Genomic loci influence patterns of structural covariance in the human brain.

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.

Accuracy of TrUE-Net in comparison to established white matter hyperintensity segmentation methods: An independent validation study.

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.

Automated Quality Evaluation Index for Arterial Spin Labeling Derived Cerebral Blood Flow Maps.

BACKGROUND: Arterial spin labeling (ASL) derived cerebral blood flow (CBF) maps are prone to artifacts and noise that can degrade image quality. PURPOSE: To develop an automated and objective quality evaluation index (QEI) for ASL CBF maps. STUDY TYPE: Retrospective. POPULATION: Data from N = 221 adults, including patients with Alzheimer's disease (AD), Parkinson's disease, and traumatic brain injury. FIELD STRENGTH/SEQUENCE: Pulsed or pseudocontinuous ASL acquired at 3 T using non-background suppressed 2D gradient-echo echoplanar imaging or background suppressed 3D spiral spin-echo readouts. ASSESSMENT: The QEI was developed using N = 101 2D CBF maps rated as unacceptable, poor, average, or excellent by two neuroradiologists and validated by 1) leave-one-out cross validation, 2) assessing if CBF reproducibility in N = 53 cognitively normal adults correlates inversely with QEI, 3) if iterative discarding of low QEI data improves the Cohen's d effect size for CBF differences between preclinical AD (N = 27) and controls (N = 53), 4) comparing the QEI with manual ratings for N = 50 3D CBF maps, and 5) comparing the QEI with another automated quality metric. STATISTICAL TESTS: Inter-rater reliability and manual vs. automated QEI were quantified using Pearson's correlation. P < 0.05 was considered significant. RESULTS: The correlation between QEI and manual ratings (R = 0.83, CI: 0.76-0.88) was similar (P = 0.56) to inter-rater correlation (R = 0.81, CI: 0.73-0.87) for the 2D data. CBF reproducibility correlated negatively (R = -0.74, CI: -0.84 to -0.59) with QEI. The effect size comparing patients and controls improved (R = 0.72, CI: 0.59-0.82) as low QEI data was discarded iteratively. The correlation between QEI and manual ratings (R = 0.86, CI: 0.77-0.92) of 3D ASL was similar (P = 0.09) to inter-rater correlation (R = 0.78, CI: 0.64-0.87). The QEI correlated (R = 0.87, CI: 0.77-0.92) significantly better with manual ratings than did an existing approach (R = 0.54, CI: 0.30-0.72). DATA CONCLUSION: Automated QEI performed similarly to manual ratings and can provide scalable ASL quality control. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

Hoarding Symptoms in Late Life Depression are Associated With Greater Executive Dysfunction and Disability and Poorer Response to Depression Treatment.

OBJECTIVES: Late life depression (LLD) and hoarding disorder (HD) are common in older adults and characterized by executive dysfunction and disability. We aimed to determine the frequency of co-occurring HD in LLD and examine hoarding severity as an additional contributor to executive dysfunction, disability, and response to psychotherapy for LLD. DESIGN: Cross-sectional. SETTING: Outpatient psychiatry program. PARTICIPANTS: Eighty-three community-dwelling adults ages 65-90 with LLD. INTERVENTION: Problem-solving therapy. MEASUREMENTS: Measures of executive function, disability, depression, and hoarding severity were completed at post-treatment. Pearson's chi-squared tests evaluated group differences in rates of cognitive impairment, disability, and depression treatment response between participants with HD (LLD+HD) and LLD only. Separate linear regressions assessed associations between hoarding severity and executive function, disability, and psychotherapy response. Covariates included age, education, gender, and depression severity. RESULTS: 30.1% (25/83) of LLD participants met HD criteria. Relative to LLD, LLD+HD participants demonstrated greater impairment rates on measures of executive function (Letter-Number-Sequencing, X2(1)=4.0, p = 0.045; Stroop-Interference, X2(1) = 4.8, p = 0.028). Greater hoarding severity was associated with poorer executive functioning performance (Letter-Number-Sequencing (t[70] = -2.1, ß = -0.05, p = 0.044), Digit-Span (t[71] = -2.4, ß = -0.07, p = 0.019), Letter-Fluency (t[ 71] = -2.8, ß = -0.24, p = 0.006)). Rates of disability were significantly higher for LLD+HD (88.0%) than LLD (62.3%), (X2[1] = 5.41, p = 0.020) and higher hoarding severity was related to greater disability (t[72] = 2.97, ß = 0.13, p = 0.004). Depression treatment response rates were significantly lower for LLD+HD (24.0%) compared to LLD (48.3%), X2(1) = 4.26, p = 0.039, and HD status predicted psychotherapy response, t(67) = -2.15, ß = -15.6, p = 0.035. CONCLUSIONS: We found 30.1% co-occurrence of HD in LLD, which was accompanied by greater executive dysfunction, disability, and poorer response to depression treatment. Results underscore the need for increased screening of hoarding behaviors in LLD and tailored interventions for this LLD+HD group.

Relationship of Hoarding and Depression Symptoms in Older Adults.

Hoarding disorder (HD) is a debilitating neuropsychiatric condition that affects 2%-6% of the population and increases in incidence with age. Major depressive disorder (MDD) co-occurs with HD in approximately 50% of cases and leads to increased functional impairment and disability. However, only one study to date has examined the rate and trajectory of hoarding symptoms in older individuals with a lifetime history of MDD, including those with current active depression (late-life depression; LLD). We therefore sought to characterize this potentially distinct phenotype. We determined the incidence of HD in two separate cohorts of participants with LLD (n = 73) or lifetime history of MDD (n = 580) and examined the reliability and stability of hoarding symptoms using the Saving Inventory-Revised (SI-R) and Hoarding Rating Scale-Self Report (HRS), as well as the co-variance of hoarding and depression scores over time. HD was present in 12% to 33% of participants with MDD, with higher rates found in those with active depressive symptoms. Hoarding severity was stable across timepoints in both samples (all correlations >0.75), and fewer than 30% of participants in each sample experienced significant changes in severity between any two timepoints. Change in depression symptoms over time did not co-vary with change in hoarding symptoms. These findings indicate that hoarding is a more common comorbidity in LLD than previously suggested, and should be considered in screening and management of LLD. Future studies should further characterize the interaction of these conditions and their impact on outcomes, particularly functional impairment in this vulnerable population.

Anxiety in late-life depression is associated with poorer performance across multiple cognitive domains.

OBJECTIVE: Anxiety is a common comorbid feature of late-life depression (LLD) and is associated with poorer global cognitive functioning independent of depression severity. However, little is known about whether comorbid anxiety is associated with a domain-specific pattern of cognitive dysfunction. We therefore examined group differences (LLD with and without comorbid anxiety) in cognitive functioning performance across multiple domains. METHOD: Older adults with major depressive disorder (N = 228, ages 65-91) were evaluated for anxiety and depression severity, and cognitive functioning (learning, memory, language, processing speed, executive functioning, working memory, and visuospatial functioning). Ordinary least squares regression adjusting for age, sex, education, and concurrent depression severity examined anxiety group differences in performance on tests of cognitive functioning. RESULTS: Significant group differences emerged for confrontation naming and visuospatial functioning, as well as for verbal fluency, working memory, and inhibition with lower performance for LLD with comorbid anxiety compared to LLD only, controlling for depression severity. CONCLUSIONS: Performance patterns identified among older adults with LLD and comorbid anxiety resemble neuropsychological profiles typically seen in neurodegenerative diseases of aging. These findings have potential implications for etiological considerations in the interpretation of neuropsychological profiles.

Anxiety in late-life depression: Associations with brain volume, amyloid beta, white matter lesions, cognition, and functional ability.

OBJECTIVES: Late-life depression (LLD) is common and frequently co-occurs with neurodegenerative diseases of aging. Little is known about how heterogeneity within LLD relates to factors typically associated with neurodegeneration. Varying levels of anxiety are one source of heterogeneity in LLD. We examined associations between anxiety symptom severity and factors associated with neurodegeneration, including regional brain volumes, amyloid beta (Aß) deposition, white matter disease, cognitive dysfunction, and functional ability in LLD. PARTICIPANTS AND MEASUREMENTS: Older adults with major depression (N = 121, Ages 65-91) were evaluated for anxiety severity and the following: brain volume (orbitofrontal cortex [OFC], insula), cortical Aß standardized uptake value ratio (SUVR), white matter hyperintensity (WMH) volume, global cognition, and functional ability. Separate linear regression analyses adjusting for age, sex, and concurrent depression severity were conducted to examine associations between anxiety and each of these factors. A global regression analysis was then conducted to examine the relative associations of these variables with anxiety severity. RESULTS: Greater anxiety severity was associated with lower OFC volume (ß = -68.25, t = -2.18, p = .031) and greater cognitive dysfunction (ß = 0.23, t = 2.46, p = .016). Anxiety severity was not associated with insula volume, Aß SUVR, WMH, or functional ability. When examining the relative associations of cognitive functioning and OFC volume with anxiety in a global model, cognitive dysfunction (ß = 0.24, t = 2.62, p = .010), but not OFC volume, remained significantly associated with anxiety. CONCLUSIONS: Among multiple factors typically associated with neurodegeneration, cognitive dysfunction stands out as a key factor associated with anxiety severity in LLD which has implications for cognitive and psychiatric interventions.

Timing of Alzheimer's disease biomarker progressions: A two-decade observational study from the Alzheimer's Disease Neuroimaging Initiative (ADNI).

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.

Arterial spin labeling perfusion MRI in the Alzheimer's Disease Neuroimaging Initiative: Past, present, and future.

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.

Standardized statistical framework for comparison of biomarkers: Techniques from ADNI.

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.

Self- and study partner-reported cognitive decline in older adults without dementia: The role of α-synuclein and amyloid biomarkers in the Alzheimer's Disease Neuroimaging Initiative.

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 (Aß+ or Aß-) 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, Aß+/α-syn+ had the greatest cognitive decline. Aß-/α-syn+ did not differ from Aß-/α-syn- across ECog scores. Study partner-reported results had a similar pattern, but Aß+/α-syn- and Aß+/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, Aß+/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 (Aß)-/α-syn-, Aß-/α-syn+, Aß+/α-syn-, and Aß+/α-syn+ biomarker groups were created. Aß+/α-syn+ had greater subjective cognitive decline (SCD) than the other biomarker groups. Aß-/α-syn+ did not differ from Aß-/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.

Identifying individuals with non-Alzheimer's disease co-pathologies: A precision medicine approach to clinical trials in sporadic Alzheimer's disease.

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 [Aß+] 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), Aß 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.

Association of CSF α-synuclein seed amplification assay positivity with disease progression and cognitive decline: A longitudinal Alzheimer's Disease Neuroimaging Initiative study.

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 (Aß), 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 Aß42 positivity but did not impact the progression of either CSF Aß42 or CSF p-tau181 status. CSF Aß42, p-tau181, and α-syn SAA were all strong predictors of clinical progression, particularly CSF Aß42. 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 (Aß) pathology and greater cognitive decline. SAA status did not impact the progression of either CSF Aß42 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.

Personalizing progressive changes to brain structure in Alzheimer's disease using normative modeling.

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.

Design and validation of the ADNI MR protocol.

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 mm3 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.

Individuals with Alzheimer's disease and low tau burden: Characteristics and implications.

INTRODUCTION: Abnormal amyloid-beta (Aß) 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 Aß+ unimpaired and impaired individuals with low tau (A+T-) in relation to their higher tau counterparts (A+T+). RESULTS: Seventy-one percent of Aß+ unimpaired and 42% of impaired Aß+ 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 Aß- and tau-modifying therapies.

A cross-sectional study of α-synuclein seed amplification assay in Alzheimer's disease neuroimaging initiative: Prevalence and associations with Alzheimer's disease biomarkers and cognitive function.

INTRODUCTION: Alzheimer's disease (AD) pathology is defined by ß-amyloid (Aß) 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, Aß 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 Aß 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 Aß 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.

The Alzheimer's Disease Neuroimaging Initiative in the era of Alzheimer's disease treatment: A review of ADNI studies from 2021 to 2022.

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.

Overview of ADNI MRI.

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.

Head-to-head comparison of leading blood tests for Alzheimer's disease pathology.

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 Aß42/Aß40 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.