Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials

IntroductionThe Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued development and standardization of methodologies for biomarkers and has provided an increased depth and breadth of data available to qualified researchers. This review summarizes the over 400 publications using ADNI data during 2014 and 2015.MethodsWe used standard searches to find publications using ADNI data.Results(1) Structural and functional changes, including subtle changes to hippocampal shape and texture, atrophy in areas outside of hippocampus, and disruption to functional networks, are detectable in presymptomatic subjects before hippocampal atrophy; (2) In subjects with abnormal β-amyloid deposition (Aβ+), biomarkers become abnormal in the order predicted by the amyloid cascade hypothesis; (3) Cognitive decline is more closely linked to tau than Aβ deposition; (4) Cerebrovascular risk factors may interact with Aβ to increase white-matter (WM) abnormalities which may accelerate Alzheimer's disease (AD) progression in conjunction with tau abnormalities; (5) Different patterns of atrophy are associated with impairment of memory and executive function and may underlie psychiatric symptoms; (6) Structural, functional, and metabolic network connectivities are disrupted as AD progresses. Models of prion-like spreading of Aβ pathology along WM tracts predict known patterns of cortical Aβ deposition and declines in glucose metabolism; (7) New AD risk and protective gene loci have been identified using biologically informed approaches; (8) Cognitively normal and mild cognitive impairment (MCI) subjects are heterogeneous and include groups typified not only by “classic” AD pathology but also by normal biomarkers, accelerated decline, and suspected non-Alzheimer's pathology; (9) Selection of subjects at risk of imminent decline on the basis of one or more pathologies improves the power of clinical trials; (10) Sensitivity of cognitive outcome measures to early changes in cognition has been improved and surrogate outcome measures using longitudinal structural magnetic resonance imaging may further reduce clinical trial cost and duration; (11) Advances in machine learning techniques such as neural networks have improved diagnostic and prognostic accuracy especially in challenges involving MCI subjects; and (12) Network connectivity measures and genetic variants show promise in multimodal classification and some classifiers using single modalities are rivaling multimodal classifiers.DiscussionTaken together, these studies fundamentally deepen our understanding of AD progression and its underlying genetic basis, which in turn informs and improves clinical trial design.

مقالات اخیر از طرح ابتکاری بیماری آلزایمر: مروری بر پیشرفت در جهت بهبود تحقیقات بالینی بعد از میلاد

ابتکار عمل neuroimaging Alzheimer's Disease (ADNI)توسعه و استانداردسازی روش‌شناسی نشانگرهای زیستی را ادامه داده و عمق و گستردگی داده‌های موجود برای محققان خبره را فراهم کرده‌است. این بازبینی بیش از ۴۰۰ مقاله را با استفاده از داده‌های ADNI در طول سال ۲۰۱۴ و ۲۰۱۵.Meth منتشر می‌کند، که شامل تغییرات ظریف در شکل هیپوکامپ و بافت، آتروفی در نواحی خارج از هیپوکامپ، و اختلال در شبکه‌های کارکردی می‌شود. ((۱۰)حساسیت معیارهای پیامد شناختی در روش‌های یادگیری ماشینی و کاهش در متابولیسم گلوکز؛ (۷)حساسیت روش‌های یادگیری ماشینی و کاهش در متابولیسم گلوکز؛ (۱۱)حساسیت روش‌های یادگیری ماشینی به ویژه در طبقه‌بندی چند وجهی و برخی از بندها با استفاده از روش‌های منفرد، درک ما از پیشرفت بعد از میلاد و اساس ژنتیکی اساسی آن را عمیق‌تر می‌سازد.

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