Nordberg, Agneta

Importance Amyloid positron emission tomography (PET) is increasingly used in research and clinical settings to determine the etiology of cognitive decline and eligibility for amyloid-targeting therapies. To assist with amyloid PET evaluation and to guide clinical decision-making, images can be quantified in a standardized unit called Centiloid, the interpretation of which can vary according to the method and threshold used. Objective To collect Centiloid values from available studies and determine robust positivity cutoffs using data-driven methods and correspondence with visual reads. Data Sources PubMed search (October 2024) identified studies with Centiloid values. Corresponding authors were invited to share individual participant data. Additional data were obtained through access-controlled repositories and conference outreach (July 2024-July 2025). Study Selection Studies were included if they provided Centiloids, radiotracer, age, and sex. Data Extraction and Synthesis Each study was analyzed using a unified statistical pipeline; study estimates were pooled using random-effects meta-analysis. Main Outcomes and Measures Gaussian mixture models (GMMs) were fitted to Centiloid values for each study. In studies with a bimodal distribution (per integrated completed likelihood), single cutoffs for positivity were set as mean plus 2 SDs of the lower gaussian component. Using GMMs, a double-cutoff approach defined a lower certainty range using a 90% posterior probability cutoff for assignment to the low (amyloid-negative) vs high (amyloid-positive) component. An alternative Centiloid cutoff was derived from maximizing the correspondence (Cohen κ) with the binary visual reads when available. Results This meta-analysis included cross-sectional amyloid PET scans acquired with 5 radiotracers from 49 227 participants across 53 studies from 15 countries (mean age, 71 years; 54% female, 62% cognitively impaired). The data-driven GMM approach identified a bimodal distribution in 51 studies (n = 48 786), resulting in a single cutoff for positivity of 18 Centiloids (95% CI,16-19; I 2 = 97%). The double-cutoff approach revealed high confidence for interpreting scans as negative when Centiloid values were lower than 11 (95% CI, 9-13; I 2 = 95%) and interpreting scans as positive if Centiloid values were higher than 26 (95% CI, 24-28; I 2 = 95%). In analyses of correspondence with binary (positive or negative) visual reads of amyloid PET scans (n = 35 045; 36 studies), Centiloids were highly predictive of visual positivity (Cohen κ, 0.86; 95% CI, 0.83-0.89; I 2 = 96%) with a cutoff of 27 Centiloids (95% CI, 24-30; I 2 = 80%). Conclusions and Relevance In this individual participant data meta-analysis, positivity cutoffs converged around 18 Centiloids (data-driven) and 27 Centiloids (visual reads). Findings from a double-cutoff analysis suggest that scans in the 11 to 26 Centiloid range should be interpreted with caution depending on the context of use.

Abstract Alzheimer's disease (AD) is neuropathologically defined by amyloid‐beta (Aβ) plaques and tau neurofibrillary tangles. However, co‐pathologies and other pathobiological processes are involved in the pathogenesis of AD, contributing to neurodegeneration and clinical symptoms. The most common co‐pathologies in people with AD are alpha‐synucleinopathy, vascular brain injury and transactive response DNA‐binding protein of 43 kDa‐related pathology. Neuroinflammation, iron accumulation, cholinergic dysfunction and cellular senescence are recognized pathobiological processes beyond Aβ‐ and tau‐related pathology. However, the exact mechanisms by which these co‐pathologies and pathobiological processes contribute to the neurodegeneration and clinical symptoms in people with AD remain unclear. The individual combination of these co‐pathologies and pathobiological processes increases phenotypical heterogeneity in people with AD. This highlights the unmet need to advance their current understanding, and the field strives to develop accurate biomarkers for personalized assessment and investigation. Elucidating this biologic‐clinical complexity and heterogeneity is crucial for increasing our current understanding of AD, with implications for diagnosis, prognosis and therapeutics.

Importance Since 2018, a movement has emerged to define Alzheimer disease (AD) as a purely biological entity based on biomarker findings. The recent revision of the Alzheimer’s Association (AA) criteria for AD furthers this direction. However, concerns about a purely biological definition of AD being applied clinically, the understanding of AD by society at large, and the translation of blood-based biomarkers into clinical practice prompt these International Working Group (IWG) updated recommendations. Objective To consider the revised AA criteria and to offer an alternative definitional view of AD as a clinical-biological construct for clinical use. The recommendations of the 2021 IWG diagnostic criteria are updated for further elaborating at-risk and presymptomatic states. Evidence Review PubMed was searched for articles published between July 1, 2020, and March 1, 2024, using the terms “biomarker” OR “amyloid” OR “tau” OR “neurodegeneration” OR “preclinical” OR “CSF” OR “PET” OR “plasma” AND “Alzheimer’s disease.” The references of relevant articles were also searched. Findings In the new AA diagnostic criteria, AD can be defined clinically as encompassing cognitively normal people having a core 1 AD biomarker. However, recent literature shows that the majority of biomarker-positive cognitively normal individuals will not become symptomatic along a proximate timeline. In the clinical setting, disclosing a diagnosis of AD to cognitively normal people with only core 1 AD biomarkers represents the most problematic implication of a purely biological definition of the disease. Conclusions and Relevance The ultimate aim of the field was to foster effective AD treatments, including preventing symptoms and dementia. The approach of diagnosing AD without a clinical and biological construct would be unwarranted and potentially concerning without a clear knowledge of when or whether symptoms will ever develop. It is recommended that those who are amyloid-positive only and, more generally, most biomarker-positive cognitively normal individuals, should not be labeled as having AD. Rather, they should be considered as being at risk for AD. The expansion of presymptomatic AD is viewed as a better diagnostic construct for those with a specific pattern of biomarkers, indicating that they are proximate to the expression of symptoms in the near future.

AbstractBackgroundThe field of biological subtypes of Alzheimer’s disease (AD) has recently gained attention as a strong driver of precision medicine and future clinical trials. Neuropathology and neuroimaging studies have consistently identified four subtypes: hippocampal sparing AD, typical AD, limbic predominant AD, and minimal atrophy or minimal tau NFT AD. An important and still unresolved question is whether a truly hippocampal sparing subtype of AD can really exist, since it would challenge the widely accepted model of NFT spread. To address this question, we conducted a systematic review of the literature and performed original analyses on tau PET data.MethodOur systematic review included a search on EMBASE, PubMed, and Web of Science databases up to October 2020. Original analyses included implementation of several methods for AD subtyping on tau PET, and utilization of five complementary cut points to identify hippocampal sparing AD cases both in published studies and in data from the Alzheimer's Disease Neuroimaging Initiative (ADNI).ResultIn the three reviewed neuropathologic studies, we did not find any individual case with tau NFT in the association cortex while completely sparing the hippocampus (i.e., truly hippocampal sparing cases). In the in vivo tau PET studies, more lenient cut points consistently identified AD patients with tau NFT in the association cortex while completely sparing the hippocampus.ConclusionOur current data suggests that the hippocampal sparing subtype of AD does exist ante‐mortem, at earlier stages of the disease, but more research is needed to understand its pathogenesis and progression during life. Based on the findings from both in vivo tau PET and neuropathologic studies, we suggest that there are two possible independent pathways of tau spread: (1) a canonical pathway with early involvement of entorhinal cortex with subsequent involvement of limbic regions before eventually affecting multimodal association cortices, and (2) a less common pathway that affects multimodal association cortices with limbic involvement observed at end stages of the disease. As emphasized in the Murray 2011 study, hippocampal sparing relative to greater cortical involvement defines the phenotype.