutations in SNCA , the α-synuclein gene, cause inherited cases of PD and dementia with Lewy bodies In PD, α-synuclein pathology is widespread in the CNS and PNS α-Synuclein pathology originates in a small number of nerve cells, from which it spreads in a prion-like fashion Clinically, the development of the pathological changes of PD is reflected by the presence of nonmotor and motor symptoms

Parkinson’s disease (PD) is mainly managed by pharmacological therapy (e.g., Benserazide and dopamine agonists). However, prolonged use of these drugs would gradually diminish their dopaminergic effect. Gut dysbiosis was observed in some patients with PD, suggesting close association between the gut microbiome and PD. Probiotics modulate the host’s gut microbiota beneficially. A 3-month randomized, double-blind, placebo-controlled clinical trial was conducted to investigate the beneficial effect of probiotic co-administration in patients with PD. Eighty-two PD patients were recruited and randomly divided into probiotic [ n  = 48; Bifidobacterium animalis subsp. lactis Probio-M8 (Probio-M8), Benserazide, dopamine agonists] and placebo ( n  = 34; placebo, Benserazide, dopamine agonists) groups. Finally, 45 and 29 patients from Probio-M8 and placebo groups provided complete fecal and serum samples for further omics analysis, respectively. The results showed that Probio-M8 co-administration conferred added benefits by improving sleep quality, alleviating anxiety, and gastrointestinal symptoms. Metagenomic analysis showed that, after the intervention, there were significantly more species-level genome bins (SGBs) of Bifidobacterium animalis , Ruminococcaceae , and Lachnospira , while less Lactobacillus fermentum and Klebsiella oxytoca in Probio-M8 group ( P  < 0.05). Interestingly, Lactobacillus fermentum correlated positively with the scores of UPDRS-III, HAMA, HAMD-17, and negatively with MMSE. Klebsiella oxytoca correlated negatively with feces hardness. Moreover, co-administering Probio-M8 increased SGBs involved in tryptophan degradation, gamma-aminobutyric acid, short-chain fatty acids, and secondary bile acid biosynthesis, as well as serum acetic acid and dopamine levels ( P  < 0.05). Taken together, Probio-M8 synergized with the conventional regimen and strengthened the clinical efficacy in managing PD, accompanied by modifications of the host’s gut microbiome, gut microbial metabolic potential, and serum metabolites.