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    • Since the publication of the

    2023-08-24

    Since the publication of the 2011 guidelines, data have continued to accumulate indicating that the cognitive decline in AD occurs continuously over a long period [6–8], and that progression of biomarker measures is also a continuous process that begins before symptoms [9–14]. Thus, the disease is now regarded as a continuum rather than three distinct clinically defined entities [15]. This concept was recognized but was not formalized in the 2011 NIA-AA guidelines [4,5]. A common theme in the 2011 recommendations was the use of imaging and cerebrospinal fluid (CSF) biomarkers. In symptomatic individuals, biomarkers were used to refine confidence that AD pathologic changes contributed to a person's cognitive impairments [2,3,5]. In the case of preclinical AD, biomarkers were used to define the construct [4]. In the 2011 recommendations, amyloid biomarkers were placed at the apex of the biomarker hierarchy preclinically [4], whereas in contrast, all AD biomarkers, including those reflecting neurodegeneration, were placed on equal footing in the MCI and dementia guidelines [2,3]. Although this discrepancy was noted at the time [5], there is now a growing consensus that application of biomarkers should be harmonized conceptually across the disease continuum and that biomarkers of neurodegeneration are not equivalent to those reflecting amyloid and pathologic tau accumulation [16]. A major motivation for updating the 2011 guidelines has been the evolution in thinking about biomarkers. Studies published since 2011 have reinforced the idea that certain imaging and CSF biomarkers are valid proxies for neuropathologic changes of AD. Imaging-to-autopsy comparison studies have established that amyloid positron emission tomography (PET) is a valid in vivo surrogate for Aβ deposits (in 4E1RCat parenchyma/vessel walls) [17–24]. It is also now widely accepted that CSF Aβ42 (or the Aβ42/Aβ40 ratio) is a valid indicator of the abnormal pathologic state associated with cerebral Aβ [25]. An additional development has been the introduction of PET ligands for pathologic tau [26–28]. By contrast, additional research has highlighted the fact that measures of neurodegeneration or neuronal injury that are commonly used in AD research—magnetic resonance imaging (MRI), fluoro-deoxyglucose (FDG) PET, and CSF total tau (T-tau)—are not specific for AD but rather are nonspecific indicators of damage that may derive from a variety of etiologies, for example, cerebrovascular injury [29].
    Guiding principles for updating NIA-AA guidelines for AD First, the overall objective was to create a scheme for defining and staging the disease across its entire spectrum. Experience with the 2011 NIA-AA recommendations has shown that a common framework for defining and staging the disease facilitates standardized reporting of research findings across the field [30–45]. Second, we determined that these recommendations should be cast as a “research framework,” not as diagnostic criteria or guidelines. Unlike the 2011 NIA-AA criteria for MCI or AD dementia based on clinical criteria (i.e., without biomarkers) [2,3], the 2018 research framework is not intended for general clinical practice. It is called a “research framework” because it needs to be thoroughly examined and modified if needed before being adopted into general clinical practice. There are two categories of studies that will achieve this ultimate goal: longitudinal cohort studies and randomized placebo controlled trials. Cohort studies, particularly community- and population-based cohorts, will examine the extent to which temporal relationships and patterns of signs, symptoms, and biomarkers expected by this framework align with what is observed. These results will support convergent and divergent validity. Trials showing that an intervention modifies both biomarkers and signs and symptoms will establish criterion validity (i.e., a disease-modifying effect). Other areas of medicine have used this approach to define pathologic processes using biomarkers, for example, bone mineral density, hypertension, hyperlipidemia, and diabetes are defined by biomarkers. Interventions modulating these biomarkers have been shown to reduce the likelihood of developing fractures and myocardial and cerebral infarctions [46,47].