Phase I trial data presented at MSToronto2026 indicate that the chimeric antigen receptor (CAR) T cell therapy azercabtagene zapreleucel (azer-cel) is safe and has the potential to improve outcomes in people with progressive multiple sclerosis.
New WHO guidelines on risk reduction for cognitive decline and dementia call for a proactive, life-course approach. Clinicians have a key role in identifying and managing modifiable risk factors, and tailored multidomain interventions and population-based strategies are needed to make the promotion of cognitive health equitable and scalable.
Neuroimmunology is a rapidly expanding field in which many breakthroughs have been fuelled by studies in animal models that capture aspects of human neurological disease. However, the variety of animal models available, with their relative merits and drawbacks, is not well documented in the literature, posing a hurdle for scientists who are venturing into the world of neuroimmunology. Moreover, nuances between animal models, their utility for studying neuroimmunological processes and the variables that affect their associated clinical and pathological outcomes can affect the reproducibility and clinical relevance of findings at the preclinical stage. In this Review, the International Society of Neuroimmunology White Paper Task Force describes animal models that can be used to study neuroimmunological aspects of neurological disease and the intrinsic and extrinsic factors that affect readouts from these models. We provide guidance on how to manipulate these factors to gain insight into neuroimmunology and to control them for improved reproducibility. We also consider the advantages and limitations of available tools, including robust genetic systems, neuroimmunological imaging, functional readouts and omics-based cell profiling. Finally, we discuss how animal models have advanced drug development to treat neuroimmunological diseases and how the same principles can provide insight into a variety of neurological disorders. We aim to provide guidance on how to optimize the use of animal models to gain insight into neuroimmunological mechanisms and support the preclinical drug discovery pipeline. Neuroimmunology breakthroughs have been fuelled by studies in animal models. In this Review, the International Society of Neuroimmunology White Paper Task Force describes animal models that can be used to study neuroimmunological aspects of neurological disease and provide guidance on how to optimize use of animal models to gain insight into neuroimmunological mechanisms.
Mitochondrial dysfunction is increasingly recognized as a shared downstream pathogenic mechanism across a wide spectrum of neurological disorders, ranging from primary mitochondrial diseases to conditions including amyotrophic lateral sclerosis, Alzheimer disease, Parkinson disease, multiple sclerosis, hereditary ataxias and idiopathic inflammatory myopathies. This Review examines the role of mitochondrial biomarkers in improving diagnostic accuracy, patient stratification and monitoring of disease progression and therapeutic response. Primary mitochondrial diseases are presented as proof-of-concept models of impaired oxidative phosphorylation, providing a framework for biomarker identification and validation with translational relevance to other neurological diseases. Mitochondrial biomarkers can be broadly categorized into four domains: fluid biomarkers, reflecting metabolic alterations and stress signalling; genetic biomarkers, capturing mitochondrial DNA integrity and dynamics; multi-omics approaches, integrating transcriptomic, proteomic and metabolomic signatures; and imaging biomarkers, enabling in vivo assessment of structural and functional consequences of mitochondrial dysfunction. Across disorders, these biomarkers reveal shared disturbances in bioenergetics, redox homeostasis, mitochondrial genome maintenance and inflammatory signalling. However, clinical implementation remains limited by methodological heterogeneity, biological variability and reduced disease specificity. Integrated, multimodal biomarker strategies, combined with longitudinal validation, will be essential for supporting precision medicine and guiding the development of therapies to target mitochondrial pathways in neurology. Mitochondrial dysfunction is increasingly recognized as a convergent downstream pathogenic process across many neurological disorders. This Review evaluates how mitochondrial biomarkers can enhance diagnostic accuracy, support patient stratification and enable monitoring of disease progression and therapeutic response.
Population-based cohorts that combine genetic data with whole-body multimodal imaging are transforming how we map the genetic architecture of the brain in its broader bodily context. Historically, imaging genetics has focused largely on single organs, especially the brain, with separate efforts targeting the heart, skeleton and other organs for systemic diseases, and limited integration across organ systems. Yet, strong brain–body interactions and the high multimorbidity of brain and systemic diseases highlight the need for a brain-centred multi-organ perspective. Here we introduce the emerging field of brain-focused multi-organ imaging genetics, outlining key data resources and interdisciplinary analytical frameworks for large-scale multi-organ genetic discovery and reviewing the genetic associations between brain diseases and imaging phenotypes across organ systems. We discuss how these advances support a whole-body integrated view of brain health and disease and how they are beginning to reshape clinical translation for neurological conditions. We outline a roadmap for agentic artificial intelligence co-scientists that work alongside human researchers throughout the scientific discovery process, arguing that such systems will be essential for achieving an integrated understanding of brain health and disease, both as tools for individual researchers and as a collaborative infrastructure for the whole field. This article provides an overview of brain-focused multi-organ imaging genetics, outlining key data resources and analytical frameworks and reviewing cross-organ genetic insights into brain diseases. The authors propose a roadmap for implementing agentic AI co-scientists as essential infrastructure for advancing an integrated, whole-body understanding of brain health and disease.
