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Kathryn B Holroyd,1 Lisa Fosdick,2 Gwenn S Smith,1 Jeannie-Marie Leoutsakos,1 Cynthia A Munro,1 Esther S Oh,1 Kristen E Drake,2 Paul B Rosenberg,1 William S Anderson,1 Stephen Salloway,3–5 J Cara Pendergrass,6 Anna D Burke,7 David A Wolk,8 David F Tang-Wai,9–11 Francisco A Ponce,12 Wael F Asaad,13,14 Marwan N Sabbagh,15 Michael S Okun,16 Gordon Baltuch,17 Kelly D Foote,18 Steven D Targum,2,6 Andres M Lozano,10,11 Constantine G Lyketsos1 1Johns Hopkins University Memory and Alzheimer's Treatment Center, Baltimore, MD, 2Functional Neuromodulation Ltd, Minneapolis, MN, 3Department of Neurology, Butler Hospital, 4Department of Neurology, Rhode Island Hospital, 5Department of Neurology, Warren Alpert Medical School of Brown University, Providence, RI, 6Clintara LLC, Boston, MA, 7Banner Alzheimer's Institute, Phoenix, AZ, 8Penn Memory Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA; 9Department of Neurology, 10Department of Neurosurgery, University of Toronto, 11Division of Neurology, University Health Network Memory Clinic, Toronto, ON, Canada; 12Division of Neurological Surgery, Barrow Neurological Institute, St Joseph's Hospital and Medical Center, Phoenix, AZ, 13Department of Neurosurgery, Rhode Island Hospital, 14Department of Neurosurgery, Warren Alpert Medical School of Brown University, Providence, RI, 15Banner Sun Health Research Institute, Sun City, AZ, 16Center for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida – Gainsville, Gainsville, FL, 17Center for Functional and Restorative Neurosurgery, University of Pennsylvania, Philadelphia, PA, 18Department of Neurosurgery, Center for Movement Disorders and Neurorestoration, University of Florida, Gainsville, FL, USA Background: There are currently few available treatments and no cure for Alzheimer disease (AD), a growing public health burden. Animal models and an open-label human trial have indicated that deep brain stimulation (DBS) of memory circuits may improve symptoms and possibly slow disease progression. The ADvance trial was designed to examine DBS of the fornix as a treatment for mild AD. Methods: ADvance is a randomized, double-blind, placebo-controlled, delayed-start, multicenter clinical trial conducted at six sites in the US and one site in Canada. Eighty-five subjects initially consented to be screened for the trial. Of these, 42 subjects who met inclusion and exclusion criteria were implanted with DBS leads anterior to the columns of the fornix bilaterally. They were randomized 1:1 to DBS “off” or DBS “on” groups for the initial 12 months of follow-up. After 1 year, all subjects will have their devices turned “on” for the remainder of the study. Postimplantation, subjects will return for 13 follow-up visits over 48 months for cognitive and psychiatric assessments, brain imaging (up to 12 months), and safety monitoring. The primary outcome measures include Alzheimer's Disease Assessment Scale – cognitive component (ADAS-cog-13), Clinical Dementia Rating sum of boxes (CDR-SB), and cerebral glucose metabolism measured with positron emission tomography. This report details the study methods, baseline subject characteristics of screened and implanted participants, and screen-to-baseline test–retest reliability of the cognitive outcomes. Results: Implanted subjects had a mean age of 68.2 years, were mostly male (55%), and had baseline mean ADAS-cog-13 and CDR-SB scores of 28.9 (SD, 5.2) and 3.9 (SD, 1.6), respectively. There were no significant differences between screened and implanted or nonimplanted subjects on most demographic or clinical assessments. Implanted subjects had significantly lower (better) ADAS-cog-11 (17.5 vs 21.1) scores, but did not differ on CDR-SB. Scores on the major outcome measures for the trial were consistent at screening and baseline. Conclusion: ADvance was successful in enrolling a substantial group of patients for this novel application of DBS, and the study design is strengthened by rigorous subject selection from seven sites, a double-blind placebo-controlled design, and extensive open-label follow-up. Keywords: deep brain stimulation, Alzheimer disease, fornix, methods, clinical trials

AimsLewy body diseases (LBD) are characterized by alpha-synuclein (SYN) pathology, but comorbid Alzheimer's disease (AD) pathology is common and the relationship between these pathologies in microanatomic hippocampal subfields is understudied. Here we use digital histological methods to test the association between hippocampal SYN pathology and the distribution of tau and amyloid-beta (Aβ) pathology in LBD and contrast with AD subjects. We also correlate pathologic burden with antemortem episodic memory testing.MethodsHippocampal sections from 49 autopsy-confirmed LBD cases, 30 with no/low AD copathology (LBD - AD) and 19 with moderate/severe AD copathology (LBD + AD), and 30 AD patients were stained for SYN, tau, and Aβ. Sections underwent digital histological analysis of subfield pathological burden which was correlated with antemortem memory testing.ResultsLBD - AD and LBD + AD had similar severity and distribution of SYN pathology (P > 0.05), CA2/3 being the most affected subfield (P

Background: Significant heterogeneity in clinical features of frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS) cases with the pathogenic C9orf72 expansion (C9P) have been described. To clarify this issue, we compared a large C9P cohort with carefully matched non-expansion (C9N) cases with a known or highly-suspected underlying TAR DNA-binding protein 43 (TDP-43) proteinopathy.Methods: A retrospective case-control study was carried out using available cross-sectional and longitudinal clinical and neuropsychological data, MRI voxel-based morphometry (VBM) and neuropathological assessment from 64 C9P cases (ALS=31, FTLD=33) and 79 C9N cases (ALS=36, FTLD=43).Results: C9P cases had an earlier age of onset (p=0.047) and, in the subset of patients who were deceased, an earlier age of death (p=0.014) than C9N. C9P had more rapid progression than C9N: C9P ALS cases had a shortened survival (2.6 ± 0.3 years) compared to C9N ALS (3.8 ± 0.4 years; log-rank λ2=4.183, p=0.041), and C9P FTLD showed a significantly greater annualised rate of decline in letter fluency (4.5 ± 1.3 words/year) than C9N FTLD (1.4 ± 0.8 words/year, p=0.023). VBM revealed greater atrophy in the right frontoinsular, thalamus, cerebellum and bilateral parietal regions for C9P FTLD relative to C9N FTLD, and regression analysis related verbal fluency scores to atrophy in frontal and parietal regions. Neuropathological analysis found greater neuronal loss in the mid-frontal cortex in C9P FTLD, and mid-frontal cortex TDP-43 inclusion severity correlated with poor letter fluency performance.Conclusions: C9P cases may have a shorter survival in ALS and more rapid rate of cognitive decline related to frontal and parietal disease in FTLD. C9orf72 genotyping may provide useful prognostic and diagnostic clinical information for patients with ALS and FTLD. [ABSTRACT FROM AUTHOR]

The frequency and clinical and pathological characteristics associated with the Gly206Ala presenilin 1 (PSEN1) mutation in Puerto Rican and non-Puerto Rican Hispanics were evaluated at the University of Pennsylvania's Alzheimer's Disease Center. DNAs from all cohort subjects were genotyped for the Gly206Ala PSEN1 mutation. Carriers and non-carriers with neurodegenerative disease dementias were compared for demographic, clinical, psychometric, and biomarker variables. Nineteen (12.6%) of 151 unrelated subjects with dementia were discovered to carry the PSEN1 Gly206Ala mutation. Microsatellite marker genotyping determined a common ancestral haplotype for all carriers. Carriers were all of Puerto Rican heritage with significantly younger age of onset, but otherwise were clinically and neuropsychologically comparable to those of non-carriers with AD. Three subjects had extensive topographic and biochemical biomarker assessments that were also typical of non-carriers with AD. Neuropathological examination in one subject revealed severe, widespread plaque and tangle pathology without other meaningful disease lesions. The PSEN1 Gly206Ala mutation is notably frequent in unrelated Puerto Rican immigrants with dementia in Philadelphia. Considered together with the increased prevalence and mortality of AD reported in Puerto Rico, these high rates may reflect hereditary risk concentrated in the island which warrants further study. [ABSTRACT FROM AUTHOR]

There is growing recognition of an interaction between cerebrovascular disease and Alzheimer's disease, but the mechanisms of this interaction remain poorly understood. While macroscopic stroke can clearly produce cognitive deficits and accelerate Alzheimer's disease, the prevalence and implications of microvascular disease in Alzheimer's disease pathogenesis has been harder to define. At present, white matter (WM) lesions, primarily defined as hyperintensities seen on T2-weighted magnetic resonance imaging (MRI), provide the best biomarker of cerebrovascular disease at the microvascular level. However, T2 hyperintensities in WM can also be caused by other mechanisms such as inflammation. Arterial spin labeled (ASL) perfusion MRI provides a noninvasive approach for quantifying cerebral blood flow (CBF). We explored CBF measurements with ASL in AD patients, mild cognitive impairment patients, and an age-matched control group to determine if CBF in gray matter or WM could be correlated with WM lesions, or to stratify patients by microvascular disease severity. In a retrospective sample, we were able to obtain credible measures of WM CBF using ASL MRI and observed trends suggesting that WM CBF may provide a useful biomarker of microvascular disease. Future prospective studies in larger cohorts with optimized ASL MRI protocols will be needed to validate these observations. [ABSTRACT FROM AUTHOR]

Objective: To investigate whether some patients with very mild Alzheimer's disease (AD) demonstrate disproportionate executive dysfunction relative to amnesia and how this relates to functional impairment in daily life, future clinical decline, APOE genotype and regional cortical thickness measured from MRI scan data.Methods: The Alzheimer's Disease Neuroimaging Initiative dataset was interrogated for a primary sample of patients with very mild AD dementia (n=100) and a secondary confirmatory sample of patients with mild cognitive impairment (n=396). An executive predominant subgroup was defined as having executive performance ≥2 SDs worse than memory performance and a memory predominant subgroup was defined conversely. A priori regions of interest from a previous study of an AD patient sample were used to obtain cortical thickness measures.Results: Despite equivalent global measures of impairment (Mini-Mental State Examination, Clinical Dementia Rating (CDR) Sum of Boxes), executive predominant patients (n=88) were more impaired on other executive measures and in the CDR Judgement and Problem Solving box (p<0.005) while memory predominant patients (n=56) were more impaired on other memory measures (p<0.05). The APOE-ε4 allele was much more frequent in the memory predominant subgroup (p<0.0001). Frontoparietal cortical regions were thinner in the executive predominant group than in the memory predominant group (p<0.05).Conclusions: A dysexecutive clinical phenotype of very mild AD is not rare and is associated with more problem solving difficulties and possibly more rapid progression compared with patients with a predominant amnesic phenotype. Executive predominant AD may reflect an alternative underlying pathophysiology related to genetic status, reflected in more prominent pathological alterations in frontoparietal regions subserving executive function. These findings, which deserve further investigation, may have implications for diagnosis, prognostication, monitoring and related issues involved in clinical research and care. [ABSTRACT FROM AUTHOR]

This paper for the 20th anniversary of the Alzheimer's Disease Neuroimaging Initiative (ADNI) provides an overview of magnetic resonance imaging (MRI) of medial temporal lobe (MTL) subregions in ADNI using a dedicated high-resolution T2-weighted sequence. A review of the work that supported the inclusion of this imaging modality into ADNI Phase 3 is followed by a brief description of the ADNI MTL imaging and analysis protocols and a summary of studies that have used these data. This review is supplemented by a new study that uses novel surface-based tools to characterize MTL neurodegeneration across biomarker-defined AD stages. This analysis reveals a pattern of spreading cortical thinning associated with increasing levels of tau pathology in the presence of elevated amyloid beta, with apparent epicenters in the transentorhinal region and inferior hippocampal subfields. The paper concludes with an outlook for high-resolution imaging of the MTL in ADNI Phase 4. HIGHLIGHTS: As of Phase 3, the Alzheimer's Disease Neuroimaging Initiative (ADNI) magnetic resonance imaging (MRI) protocol includes a high-resolution T2-weighted MRI scan optimized for imaging hippocampal subfields and medial temporal lobe (MTL) subregions. These scans are processed by the ADNI core to obtain automatic segmentations of MTL subregions and to derive morphologic measurements. More detailed granular examination of MTL neurodegeneration in response to disease progression is achieved by applying surface-based modeling techniques. Surface-based analysis of gray matter loss in MTL subregions reveals increasing and spatially expanding patterns of neurodegeneration with advancing stages of Alzheimer's disease (AD), as defined based on amyloid and tau positron emission tomography biomarkers in accordance with recently proposed criteria. These patterns closely align with post mortem literature on spread of pathological tau in AD, supporting the role of tau pathology in the presence of elevated levels of amyloid beta as the driver of neurodegeneration., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: Anti-amyloid antibody therapies such as lecanemab are increasingly being used to treat Alzheimer's disease (AD). These therapies are associated with a high rate of amyloid-related imaging abnormalities (ARIA)., Methods: We review the case history of a patient who developed ARIA associated with lecanemab treatment., Results: In addition to microhemorrhages and cerebral edema that are recognized features of ARIA, the patient developed several ischemic strokes. The patient also experienced frequent electrographic seizures without overt clinical seizures. The patient demonstrated clinical and radiographic improvement after steroid treatment., Discussion: Our case suggests that ischemic strokes may be a feature of ARIA and highlights the importance of having a high clinical suspicion for seizures in ARIA. As anti-amyloid therapies are likely going to be increasingly used to treat AD, it is important to appreciate the spectrum of clinical and radiographic findings that can result as side effects from this class of therapies., Highlights: We report a patient who developed severe amyloid-related imaging abnormalities (ARIA) after treatment with lecanemab. Our report suggests that ischemic strokes may be a novel imaging feature of ARIA. Our report highlights the need for high clinical suspicion for seizures in ARIA., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Identifying individuals with early-stage Alzheimer's disease (AD) at greater risk of steeper clinical decline would enable better-informed medical, support, and life planning decisions. Despite accumulating evidence on the clinical prognostic value of tau positron emission tomography (PET) in typical late-onset amnestic AD, its utility in predicting clinical decline in individuals with atypical forms of AD remains unclear. Across heterogeneous clinical phenotypes, patients with atypical AD consistently exhibit abnormal tau accumulation in the posterior nodes of the default mode network of the cerebral cortex. This evidence suggests that tau burden in this functional network could be a common imaging biomarker for prognostication across the syndromic spectrum of AD. Here, we examined the relationship between baseline tau PET signal and the rate of subsequent clinical decline in a sample of 48 A+/T+/N+ patients with mild cognitive impairment or mild dementia due to AD with atypical clinical phenotypes: Posterior Cortical Atrophy (n = 16), logopenic variant Primary Progressive Aphasia (n = 15), and amnestic syndrome with multi-domain impairment and young age of onset < 65 years (n = 17). All patients underwent magnetic resonance imaging (MRI), tau PET, and amyloid PET scans at baseline. Each patient's longitudinal clinical decline was assessed by calculating the annualized change in the Clinical Dementia Rating Sum-of-Boxes (CDR-SB) scores from baseline to follow-up (mean time interval = 14.55 ± 3.97 months). Atypical early AD patients showed an increase in CDR-SB by 1.18 ± 1.25 points per year: t(47) = 6.56, p < .001, Cohen's d = 0.95. Across clinical phenotypes, baseline tau in the default mode network was the strongest predictor of clinical decline (R2 = .30), outperforming a simpler model with baseline clinical impairment and demographic variables (R2 = .10), tau in other functional networks (R2 = .11-.26), and the magnitude of cortical atrophy (R2 = .20) and amyloid burden (R2 = .09) in the default mode network. Overall, these findings point to the contribution of default mode network tau to predicting the magnitude of clinical decline in atypical early AD patients one year later. This simple measure could aid the development of a personalized prognostic, monitoring, and treatment plan, which would help clinicians not only predict the natural evolution of the disease but also estimate the effect of disease-modifying therapies on slowing subsequent clinical decline given the patient's tau burden while still early in the disease course., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Introduction: Regional glucose hypometabolism resulting in glutamate loss has been shown as one of the characteristics of Alzheimer's disease (AD). Because the impact of AD varies between the sexes, we utilized glutamate-weighted chemical exchange saturation transfer (GluCEST) magnetic resonance imaging (MRI) for high-resolution spatial mapping of cerebral glutamate and investigated subregional changes in a sex-specific manner., Methods: Eight-month-old male and female AD mice harboring mutant amyloid precursor protein (APP NL-F/NL-F : n = 36) and wild-type (WT: n = 39) mice underwent GluCEST MRI, followed by proton magnetic resonance spectroscopy ( 1 H-MRS) in hippocampus and thalamus/hypothalamus using 9.4T preclinical MR scanner., Results: GluCEST measurements revealed significant (p ≤ 0.02) glutamate loss in the entorhinal cortex (% change ± standard error: 8.73 ± 2.12%), hippocampus (11.29 ± 2.41%), and hippocampal fimbriae (19.15 ± 2.95%) of male AD mice. A similar loss of hippocampal glutamate in male AD mice (11.22 ± 2.33%; p = 0.01) was also observed in 1 H-MRS., Discussions: GluCEST MRI detected glutamate reductions in the fimbria and entorhinal cortex of male AD mice, which was not reported previously. Resilience in female AD mice against these changes indicates an intact status of cerebral energy metabolism., Highlights: Glutamate levels were monitored in different brain regions of early-stage Alzheimer's disease (AD) and wild-type male and female mice using glutamate-weighted chemical exchange saturation transfer (GluCEST) magnetic resonance imaging (MRI). Male AD mice exhibited significant glutamate loss in the hippocampus, entorhinal cortex, and the fimbriae of the hippocampus. Interestingly, female AD mice did not have any glutamate loss in any brain region and should be investigated further to find the probable cause. These findings demonstrate previously unreported sex-specific glutamate changes in hippocampal sub-regions using high-resolution GluCEST MRI., (© 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.)

Aggregation of misfolded α-synuclein (aSyn) within the brain is the pathologic hallmark of Lewy body diseases (LBD), including Parkinson's disease (PD) and dementia with Lewy bodies (DLB). Evidence exists for aSyn "strains" - conformations with distinct biological properties. However, biomarkers for PD vs. DLB, including potential aSyn strain differences, are lacking. Here, we used two monoclonal antibodies selective for different in vitro aSyn species - termed Strain A and B - to evaluate human brain tissue, cerebrospinal fluid (CSF), and plasma. Surprisingly, levels of Strain A and B aSyn species differed in plasma from individuals with PD vs. DLB in two independent cohorts. Lower plasma aSyn Strain A species also predicted subsequent PD cognitive decline. Strain A and Strain B aSyn species were undetectable in CSF, but plasma aSyn species could template aSyn fibrillization, particularly in PD. Our findings suggest that aSyn strains may impact LBD clinical presentation and originate outside the brain., Competing Interests: Competing interests: Dr Tropea has received consulting fees and honoraria from Sanofi Genzyme, Bial, and the Parkinson Foundation. The following authors declare that they have no competing interests: GTK, SA, RSA JFM, ACP, DJI, RTS, RDR, KD, VL.

The medial temporal lobe (MTL) is a hotspot for neuropathology, and measurements of MTL atrophy are often used as a biomarker for cognitive decline associated with neurodegenerative disease. Due to the aggregation of multiple proteinopathies in this region, the specific relationship of MTL atrophy to distinct neuropathologies is not well understood. Here, we develop two quantitative algorithms using deep learning to measure phosphorylated tau (p-tau) and TDP-43 (pTDP-43) pathology, which are both known to accumulate in the MTL and are associated with MTL neurodegeneration. We focus on these pathologies in the context of Alzheimer's disease (AD) and limbic predominant age-related TDP-43 encephalopathy (LATE) and apply our deep learning algorithms to distinct histology sections, on which MTL subregions were digitally annotated. We demonstrate that both quantitative pathology measures show high agreement with expert visual ratings of pathology and discriminate well between pathology stages. In 140 cases with antemortem MR imaging, we compare the association of semi-quantitative and quantitative postmortem measures of these pathologies in the hippocampus with in vivo structural measures of the MTL and its subregions. We find widespread associations of p-tau pathology with MTL subregional structural measures, whereas pTDP-43 pathology had more limited associations with the hippocampus and entorhinal cortex. Quantitative measurements of p-tau pathology resulted in a significantly better model of antemortem structural measures than semi-quantitative ratings and showed strong associations with cortical thickness and volume. By providing a more granular measure of pathology, the quantitative p-tau measures also showed a significant negative association with structure in a severe AD subgroup where semi-quantitative ratings displayed a ceiling effect. Our findings demonstrate the advantages of using quantitative neuropathology to understand the relationship of pathology to structure, particularly for p-tau, and motivate the use of quantitative pathology measurements in future studies., (© 2024. The Author(s).)

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., (© 2024 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Genetic variants and epigenetic features both contribute to the risk of Alzheimer's disease (AD). We studied the AD association of CpG-related single nucleotide polymorphisms (CGS), which act as a hub of both the genetic and epigenetic effects, in Caribbean Hispanics (CH) and generalized the findings to Non-Hispanic Whites (NHW). First, we conducted a genome-wide, sliding-window-based association with AD, in 7,155 CH and 1,283 NHW participants. Next, using data from the dorsolateral prefrontal cortex in 179 CH brains, we tested the cis- and trans-effects of AD-associated CGS on brain DNA methylation to mRNA expression. For the genes with significant cis- and trans-effects, we investigated their enriched pathways. We identified six genetic loci in CH with CGS dosage associated with AD at genome-wide significance levels: ADAM20 (Score = 55.19, P = 4.06 × 10 -8 ), the intergenic region between VRTN and SYNDIG1L (Score = - 37.67, P = 2.25 × 10 -9 ), SPG7 (16q24.3) (Score = 40.51, P = 2.23 × 10 -8 ), PVRL2 (Score = 125.86, P = 1.64 × 10 -9 ), TOMM40 (Score = - 18.58, P = 4.61 × 10 -8 ), and APOE (Score = 75.12, P = 7.26 × 10 -26 ). CGSes in PVRL2 and APOE were also significant in NHW. Except for ADAM20, CGSes in the other five loci were associated with CH brain methylation levels (mQTLs) and CGSes in SPG7, PVRL2, and APOE were also mQTLs in NHW. Except for SYNDIG1L (P = 0.08), brain methylation levels in the other five loci affected downstream mRNA expression in CH (P < 0.05), and methylation at VRTN and TOMM40 were also associated with mRNA expression in NHW. Gene expression in these six loci were also regulated by CpG sites in genes that were enriched in the neuron projection and glutamatergic synapse pathways (FDR < 0.05). DNA methylation at all six loci and mRNA expression of SYNDIG1 and TOMM40 were significantly associated with Braak Stage in CH. In summary, we identified six CpG-related genetic loci associated with AD in CH, harboring both genetic and epigenetic risks. However, their downstream effects on mRNA expression maybe ethnic specific and different from NHW., (© 2024. The Author(s).)

Background: Excessive daytime sleepiness (EDS) is a disabling symptom of Lewy body disorders (LBD). The hypothalamus is a key sleep-wake regulator, but its contribution to EDS in LBD remains unclear., Objectives: Use diffusion MRI to evaluate the relationship of hypothalamic microstructure to EDS symptoms in LBD., Methods: We studied 102 patients with clinically-defined LBD (Parkinson's disease, n=93; Parkinson's disease dementia, n=4; and dementia with Lewy bodies, n=5) and Epworth Sleepiness Scale (ESS) within 2 years of MRI. Mean diffusivity (MD) was compared between EDS+ (ESS≥10, n=37) and EDS- (ESS<10, n=65) groups in the whole hypothalamus and three subregions, covarying for age and sex. Secondary analyses tested correlations between subregion MD and continuous ESS, global cognition, and motor scores; and between subregion volume and continuous ESS., Results: MD was increased in EDS+ compared to EDS- only in the inferior tuberal subregion (Cohen's d=0.43, p=0.043, β=0.117±0.057), with trend level differences in the whole hypothalamus (Cohen's d=0.39, p=0.064, β=0.070±0.037) and superior tuberal subregion (Cohen's d=0.38, p=0.073, β=0.063±0.035). No difference was seen in the posterior subregion (Cohen's d=0.1, p=0.628, β=0.019±0.038). Significant correlations with continuous ESS were seen in MD of whole hypothalamus (r 2 =0.074, p=0.0057), superior tuberal (r 2 =0.081, p=0.0038), and inferior tuberal (r 2 =0.073, p=0.0059) subregions. There was no correlation of hypothalamic MD with global cognition or motor scores, and no correlation of whole/subregional hypothalamic volumes with ESS., Conclusions: Daytime sleepiness associates with increased MD in the inferior tuberal hypothalamus in an LBD cohort. This suggests degeneration within this region could contribute to EDS symptoms.

Behavioral variant frontotemporal dementia (bvFTD) is a clinical syndrome primarily caused by either tau (bvFTD-tau) or TDP-43 (bvFTD-TDP) proteinopathies. We previously found lower cortical layers and dorsolateral regions accumulate greater tau than TDP-43 pathology; however, patterns of laminar neurodegeneration across diverse cytoarchitecture in bvFTD is understudied. We hypothesized that bvFTD-tau and bvFTD-TDP have distinct laminar distributions of pyramidal neurodegeneration along cortical gradients, a topologic order of cytoarchitectonic subregions based on increasing pyramidal density and laminar differentiation. Here, we tested this hypothesis in a frontal cortical gradient consisting of five cytoarchitectonic types (i.e., periallocortex, agranular mesocortex, dysgranular mesocortex, eulaminate-I isocortex, eulaminate-II isocortex) spanning anterior cingulate, paracingulate, orbitofrontal, and mid-frontal gyri in bvFTD-tau (n=27), bvFTD-TDP (n=47), and healthy controls (HC; n=32). We immunostained all tissue for total neurons (NeuN; neuronal-nuclear protein) and pyramidal neurons (SMI32; non-phosphorylated neurofilament) and digitally quantified NeuN-immunoreactivity (ir) and SMI32-ir in supragranular II-III, infragranular V-VI, and all I-VI layers in each cytoarchitectonic type. We used linear mixed-effects models adjusted for demographic and biologic variables to compare SMI32-ir between groups and examine relationships with the cortical gradient, long-range pathways, and clinical symptoms. We found regional and laminar distributions of SMI32-ir expected for HC, validating our measures within the cortical gradient framework. While SMI32-ir loss was relatively uniform along the cortical gradient in bvFTD-TDP, SMI32-ir progressively decreased along the cortical gradient of bvFTD-tau and included greater SMI32-ir loss in supragranular eulaminate-II isocortex in bvFTD-tau versus bvFTD-TDP (p=0.039). Using a ratio of SMI32-ir to model known long-range connectivity between infragranular mesocortex and supragranular isocortex, we found a larger laminar ratio in bvFTD-tau versus bvFTD-TDP (p=0.019), suggesting select long-projecting pathways may contribute to isocortical-predominant degeneration in bvFTD-tau. In cytoarchitectonic types with the highest NeuN-ir, we found lower SMI32-ir in bvFTD-tau versus bvFTD-TDP (p=0.047), suggesting pyramidal neurodegeneration may occur earlier in bvFTD-tau. Lastly, we found that reduced SMI32-ir related to behavioral severity and frontal-mediated letter fluency, not temporal-mediated confrontation naming, demonstrating the clinical relevance and specificity of frontal pyramidal neurodegeneration to bvFTD-related symptoms. Our data suggest loss of neurofilament-rich pyramidal neurons is a clinically relevant feature of bvFTD that selectively worsens along a frontal cortical gradient in bvFTD-tau, not bvFTD-TDP. Therefore, tau-mediated degeneration may preferentially involve pyramidal-rich layers that connect more distant cytoarchitectonic types. Moreover, the hierarchical arrangement of cytoarchitecture along cortical gradients may be an important neuroanatomical framework for identifying which types of cells and pathways are differentially involved between proteinopathies., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Blood-based biomarkers of Alzheimer disease (AD) may facilitate testing of historically under-represented groups. The Study of Race to Understand Alzheimer Biomarkers (SORTOUT-AB) is a multi-center longitudinal study to compare AD biomarkers in participants who identify their race as either Black or white. Plasma samples from 324 Black and 1,547 white participants underwent analysis with C 2 N Diagnostics' PrecivityAD test for Aβ42 and Aβ40. Compared to white individuals, Black individuals had higher average plasma Aβ42/40 levels at baseline, consistent with a lower average level of amyloid pathology. Interestingly, this difference resulted from lower average levels of plasma Aβ40 in Black participants. Despite the differences, Black and white individuals had similar longitudinal rates of change in Aβ42/40, consistent with a similar rate of amyloid accumulation. Our results agree with multiple recent studies demonstrating a lower prevalence of amyloid pathology in Black individuals, and additionally suggest that amyloid accumulates consistently across both groups., (© 2024. The Author(s).)

The most commonly used neuroimaging biomarkers of brain structure, particularly in neurodegenerative diseases, have traditionally been summary measurements from ROIs derived from structural MRI, such as volume and thickness. Advances in MR acquisition techniques, including high-field imaging, and emergence of learning-based methods have opened up opportunities to interrogate brain structure in finer detail, allowing investigators to move beyond macrostructural measurements. On the one hand, superior signal contrast has the potential to make appearance-based metrics that directly analyze intensity patterns, such as texture analysis and radiomics features, more reliable. Quantitative MRI, particularly at high-field, can also provide a richer set of measures with greater interpretability. On the other hand, use of neural networks-based techniques has the potential to exploit subtle patterns in images that can now be mined with advanced imaging. Finally, there are opportunities for integration of multimodal data at different spatial scales that is enabled by developments in many of the above techniques-for example, by combining digital histopathology with high-resolution ex-vivo and in-vivo MRI. Some of these approaches are at early stages of development and present their own set of challenges. Nonetheless, they hold promise to drive the next generation of validation and biomarker studies. This article will survey recent developments in this area, with a particular focus on Alzheimer's disease and related disorders. However, most of the discussion is equally relevant to imaging of other neurological disorders, and even to other organ systems of interest. It is not meant to be an exhaustive review of the available literature, but rather presented as a summary of recent trends through the discussion of a collection of representative studies with an eye towards what the future may hold.

Our current understanding of the spread and neurodegenerative effects of tau neurofibrillary tangles (NFTs) within the medial temporal lobe (MTL) during the early stages of Alzheimer's Disease (AD) is limited by the presence of confounding non-AD pathologies and the two-dimensional (2-D) nature of conventional histology studies. Here, we combine ex vivo MRI and serial histological imaging from 25 human MTL specimens to present a detailed, 3-D characterization of quantitative NFT burden measures in the space of a high-resolution, ex vivo atlas with cytoarchitecturally-defined subregion labels, that can be used to inform future in vivo neuroimaging studies. Average maps show a clear anterior to poster gradient in NFT distribution and a precise, spatial pattern with highest levels of NFTs found not just within the transentorhinal region but also the cornu ammonis (CA1) subfield. Additionally, we identify granular MTL regions where measures of neurodegeneration are likely to be linked to NFTs specifically, and thus potentially more sensitive as early AD biomarkers., (© 2024. The Author(s).)

Introduction: We investigate pathological correlates of plasma phosphorylated tau 181 (p-tau 181 ), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) across a clinically diverse spectrum of neurodegenerative disease, including normal cognition (NormCog) and impaired cognition (ImpCog)., Methods: Participants were NormCog (n = 132) and ImpCog (n = 461), with confirmed β-amyloid (Aβ+/-) status (cerebrospinal fluid, positron emission tomography, autopsy) and single molecule array plasma measurements. Logistic regression and receiver operating characteristic (ROC) area under the curve (AUC) tested how combining plasma analytes discriminated Aβ+ from Aβ-. Survival analyses tested time to clinical dementia rating (global CDR) progression., Results: Multivariable models (p-tau+GFAP+NfL) had the best performance to detect Aβ+ in NormCog (ROCAUC = 0.87) and ImpCog (ROCAUC = 0.87). Survival analyses demonstrated that higher NfL best predicted faster CDR progression for both Aβ+ (hazard ratio [HR] = 2.94; p = 8.1e-06) and Aβ- individuals (HR = 3.11; p = 2.6e-09)., Discussion: Combining plasma biomarkers can optimize detection of Alzheimer's disease (AD) pathology across cognitively normal and clinically diverse neurodegenerative disease., Highlights: Participants were clinically heterogeneous, with autopsy- or biomarker-confirmed Aβ. Combining plasma p-tau 181 , GFAP, and NfL improved diagnostic accuracy for Aβ status. Diagnosis by plasma biomarkers is more accurate in amnestic AD than nonamnestic AD. Plasma analytes show independent associations with tau PET and post mortem Aβ/tau. Plasma NfL predicted longitudinal cognitive decline in both Aβ+ and Aβ- individuals., (© 2024 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Background: Volumetry of subregions in the medial temporal lobe (MTL) computed from automatic segmentation in MRI can track neurodegeneration in Alzheimer's disease. However, image quality may vary in MRI. Poor quality MR images can lead to unreliable segmentation of MTL subregions. Considering that different MRI contrast mechanisms and field strengths (jointly referred to as "modalities" here) offer distinct advantages in imaging different parts of the MTL, we developed a muti-modality segmentation model using both 7 tesla (7T) and 3 tesla (3T) structural MRI to obtain robust segmentation in poor-quality images., Method: MRI modalities including 3T T1-weighted, 3T T2-weighted, 7T T1-weighted and 7T T2-weighted (7T-T2w) of 197 participants were collected from a longitudinal aging study at the Penn Alzheimer's Disease Research Center. Among them, 7T-T2w was used as the primary modality, and all other modalities were rigidly registered to the 7T-T2w. A model derived from nnU-Net took these registered modalities as input and outputted subregion segmentation in 7T-T2w space. 7T-T2w images most of which had high quality from 25 selected training participants were manually segmented to train the multi-modality model. Modality augmentation, which randomly replaced certain modalities with Gaussian noise, was applied during training to guide the model to extract information from all modalities. To compare our proposed model with a baseline single-modality model in the full dataset with mixed high/poor image quality, we evaluated the ability of derived volume/thickness measures to discriminate Amyloid+ mild cognitive impairment (A+MCI) and Amyloid- cognitively unimpaired (A-CU) groups, as well as the stability of these measurements in longitudinal data., Results: The multi-modality model delivered good performance regardless of 7T-T2w quality, while the single-modality model under-segmented subregions in poor-quality images. The multi-modality model generally demonstrated stronger discrimination of A+MCI versus A-CU. Intra-class correlation and Bland-Altman plots demonstrate that the multi-modality model had higher longitudinal segmentation consistency in all subregions while the single-modality model had low consistency in poor-quality images., Conclusion: The multi-modality MRI segmentation model provides an improved biomarker for neurodegeneration in the MTL that is robust to image quality. It also provides a framework for other studies which may benefit from multimodal imaging., Competing Interests: Declaration of Competing Interests D.A.W. has served as a paid consultant to Eli Lilly, GE Healthcare, Merck, Janssen and Qynapse. He serves on a DSMB for Functional Neuromodulation. He received grants from Eli Lilly/Avid Radiopharmaceuticals, Merck and Biogen. He is also now on a DSMB for GSK. S.R.D. received consultation fees from Rancho Biosciences and Nia Therapeutics. L.X. is a paid employee of Siemens Healthineers. He received personal consulting fees from Galileo CDS, Inc. L.E.M.W. was supported by MultiPark, a strategic research area at Lund University.

Postmortem MRI allows brain anatomy to be examined at high resolution and to link pathology measures with morphometric measurements. However, automated segmentation methods for brain mapping in postmortem MRI are not well developed, primarily due to limited availability of labeled datasets, and heterogeneity in scanner hardware and acquisition protocols. In this work, we present a high-resolution dataset of 135 postmortem human brain tissue specimens imaged at 0.3 mm 3 isotropic using a T2w sequence on a 7T whole-body MRI scanner. We developed a deep learning pipeline to segment the cortical mantle by benchmarking the performance of nine deep neural architectures, followed by post-hoc topological correction. We evaluate the reliability of this pipeline via overlap metrics with manual segmentation in 6 specimens, and intra-class correlation between cortical thickness measures extracted from the automatic segmentation and expert-generated reference measures in 36 specimens. We also segment four subcortical structures (caudate, putamen, globus pallidus, and thalamus), white matter hyperintensities, and the normal appearing white matter, providing a limited evaluation of accuracy. We show generalizing capabilities across whole-brain hemispheres in different specimens, and also on unseen images acquired at 0.28 mm 3 and 0.16 mm 3 isotropic T2*w fast low angle shot (FLASH) sequence at 7T. We report associations between localized cortical thickness and volumetric measurements across key regions, and semi-quantitative neuropathological ratings in a subset of 82 individuals with Alzheimer's disease (AD) continuum diagnoses. Our code, Jupyter notebooks, and the containerized executables are publicly available at the project webpage (https://pulkit-khandelwal.github.io/exvivo-brain-upenn/)., Competing Interests: David A. Wolk has received grant support from Merck, Biogen, and Eli Lilly/Avid. David A. Wolk received consultation fees from Neuronix, Eli Lilly, and Qynaps and is on the Data and Safety Monitoring Board for a clinical trial run by Functional Neuromodulation. John Q. Trojanowski received revenue from the sale of Avid to Eli Lilly as co-inventor on imaging-related patents submitted by the University of Pennsylvania. David J. Irwin is member of the science advisory board of Denali Therapeutics. Sandhitsu R. Das received consultation fees from Rancho Biosciences and Nia Therapeutics. The other authors have nothing to disclose., (© 2024 Massachusetts Institute of Technology. Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.)

Introduction: Individuals in socioeconomically disadvantaged neighborhoods exhibit increased risk for impaired cognitive function. Whether this association relates to the major dementia-related neuropathologies is unknown., Methods: This cross-sectional study included 469 autopsy cases from 2011 to 2023. The relationships between neighborhood disadvantage measured by Area Deprivation Index (ADI) percentiles categorized into tertiles, cognition evaluated by the last Mini-Mental State Examination (MMSE) scores before death, and 10 dementia-associated proteinopathies and cerebrovascular disease were assessed using regression analyses., Results: Higher ADI was significantly associated with lower MMSE score. This was mitigated by increasing years of education. ADI was not associated with an increase in dementia-associated neuropathologic change. Moreover, the significant association between ADI and cognition remained even after controlling for changes in major dementia-associated proteinopathies or cerebrovascular disease., Discussion: Neighborhood disadvantage appears to be associated with decreased cognitive reserve. This association is modified by education but is independent of the major dementia-associated neuropathologies., (© 2024 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: Multimodal evidence indicates Alzheimer's disease (AD) is characterized by early white matter (WM) changes that precede overt cognitive impairment. WM changes have overwhelmingly been investigated in typical, amnestic mild cognitive impairment and AD; fewer studies have addressed WM change in atypical, non-amnestic syndromes. We hypothesized each non-amnestic AD syndrome would exhibit WM differences from amnestic and other non-amnestic syndromes., Materials and Methods: Participants included 45 cognitively normal (CN) individuals; 41 amnestic AD patients; and 67 patients with non-amnestic AD syndromes including logopenic-variant primary progressive aphasia (lvPPA, n = 32), posterior cortical atrophy (PCA, n = 17), behavioral variant AD (bvAD, n = 10), and corticobasal syndrome (CBS, n = 8). All had T1-weighted MRI and 30-direction diffusion-weighted imaging (DWI). We performed whole-brain deterministic tractography between 148 cortical and subcortical regions; connection strength was quantified by tractwise mean generalized fractional anisotropy. Regression models assessed effects of group and phenotype as well as associations with grey matter volume. Topological analyses assessed differences in persistent homology (numbers of graph components and cycles). Additionally, we tested associations of topological metrics with global cognition, disease duration, and DWI microstructural metrics., Results: Both amnestic and non-amnestic patients exhibited lower WM connection strength than CN participants in corpus callosum, cingulum, and inferior and superior longitudinal fasciculi. Overall, non-amnestic patients had more WM disease than amnestic patients. LvPPA patients had left-lateralized WM degeneration; PCA patients had reductions in connections to bilateral posterior parietal, occipital, and temporal areas. Topological analysis showed the non-amnestic but not the amnestic group had more connected components than controls, indicating persistently lower connectivity. Longer disease duration and cognitive impairment were associated with more connected components and fewer cycles in individuals' brain graphs., Discussion: We have previously reported syndromic differences in GM degeneration and tau accumulation between AD syndromes; here we find corresponding differences in WM tracts connecting syndrome-specific epicenters. Determining the reasons for selective WM degeneration in non-amnestic AD is a research priority that will require integration of knowledge from neuroimaging, biomarker, autopsy, and functional genetic studies. Furthermore, longitudinal studies to determine the chronology of WM vs. GM degeneration will be key to assessing evidence for WM-mediated tau spread., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Phillips, Adluru, Chung, Radhakrishnan, Olm, Cook, Gee, Cousins, Arezoumandan, Wolk, McMillan, Grossman and Irwin.)

We used indirect brain mapping with virtual lesion tractography to test the hypothesis that the extent of white matter tract disconnection due to white matter hyperintensities (WMH) is associated with corresponding tract-specific cognitive performance decrements. To estimate tract disconnection, WMH masks were extracted from FLAIR MRI data of 481 cognitively intact participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) and used as regions of avoidance for fiber tracking in diffusion MRI data from 50 healthy young participants from the Human Connectome Project. Estimated tract disconnection in the right inferior fronto-occipital fasciculus, right frontal aslant tract, and right superior longitudinal fasciculus mediated the effects of WMH volume on executive function. Estimated tract disconnection in the left uncinate fasciculus mediated the effects of WMH volume on memory and in the right frontal aslant tract on language. In a subset of ADNI control participants with amyloid data, positive status increased the probability of periventricular WMH and moderated the relationship between WMH burden and tract disconnection in executive function performance., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Introduction: Variability in relationship of tau-based neurofibrillary tangles (T) and neurodegeneration (N) in Alzheimer's disease (AD) arises from non-specific nature of N, modulated by non-AD co-pathologies, age-related changes, and resilience factors., Methods: We used regional T-N residual patterns to partition 184 patients within the Alzheimer's continuum into data-driven groups. These were compared with groups from 159 non-AD (amyloid "negative") patients partitioned using cortical thickness, and groups in 98 patients with ante mortem MRI and post mortem tissue for measuring N and T, respectively. We applied the initial T-N residual model to classify 71 patients in an independent cohort into predefined groups., Results: AD groups displayed spatial T-N mismatch patterns resembling neurodegeneration patterns in non-AD groups, similarly associated with non-AD factors and diverging cognitive outcomes. In the autopsy cohort, limbic T-N mismatch correlated with TDP-43 co-pathology., Discussion: T-N mismatch may provide a personalized approach for determining non-AD factors associated with resilience/vulnerability in AD., (© 2023 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Objective: Alzheimer's disease neuropathologic change and alpha-synucleinopathy commonly co-exist and contribute to the clinical heterogeneity of dementia. Here, we examined tau epitopes marking various stages of tangle maturation to test the hypotheses that tau maturation is more strongly associated with beta-amyloid compared to alpha-synuclein, and within the context of mixed pathology, mature tau is linked to Alzheimer's disease clinical phenotype and negatively associated with Lewy body dementia., Methods: We used digital histology to measure percent area-occupied by pathology in cortical regions among individuals with pure Alzheimer's disease neuropathologic change, pure alpha-synucleinopathy, and a co-pathology group with both Alzheimer's and alpha-synuclein pathologic diagnoses. Multiple tau monoclonal antibodies were used to detect early (AT8, MC1) and mature (TauC3) epitopes of tangle progression. We used linear/logistic regression to compare groups and test the association between pathologies and clinical features., Results: There were lower levels of tau pathology (β = 1.86-2.96, p < 0.001) across all tau antibodies in the co-pathology group compared to the pure Alzheimer's pathology group. Among individuals with alpha-synucleinopathy, higher alpha-synuclein was associated with greater early tau (AT8 β = 1.37, p < 0.001; MC1 β = 1.2, p < 0.001) but not mature tau (TauC3 p = 0.18), whereas mature tau was associated with beta-amyloid (β = 0.21, p = 0.01). Finally, lower tau, particularly TauC3 pathology, was associated with lower frequency of both core clinical features and categorical clinical diagnosis of dementia with Lewy bodies., Interpretation: Mature tau may be more closely related to beta-amyloidosis than alpha-synucleinopathy, and pathophysiological processes of tangle maturation may influence the clinical features of dementia in mixed Lewy-Alzheimer's pathology., (© 2024 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Mixed pathologies are common in neurodegenerative disease; however, antemortem imaging rarely captures copathologic effects on brain atrophy due to a lack of validated biomarkers for non-Alzheimer's pathologies. We leveraged a dataset comprising antemortem MRI and postmortem histopathology to assess polypathologic associations with atrophy in a clinically heterogeneous sample of 125 human dementia patients (41 female, 84 male) with T1-weighted MRI ≤ 5 years before death and postmortem ordinal ratings of amyloid-[Formula: see text], tau, TDP-43, and [Formula: see text]-synuclein. Regional volumes were related to pathology using linear mixed-effects models; approximately 25% of data were held out for testing. We contrasted a polypathologic model comprising independent factors for each proteinopathy with two alternatives: a model that attributed atrophy entirely to the protein(s) associated with the patient's primary diagnosis and a protein-agnostic model based on the sum of ordinal scores for all pathology types. Model fits were evaluated using log-likelihood and correlations between observed and fitted volume scores. Additionally, we performed exploratory analyses relating atrophy to gliosis, neuronal loss, and angiopathy. The polypathologic model provided superior fits in the training and testing datasets. Tau, TDP-43, and [Formula: see text]-synuclein burden were inversely associated with regional volumes, but amyloid-[Formula: see text] was not. Gliosis and neuronal loss explained residual variance in and mediated the effects of tau, TDP-43, and [Formula: see text]-synuclein on atrophy. Regional brain atrophy reflects not only the primary molecular pathology but also co-occurring proteinopathies; inflammatory immune responses may independently contribute to degeneration. Our findings underscore the importance of antemortem biomarkers for detecting mixed pathology., (Copyright © 2024 the authors.)

Background: Posterior cortical atrophy is a rare syndrome characterised by early, prominent, and progressive impairment in visuoperceptual and visuospatial processing. The disorder has been associated with underlying neuropathological features of Alzheimer's disease, but large-scale biomarker and neuropathological studies are scarce. We aimed to describe demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy in a large international cohort., Methods: We searched PubMed between database inception and Aug 1, 2021, for all published research studies on posterior cortical atrophy and related terms. We identified research centres from these studies and requested deidentified, individual participant data (published and unpublished) that had been obtained at the first diagnostic visit from the corresponding authors of the studies or heads of the research centres. Inclusion criteria were a clinical diagnosis of posterior cortical atrophy as defined by the local centre and availability of Alzheimer's disease biomarkers (PET or CSF), or a diagnosis made at autopsy. Not all individuals with posterior cortical atrophy fulfilled consensus criteria, being diagnosed using centre-specific procedures or before development of consensus criteria. We obtained demographic, clinical, biofluid, neuroimaging, and neuropathological data. Mean values for continuous variables were combined using the inverse variance meta-analysis method; only research centres with more than one participant for a variable were included. Pooled proportions were calculated for binary variables using a restricted maximum likelihood model. Heterogeneity was quantified using I 2 ., Findings: We identified 55 research centres from 1353 papers, with 29 centres responding to our request. An additional seven centres were recruited by advertising via the Alzheimer's Association. We obtained data for 1092 individuals who were evaluated at 36 research centres in 16 countries, the other sites having not responded to our initial invitation to participate to the study. Mean age at symptom onset was 59·4 years (95% CI 58·9-59·8; I 2 =77%), 60% (56-64; I 2 =35%) were women, and 80% (72-89; I 2 =98%) presented with posterior cortical atrophy pure syndrome. Amyloid β in CSF (536 participants from 28 centres) was positive in 81% (95% CI 75-87; I 2 =78%), whereas phosphorylated tau in CSF (503 participants from 29 centres) was positive in 65% (56-75; I 2 =87%). Amyloid-PET (299 participants from 24 centres) was positive in 94% (95% CI 90-97; I 2 =15%), whereas tau-PET (170 participants from 13 centres) was positive in 97% (93-100; I 2 =12%). At autopsy (145 participants from 13 centres), the most frequent neuropathological diagnosis was Alzheimer's disease (94%, 95% CI 90-97; I 2 =0%), with common co-pathologies of cerebral amyloid angiopathy (71%, 54-88; I 2 =89%), Lewy body disease (44%, 25-62; I 2 =77%), and cerebrovascular injury (42%, 24-60; I 2 =88%)., Interpretation: These data indicate that posterior cortical atrophy typically presents as a pure, young-onset dementia syndrome that is highly specific for underlying Alzheimer's disease pathology. Further work is needed to understand what drives cognitive vulnerability and progression rates by investigating the contribution of sex, genetics, premorbid cognitive strengths and weaknesses, and brain network integrity., Funding: None., Competing Interests: Declaration of interests MC received research support from the Fonds de Recherche du Québec–Santé (FRQS). MF, FA, EC, FC, and GM receive research support from the Foundation Research on Alzheimer Disease and Italian Ministry of Healthy (#GR-2010-2303035). MEM receives research support from the NIH (R01 AG054449, R01 AG075802, U01-AG057195 and P30 AG062677). Data from Mayo Clinic (Jacksonville) was supported by the State of Florida Alzheimer's Disease Initiative and the Mayo Clinic Alzheimer's Disease Research Center. BD receives research funding from NIA R21-AG051987, P50-AG005134, and R01-DC014296 and philanthropic funding to the MGH FTD Unit including the Mooney Family Fund. KY is an Etherington posterior cortical atrophy Senior Research Fellow and is funded by the Alzheimer's Society, grant number 453 (AS-JF-18-003). The work was also supported by an Alzheimer's Research UK Senior Research Fellowship and ESRC/NIHR (ES/L001810/1) grant to SC. JMS acknowledges the support of the National Institute for Health Research University College London Hospitals Biomedical Research Centre, ARUK (ARUK-PG2017–1946), Weston Brain Institute (UB170045), Medical Research Council, and British Heart Foundation. TL is supported by an Alzheimer's Research UK senior fellowship. The Queen Square Brain Bank is supported by the Reta Lila Weston Institute for Neurological Studies and the Medical Research Council. The Dementia Research Centre is supported by Alzheimer's Research UK, Brain Research Trust, and The Wolfson Foundation. This work was also supported by the NIHR Queen Square Dementia Biomedical Research Unit, and the NIHR UCL/H Biomedical Research Centre. This work was supported by the MRC Dementia Platform UK and the UK Dementia Research Institute at UCL, which receives its funding from UK DRI, funded by the UK Medical Research Council, Alzheimer's Society and Alzheimer's Research UK. DG, AH, and GL receive research support from Shiley-Marcos ADRC P30 AG062429. KJ, JW, and JGR receive research funding from the NIH (R01-AG50603). BDCB receives funding from Alzheimer Nederland (#WE.15-2019-13, WE.03-2021-15, and #WE.06-2023-01). MM, JR, and KA were supported by the NIHR Cambridge Biomedical Research Centre including the Cambridge Brain Bank (BRC-1215-20014. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care) and the Race Against Dementia. M.F.M. receives research support from the NIA (1RF1AG050967). RM is supported by France Alzheimer, Fondation Recherche Alzheimer, Philippe Chatrier Foundation and by Rosita Gomez Association. OH has acquired research support (for the institution) from ADx, AVID Radiopharmaceuticals, Biogen, Eli Lilly, Eisai, Fujirebio, GE Healthcare, Pfizer, and Roche and has received consultancy or speaker fees from AC Immune, Amylyx, Alzpath, BioArctic, Biogen, Cerveau, Fujirebio, Genentech, Novartis, Roche, and Siemens. Work at the Lund University was supported by the Swedish Research Council (2016-00906), the Knut and Alice Wallenberg foundation (2017-0383), the Marianne and Marcus Wallenberg foundation (2015·0125), the Strategic Research Area MultiPark (Multidisciplinary Research in Parkinson's disease) at Lund University, the Swedish Alzheimer Foundation (AF-939932), the Swedish Brain Foundation (FO2021-0293), The Parkinson foundation of Sweden (1280/20), the Konung Gustaf V:s och Drottning Victorias Frimurarestiftelse, the Skåne University Hospital Foundation (2020-O000028), Regionalt Forskningsstöd (2020-0314), and the Swedish federal Government under the ALF agreement (2018-Projekt0279). PN is supported by The Mater Foundation. DP, SPC, and GT are supported by The Italian Ministry of Health (Ricerca Finalizzata Progetto Reti Nazionale AD NET-2011-02346784). OP, NC, JB, JH, and DF were supported by funding to ForeFront, a collaborative research group dedicated to the study of frontotemporal dementia and motor neuron disease, from the National Health and Medical Research Council (NHMRC) (GNT1037746) and the Australian Research Council (ARC) Centre of Excellence in Cognition and its Disorders Memory Program (CE11000102). OP is supported by an NHMRC Leadership Fellowship (GNT2008020). LA receives research support from Indiana Alzheimer's Disease Research Center (P30 AG010133 and LEADS (U01AG6057195). ER, SW, and MM received research support from the NIH (P30AG13854 and P30AG072977). BDCB receives funding from Alzheimer Nederland (#WE.15-2019-13, WE.03-2021-15, and #WE.06-2023-01). Data from Geneva was supported by Alzheimer's Disease Research Center (ADRC) grants (NIA P50 AG005138 and P30 AG066514). Data from Xuanwu Hospital was supported by the National Natural Science Foundation of China (81971011) and Beijing Municipal Science and Technology Committee (7202060). Research of Alzheimer Center Amsterdam has been funded by ZonMW, NWO, EU-FP7, EU-JPND, Alzheimer Nederland, Hersenstichting CardioVascular Onderzoek Nederland, Health Holland, Topsector Life Sciences & Health, stichting Dioraphte, Gieskes-Strijbis fonds, stichting Equilibrio, Edwin Bouw fonds, Pasman stichting, stichting Alzheimer & Neuropsychiatrie Foundation, Philips, Biogen MA, Novartis-NL, Life-MI, AVID, Roche BV, Fujifilm, and Combinostics. Data from Penn Frontotemporal Degeneration Center was funded by NIH grants (R01-AG054519 and K01-AG061277). Data from MASS's group comes from The Sant Pau Initiative on Neurodegeneration cohort. LTG receives research support from the NIH (K24053435) and R01AG075802. GDR receives research support from the NIH/NIA (R35 AG072362, P30-AG062422, U01-AG057195, and P01-AG019724). Other support to GDR includes National Institute of Neurological Disorders and Stroke, Alzheimer's Association, American College of Radiology, Rainwater Charitable Foundation, Shanendoah Foundation, Avid Radiopharmaceuticals, GE Healthcare, Life Molecular Imaging, and Genentech. LA has received personal compensation for serving as a consultant for Biogen, Two Labs, FL Dept Health, Genentech, NIH Biobank, Eli Lilly, GE Healthcare, Eisai, and Roche Diagnostics and for serving on a Data Safety and Monitoring Board for IQVIA. LA receives research support from the National Institute on Aging, the Alzheimer's Association, Roche Diagnostics, AVID radiopharmaceuticals, Life Molecular Imaging, and Eli Lilly. MFM is the section editor for Behavioral Neurology for UpToDate. JGR serves on the Drug Safety Monitoring Board for the National Institute of Neurological Disorders and Stroke StrokeNET. KAJ is an Associate Editor for Annals of Clinical and Translational Neurology and is on the editorial boards of Journal of Neurology, Acta Neuropathologica, and Neuropathology and Applied Neurobiology. JLW is an Associate Editor for Brain Connectivity and Journal of Alzheimer's Disease. RO has received research support from Avid Radiopharmaceuticals, has given lectures in symposia sponsored by GE Healthcare and is an editorial board member of Alzheimer's Research & Therapy and the European Journal of Nuclear Medicine and Molecular Imaging. FA is Associate Editor of NeuroImage: Clinical, has received speaker honoraria from Biogen Idec, Italfarmaco, Roche and Zambon, and receives or has received research supports from the Italian Ministry of Health, the Italian Ministry of University and Research, AriSLA (Fondazione Italiana di Ricerca per la SLA), and the European Research Council and Foundation Research on Alzheimer Disease. MF is Editor-in-Chief of the Journal of Neurology, Associate Editor of Human Brain Mapping, Neurological Sciences, and Radiology; received compensation for consulting services from Alexion, Almirall, Biogen, Merck, Novartis, Roche, and Sanofi; speaking activities from Bayer, Biogen, Celgene, Chiesi Italia SpA, Eli Lilly, Genzyme, Janssen, Merck-Serono, Neopharmed Gentili, Novartis, Novo Nordisk, Roche, Sanofi, Takeda, and TEVA; participation in Advisory Boards for Alexion, Biogen, Bristol-Myers Squibb, Merck, Novartis, Roche, Sanofi, Sanofi-Aventis, Sanofi-Genzyme, and Takeda; scientific direction of educational events for Biogen, Merck, Roche, Celgene, Bristol-Myers Squibb, Lilly, Novartis, and Sanofi-Genzyme; and receives research support from Biogen Idec, Merck-Serono, Novartis, Roche, Italian Ministry of Health, and Fondazione Italiana Sclerosi Multipla. GDR has served on Scientific Advisory Boards for Alector, Eli Lilly, Genentech, Merck, and Roche. He serves on a Data Safety and Monitoring Board for Johnson & Johnson. He is an Associate Editor for JAMA Neurology. The other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Evaluating correlations between disease biomarkers and clinical outcomes is crucial in biomedical research. During the early stages of many chronic diseases, changes in biomarkers and clinical outcomes are often subtle. A major challenge to detecting subtle correlations is that studies with large sample sizes are usually needed to achieve sufficient statistical power. This challenge is even greater when biofluid and imaging biomarker data are used because the required procedures are burdensome, perceived as invasive, and/or expensive, limiting sample sizes in individual studies. Combining data across multiple studies may increase statistical power, but biomarker data may be generated using different assay platforms, scanner types, or processing protocols, which may affect measured biomarker values. Therefore, harmonizing biomarker data is essential to combining data across studies. Bridging studies involve re-processing of a subset of samples or imaging scans to evaluate how biomarker values vary by studies. This presents an analytic challenge on how to best harmonize biomarker data across studies to allow unbiased and optimal estimates of their correlations with standardized clinical outcomes. We conceptualize that a latent biomarker underlies the observed biomarkers across studies, and propose a novel approach that integrates the data in the bridging study with the study-specific biomarker data for estimating the biological correlations between biomarkers and clinical outcomes. Through extensive simulations, we compare our method to several alternative methods/algorithms often used to estimate the correlations. Finally, we demonstrate the application of this methodology to a real-world multi-center Alzheimer's disease biomarker study to correlate cerebrospinal fluid biomarker concentrations with cognitive outcomes., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Disease heterogeneity has been a critical challenge for precision diagnosis and treatment, especially in neurologic and neuropsychiatric diseases. Many diseases can display multiple distinct brain phenotypes across individuals, potentially reflecting disease subtypes that can be captured using MRI and machine learning methods. However, biological interpretability and treatment relevance are limited if the derived subtypes are not associated with genetic drivers or susceptibility factors. Herein, we describe Gene-SGAN - a multi-view, weakly-supervised deep clustering method - which dissects disease heterogeneity by jointly considering phenotypic and genetic data, thereby conferring genetic correlations to the disease subtypes and associated endophenotypic signatures. We first validate the generalizability, interpretability, and robustness of Gene-SGAN in semi-synthetic experiments. We then demonstrate its application to real multi-site datasets from 28,858 individuals, deriving subtypes of Alzheimer's disease and brain endophenotypes associated with hypertension, from MRI and single nucleotide polymorphism data. Derived brain phenotypes displayed significant differences in neuroanatomical patterns, genetic determinants, biological and clinical biomarkers, indicating potentially distinct underlying neuropathologic processes, genetic drivers, and susceptibility factors. Overall, Gene-SGAN is broadly applicable to disease subtyping and endophenotype discovery, and is herein tested on disease-related, genetically-associated neuroimaging phenotypes., (© 2024. The Author(s).)

Spatial normalization-the process of mapping subject brain images to an average template brain-has evolved over the last 20+ years into a reliable method that facilitates the comparison of brain imaging results across patients, centers & modalities. While overall successful, sometimes, this automatic process yields suboptimal results, especially when dealing with brains with extensive neurodegeneration and atrophy patterns, or when high accuracy in specific regions is needed. Here we introduce WarpDrive, a novel tool for manual refinements of image alignment after automated registration. We show that the tool applied in a cohort of patients with Alzheimer's disease who underwent deep brain stimulation surgery helps create more accurate representations of the data as well as meaningful models to explain patient outcomes. The tool is built to handle any type of 3D imaging data, also allowing refinements in high-resolution imaging, including histology and multiple modalities to precisely aggregate multiple data sources together., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: A.H. reports a relationship with Boston Scientific Corporation that includes: speaking and lecture fees. L.A. reports a relationship with Boston Scientific Corporation that includes: consulting or advisory. L.A. reports a relationship with Medtronic that includes: consulting or advisory. K.F. reports a relationship with Medtronic that includes: consulting or advisory. K.F. reports a relationship with Boston Scientific Corporation that includes: consulting or advisory. K.F. reports a relationship with Abbott that includes: funding grants. K.F. reports a relationship with Functional Neuromodulation that includes: funding grants. D.W. reports a relationship with Functional Neuromodulation that includes: funding grants. D.W. reports a relationship with Avid Lily that includes: funding grants. D.W. reports a relationship with Merck that includes: funding grants. D.W. reports a relationship with Jannsen that includes: consulting or advisory. D.W. reports a relationship with GE Healthcare that includes: consulting or advisory. D.W. reports a relationship with Biogen that includes: consulting or advisory. D.W. reports a relationship with Neuronix that includes: consulting or advisory. S.S. reports a relationship with Elsai that includes: consulting or advisory. S.S. reports a relationship with Lilly that includes: consulting or advisory. S.S. reports a relationship with Roche that includes: consulting or advisory. S.S. reports a relationship with Novartis that includes: consulting or advisory. S.S. reports a relationship with Biogen that includes: consulting or advisory. G.S. reports a relationship with NIH that includes: funding grants. M.S. reports a relationship with Allergan that includes: consulting or advisory. M.S. reports a relationship with Biogen that includes: consulting or advisory. M.S. reports a relationship with Roche that includes: consulting or advisory. M.S. reports a relationship with Cortexyme that includes: consulting or advisory. M.S. reports a relationship with Bracket that includes: consulting or advisory. M.S. reports a relationship with Brain Health Inc that includes: consulting or advisory. M.S. reports a relationship with uMethod Health that includes: consulting or advisory. C.L. reports a relationship with Functional Neuromodulation that includes: funding grants. C.L. reports a relationship with Avanir that includes: funding grants. C.L. reports a relationship with Eli Lily that includes: funding grants. C.L. reports a relationship with NFL Benefits Office that includes: funding grants. M.O. reports a relationship with NIH that includes: funding grants. M.O. reports a relationship with Tourette Association of America Grant that includes: funding grants. M.O. reports a relationship with Parkinson's Alliance that includes: funding grants. M.O. reports a relationship with Smallwood Foundation that includes: funding grants. M.O. reports a relationship with Parkinson's Foundation Medical Director that includes: consulting or advisory. M.O. reports a relationship with Books4Patients that includes: consulting or advisory. M.O. reports a relationship with American Academy of Neurology that includes: consulting or advisory. M.O. reports a relationship with Peerview that includes: consulting or advisory. M.O. reports a relationship with WebMD Medscape that includes: consulting or advisory. M.O. reports a relationship with Mededicus that includes: consulting or advisory. M.O. reports a relationship with Movement Disorders Society that includes: consulting or advisory. M.O. reports a relationship with Taylor and Francis that includes: consulting or advisory. M.O. reports a relationship with Demos that includes: consulting or advisory. M.O. reports a relationship with Robert Rose that includes: consulting or advisory. M.O. reports a relationship with Medtronic that includes: non-financial support. A.L. reports a relationship with Medtronic that includes: funding grants. A.L. reports a relationship with Functional Neuromodulation that includes: funding grants. A.L. reports a relationship with Medtronic that includes: consulting or advisory. A.L. reports a relationship with St. Jude that includes: consulting or advisory. A.L. reports a relationship with Boston Scientific that includes: consulting or advisory. A.L. has patent #US Patent 8346,365 licensed to Functional Neuromodulation., (Copyright © 2023. Published by Elsevier B.V.)

With recent data demonstrating that lecanemab treatment can slow cognitive and functional decline in early symptomatic Alzheimer disease (AD), it is widely anticipated that this drug and potentially other monoclonal antibody infusions targeting β-amyloid protein will imminently be realistic options for some patients with AD. Given that these new antiamyloid monoclonal antibodies (mAbs) are associated with nontrivial risks and burdens of treatment that are radically different from current mainstays of AD management, effectively and equitably translating their use to real-world clinical care will require systematic and practice-specific modifications to existing workflows and infrastructure. In this Emerging Issues in Neurology article, we provide practical guidance for a wide audience of neurology clinicians on logistic adaptations and decision making around emerging antiamyloid mAbs. Specifically, we briefly summarize the rationale and available evidence supporting antiamyloid mAb use in AD to facilitate appropriate communication with patients and care partners on potential benefits. We also discuss pragmatic approaches to optimizing patient selection and treatment monitoring, with a particular focus on the value of incorporating shared decision making and multidisciplinary collaboration. In addition, we review some of the recognized limitations of current knowledge and highlight areas of future evolution to guide the development of sustainable and flexible models for treatment and follow-up. As the field enters a new era with disease-modifying treatment options for AD, it will be critical for neurology practices to prepare and continually innovate to ensure optimal outcomes for patients., (© 2023 American Academy of Neurology.)