Imaging plus X: multimodal models of neurodegenerative disease

PURPOSE OF REVIEW: This article argues that the time is approaching for data-driven disease modelling to take centre stage in the study and management of neurodegenerative disease. The snowstorm of data now available to the clinician defies qualitative evaluation; the heterogeneity of data types complicates integration through traditional statistical methods; and the large datasets becoming available remain far from the big-data sizes necessary for fully data-driven machine-learning approaches. The recent emergence of data-driven disease progression models provides a balance between imposed knowledge of disease features and patterns learned from data. The resulting models are both predictive of disease progression in individual patients and informative in terms of revealing underlying biological patterns. RECENT FINDINGS: Largely inspired by observational models, data-driven disease progression models have emerged in the last few years as a feasible means for understanding the development of neurodegenerative diseases. These models have revealed insights into frontotemporal dementia, Huntington's disease, multiple sclerosis, Parkinson's disease and other conditions. For example, event-based models have revealed finer graded understanding of progression patterns; self-modelling regression and differential equation models have provided data-driven biomarker trajectories; spatiotemporal models have shown that brain shape changes, for example of the hippocampus, can occur before detectable neurodegeneration; and network models have provided some support for prion-like mechanistic hypotheses of disease propagation. The most mature results are in sporadic Alzheimer's disease, in large part because of the availability of the Alzheimer's disease neuroimaging initiative dataset. Results generally support the prevailing amyloid-led hypothetical model of Alzheimer's disease, while revealing finer detail and insight into disease progression. SUMMARY: The emerging field of disease progression modelling provides a natural mechanism to integrate different kinds of information, for example from imaging, serum and cerebrospinal fluid markers and cognitive tests, to obtain new insights into progressive diseases. Such insights include fine-grained longitudinal patterns of neurodegeneration, from early stages, and the heterogeneity of these trajectories over the population. More pragmatically, such models enable finer precision in patient staging and stratification, prediction of progression rates and earlier and better identification of at-risk individuals. We argue that this will make disease progression modelling invaluable for recruitment and end-points in future clinical trials, potentially ameliorating the high failure rate in trials of, e.g., Alzheimer's disease therapies. We review the state of the art in these techniques and discuss the future steps required to translate the ideas to front-line application.This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0

Data-Driven Sequence of Changes to Anatomical Brain Connectivity in Sporadic Alzheimer's Disease

Model-based investigations of transneuronal spreading mechanisms in neurodegenerative diseases relate the pattern of pathology severity to the brain’s connectivity matrix, which reveals information about how pathology propagates through the connectivity network. Such network models typically use networks based on functional or structural connectivity in young and healthy individuals, and only end-stage patterns of pathology, thereby ignoring/excluding the effects of normal aging and disease progression. Here, we examine the sequence of changes in the elderly brain’s anatomical connectivity over the course of a neurodegenerative disease. We do this in a data-driven manner that is not dependent upon clinical disease stage, by using event-based disease progression modeling. Using data from the Alzheimer’s Disease Neuroimaging Initiative dataset, we sequence the progressive decline of anatomical connectivity, as quantified by graph-theory metrics, in the Alzheimer’s disease brain. Ours is the first single model to contribute to understanding all three of the nature, the location, and the sequence of changes to anatomical connectivity in the human brain due to Alzheimer’s disease. Our experimental results reveal new insights into Alzheimer’s disease: that degeneration of anatomical connectivity in the brain may be a viable, even early, biomarker and should be considered when studying such neurodegenerative diseases

Role of pathogenic proteins and chronic inflammation in the occurrence of Аlzheimer's disease

Хвороба Альцгеймера – найпоширеніша форма деменції, якою страждає до 70 % від всіх хворих на деменцію. Наразі актуальність цього нейродегенеративного захворювання зросла через його поширеність та відсутність етіологічного і ефективного лікування. Наслідком цього є зростання кількості досліджень і наукових праць націлених на вивчення цієї хвороби. Метою роботи було провести аналіз та систематизувати дані щодо поширення, соціально-економічного значення, теорій виникнення, а також ролі патогенних білків в розвитку хвороби Альцгеймера. Автори провели пошук інформації в електронних базах даних, таких як PubMed та Google Scholar, з науковими працями і статтями останніх 25 років за такими ключовими термінами, як хвороба Альцгеймера, β-амілоїд, тау-пептид, метали, запалення, білки S100. У світі нараховують більше 56 мільйонів людей з хворобою Альцгеймера, її має кожен 10 житель США старше 65 років, причому з віком ризик збільшується. Серед причин смерті хвороба Альцгеймера займає шосту позицію, а витрати на хвору людину з таким діагнозом втричі перевищують за звичайні в тій же віковій групі. Саме тому це питання має значне соціально-економічне значення. Протягом останніх десятиліть було висунуто багато гіпотез виникнення хвороби. Довгий час ключовими вважалися теорія агрегації β-амілоїду та теорія білка тау, але згодом пріоритети почали змінюватися. Було виявлено що наявність патогенних мікроорганізмів може становити ризик для виникнення хвороби Альцгеймера. Також деякі дослідження вказують на роль ацетилхоліну в розвитку хвороби, однак, дані клінічних випробувань це не підтвердили. Має місце порушення гомеостазу металів, що сприяє когнітивному дефіциту та розвитку нейродегенерації. Мікроглія, астроцити і нейрони беруть участь у запальному процесі при хворобі Альцгеймера. Наявне зачароване коло, коли Aβ спричиняє судинну недостатність, що в свою чергу призводить до збільшення накопичення Aβ. Є дані про пряму залежність між оксидативним стресом та дисфункцією нейронів. Безсумнівно в розвитку хвороби Альцгеймера провідну роль відіграють патогенні білки, в тому числі Aβ-пептид, тау-пептид та білки родини S100. Незважаючи на численні дослідження, визначення причинної чи наслідкової ролі різноманітних патологічних чинників та змін при хворобі Альцгеймера є досі неоднозначними і неостаточними. Все це дає підстави для подальшого наукового пошуку в цьому напрямку.Alzheimer's disease is the most common form of dementia affecting up to 70% of all patients with dementia. Currently, the relevance of this neurodegenerative disease has increased due to its prevalence and lack of etiological and effective treatment. The consequence of this is an increase in the number of studies and scientific works aimed at studying this disease. The aim of the study was to analyze and systematize data on the prevalence, socioeconomic significance, theories of origin, as well as the role of pathogenic proteins in the development of Alzheimer's disease. The authors searched for information in electronic databases such as PubMed and Google Scholar, with scientific papers and articles from the last 25 years on such key terms as Alzheimer's disease, β-amyloid, tau-peptide, metals, inflammation, S100 proteins. There are more than 56 million people with Alzheimer's disease in the world and the risk increases with age. Among the causes of death, Alzheimer's disease ranks sixth, and the costs of care about person with this diagnosis are three times higher than for other diseases in the same age group. That is why this issue has significant socio-economic significance. Many hypotheses have emerged in recent decades. For a long time, the theory of β-amyloid aggregation and the theory of tau protein were considered main, but later the priorities began to change. It has been found that the presence of pathogenic microorganisms can pose a risk for Alzheimer's disease. Also, some studies indicate the role of acetylcholine in the development of the disease, however, clinical trials have not confirmed this. There is a violation of metal homeostasis, which contributes to cognitive deficits and the development of neurodegeneration. Microglia, astrocytes and neurons are involved in the inflammatory process in Alzheimer's disease. There is a vicious circle when Aβ causes vascular insufficiency, which in turn leads to an increase in Aβ accumulation. Also there is evidence of a direct relationship between oxidative stress and neuronal dysfunction. Undoubtedly, pathogenic proteins, including Aβ-peptide, tau-peptide and proteins of the S100 family, play a leading role in the development of Alzheimer's disease. Despite numerous studies, the causal or consequential role of various pathological factors and changes in Alzheimer's disease is still ambiguous and inconsistent. All this gives grounds for further scientific research in this direction

Development of a Multicomponent Intervention to Prevent Alzheimer's Disease

Recent advances in vascular risk management have successfully reduced the prevalence of Alzheimer's Disease (AD) in several epidemiologic investigations. It is now widely accepted that cerebrovascular disease is both directly and indirectly involved in AD pathogenesis. Herein, we review the non-pharmacological and pharmacological therapeutic approaches for AD treatment. MIND [Mediterranean and DASH (Dietary Approaches to Stop Hypertension) Intervention for Neurodegenerative Delay] diet is an important dietary treatment for prevention of AD. Multi domain intervention including diet, exercise, cognitive training, and intensive risk managements also prevented cognitive decline in the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) study. To confirm these favorable effects of life-style intervention, replica studies are being planned worldwide. Promotion of β-amyloid (Aβ) clearance has emerged as a promising pharmacological approach because insufficient removal of Aβ is more important than excessive Aβ production in the pathogenesis of the majority of AD patients. Most AD brains exhibit accompanying cerebral amyloid angiopathy, and Aβ distribution in cerebral amyloid angiopathy closely corresponds with the intramural periarterial drainage (IPAD) route, emphasizing the importance of Aβ clearance. In view of these facts, promotion of the major vascular-mediated Aβ elimination systems, including capillary transcytosis, the glymphatic system, and IPAD, have emerged as new treatment strategies in AD. In particular, the beneficial effects of cilostazol were shown in several clinical observation studies, and cilostazol facilitated IPAD in a rodent AD model. The COMCID (Cilostazol for prevention of Conversion from MCI to Dementia) trial, evaluating the efficacy of cilostazol for patients with mild cognitive impairment is currently ongoing in Japan. Such therapeutic approaches involving maintenance of cerebrovascular integrity and promotion of vascular-mediated Aβ clearance have the potential to be mainstream treatments for sporadic AD

Communicability distance reveals hidden patterns of alzheimer’s disease

The communicability distance between pairs of regions in human brain is used as a quantitative proxy for studying Alzheimer’s disease. Using this distance, we obtain the shortest communicability path lengths between different regions of brain networks from patients with Alzheimer’s disease (AD) and healthy cohorts (HC). We show that the shortest communicability path length is significantly better than the shortest topological path length in distinguishing AD patients from HC. Based on this approach, we identify 399 pairs of brain regions for which there are very significant changes in the shortest communicability path length after AD appears. We find that 42% of these regions interconnect both brain hemispheres, 28% connect regions inside the left hemisphere only, and 20% affect vermis connection with brain hemispheres. These findings clearly agree with the disconnection syndrome hypothesis of AD. Finally, we show that in 76.9% of damaged brain regions the shortest communicability path length drops in AD in relation to HC. This counterintuitive finding indicates that AD transforms the brain network into a more efficient system from the perspective of the transmission of the disease, because it drops the circulability of the disease factor around the brain regions in relation to its transmissibility to other regions

Early role of vascular dysregulation on late-onset Alzheimer's disease based on multifactorial data-driven analysis

Multifactorial mechanisms underlying late-onset Alzheimer’s disease (LOAD) are poorly characterized from an integrative perspective. Here spatiotemporal alterations in brain amyloid-β deposition, metabolism, vascular, functional activity at rest, structural properties, cognitive integrity and peripheral proteins levels are characterized in relation to LOAD progression. We analyse over 7,700 brain images and tens of plasma and cerebrospinal fluid biomarkers from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Through a multifactorial data-driven analysis, we obtain dynamic LOAD–abnormality indices for all biomarkers, and a tentative temporal ordering of disease progression. Imaging results suggest that intra-brain vascular dysregulation is an early pathological event during disease development. Cognitive decline is noticeable from initial LOAD stages, suggesting early memory deficit associated with the primary disease factors. High abnormality levels are also observed for specific proteins associated with the vascular system’s integrity. Although still subjected to the sensitivity of the algorithms and biomarkers employed, our results might contribute to the development of preventive therapeutic interventions