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Traumatic Brain Injury (TBI) is a risk factor for Alzheimers disease and Alzheimers disease related dementias (AD/ADRD) and otherwise classified post-traumatic neurodegeneration (PTND). Targeted research is needed to elucidate the circumstances and mechanisms through which TBI contributes to the initiation, development, and progression of AD/ADRD pathologies including multiple etiology dementia (MED). The National Institutes of Health hosts triennial ADRD summits to inform a national research agenda, and TBI was included for a second time in 2022. A multidisciplinary expert panel of TBI and dementia researchers was convened to re-evaluate the 2019 research recommendations for understanding TBI as an AD/ADRD risk factor and to assess current progress and research gaps in understanding post-TBI AD/ADRD. Refined and new recommendations were presented during the MED special topic session at the virtual ADRD Summit in March 2022. Final research recommendations incorporating broad stakeholder input are organized into four priority areas as follows: (1) Promote interdisciplinary collaboration and data harmonization to accelerate progress of rigorous, clinically meaningful research; (2) Characterize clinical and biological phenotypes of PTND associated with varied lifetime TBI histories in diverse populations to validate multimodal biomarkers; (3) Establish and enrich infrastructure to support multimodal longitudinal studies of individuals with varied TBI exposure histories and standardized methods including common data elements (CDEs) for ante-mortem and post-mortem clinical and neuropathological characterization; and (4) Support basic and translational research to elucidate mechanistic pathways, development, progression, and clinical manifestations of post-TBI AD/ADRDs. Recommendations conceptualize TBI as a contributor to MED and emphasize the unique opportunity to study AD/ADRD following known exposure, to inform disease mechanisms and treatment targets for shared common AD/ADRD pathways.

ImportanceOne major advantage of developing large, federally funded networks for clinical research in neurology is the ability to have a trial-ready network that can efficiently conduct scientifically rigorous projects to improve the health of people with neurologic disorders.ObservationsNational Institute of Neurological Disorders and Stroke Network for Excellence in Neuroscience Clinical Trials (NeuroNEXT) was established in 2011 and renewed in 2018 with the goal of being an efficient network to test between 5 and 7 promising new agents in phase II clinical trials. A clinical coordinating center, data coordinating center, and 25 sites were competitively chosen. Common infrastructure was developed to accelerate timelines for clinical trials, including central institutional review board (a first for the National Institute of Neurological Disorders and Stroke), master clinical trial agreements, the use of common data elements, and experienced research sites and coordination centers. During the first 7 years, the network exceeded the goal of conducting 5 to 7 studies, with 9 funded. High interest was evident by receipt of 148 initial applications for potential studies in various neurologic disorders. Across the first 8 studies (the ninth study was funded at end of initial funding period), the central institutional review board approved the initial protocol in a mean (SD) of 59 (21) days, and additional sites were added a mean (SD) of 22 (18) days after submission. The median time from central institutional review board approval to first site activation was 47.5 days (mean, 102.1; range, 1-282) and from first site activation to first participant consent was 27 days (mean, 37.5; range, 0-96). The median time for database readiness was 3.5 months (mean, 4.0; range, 0-8) from funding receipt. In the 4 completed studies, enrollment met or exceeded expectations with 96% overall data accuracy across all sites. Nine peer-reviewed manuscripts were published, and 22 oral presentations or posters and 9 invited presentations were given at regional, national, and international meetings.Conclusions and relevanceNeuroNEXT initiated 8 studies, successfully enrolled participants at or ahead of schedule, collected high-quality data, published primary results in high-impact journals, and provided mentorship, expert statistical, and trial management support to several new investigators. Partnerships were successfully created between government, academia, industry, foundations, and patient advocacy groups. Clinical trial consortia can efficiently and successfully address a range of important neurologic research and therapeutic questions.

Chronic traumatic encephalopathy (CTE) is a neurodegeneration characterized by the abnormal accumulation of hyperphosphorylated tau protein within the brain. Like many other neurodegenerative conditions, at present, CTE can only be definitively diagnosed by post-mortem examination of brain tissue. As the first part of a series of consensus panels funded by the NINDS/NIBIB to define the neuropathological criteria for CTE, preliminary neuropathological criteria were used by 7 neuropathologists to blindly evaluate 25 cases of various tauopathies, including CTE, Alzheimer's disease, progressive supranuclear palsy, argyrophilic grain disease, corticobasal degeneration, primary age-related tauopathy, and parkinsonism dementia complex of Guam. The results demonstrated that there was good agreement among the neuropathologists who reviewed the cases (Cohen's kappa, 0.67) and even better agreement between reviewers and the diagnosis of CTE (Cohen's kappa, 0.78). Based on these results, the panel defined the pathognomonic lesion of CTE as an accumulation of abnormal hyperphosphorylated tau (p-tau) in neurons and astroglia distributed around small blood vessels at the depths of cortical sulci and in an irregular pattern. The group also defined supportive but non-specific p-tau-immunoreactive features of CTE as: pretangles and NFTs affecting superficial layers (layers II-III) of cerebral cortex; pretangles, NFTs or extracellular tangles in CA2 and pretangles and proximal dendritic swellings in CA4 of the hippocampus; neuronal and astrocytic aggregates in subcortical nuclei; thorn-shaped astrocytes at the glial limitans of the subpial and periventricular regions; and large grain-like and dot-like structures. Supportive non-p-tau pathologies include TDP-43 immunoreactive neuronal cytoplasmic inclusions and dot-like structures in the hippocampus, anteromedial temporal cortex and amygdala. The panel also recommended a minimum blocking and staining scheme for pathological evaluation and made recommendations for future study. This study provides the first step towards the development of validated neuropathological criteria for CTE and will pave the way towards future clinical and mechanistic studies.

Recent contributions to the body of knowledge on traumatic brain injury (TBI) favor the view that multimodal neuroimaging using structural and functional magnetic resonance imaging (MRI and fMRI, respectively) as well as diffusion tensor imaging (DTI) has excellent potential to identify novel biomarkers and predictors of TBI outcome. This is particularly the case when such methods are appropriately combined with volumetric/morphometric analysis of brain structures and with the exploration of TBI-related changes in brain network properties at the level of the connectome. In this context, our present review summarizes recent developments on the roles of these two techniques in the search for novel structural neuroimaging biomarkers that have TBI outcome prognostication value. The themes being explored cover notable trends in this area of research, including (1) the role of advanced MRI processing methods in the analysis of structural pathology, (2) the use of brain connectomics and network analysis to identify outcome biomarkers, and (3) the application of multivariate statistics to predict outcome using neuroimaging metrics. The goal of the review is to draw the community's attention to these recent advances on TBI outcome prediction methods and to encourage the development of new methodologies whereby structural neuroimaging can be used to identify biomarkers of TBI outcome.