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Background and purposeThe aging HIV-infected (HIV+) population has increased vascular comorbidities, including stroke, and increased cognitive deficits compared with the general population. Arterial spin-labeling is a technique to measure cerebral blood flow and is more sensitive than regional volume loss in assessing neurodegenerative diseases and cognitive aging. Previous studies have found global cerebral perfusion abnormalities in the HIV+ participants. In this study, we evaluated the specific regional pattern of CBF abnormalities in older HIV+ participants using quantitative whole-brain arterial spin-labeling.Materials and methodsCBF data from the UCSF HIV Over 60 Cohort and the Alzheimer Disease Neuroimaging Initiative were retrospectively evaluated to identify 19 HIV+ older adults, all with plasma viral suppression (including 5 with HIV-associated neurocognitive disorder); 13 healthy, age-matched controls; and 19 participants with early mild cognitive impairment. CBF values were averaged by ROI and compared among the 3 groups using generalized linear models.ResultsWhen we accounted for age, education, sex, and vascular risk factors, the HIV+ participants demonstrated alterations in regional cerebral perfusion, including hypoperfusion of bilateral temporal, parietal, and occipital brain regions compared with both clinically healthy participants and those with mild cognitive impairment. Arterial spin-labeling showed reasonable test characteristics in distinguishing those with HIV-associated neurocognitive disorder from healthy controls and participants with mild cognitive impairment.ConclusionsThis study found specific CBF patterns associated with HIV status despite viral suppression-data that should animate further investigations into the pathobiologic basis of vascular and cognitive abnormalities in HIV-associated neurocognitive disorders.

β-amyloid (Aβ) plaque accumulation is a hallmark of Alzheimer's disease (AD). It is believed to start many years prior to symptoms and is reflected by reduced cerebrospinal fluid (CSF) levels of the peptide Aβ1-42 (Aβ42). Here we tested the hypothesis that baseline levels of CSF proteins involved in microglia activity, synaptic function and Aβ metabolism predict the development of Aβ plaques, assessed by longitudinal CSF Aβ42 decrease in cognitively healthy people. Forty-six healthy people with three to four serial CSF samples were included (mean follow-up 3 years, range 2-4 years). There was an overall reduction in Aβ42 from a mean concentration of 211-195 pg ml(-1) after 4 years. Linear mixed-effects models using longitudinal Aβ42 as the response variable, and baseline proteins as explanatory variables (n=69 proteins potentially relevant for Aβ metabolism, microglia or synaptic/neuronal function), identified 10 proteins with significant effects on longitudinal Aβ42. The most significant proteins were angiotensin-converting enzyme (ACE, P=0.009), Chromogranin A (CgA, P=0.009) and Axl receptor tyrosine kinase (AXL, P=0.009). Receiver-operating characteristic analysis identified 11 proteins with significant effects on longitudinal Aβ42 (largely overlapping with the proteins identified by linear mixed-effects models). Several proteins (including ACE, CgA and AXL) were associated with Aβ42 reduction only in subjects with normal baseline Aβ42, and not in subjects with reduced baseline Aβ42. We conclude that baseline CSF proteins related to Aβ metabolism, microglia activity or synapses predict longitudinal Aβ42 reduction in cognitively healthy elders. The finding that some proteins only predict Aβ42 reduction in subjects with normal baseline Aβ42 suggest that they predict future development of the brain Aβ pathology at the earliest stages of AD, prior to widespread development of Aβ plaques.

Introduction: Hyperammonemia occurs as a result of the inability to convert ammonia, a metabolic toxin, into urea due to a block in the urea cycle, and there resulting neurotoxicity is responsible for the pathogenesis. Case Presentation: Our patient was 7 days old when followed up in an external center for 3 days with a preliminary diagnosis of neonatal sepsis. Lethargy, vomiting, tachypnea, and convulsions, which are frequently seen in the first neonatal forms of urea cycle disorders, were also present in our patient. He was referred to us as a result of high ammonia levels when he was examined in terms of congenital metabolic diseases. He was intubated due to the rapid development of respiratory failure. When he was admitted to our intensive care unit with hyperammonemia, light reflex could not be obtained, and widespread cutis marmaratus was developed. Continuous renal replacement therapy was started in our patient and administered intermittently for 120 hours. The glucose infusion rate was followed by high fluid. When it orally tolerated, it is supported with sodium benzoate and sodium stearyl fumarate to reduce ammonia. Nutrition was limited to protein with Basic P. Conclusion: After staying in the intensive care unit for 30 days, our patient was discharged with the recommendation of outpatient follow-up by the pediatric metabolism physician. When our patient came for his check up after two months,there was no nystagmus and no seizures.

Amyloid-β accumulation in the brain is thought to be one of the earliest events in Alzheimer's disease, possibly leading to synaptic dysfunction, neurodegeneration and cognitive/functional decline. The earliest detectable changes seen with neuroimaging appear to be amyloid-β accumulation detected by (11)C-labelled Pittsburgh compound B positron emission tomography imaging. However, some individuals tolerate high brain amyloid-β loads without developing symptoms, while others progressively decline, suggesting that events in the brain downstream from amyloid-β deposition, such as regional brain atrophy rates, play an important role. The main purpose of this study was to understand the relationship between the regional distributions of increased amyloid-β and the regional distribution of increased brain atrophy rates in patients with mild cognitive impairment. To simultaneously capture the spatial distributions of amyloid-β and brain atrophy rates, we employed the statistical concept of parallel independent component analysis, an effective method for joint analysis of multimodal imaging data. Parallel independent component analysis identified significant relationships between two patterns of amyloid-β deposition and atrophy rates: (i) increased amyloid-β burden in the left precuneus/cuneus and medial-temporal regions was associated with increased brain atrophy rates in the left medial-temporal and parietal regions; and (ii) in contrast, increased amyloid-β burden in bilateral precuneus/cuneus and parietal regions was associated with increased brain atrophy rates in the right medial temporal regions. The spatial distribution of increased amyloid-β and the associated spatial distribution of increased brain atrophy rates embrace a characteristic pattern of brain structures known for a high vulnerability to Alzheimer's disease pathology, encouraging for the use of (11)C-labelled Pittsburgh compound B positron emission tomography measures as early indicators of Alzheimer's disease. These results may begin to shed light on the mechanisms by which amyloid-β deposition leads to neurodegeneration and cognitive decline and the development of a more specific Alzheimer's disease-specific imaging signature for diagnosis and use of this knowledge in the development of new anti-therapies for Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Background: Brain ageing is highly heterogeneous, as it is driven by a variety of normal and neuropathological processes. These processes may differentially affect structural and functional brain ageing across individuals, with more pronounced ageing (older brain age) during midlife being indicative of later development of dementia. Here, we examined whether brain-ageing heterogeneity in unimpaired older adults related to neurodegeneration, different cognitive trajectories, genetic and amyloid-beta (Aβ) profiles, and to predicted progression to Alzheimer's disease (AD)., Methods: Functional and structural brain age measures were obtained for resting-state functional MRI and structural MRI, respectively, in 3460 cognitively normal individuals across an age range spanning 42-85 years. Participants were categorised into four groups based on the difference between their chronological and predicted age in each modality: advanced age in both (n = 291), resilient in both (n = 260) or advanced in one/resilient in the other (n = 163/153). With the resilient group as the reference, brain-age groups were compared across neuroimaging features of neuropathology (white matter hyperintensity volume, neuronal loss measured with Neurite Orientation Dispersion and Density Imaging, AD-specific atrophy patterns measured with the Spatial Patterns of Abnormality for Recognition of Early Alzheimer's Disease index, amyloid burden using amyloid positron emission tomography (PET), progression to mild cognitive impairment and baseline and longitudinal cognitive measures (trail making task, mini mental state examination, digit symbol substitution task)., Findings: Individuals with advanced structural and functional brain-ages had more features indicative of neurodegeneration and they had poor cognition. Individuals with a resilient brain-age in both modalities had a genetic variant that has been shown to be associated with age of onset of AD. Mixed brain-age was associated with selective cognitive deficits., Interpretation: The advanced group displayed evidence of increased atrophy across all neuroimaging features that was not found in either of the mixed groups. This is in line with biomarkers of preclinical AD and cerebrovascular disease. These findings suggest that the variation in structural and functional brain ageing across individuals reflects the degree of underlying neuropathological processes and may indicate the propensity to develop dementia in later life., Funding: The National Institute on Aging, the National Institutes of Health, the Swiss National Science Foundation, the Kaiser Foundation Research Institute and the National Heart, Lung, and Blood Institute., Competing Interests: Declaration of interests TB has received investigator-initiated research awards from the NIH, the Alzheimer’s Association, the Foundation at Barnes-Jewish Hospital, Siemens Healthineers, Hyperfine and Avid Radiopharmaceuticals (a wholly-owned subsidiary of Eli Lilly and Company). She participates as a site investigator in clinical trials sponsored by Eli Lilly and Company, Biogen, Eisai, Jaansen, and Roche. She has served as a paid and unpaid consultant to Eisai, Siemens, Biogen, Janssen, Hyperfine, Merck Lilly, and Bristol-Myers Squibb. JCM has served as a paid consultant to the Barcelona Brain Research Center and the Native Alzheimer Disease-related Resource Center in Minority Aging Research. He also received payments for presentations at the AAIM meeting, Longer Life Foundation and the International Brain Health Symposium. JCM has received travel support to attend meetings including: AAIM, DIAN, AD/PD, ATRI/ADNI, ADRC, ADC, the International conference on Health Aging & Biomarkers and the International Brain Health Symposium. He has served on the advisory board for the Cure Alzheimer’s Fund and LEADS at Indiana University. IMN has received payments from Premier, Inc for participating in an advisory board, from Peerview for an educational talk, and from Subtle Medical, Inc for consulting. DW has served as a paid consultant to Qynapse, Beckman Coulter and Eli Lilly. He also received grants from the NIH and Biogen paid to his institution and received travel support from the Alzheimer's Association. SR is an NIA IRP employee and has served on the advisory board of Dementia Platforms, UK, the Canadian Consortium on Neurodegeneration in Aging and the Adult Aging Brain Connectome. She has received travel support from the McKnight Foundation to attend an annual meeting., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

On the 20th anniversary of the Alzheimer's Disease Neuroimaging Initiative (ADNI), this paper provides a comprehensive overview of the role of arterial spin labeling (ASL) magnetic resonance imaging (MRI) in understanding perfusion changes in the aging brain and the relationship with Alzheimer's disease (AD) pathophysiology and its comorbid conditions. We summarize previously used acquisition protocols, available data, and the motivation for adopting a multi-post-labeling delay (PLD) acquisition scheme in the latest ADNI MRI protocol (ADNI 4). We also detail the process of setting up this scheme on different scanners, emphasizing the potential of ASL imaging in future AD research. HIGHLIGHTS: The Alzheimer's Disease Neuroimaging Initiative (ADNI) adopted multimodal arterial spin labeling magnetic resonance imaging (ASL MRI) to meet evolving biomarker requirements. The ADNI provides one of the largest multisite, multi-vendor ASL data collections. The ADNI 4 incorporates multi-post-labeling delay ASL techniques to jointly quantify cerebral blood flow and arterial transit time. ADNI 4 ASL MRI protocol is apt for detecting early Alzheimer's disease with cerebrovascular pathology., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: Alzheimer's Disease Neuroimaging Initiative (ADNI) has been pivotal in identifying and refining Alzheimer's disease (AD) biomarkers for clinical trials. This study leverages longitudinal data from participants who have progressed to amyloid-positivity during their study participation to track evolution of biomarkers and cognitive function., Methods: We modeled AD biomarker (positron emission tomography [PET], structural, cerebrospinal fluid [CSF], cognition) trajectories before and after observed amyloid-positivity onset time to detect time at which each biomarker had detectable trajectory changes., Results: Analysis of a sub-cohort of the 20-year ADNI study (N = 90) recapitulated Alzheimer's progression beginning with amyloid alterations -4.8 to -5.3 years relative to amyloid-positivity, succeeded by neurodegeneration (t = -4.0 to -4.1 years), and CSF tau (t = -0.4 to -0.5 years). Cognitive decline was observed to significantly correspond with emergence of amyloid-positivity (t = 0.2 to 2.4 years)., Discussion: Our results corroborate temporal progression curves of AD biomarkers, providing insights on earliest detectable changes in objective and subjective cognitive function assessments., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: Cerebrospinal fluid (CSF) α-synuclein (α-syn) seed amplification assay (SAA) is a sensitive and specific tool for detecting Lewy body co-pathology in Alzheimer's disease., Methods: A total of 1637 cross-sectional and 407 longitudinal CSF samples from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were tested with SAA. We examined longitudinal dynamics of amyloid beta (Aβ), α-syn seeds, and phosphorylated tau181 (p-tau181), along with global and domain-specific cognition in stable SAA+, stable SAA-, and those who converted to SAA+ from SAA-., Results: SAA+ individuals had faster cognitive decline than SAA-, notably in mild cognitive impairment, and presented with earlier symptom onset. SAA+ conversion was associated with CSF Aβ42 positivity but did not impact the progression of either CSF Aβ42 or CSF p-tau181 status. CSF Aβ42, p-tau181, and α-syn SAA were all strong predictors of clinical progression, particularly CSF Aβ42. In vitro, CSF α-syn SAA kinetic parameters were associated with participant demographics, clinical profiles, and cognitive decline., Discussion: These results highlight the interplay between amyloid and α-syn and their association with disease progression., Highlights: Seed amplification assay (SAA) positivity was associated with greater cognitive decline and earlier symptom onset. Thirty-four Alzheimer's Disease Neuroimaging Initiative (ADNI) individuals progressed from SAA- to SAA+, that is, ≈ 5% conversion. SAA conversion was associated with amyloid beta (Aβ) pathology and greater cognitive decline. SAA status did not impact the progression of either CSF Aβ42 or phosphorylated tau181 biomarkers. Change in clinical diagnosis was associated with both Alzheimer's disease biomarkers and SAA. SAA kinetic parameters were associated with clinical features and progression., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: Blood tests have the potential to improve the accuracy of Alzheimer's disease (AD) clinical diagnosis, which will enable greater access to AD-specific treatments. This study compared leading commercial blood tests for amyloid pathology and other AD-related outcomes., Methods: Plasma samples from the Alzheimer's Disease Neuroimaging Initiative were assayed with AD blood tests from C2N Diagnostics, Fujirebio Diagnostics, ALZPath, Janssen, Roche Diagnostics, and Quanterix. Outcomes measures were amyloid positron emission tomography (PET), tau PET, cortical thickness, and dementia severity. Logistic regression models assessed the classification accuracies of individual or combined plasma biomarkers for binarized outcomes, and Spearman correlations evaluated continuous relationships between individual plasma biomarkers and continuous outcomes., Results: Measures of plasma p-tau217, either individually or in combination with other plasma biomarkers, had the strongest relationships with all AD outcomes., Discussion: This study identified the plasma biomarker analytes and assays that most accurately classified amyloid pathology and other AD-related outcomes., Highlights: Plasma p-tau217 measures most accurately classified amyloid and tau status. Plasma Aβ42/Aβ40 had relatively low accuracy in classification of amyloid status. Plasma p-tau217 measures had higher correlations with cortical thickness than NfL. Correlations of plasma biomarkers with dementia symptoms were relatively low., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: Recent technological advances have increased the risk that de-identified brain images could be re-identified from face imagery. The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a leading source of publicly available de-identified brain imaging, who quickly acted to protect participants' privacy., Methods: An independent expert committee evaluated 11 face-deidentification ("de-facing") methods and selected four for formal testing., Results: Effects of de-facing on brain measurements were comparable across methods and sufficiently small to recommend de-facing in ADNI. The committee ultimately recommended mri_reface for advantages in reliability, and for some practical considerations. ADNI leadership approved the committee's recommendation, beginning in ADNI4., Discussion: ADNI4 de-faces all applicable brain images before subsequent pre-processing, analyses, and public release. Trained analysts inspect de-faced images to confirm complete face removal and complete non-modification of brain. This paper details the history of the algorithm selection process and extensive validation, then describes the production workflows for de-facing in ADNI., Highlights: ADNI is implementing "de-facing" of MRI and PET beginning in ADNI4. "De-facing" alters face imagery in brain images to help protect privacy. Four algorithms were extensively compared for ADNI and mri_reface was chosen. Validation confirms mri_reface is robust and effective for ADNI sequences. Validation confirms mri_reface negligibly affects ADNI brain measurements., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Alzheimer's disease (AD) is associated with heterogeneous atrophy patterns. We employed a semi-supervised representation learning technique known as Surreal-GAN, through which we identified two latent dimensional representations of brain atrophy in symptomatic mild cognitive impairment (MCI) and AD patients: the "diffuse-AD" (R1) dimension shows widespread brain atrophy, and the "MTL-AD" (R2) dimension displays focal medial temporal lobe (MTL) atrophy. Critically, only R2 was associated with widely known sporadic AD genetic risk factors (e.g., APOE ε4) in MCI and AD patients at baseline. We then independently detected the presence of the two dimensions in the early stages by deploying the trained model in the general population and two cognitively unimpaired cohorts of asymptomatic participants. In the general population, genome-wide association studies found 77 genes unrelated to APOE differentially associated with R1 and R2. Functional analyses revealed that these genes were overrepresented in differentially expressed gene sets in organs beyond the brain (R1 and R2), including the heart (R1) and the pituitary gland, muscle, and kidney (R2). These genes were enriched in biological pathways implicated in dendritic cells (R2), macrophage functions (R1), and cancer (R1 and R2). Several of them were "druggable genes" for cancer (R1), inflammation (R1), cardiovascular diseases (R1), and diseases of the nervous system (R2). The longitudinal progression showed that APOE ε4, amyloid, and tau were associated with R2 at early asymptomatic stages, but this longitudinal association occurs only at late symptomatic stages in R1. Our findings deepen our understanding of the multifaceted pathogenesis of AD beyond the brain. In early asymptomatic stages, the two dimensions are associated with diverse pathological mechanisms, including cardiovascular diseases, inflammation, and hormonal dysfunction-driven by genes different from APOE-which may collectively contribute to the early pathogenesis of AD. All results are publicly available at https://labs-laboratory.com/medicine/ ., (© 2024. The Author(s).)

The magnetic resonance imaging (MRI) Core has been operating since Alzheimer's Disease Neuroimaging Initiative's (ADNI) inception, providing 20 years of data including reliable, multi-platform standardized protocols, carefully curated image data, and quantitative measures provided by expert investigators. The overarching purposes of the MRI Core include: (1) optimizing and standardizing MRI acquisition methods, which have been adopted by many multicenter studies and trials worldwide and (2) providing curated images and numeric summary values from relevant MRI sequences/contrasts to the scientific community. Over time, ADNI MRI has become increasingly complex. To remain technically current, the ADNI MRI protocol has changed substantially over the past two decades. The ADNI 4 protocol contains nine different imaging types (e.g., three dimensional [3D] T1-weighted and fluid-attenuated inversion recovery [FLAIR]). Our view is that the ADNI MRI data are a greatly underutilized resource. The purpose of this paper is to educate the scientific community on ADNI MRI methods and content to promote greater awareness, accessibility, and use. HIGHLIGHTS: The MRI Core provides multi-platform standardized protocols, carefully curated image data, and quantitative analysis by expert groups. The ADNI MRI protocol has undergone major changes over the past two decades to remain technically current. As of April 25, 2024, the following numbers of image series are available: 17,141 3D T1w; 6877 FLAIR; 3140 T2/PD; 6623 GRE; 3237 dMRI; 2846 ASL; 2968 TF-fMRI; and 2861 HighResHippo (see Table 1 for abbreviations). As of April 25, 2024, the following numbers of quantitative analyses are available: FreeSurfer 10,997; BSI 6120; tensor based morphometry (TBM) and TBM-SYN 12,019; WMH 9944; dMRI 1913; ASL 925; TF-fMRI NFQ 2992; and medial temporal subregion volumes 2726 (see Table 4 for abbreviations). ADNI MRI is an underutilized resource that could be more useful to the research community., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: Neuroanatomical normative modeling captures individual variability in Alzheimer's disease (AD). Here we used normative modeling to track individuals' disease progression in people with mild cognitive impairment (MCI) and patients with AD., Methods: Cortical and subcortical normative models were generated using healthy controls (n ≈ 58k). These models were used to calculate regional z scores in 3233 T1-weighted magnetic resonance imaging time-series scans from 1181 participants. Regions with z scores < -1.96 were classified as outliers mapped on the brain and summarized by total outlier count (tOC)., Results: tOC increased in AD and in people with MCI who converted to AD and also correlated with multiple non-imaging markers. Moreover, a higher annual rate of change in tOC increased the risk of progression from MCI to AD. Brain outlier maps identified the hippocampus as having the highest rate of change., Discussion: Individual patients' atrophy rates can be tracked by using regional outlier maps and tOC., Highlights: Neuroanatomical normative modeling was applied to serial Alzheimer's disease (AD) magnetic resonance imaging (MRI) data for the first time. Deviation from the norm (outliers) of cortical thickness or brain volume was computed in 3233 scans. The number of brain-structure outliers increased over time in people with AD. Patterns of change in outliers varied markedly between individual patients with AD. People with mild cognitive impairment whose outliers increased over time had a higher risk of progression from AD., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Brain aging process is influenced by various lifestyle, environmental and genetic factors, as well as by age-related and often coexisting pathologies. Magnetic resonance imaging and artificial intelligence methods have been instrumental in understanding neuroanatomical changes that occur during aging. Large, diverse population studies enable identifying comprehensive and representative brain change patterns resulting from distinct but overlapping pathological and biological factors, revealing intersections and heterogeneity in affected brain regions and clinical phenotypes. Herein, we leverage a state-of-the-art deep-representation learning method, Surreal-GAN, and present methodological advances and extensive experimental results elucidating brain aging heterogeneity in a cohort of 49,482 individuals from 11 studies. Five dominant patterns of brain atrophy were identified and quantified for each individual by respective measures, R-indices. Their associations with biomedical, lifestyle and genetic factors provide insights into the etiology of observed variances, suggesting their potential as brain endophenotypes for genetic and lifestyle risks. Furthermore, baseline R-indices predict disease progression and mortality, capturing early changes as supplementary prognostic markers. These R-indices establish a dimensional approach to measuring aging trajectories and related brain changes. They hold promise for precise diagnostics, especially at preclinical stages, facilitating personalized patient management and targeted clinical trial recruitment based on specific brain endophenotypic expression and prognosis., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Introduction: Well-chosen biomarkers have the potential to increase the efficiency of clinical trials and drug discovery and should show good precision as well as clinical validity., Methods: We suggest measures that operationalize these criteria and describe a general approach that can be used for inference-based comparisons of biomarker performance. The methods are applied to measures obtained from structural magnetic resonance imaging (MRI) from individuals with mild dementia (n = 70) or mild cognitive impairment (MCI; n = 303) enrolled in the Alzheimer's Disease Neuroimaging Initiative., Results: Ventricular volume and hippocampal volume showed the best precision in detecting change over time in both individuals with MCI and with dementia. Differences in clinical validity varied by group., Discussion: The methodology presented provides a standardized framework for comparison of biomarkers across modalities and across different methods used to generate similar measures and will help in the search for the most promising biomarkers., Highlights: A framework for comparison of biomarkers on pre-defined criteria is presented. Criteria for comparison include precision in capturing change and clinical validity. Ventricular volume has high precision in change for both dementia and mild cognitive impairment (MCI) trials. Imaging measures' performance in clinical validity varies more for dementia than for MCI., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: Subjective cognitive decline (SCD) may be an early marker of Alzheimer's disease (AD) pathology. Until recently, it was impossible to measure biomarkers specific for α-synuclein pathology; therefore, its association with subjective reports of cognitive decline is unknown., Methods: Alzheimer's Disease Neuroimaging Initiative participants without dementia (n = 918) were classified as positive or negative for amyloid beta (Aβ+ or Aβ-) and α-synuclein (α-syn+ or α-syn-) biomarkers. Self- and study partner-reported cognitive decline was measured with the Everyday Cognition (ECog) questionnaire., Results: Per self-report, Aβ+/α-syn+ had the greatest cognitive decline. Aβ-/α-syn+ did not differ from Aβ-/α-syn- across ECog scores. Study partner-reported results had a similar pattern, but Aβ+/α-syn- and Aβ+/α-syn+ did not differ across ECog scores. Mild cognitive impairment classification moderated the study partner-reported memory score., Discussion: While α-syn+ alone did not increase subjective reports of cognitive decline, Aβ+/α-syn+ had the most self- and study partner-rated cognitive decline. Therefore, the presence of multiple pathologies was associated with greater SCD., Highlights: Cerebrospinal fluid α-synuclein (α-syn) seed amplification assay was used to determine α-syn positivity. Amyloid beta (Aβ)-/α-syn-, Aβ-/α-syn+, Aβ+/α-syn-, and Aβ+/α-syn+ biomarker groups were created. Aβ+/α-syn+ had greater subjective cognitive decline (SCD) than the other biomarker groups. Aβ-/α-syn+ did not differ from Aβ-/α-syn- across self- or study-partner reported SCD scores. Study partner-reported subjective memory results were largely driven by participants with mild cognitive impairment., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Phase four of the Alzheimer's Disease Neuroimaging Initiative (ADNI4) magnetic resonance imaging (MRI) protocols aim to maintain longitudinal consistency across two decades of data acquisition, while adopting new technologies. Here we describe and justify the study's design and targeted biomarkers. The ADNI4 MRI protocol includes nine MRI sequences. Some sequences require the latest hardware and software system upgrades and are continuously rolled out as they become available at each site. The main sequence additions/changes in ADNI4 are: (1) compressed sensing (CS) T1-weighting, (2) pseudo-continuous arterial spin labeling (ASL) on all three vendors (GE, Siemens, Philips), (3) multiple-post-labeling-delay ASL, (4) 1 mm 3 isotropic 3D fluid-attenuated inversion recovery, and (5) CS 3D T2-weighted. ADNI4 aims to help the neuroimaging community extract valuable imaging biomarkers and provide a database to test the impact of advanced imaging strategies on diagnostic accuracy and disease sensitivity among individuals lying on the cognitively normal to impaired spectrum. HIGHLIGHTS: A summary of MRI protocols for phase four of the Alzheimer's Disease Neuroimaging Initiative (ADNI 4). The design and justification for the ADNI 4 MRI protocols. Compressed sensing and multi-band advances have been applied to improve scan time. ADNI4 protocols aim to streamline safety screening and therapy monitoring. The ADNI4 database will be a valuable test bed for academic research., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

The progression of Parkinson's disease (PD) is associated with microstructural alterations in neural pathways, contributing to both motor and cognitive decline. However, conflicting findings have emerged due to the use of heterogeneous methods in small studies. Here we performed a large diffusion MRI study in PD, integrating data from 17 cohorts worldwide, to identify stage-specific profiles of white matter differences. Diffusion-weighted MRI data from 1654 participants diagnosed with PD (age: 20-89 years; 33% female) and 885 controls (age: 19-84 years; 47% female) were analyzed using the ENIGMA-DTI protocol to evaluate white matter microstructure. Skeletonized maps of fractional anisotropy (FA) and mean diffusivity (MD) were compared across Hoehn and Yahr (HY) disease groups and controls to reveal the profile of white matter alterations at different stages. We found an enhanced, more widespread pattern of microstructural alterations with each stage of PD, with eventually lower FA and higher MD in almost all regions of interest: Cohen's d effect sizes reached d = -1.01 for FA differences in the fornix at PD HY Stage 4/5. The early PD signature in HY stage 1 included higher FA and lower MD across the entire white matter skeleton, in a direction opposite to that typical of other neurodegenerative diseases. FA and MD were associated with motor and non-motor clinical dysfunction. While overridden by degenerative changes in the later stages of PD, early PD is associated with paradoxically higher FA and lower MD in PD, consistent with early compensatory changes associated with the disorder., (© 2024. The Author(s).)

Introduction: Alzheimer's disease (AD) pathology is defined by β-amyloid (Aβ) plaques and neurofibrillary tau, but Lewy bodies (LBs; 𝛼-synuclein aggregates) are a common co-pathology for which effective biomarkers are needed., Methods: A validated α-synuclein Seed Amplification Assay (SAA) was used on recent cerebrospinal fluid (CSF) samples from 1638 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants, 78 with LB-pathology confirmation at autopsy. We compared SAA outcomes with neuropathology, Aβ and tau biomarkers, risk-factors, genetics, and cognitive trajectories., Results: SAA showed 79% sensitivity and 97% specificity for LB pathology, with superior performance in identifying neocortical (100%) compared to limbic (57%) and amygdala-predominant (60%) LB-pathology. SAA+ rate was 22%, increasing with disease stage and age. Higher Aβ burden but lower CSF p-tau181 associated with higher SAA+ rates, especially in dementia. SAA+ affected cognitive impairment in MCI and Early-AD who were already AD biomarker positive., Discussion: SAA is a sensitive, specific marker for LB-pathology. Its increase in prevalence with age and AD stages, and its association with AD biomarkers, highlights the clinical importance of α-synuclein co-pathology in understanding AD's nature and progression., Highlights: SAA shows 79% sensitivity, 97% specificity for LB-pathology detection in AD. SAA positivity prevalence increases with disease stage and age. Higher Aβ burden, lower CSF p-tau181 linked with higher SAA+ rates in dementia. SAA+ impacts cognitive impairment in early disease stages. Study underpins need for wider LB-pathology screening in AD treatment., (© 2024 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: The effects of sex, race, and Apolipoprotein E ( APOE ) - Alzheimer's disease (AD) risk factors - on white matter integrity are not well characterized., Methods: Diffusion MRI data from nine well-established longitudinal cohorts of aging were free-water (FW)-corrected and harmonized. This dataset included 4,702 participants (age=73.06 ± 9.75) with 9,671 imaging sessions over time. FW and FW-corrected fractional anisotropy (FA FWcorr ) were used to assess differences in white matter microstructure by sex, race, and APOE -ε4 carrier status., Results: Sex differences in FA FWcorr in association and projection tracts, racial differences in FA FWcorr in projection tracts, and APOE -ε4 differences in FW limbic and occipital transcallosal tracts were most pronounced., Discussion: There are prominent differences in white matter microstructure by sex, race, and APOE -ε4 carrier status. This work adds to our understanding of disparities in AD. Additional work to understand the etiology of these differences is warranted., Competing Interests: SCJ has served on advisory boards for Enigma Biomedical and ALZPath in the past two years. AJS receives support from multiple NIH grants (P30 AG010133, P30 AG072976, R01 AG019771, R01 AG057739, U19 AG024904, R01 LM013463, R01 AG068193, T32 AG071444, U01 AG068057, U01 AG072177, U19 AG074879, and U24 AG074855). He has also received support from Avid Radiopharmaceuticals, a subsidiary of Eli Lilly (in kind contribution of PET tracer precursor) and participated in Scientific Advisory Boards (Bayer Oncology, Eisai, Novo Nordisk, and Siemens Medical Solutions USA, Inc) and an Observational Study Monitoring Board (MESA, NIH NHLBI), as well as External Advisory Committees for multiple NIA grants. He also serves as Editor-in-Chief of Brain Imaging and Behavior, a Springer-Nature Journal.

Introduction: Abnormal amyloid-beta (Aβ) and tau deposition define Alzheimer's Disease (AD), but non-elevated tau is relatively frequent in patients on the AD pathway., Methods: We examined characteristics and regional patterns of 397 Aβ+ unimpaired and impaired individuals with low tau (A+T-) in relation to their higher tau counterparts (A+T+)., Results: Seventy-one percent of Aβ+ unimpaired and 42% of impaired Aβ+ individuals were categorized as A+T- based on global tau. In impaired individuals only, A+T- status was associated with older age, male sex, and greater cardiovascular risk. α-synuclein was linked to poorer cognition, particularly when tau was low. Tau burden was most frequently elevated in a common set of temporal regions regardless of T+/T- status., Discussion: Low tau is relatively common in patients on the AD pathway and is linked to comorbidities that contribute to impairment. These findings have implications for the selection of individuals for Aβ- and tau-modifying therapies., (© 2024 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Background: Tau pathology correlates with and predicts clinical decline in Alzheimer's disease. Approved tau-targeted therapies are not available., Methods: ADAMANT, a 24-month randomised, placebo-controlled, parallel-group, double-blinded, multicenter, Phase 2 clinical trial (EudraCT2015-000630-30, NCT02579252) enrolled 196 participants with Alzheimer's disease; 119 are included in this post-hoc subgroup analysis. AADvac1, active immunotherapy against pathological tau protein. A machine learning model predicted likely Amyloid+Tau+ participants from baseline MRI., Statistical Methods: MMRM for change from baseline in cognition, function, and neurodegeneration; linear regression for associations between antibody response and endpoints., Results: The prediction model achieved PPV of 97.7% for amyloid, 96.2% for tau. 119 participants in the full analysis set (70 treatment and 49 placebo) were classified as A+T+. A trend for CDR-SB 104-week change (estimated marginal means [emm] = -0.99 points, 95% CI [-2.13, 0.13], p = 0.0825]) and ADCS-MCI-ADL (emm = 3.82 points, CI [-0.29, 7.92], p = 0.0679) in favour of the treatment group was seen. Reduction was seen in plasma NF-L (emm = -0.15 log pg/mL, CI [-0.27, -0.03], p = 0.0139). Higher antibody response to AADvac1 was related to slowing of decline on CDR-SB (rho = -0.10, CI [-0.21, 0.01], p = 0.0376) and ADL (rho = 0.15, CI [0.03, 0.27], p = 0.0201), and related to slower brain atrophy (rho = 0.18-0.35, p < 0.05 for temporal volume, whole cortex, and right and left hippocampus)., Conclusions: In the subgroup of ML imputed or CSF identified A+T+, AADvac1 slowed AD-related decline in an antibody-dependent manner. Larger anti-tau trials are warranted., Funding: AXON Neuroscience SE., Competing Interests: Declaration of interests Nick Cullen received personal fees from AXON Neuroscience SE. All authors affiliated with AXON NEUROSCIENCE SE or one of its subsidiaries received salary from their respective companies. Jozef Hanes, Eva Kontsekova, and Branislav Kovacech report patents with AXON Neuroscience R&D Services SE. Petr Novak received payments from F. Hoffmann-La Roche AG. The investigators’ institutions received reimbursement on a per-patient per-visit basis. Duygu Tosun’s institution received payments from AXON Neuroscience for image processing, and payments to the institution from Siemens Medical Solutions USA, Inc., Takeda Pharmaceutical Company Ltd., DOD WW81XWH-19-1-0669, NIH/NIA U19AG024904, NIH/NIA U01AG068057, NIH/NIA U24AG074855, NIH/NIA R01AG058676. Reinhold Schmidt has received personal fees and honoraria for image analyses from AXON NEUROSCIENCE. Stefan Ropele reports no conflict of interest. Bengt Winblad reports personal fees for taking part in Scientific Advisory Board meetings and Data Safety Management Board meetings from AXON NEUROSCIENCE, and from Alzinova DSMB and Artery TX SAB. Dr. Feldman reports a service agreement between Axon Neuroscience and UCSD for consulting and travel with all payments to UCSD and no personal funds received. Other activities to report include: grant funding from Annovis (QR Pharma), Vivoryon (Probiodrug), AC Immune, and LuMind; service agreements for consulting activities with LuMind, Genentech (DSMB), Roche/Banner (DMC), Tau Consortium (SAB), Samus Therapeutics, Biosplice Therapeutics, Novo Nordisk Inc., Janssen Research & Development LLC, and Arrowhead Pharmaceuticals with no personal funds received and all payments to UCSD. He also reports a philanthropic donation to UCSD from the Epstein Family Alzheimer's Disease Collaboration for therapeutic research in AD., (Copyright © 2023 AXON NEUROSCIENCE SE. Published by Elsevier B.V. All rights reserved.)

White matter hyperintensities (WMH) are nearly ubiquitous in the aging brain, and their topography and overall burden are associated with cognitive decline. Given their numerosity, accurate methods to automatically segment WMH are needed. Recent developments, including the availability of challenge data sets and improved deep learning algorithms, have led to a new promising deep-learning based automated segmentation model called TrUE-Net, which has yet to undergo rigorous independent validation. Here, we compare TrUE-Net to six established automated WMH segmentation tools, including a semi-manual method. We evaluated the techniques at both global and regional level to compare their ability to detect the established relationship between WMH burden and age. We found that TrUE-Net was highly reliable at identifying WMH regions with low false positive rates, when compared to semi-manual segmentation as the reference standard. TrUE-Net performed similarly or favorably when compared to the other automated techniques. Moreover, TrUE-Net was able to detect relationships between WMH and age to a similar degree as the reference standard semi-manual segmentation at both the global and regional level. These results support the use of TrUE-Net for identifying WMH at the global or regional level, including in large, combined datasets., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflict of interest., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

The Alzheimer's Disease Neuroimaging Initiative (ADNI) aims to improve Alzheimer's disease (AD) clinical trials. Since 2006, ADNI has shared clinical, neuroimaging, and cognitive data, and biofluid samples. We used conventional search methods to identify 1459 publications from 2021 to 2022 using ADNI data/samples and reviewed 291 impactful studies. This review details how ADNI studies improved disease progression understanding and clinical trial efficiency. Advances in subject selection, detection of treatment effects, harmonization, and modeling improved clinical trials and plasma biomarkers like phosphorylated tau showed promise for clinical use. Biomarkers of amyloid beta, tau, neurodegeneration, inflammation, and others were prognostic with individualized prediction algorithms available online. Studies supported the amyloid cascade, emphasized the importance of neuroinflammation, and detailed widespread heterogeneity in disease, linked to genetic and vascular risk, co-pathologies, sex, and resilience. Biological subtypes were consistently observed. Generalizability of ADNI results is limited by lack of cohort diversity, an issue ADNI-4 aims to address by enrolling a diverse cohort., (© 2023 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: Biomarkers remain mostly unavailable for non-Alzheimer's disease neuropathological changes (non-ADNC) such as transactive response DNA-binding protein 43 (TDP-43) proteinopathy, Lewy body disease (LBD), and cerebral amyloid angiopathy (CAA)., Methods: A multilabel non-ADNC classifier using magnetic resonance imaging (MRI) signatures was developed for TDP-43, LBD, and CAA in an autopsy-confirmed cohort (N = 214)., Results: A model using demographic, genetic, clinical, MRI, and ADNC variables (amyloid positive [Aβ+] and tau+) in autopsy-confirmed participants showed accuracies of 84% for TDP-43, 81% for LBD, and 81% to 93% for CAA, outperforming reference models without MRI and ADNC biomarkers. In an ADNI cohort (296 cognitively unimpaired, 401 mild cognitive impairment, 188 dementia), Aβ and tau explained 33% to 43% of variance in cognitive decline; imputed non-ADNC explained an additional 16% to 26%. Accounting for non-ADNC decreased the required sample size to detect a 30% effect on cognitive decline by up to 28%., Discussion: Our results lead to a better understanding of the factors that influence cognitive decline and may lead to improvements in AD clinical trial design., (© 2023 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Normal and pathologic neurobiological processes influence brain morphology in coordinated ways that give rise to patterns of structural covariance (PSC) across brain regions and individuals during brain aging and diseases. The genetic underpinnings of these patterns remain largely unknown. We apply a stochastic multivariate factorization method to a diverse population of 50,699 individuals (12 studies and 130 sites) and derive data-driven, multi-scale PSCs of regional brain size. PSCs were significantly correlated with 915 genomic loci in the discovery set, 617 of which are newly identified, and 72% were independently replicated. Key pathways influencing PSCs involve reelin signaling, apoptosis, neurogenesis, and appendage development, while pathways of breast cancer indicate potential interplays between brain metastasis and PSCs associated with neurodegeneration and dementia. Using support vector machines, multi-scale PSCs effectively derive imaging signatures of several brain diseases. Our results elucidate genetic and biological underpinnings that influence structural covariance patterns in the human brain., Competing Interests: Competing interests statement:D.H.W. served as Site PI for studies by Biogen, Merck, and Eli Lilly/Avid. He has received consulting fees from GE Healthcare and Neuronix. He is on the DSMB for a trial sponsored by Functional Neuromodulation. A.J.S. receives support from multiple NIH grants (P30 AG010133, P30 AG072976, R01 AG019771, R01 AG057739, U01 AG024904, R01 LM013463, R01 AG068193, T32 AG071444, U01 AG068057, and U01 AG072177). He has also received support from Avid Radiopharmaceuticals, a subsidiary of Eli Lilly (in-kind contribution of PET tracer precursor); Bayer Oncology (Scientific Advisory Board); Eisai (Scientific Advisory Board); Siemens Medical Solutions, Inc. (Dementia Advisory Board); and Springer-Nature Publishing (Editorial Office Support as Editor-in-Chief, Brain Imaging, and Behavior). O.C. reports having received consulting fees from AskBio (2020) and Therapanacea (2022), having received payments for writing a lay audience short paper from Expression Santé (2019), and that his laboratory has received grants (paid to the institution) from Qynapse (2017 to present). Members of his laboratory have co-supervised a Ph.D. thesis with myBrainTechnologies (2016 to 2019) and with Qynapse (2017 to present). O.C.’s spouse is an employee and holds stock options of myBrainTechnologies (2015 to present). O.C. has a patent registered at the International Bureau of the World Intellectual Property Organization (PCT/IB2016/0526993, J.-B. Schiratti, S. Allassonniere, O.C., S. Durrleman, A method for determining the temporal progression of a biological phenomenon and associated methods and devices) (2017). M.E. receives support from multiple NIH grants, the Alzheimer’s Association, and the Alzheimer’s Therapeutic Research Institute. M.V.Z. serves as a consultant and/or speaker for the following pharmaceutical companies: Eurofarma, Lundbeck, Abbott, Greencare, Myralis, and Elleven Healthcare.

Introduction: The Centiloid (CL) project was developed to harmonize the quantification of amyloid beta (Aβ) positron emission tomography (PET) scans to a unified scale. The CL neocortical mask was defined using 11 C Pittsburgh compound B (PiB), overlooking potential differences in regional distribution among Aβ tracers. We created a universal mask using an independent dataset of five Aβ tracers, and investigated its impact on inter-tracer agreement, tracer variability, and group separation., Methods: Using data from the Alzheimer's Dementia Onset and Progression in International Cohorts (ADOPIC) study (Australian Imaging Biomarkers and Lifestyle + Alzheimer's Disease Neuroimaging Initiative + Open Access Series of Imaging Studies), age-matched pairs of mild Alzheimer's disease (AD) and healthy controls (HC) were selected: 18 F-florbetapir ( N  = 147 pairs), 18 F-florbetaben ( N  = 22), 18 F-flutemetamol ( N  = 10), 18 F-NAV ( N  = 42), 11 C-PiB ( N  = 63). The images were spatially and standardized uptake value ratio normalized. For each tracer, the mean AD-HC difference image was thresholded to maximize the overlap with the standard neocortical mask. The universal mask was defined as the intersection of all five masks. It was evaluated on the Global Alzheimer's Association Interactive Network (GAAIN) head-to-head datasets in terms of inter-tracer agreement and variance in the young controls (YC) and on the ADOPIC dataset comparing separation between HC/AD and HC/mild cognitive impairment (MCI)., Results: In the GAAIN dataset, the universal mask led to a small reduction in the variance of the YC, and a small increase in the inter-tracer agreement. In the ADOPIC dataset, it led to a better separation between HC/AD and HC/MCI at baseline., Discussion: The universal CL mask led to an increase in inter-tracer agreement and group separation. Those increases were, however, very small, and do not provide sufficient benefits to support departing from the existing standard CL mask, which is suitable for the quantification of all Aβ tracers., Highlights: This study built an amyloid universal mask using a matched cohort for the five most commonly used amyloid positron emission tomography tracers.There was a high overlap between each tracer-specific mask.Differences in quantification and group separation between the standard and universal mask were small.The existing standard Centiloid mask is suitable for the quantification of all amyloid beta tracers., Competing Interests: Chris Rowe has received research grants from Piramal Imaging, GE Healthcare, Cerveau, Astra Zeneca, and Biogen. Victor Villemagne is and has been a consultant or paid speaker at sponsored conference sessions for Eli Lilly, Piramal Imaging, Life Molecular Imaging, GE Healthcare, Abbvie, Lundbeck, Shanghai Green Valley Pharmaceutical Co Ltd, IXICO, and Hoffmann La Roche. The other authors have nothing to disclose., (© 2023 Commonwealth of Australia. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Background: Efforts to develop neuroimaging-based biomarkers in major depressive disorder (MDD), at the individual level, have been limited to date. As diagnostic criteria are currently symptom-based, MDD is conceptualized as a disorder rather than a disease with a known etiology; further, neural measures are often confounded by medication status and heterogeneous symptom states., Methods: We describe a consortium to quantify neuroanatomical and neurofunctional heterogeneity via the dimensions of novel multivariate coordinate system (COORDINATE-MDD). Utilizing imaging harmonization and machine learning methods in a large cohort of medication-free, deeply phenotyped MDD participants, patterns of brain alteration are defined in replicable and neurobiologically-based dimensions and offer the potential to predict treatment response at the individual level. International datasets are being shared from multi-ethnic community populations, first episode and recurrent MDD, which are medication-free, in a current depressive episode with prospective longitudinal treatment outcomes and in remission. Neuroimaging data consist of de-identified, individual, structural MRI and resting-state functional MRI with additional positron emission tomography (PET) data at specific sites. State-of-the-art analytic methods include automated image processing for extraction of anatomical and functional imaging variables, statistical harmonization of imaging variables to account for site and scanner variations, and semi-supervised machine learning methods that identify dominant patterns associated with MDD from neural structure and function in healthy participants., Results: We are applying an iterative process by defining the neural dimensions that characterise deeply phenotyped samples and then testing the dimensions in novel samples to assess specificity and reliability. Crucially, we aim to use machine learning methods to identify novel predictors of treatment response based on prospective longitudinal treatment outcome data, and we can externally validate the dimensions in fully independent sites., Conclusion: We describe the consortium, imaging protocols and analytics using preliminary results. Our findings thus far demonstrate how datasets across many sites can be harmonized and constructively pooled to enable execution of this large-scale project., (© 2023. The Author(s).)

Introduction: The Centiloid scale was developed to harmonise the quantification of β-amyloid (Aβ) PET images across tracers, scanners, and processing pipelines. However, several groups have reported differences across tracers and scanners even after centiloid conversion. In this study, we aim to evaluate the impact of different pre and post-processing harmonisation steps on the robustness of longitudinal Centiloid data across three large international cohort studies., Methods: All Aβ PET data in AIBL (N = 3315), ADNI (N = 3442) and OASIS3 (N = 1398) were quantified using the MRI-based Centiloid standard SPM pipeline and the PET-only pipeline CapAIBL. SUVR were converted into Centiloids using each tracer's respective transform. Global Aβ burden from pre-defined target cortical regions in Centiloid units were quantified for both raw PET scans and PET scans smoothed to a uniform 8 mm full width half maximum (FWHM) effective smoothness. For Florbetapir, we assessed the performance of using both the standard Whole Cerebellum (WCb) and a composite white matter (WM)+WCb reference region. Additionally, our recently proposed quantification based on Non-negative Matrix Factorisation (NMF) was applied to all spatially and SUVR normalised images. Correlation with clinical severity measured by the Mini-Mental State Examination (MMSE) and effect size, as well as tracer agreement in 11 C-PiB- 18 F-Florbetapir pairs and longitudinal consistency were evaluated., Results: The smoothing to a uniform resolution partially reduced longitudinal variability, but did not improve inter-tracer agreement, effect size or correlation with MMSE. Using a Composite reference region for 18 F-Florbetapir improved inter-tracer agreement, effect size, correlation with MMSE, and longitudinal consistency. The best results were however obtained when using the NMF method which outperformed all other quantification approaches in all metrics used., Conclusions: FWHM smoothing has limited impact on longitudinal consistency or outliers. A Composite reference region including subcortical WM should be used for computing both cross-sectional and longitudinal Florbetapir Centiloid. NMF improves Centiloid quantification on all metrics examined., (Copyright © 2022. Published by Elsevier Inc.)

Introduction: This study aimed to test the efficacy of a nutritional blend (NB) in improving nutritional biomarkers and preventing cognitive decline among older adults., Methods: A 1-year randomized, double-blind, multicenter, placebo-controlled trial with 362 adults (58.6% female, mean 78.3 years, SD = 4.8) receiving an NB or placebo. Erythrocyte ω-3 index and homocysteine concentrations were primary outcomes. Other outcomes included Patient-Reported Outcomes Measurement Information System (PROMIS) Applied Cognition-Abilities, composite cognitive score (CCS), Cognitive Function Instrument (CFI) self-assessment and study partner, hippocampal volume (HV), and Alzheimer's disease signature cortical thickness (CT)., Results: A total of 305 subjects completed the follow-up. Supplementation increased ω-3 index and decreased homocysteine, but did not affect CCS, CFI self-assessment, HV, and CT. Placebo improved and treatment did not change PROMIS at 1 month. Intervention showed a positive effect on CFI study partner., Discussion: Although improving nutritional biomarkers, this 1-year trial with a multi-nutrient novel approach was not able to show effects on cognitive outcomes among older adults., Competing Interests: C.B., J.H., and J.A.J.S. work at the Société des Produits Nestlé SA, Nestlé Research, Lausanne, Switzerland. M.W.W. and B.V. received funds from Nestlé. Other authors declare no conflict of interest. Author disclosures are available in the supporting information., (© 2022 The Authors. Alzheimer's & Dementia: Translational Research & Clinical Interventions published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)

Background: Concordance between cortical atrophy and cortical glucose hypometabolism within distributed brain networks was evaluated among cerebrospinal fluid (CSF) biomarker-defined amyloid/tau/neurodegeneration (A/T/N) groups., Method: We computed correlations between cortical thickness and fluorodeoxyglucose metabolism within 12 functional brain networks. Differences among A/T/N groups (biomarker normal [BN], Alzheimer's disease [AD] continuum, suspected non-AD pathologic change [SNAP]) in network concordance and relationships to longitudinal change in cognition were assessed., Results: Network-wise markers of concordance distinguish SNAP subjects from BN subjects within the posterior multimodal and language networks. AD-continuum subjects showed increased concordance in 9/12 networks assessed compared to BN subjects, as well as widespread atrophy and hypometabolism. Baseline network concordance was associated with longitudinal change in a composite memory variable in both SNAP and AD-continuum subjects., Conclusions: Our novel study investigates the interrelationships between atrophy and hypometabolism across brain networks in A/T/N groups, helping disentangle the structure-function relationships that contribute to both clinical outcomes and diagnostic uncertainty in AD., Competing Interests: The authors declare no conflicts of interest., (© 2022 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)

Fibroblasts of the gingiva play a key role in oral wound healing in diabetes. In this study, effects of astaxanthin (ASTX), a xanthophyll carotenoid, were tested on gingival fibroblasts in a wound healing assay in vitro. The aim of this study was to determine whether ASTX can recover delayed wound healing or not when oxidative stress is elevated by high glucose exposure. For this purpose, human gingival fibroblasts were incubated with or without ASTX following exposure to systemic doses of low glucose (LG) and high glucose (HG) in culture media (5- and 25-, 50 mM D-glucose in DMEM Ham's F12) following 24 hours of incubation. Levels of ROS (Reactive oxygen species) were determined for each experimental group by confocal microscopy. Cell proliferation and viability were assessed by an automated cell counter with trypan blue assay. Wound healing assay was designed in 60 mm petri dishes. Cells were exposed to 5-, 25-, and 50 mM glucose for 24 hours, and a straight line free of cells was created upon full confluency. 100  μ M ASTX was added to the recovery group, simultaneously. Cells were monitored with JuLI Ⓡ -Br Cell History Recorder. ROS levels were significantly increased with increasing glucose levels, while cell proliferation and viability demonstrated a negative correlation with increasing oxidative stress. ROS levels significantly decreased in the 100  μ M ASTX-treated group compared to the gingival fibroblasts treated with 50 mM HG medium-only, as well as growth rate and viability. Wound healing was delayed in a dose-dependent manner following high glucose exposure, while ASTX treatment recovered wounded area by 1.16-fold in the 50 mM HG group. Our results demonstrated that ASTX enhances gingival wound healing through its antioxidative properties following high glucose induced oxidative stress. Therefore, ASTX can be suggested as a promising candidate to maintain oral health in chronic wounds of the oral tissues related to diabetes., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Duru Aras-Tosun et al.)

Abnormal tau inclusions are hallmarks of Alzheimer's disease and predictors of clinical decline. Several tau PET tracers are available for neurodegenerative disease research, opening avenues for molecular diagnosis in vivo. However, few have been approved for clinical use. Understanding the neurobiological basis of PET signal validation remains problematic because it requires a large-scale, voxel-to-voxel correlation between PET and (immuno) histological signals. Large dimensionality of whole human brains, tissue deformation impacting co-registration, and computing requirements to process terabytes of information preclude proper validation. We developed a computational pipeline to identify and segment particles of interest in billion-pixel digital pathology images to generate quantitative, 3D density maps. The proposed convolutional neural network for immunohistochemistry samples, IHCNet, is at the pipeline's core. We have successfully processed and immunostained over 500 slides from two whole human brains with three phospho-tau antibodies (AT100, AT8, and MC1), spanning several terabytes of images. Our artificial neural network estimated tau inclusion from brain images, which performs with ROC AUC of 0.87, 0.85, and 0.91 for AT100, AT8, and MC1, respectively. Introspection studies further assessed the ability of our trained model to learn tau-related features. We present an end-to-end pipeline to create terabytes-large 3D tau inclusion density maps co-registered to MRI as a means to facilitate validation of PET tracers., Competing Interests: Declaration of Competing Interest The authors declare no competing interests., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Purpose: Positron emission tomography (PET) imaging with amyloid-beta (Aβ) tracers and 2-[18F] fluoro-2-Deoxy-D-glucose ( 18 F-FDG) is extensively employed in Alzheimer's disease (AD) studies as biomarkers of AD pathology and neurodegeneration. To reduce cost and additional burdens to the patient, early-frame uptake during Aβ PET scanning has been proposed as a surrogate measure of regional glucose metabolism. Considering the disease state specific impact of AD on neurovascular coupling, we investigated to what extent the information captured in the early frames of an Aβ-PET ( 18 F-florbetapir or 18 F-florbetaben) scan is comparable to that of a 18 F-FDG PET scan, independent of disease state., Method: A partial correlation was performed on early-frame 18 F-florbetapir and 18 F-FDG regional data from 100 participants. In a secondary analysis, we compared 92 18 F-florbetapir and 21 18 F-florbetaben early-frame Aβ scans from cognitively unimpaired and mild cognitive impairment participants to ascertain if regional early-frame information was similar across different Aβ-PET radioligands., Results: The partial correlation of early-frame 18 F-florbetapir with 18 F-FDG was significant in all 84 brain ROIs, with correlation values ranging from 0.61 to 0.94. There were no significant differences between early-frame 18 F-florbetapir and 18 F-florbetaben images., Conclusion: Overall, we find that the regional uptake measurements from early-frame 18 F-florbetapir are strongly correlated with regional glucose metabolism as measured in ground-truth 18 F-FDG PET scans, regardless of disease state. Future studies should focus on longitudinal early-frame amyloid PET imaging studies to further assess the value of early-frame imaging as a marker of brain metabolic decline., (© 2022. The Author(s).)

Background: Major depressive disorder (MDD) is a complex disorder that affects nearly 264 million people worldwide. Structural brain abnormalities in multiple neuroanatomical networks have been implicated in the etiology of MDD, but the degree to which MDD affects brain structure during early to late adulthood is unclear., Methods: We examined morphometry of brain regions commonly implicated in MDD, including the amygdala, hippocampus, anterior cingulate gyrus, lateral orbitofrontal gyrus, subgenual cortex, and insular cortex subregions, from early to late adulthood. Harmonized measures for gray matter (GM) volume and cortical thickness of each region were estimated cross-sectionally for 305 healthy controls (CTLs) and 247 individuals with MDD (MDDs), collated from four research cohorts. We modeled the nonlinear associations of age with GM volume and cortical thickness using generalized additive modeling and tested for age-dependent group differences., Results: Overall, all investigated regions exhibited smaller GM volume and thinner cortical measures with increasing age. Compared to age matched CTLs, MDDs had thicker cortices and greater GM volume from early adulthood until early middle age (average 35 years), but thinner cortices and smaller GM volume during and after middle age in the lateral orbital gyrus and all insular subregions. Deviations of the MDD and CTL models for both GM volume and cortical thickness in these regions started as early as age 18., Conclusions: The analyses revealed that brain morphometry differences between MDDs and CTLs are dependent on age and brain region. The significant age-by-group interactions in the lateral orbital frontal gyrus and insular subregions make these regions potential targets for future longitudinal studies of MDD., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

To improve understanding of Alzheimer's disease, large observational studies are needed to increase power for more nuanced analyses. Combining data across existing observational studies represents one solution. However, the disparity of such datasets makes this a non-trivial task. Here, a machine learning approach was applied to impute longitudinal neuropsychological test scores across two observational studies, namely the Australian Imaging, Biomarkers and Lifestyle Study (AIBL) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) providing an overall harmonised dataset. MissForest, a machine learning algorithm, capitalises on the underlying structure and relationships of data to impute test scores not measured in one study aligning it to the other study. Results demonstrated that simulated missing values from one dataset could be accurately imputed, and that imputation of actual missing data in one dataset showed comparable discrimination (p < 0.001) for clinical classification to measured data in the other dataset. Further, the increased power of the overall harmonised dataset was demonstrated by observing a significant association between CVLT-II test scores (imputed for ADNI) with PET Amyloid-β in MCI APOE-ε4 homozygotes in the imputed data (N = 65) but not for the original AIBL dataset (N = 11). These results suggest that MissForest can provide a practical solution for data harmonization using imputation across studies to improve power for more nuanced analyses., (© 2021. The Author(s).)

The purpose of this study was to determine whether the augmented reality in children with autism spectrum disorder is an evidence-based practice. For this purpose, a systematic literature review was conducted for determining research that implemented the augmented reality. The review followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. As a result of the review, nine single-case experimental design (SCED) research that met the inclusion criteria were analyzed using the quality indicators. At the end of the quality evaluation, the effect size of eight SCED research that were determined to have evidence of a strong or adequate quality was calculated by using Tau- U . The results of the study revealed that the augmented reality was a promising and highly effective intervention (Tau U  = 0.98) in teaching new skills for children with autism spectrum disorder., Competing Interests: No potential conflict of interest was reported by the authors., (© The British Society of Developmental Disabilities 2021.)

Current methods for measuring the chronic rates of cognitive decline and degeneration in Alzheimer's disease rely on the sensitivity of longitudinal neuropsychological batteries and clinical neuroimaging, particularly structural magnetic resonance imaging of brain atrophy, either at a global or regional scale. There is particular interest in approaches predictive of future disease progression and clinical outcomes using a single time point. If successful, such approaches could have great impact on differential diagnosis, therapeutic treatment and clinical trial inclusion. Unfortunately, it has proven quite challenging to accurately predict clinical and degeneration progression rates from baseline data. Specifically, a key limitation of the previously proposed approaches for disease progression based on the brain atrophy measures has been the limited incorporation of the knowledge from disease pathology progression models, which suggest a prion-like spread of disease pathology and hence the neurodegeneration. Here, we present a new metric for disease progression rate in Alzheimer that uses only MRI-derived atrophy data yet is able to infer the underlying rate of pathology transmission. This is enabled by imposing a spread process driven by the brain networks using a Network Diffusion Model. We first fit this model to each patient's longitudinal brain atrophy data defined on a brain network structure to estimate a patient-specific rate of pathology diffusion, called the pathology progression rate. Using machine learning algorithms, we then build a baseline data model and tested this rate metric on data from longitudinal Alzheimer's Disease Neuroimaging Initiative study including 810 subjects. Our measure of disease progression differed significantly across diagnostic groups as well as between groups with different genetic risk factors. Remarkably, hierarchical clustering revealed 3 distinct clusters based on CSF profiles with >90% accuracy. These pathological clusters exhibit progressive atrophy and clinical impairments that correspond to the proposed rate measure. We demonstrate that a subject's degeneration speed can be best predicted from baseline neuroimaging volumetrics and fluid biomarkers for subjects in the middle of their degenerative course, which may be a practical, inexpensive screening tool for future prognostic applications., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Introduction: COVID-19 is the infection caused by the new coronavirus. Specific treatment for COVID-19 has not been established, yet. It is important to determine the disease severity of the patients at the first admission. Therefore, the exploration of biomarkers is deemed necessary. We aimed to assess the diagnostic and early prognostic value of CRP and LDH levels in possible COVID-19 patients presenting with a severe clinical picture., Methodology: We evaluated the correlations of relevant routine laboratory test results with disease severity in COVID-19 patients admitted to our infectious diseases clinic. Patients were divided into severe and non-severe disease groups based on clinical findings, oxygen saturation levels in the arterial blood, biochemical test results, and radiological findings. Differences in the findings between the two disease severity groups were examined to determine potential biomarkers., Results: Median age and the CRP and LDH levels in the severe disease group were statistically significantly higher compared to the nonsevere group (p < 0.0001). No other parameters statistically significant differences have been observed between the two groups (P > 0.05)., Conclusions: CRP and LDH levels were positively correlated with lung lesions in early-stage COVID-19, potentially reflecting disease severity. Because LDH and CRP levels can potentially reflect the pulmonary function, they can be potential predictors of COVID-19- related respiratory failure. For avoiding poor prognosis; LDH and CRP should be considered as potential predictors for identifying the need for thoracic CT scans, close monitoring of pulmonary function, and aggressive supportive therapy early in the course of COVID-19., Competing Interests: No Conflict of Interest is declared, (Copyright (c) 2021 Dogan Akdogan, Mustafa Guzel, Dervis Tosun, Orhan Akpinar.)

In vivo gold standard for the ante-mortem assessment of brain β-amyloid pathology is currently β-amyloid positron emission tomography or cerebrospinal fluid measures of β-amyloid 42 or the β-amyloid 42 /β-amyloid 40 ratio. The widespread acceptance of a biomarker classification scheme for the Alzheimer's disease continuum has ignited interest in more affordable and accessible approaches to detect Alzheimer's disease β-amyloid pathology, a process that often slows down the recruitment into, and adds to the cost of, clinical trials. Recently, there has been considerable excitement concerning the value of blood biomarkers. Leveraging multidisciplinary data from cognitively unimpaired participants and participants with mild cognitive impairment recruited by the multisite biomarker study of Alzheimer's Disease Neuroimaging Initiative, here we assessed to what extent plasma β-amyloid 42 /β-amyloid 40 , neurofilament light and phosphorylated-tau at threonine-181 biomarkers detect the presence of β-amyloid pathology, and to what extent the addition of clinical information such as demographic data, APOE genotype, cognitive assessments and MRI can assist plasma biomarkers in detecting β-amyloid-positivity. Our results confirm plasma β-amyloid 42 /β-amyloid 40 as a robust biomarker of brain β-amyloid-positivity (area under curve, 0.80-0.87). Plasma phosphorylated-tau at threonine-181 detected β-amyloid-positivity only in the cognitively impaired with a moderate area under curve of 0.67, whereas plasma neurofilament light did not detect β-amyloid-positivity in either group of participants. Clinical information as well as MRI-score independently detected positron emission tomography β-amyloid-positivity in both cognitively unimpaired and impaired (area under curve, 0.69-0.81). Clinical information, particularly APOE ε4 status, enhanced the performance of plasma biomarkers in the detection of positron emission tomography β-amyloid-positivity by 0.06-0.14 units of area under curve for cognitively unimpaired, and by 0.21-0.25 units for cognitively impaired; and further enhancement of these models with an MRI-score of β-amyloid-positivity yielded an additional improvement of 0.04-0.11 units of area under curve for cognitively unimpaired and 0.05-0.09 units for cognitively impaired. Taken together, these multi-disciplinary results suggest that when combined with clinical information, plasma phosphorylated-tau at threonine-181 and neurofilament light biomarkers, and an MRI-score could effectively identify β-amyloid+ cognitively unimpaired and impaired (area under curve, 0.80-0.90). Yet, when the MRI-score is considered in combination with clinical information, plasma phosphorylated-tau at threonine-181 and plasma neurofilament light have minimal added value for detecting β-amyloid-positivity. Our systematic comparison of β-amyloid-positivity detection models identified effective combinations of demographics, APOE , global cognition, MRI and plasma biomarkers. Promising minimally invasive and low-cost predictors such as plasma biomarkers of β-amyloid 42 /β-amyloid 40 may be improved by age and APOE genotype., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)