Alzheimer's disease heterogeneity revealed by neuroanatomical normative modeling.

INTRODUCTION: Overlooking the heterogeneity in Alzheimer's disease (AD) may lead to diagnostic delays and failures. Neuroanatomical normative modeling captures individual brain variation and may inform our understanding of individual differences in AD-related atrophy. METHODS: We applied neuroanatomical normative modeling to magnetic resonance imaging from a real-world clinical cohort with confirmed AD (n = 86). Regional cortical thickness was compared to a healthy reference cohort (n = 33,072) and the number of outlying regions was summed (total outlier count) and mapped at individual- and group-levels. RESULTS: The superior temporal sulcus contained the highest proportion of outliers (60%). Elsewhere, overlap between patient atrophy patterns was low. Mean total outlier count was higher in patients who were non-amnestic, at more advanced disease stages, and without depressive symptoms. Amyloid burden was negatively associated with outlier count. DISCUSSION: Brain atrophy in AD is highly heterogeneous and neuroanatomical normative modeling can be used to explore anatomo-clinical correlations in individual patients.

Visual atrophy rating scales and amyloid PET status in an Alzheimer's disease clinical cohort.

OBJECTIVES: Visual rating scales (VRS) are the quantification method closest to the approach used in routine clinical practice to assess brain atrophy. Previous studies have suggested that the medial temporal atrophy (MTA) rating scale is a reliable diagnostic marker for AD, equivalent to volumetric quantification, while others propose a higher diagnostic utility for the Posterior Atrophy (PA) scale in early-onset AD. METHODS: Here, we reviewed 14 studies that assessed the diagnostic accuracy of PA and MTA, we explored the issue of cut-off heterogeneity, and assessed 9 rating scales in a group of patients with biomarker-confirmed diagnosis. A neuroradiologist blinded to all clinical information rated the MR images of 39 amyloid-positive and 38 amyloid-negative patients using 9 validated VRS assessing multiple brain regions. Automated volumetric analyses were performed on a subset of patients (n = 48) and on a group of cognitively normal individuals (n = 28). RESULTS: No single VRS could differentiate amyloid-positive from amyloid-negative patients with other neurodegenerative conditions. 44% of amyloid-positive patients were deemed to have age-appropriate levels of MTA. In the amyloid-positive group, 18% had no abnormal MTA or PA scores. These findings were substantially affected by cut-off selection. Amyloid-positive and amyloid-negative patients had comparable hippocampal and parietal volumes, and MTA but not PA scores correlated with the respective volumetric measures. INTERPRETATION: Consensus guidelines are needed before VRS can be recommended for use in the diagnostic workup of AD. Our data are suggestive of high intragroup variability and non-superiority of volumetric quantification of atrophy over visual assessment.

Gender representation in science publication: evidence from Brain Communications.

The persistent underrepresentation of women in Science, Technology, Engineering, Mathematics and Medicine (STEMM) points to the need to continue promoting the awareness and understanding of this phenomenon. Being one of the main outputs of scientific work, academic publications provide the opportunity to quantify the gender gap in science as well as to identify possible sources of bias and areas of improvement. Brain Communications is a 'young' journal founded in 2019, committed to transparent publication of rigorous work in neuroscience, neurology and psychiatry. For all manuscripts (n = 796) received by the journal between 2019 and 2021, we analysed the gender of all authors (n = 7721) and reviewers (n = 4492). Overall, women were 35.3% of all authors and 31.3% of invited reviewers. A considerably higher proportion of women was found in first authorship (42.4%) than in last authorship positions (24.9%). The representation of women authors and reviewers decreased further in the months following COVID-19 restrictions, suggesting a possible exacerbating role of the pandemic on existing disparities in science publication. The proportion of manuscripts accepted for publication was not significantly different according to the gender of the first, middle or last authors, meaning we found no evidence of gender bias within the review or editorial decision-making processes at Brain Communications.

A predictive model using the mesoscopic architecture of the living brain to detect Alzheimer's disease.

Background: Alzheimer's disease, the most common cause of dementia, causes a progressive and irreversible deterioration of cognition that can sometimes be difficult to diagnose, leading to suboptimal patient care. Methods: We developed a predictive model that computes multi-regional statistical morpho-functional mesoscopic traits from T1-weighted MRI scans, with or without cognitive scores. For each patient, a biomarker called "Alzheimer's Predictive Vector" (ApV) was derived using a two-stage least absolute shrinkage and selection operator (LASSO). Results: The ApV reliably discriminates between people with (ADrp) and without (nADrp) Alzheimer's related pathologies (98% and 81% accuracy between ADrp - including the early form, mild cognitive impairment - and nADrp in internal and external hold-out test sets, respectively), without any a priori assumptions or need for neuroradiology reads. The new test is superior to standard hippocampal atrophy (26% accuracy) and cerebrospinal fluid beta amyloid measure (62% accuracy). A multiparametric analysis compared DTI-MRI derived fractional anisotropy, whose readout of neuronal loss agrees with ADrp phenotype, and SNPrs2075650 is significantly altered in patients with ADrp-like phenotype. Conclusions: This new data analytic method demonstrates potential for increasing accuracy of Alzheimer diagnosis.

Alzheimer's disease is the most common cause of dementia, impacting memory, thinking and behaviour. It can be challenging to diagnose Alzheimer's disease which can lead to suboptimal patient care. During the development of Alzheimer's disease the brain shrinks and the cells within it die. One method that can be used to assess brain function is magnetic resonance imaging, which uses magnetic fields and radio waves to produce images of the brain. In this study, we develop a method that uses magnetic resonance imaging data to identify differences in the brain between people with and without Alzheimer's disease, including before obvious shrinkage of the brain occurs. This method could be used to help diagnose patients with Alzheimer's Disease.

Prevalence of Depressive Symptoms in a Memory Clinic Cohort: A Retrospective Study.

BACKGROUND: Depression has been suggested to be a cause of reversible cognitive impairment but also a risk factor for neurodegenerative disease. Studies suggest that depression prevalence may be high in early onset dementia, particularly Alzheimer's disease, but this has not been systematically assessed in a biomarker-validated clinical dementia cohort to date. OBJECTIVE: To examine the prevalence, features, and association with amyloid pathology of lifetime depressive symptoms in a memory clinic cohort meeting appropriate use criteria for amyloid PET imaging. METHODS: We included 300 patients from a single-center memory clinic cohort that received diagnostic biomarker evaluation with amyloid PET imaging according to appropriate use criteria. History of lifetime depressive symptoms was retrospectively assessed through structured review of clinical correspondence. RESULTS: One hundred forty-two (47%) patients had a history of significant depressive symptoms ('D+'). Of these, 89% had ongoing symptoms and 60% were on antidepressants at the time of presentation to our Clinic. Depressive symptoms were equally highly prevalent in the amyloid-positive and the heterogeneous group of amyloid-negative patients. CONCLUSION: Approximately half of patients who meet appropriate use criteria for amyloid PET have a history of depressive symptoms. We suggest that depression is an important feature of both neurodegenerative and non-neurodegenerative cognitive impairment and may contribute to the diagnostic uncertainty behind referral to amyloid PET.

Evaluating cognitive profiles of patients undergoing clinical amyloid-PET imaging.

Episodic memory impairment and brain amyloid-beta are two of the main hallmarks of Alzheimer's Disease. In the clinical setting, these are often evaluated through neuropsychological testing and amyloid PET imaging, respectively. The use of amyloid PET in clinical practice is only indicated in patients with substantial diagnostic uncertainty due to atypical clinical presentation, multiple comorbidities and/or early age of onset. The relationship between amyloid-beta and cognition has been previously investigated, but no study has examined how neuropsychological features relate to the presence of amyloid pathology in the clinical population that meets the appropriate use criteria for amyloid PET imaging. In this study, we evaluated a clinical cohort of patients (n = 107) who presented at the Imperial Memory Clinic and were referred for clinical amyloid PET and neuropsychological assessment as part of their diagnostic workup. We compared the cognitive performance of amyloid-positive patients (Aß-pos, n = 47) with that of stable amyloid-negative (stableAß-neg, n = 26) and progressive amyloid-negative (progAß-neg, n = 34) patients. The amyloid-positive group performed significantly worse than both amyloid-negative groups in the visuospatial and working memory domains. Episodic memory performance, however, effectively differentiated the amyloid-positive group from the stable but not the progressive amyloid-negative group. On affective questionnaires, the stable amyloid-negative group reported significantly higher levels of depression than the amyloid-positive group. In our clinical cohort, visuospatial dysfunction and working memory impairment were better indicators of amyloid positivity than episodic memory dysfunction. These findings highlight the limited value of isolated cognitive scores in patients with atypical clinical presentation, comorbidities and/or early age of onset.

Amyloid PET imaging in clinical practice.

Amyloid positron emission tomography (PET) imaging enables in vivo detection of brain Aß deposition, one of the neuropathological hallmarks of Alzheimer's disease. There is increasing evidence to support its clinical utility, with major studies showing that amyloid PET imaging improves diagnostic accuracy, increases diagnostic certainty and results in therapeutic changes. The Amyloid Imaging Taskforce has developed appropriate use criteria to guide clinicians by predefining certain scenarios where amyloid PET would be justified. This review provides a practical guide on how and when to use amyloid PET, based on the available research and our own experience. We discuss its three main appropriate indications and illustrate these with clinical cases. We stress the importance of a multidisciplinary approach when deciding who might benefit from amyloid PET imaging. Finally, we highlight some practical points and common pitfalls in its interpretation.