A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers

Plasma pTau-217 and N-terminal tau (NTA) enhance sensitivity to identify tau PET positivity in amyloid-β positive individuals

INTRODUCTION

We set out to identify tau PET-positive (A+T+) individuals among amyloid-beta (Aβ) positive participants using plasma biomarkers.

METHODS

In this cross-sectional study we assessed 234 participants across the AD continuum who were evaluated by amyloid PET with [18 F]AZD4694 and tau-PET with [18 F]MK6240 and measured plasma levels of total tau, pTau-181, pTau-217, pTau-231, and N-terminal tau (NTA-tau). We evaluated the performances of plasma biomarkers to predict tau positivity in Aβ+ individuals.

RESULTS

Highest associations with tau positivity in Aβ+ individuals were found for plasma pTau-217 (AUC [CI95% ] = 0.89 [0.82, 0.96]) and NTA-tau (AUC [CI95% ] = 0.88 [0.91, 0.95]). Combining pTau-217 and NTA-tau resulted in the strongest agreement (Cohen's Kappa = 0.74, CI95%  = 0.57/0.90, sensitivity = 92%, specificity = 81%) with PET for classifying tau positivity.

DISCUSSION

The potential for identifying tau accumulation in later Braak stages will be useful for patient stratification and prognostication in treatment trials and in clinical practice.

HIGHLIGHTS

We found that in a cohort without pre-selection pTau-181, pTau-217, and NTA-tau showed the highest association with tau PET positivity. We found that in Aβ+ individuals pTau-217 and NTA-tau showed the highest association with tau PET positivity. Combining pTau-217 and NTA-tau resulted in the strongest agreement with the tau PET-based classification.

Different aspects of failing to recover from proactive semantic interference predicts rate of progression from amnestic mild cognitive impairment to dementia

Introduction

This study investigated the role of proactive semantic interference (frPSI) in predicting the progression of amnestic Mild Cognitive Impairment (aMCI) to dementia, taking into account various cognitive and biological factors.

Methods

The research involved 89 older adults with aMCI who underwent baseline assessments, including amyloid PET and MRI scans, and were followed longitudinally over a period ranging from 12 to 55 months (average 26.05 months).

Results

The findings revealed that more than 30% of the participants diagnosed with aMCI progressed to dementia during the observation period. Using Cox Proportional Hazards modeling and adjusting for demographic factors, global cognitive function, hippocampal volume, and amyloid positivity, two distinct aspects of frPSI were identified as significant predictors of a faster decline to dementia. These aspects were fewer correct responses on a frPSI trial and a higher number of semantic intrusion errors on the same trial, with 29.5% and 31.6 % increases in the likelihood of more rapid progression to dementia, respectively.

Discussion

These findings after adjustment for demographic and biological markers of Alzheimer's Disease, suggest that assessing frPSI may offer valuable insights into the risk of dementia progression in individuals with aMCI.

Electrochemically Synthesized MIP Sensors: Applications in Healthcare Diagnostics

Early-stage detection and diagnosis of diseases is essential to the prompt commencement of treatment regimens, curbing the spread of the disease, and improving human health. Thus, the accurate detection of disease biomarkers through the development of robust, sensitive, and selective diagnostic tools has remained cutting-edge scientific research for decades. Due to their merits of being selective, stable, simple, and having a low preparation cost, molecularly imprinted polymers (MIPs) are increasingly becoming artificial substitutes for natural receptors in the design of state-of-the-art sensing devices. While there are different MIP preparation approaches, electrochemical synthesis presents a unique and outstanding method for chemical sensing applications, allowing the direct formation of the polymer on the transducer as well as simplicity in tuning the film properties, thus accelerating the trend in the design of commercial MIP-based sensors. This review evaluates recent achievements in the applications of electrosynthesized MIP sensors for clinical analysis of disease biomarkers, identifying major trends and highlighting interesting perspectives on the realization of commercial MIP-endowed testing devices for rapid determination of prevailing diseases.

Influence of Physiological Variables and Comorbidities on Plasma Aβ40, Aβ42, and p-tau181 Levels in Cognitively Unimpaired Individuals

Plasma biomarkers for Alzheimer's disease (AD) are a promising tool that may help in early diagnosis. However, their levels may be influenced by physiological parameters and comorbidities that should be considered before they can be used at the population level. For this purpose, we assessed the influences of different comorbidities on AD plasma markers in 208 cognitively unimpaired subjects. We analyzed both plasma and cerebrospinal fluid levels of Aβ40, Aβ42, and p-tau181 using the fully automated Lumipulse platform. The relationships between the different plasma markers and physiological variables were studied using linear regression models. The mean differences in plasma markers according to comorbidity groups were also studied. The glomerular filtration rate showed an influence on plasma Aβ40 and Aβ42 levels but not on the Aβ42/Aβ40 ratio. The amyloid ratio was significantly lower in diabetic and hypertensive subjects, and the mean p-tau181 levels were higher in hypertensive subjects. The glomerular filtration rate may have an inverse relationship on plasma Aβ40 and Aβ42 levels but not on the amyloid ratio, suggesting that the latter is a more stable marker to use in the general population. Cardiovascular risk factors might have a long-term effect on the amyloid ratio and plasma levels of p-tau181.

Exploring small non-coding RNAs as blood-based biomarkers to predict Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) diagnosis relies on clinical symptoms complemented with biological biomarkers, the Amyloid Tau Neurodegeneration (ATN) framework. Small non-coding RNA (sncRNA) in the blood have emerged as potential predictors of AD. We identified sncRNA signatures specific to ATN and AD, and evaluated both their contribution to improving AD conversion prediction beyond ATN alone.

METHODS

This nested case-control study was conducted within the ACE cohort and included MCI patients matched by sex. Patients free of type 2 diabetes underwent cerebrospinal fluid (CSF) and plasma collection and were followed-up for a median of 2.45-years. Plasma sncRNAs were profiled using small RNA-sequencing. Conditional logistic and Cox regression analyses with elastic net penalties were performed to identify sncRNA signatures for A+(T|N)+ and AD. Weighted scores were computed using cross-validation, and the association of these scores with AD risk was assessed using multivariable Cox regression models. Gene ontology (GO) and Kyoto encyclopaedia of genes and genomes (KEGG) enrichment analysis of the identified signatures were performed.

RESULTS

The study sample consisted of 192 patients, including 96 A+(T|N)+ and 96 A-T-N- patients. We constructed a classification model based on a 6-miRNAs signature for ATN. The model could classify MCI patients into A-T-N- and A+(T|N)+ groups with an area under the curve of 0.7335 (95% CI, 0.7327 to 0.7342). However, the addition of the model to conventional risk factors did not improve the prediction of AD beyond the conventional model plus ATN status (C-statistic: 0.805 [95% CI, 0.758 to 0.852] compared to 0.829 [95% CI, 0.786, 0.872]). The AD-related 15-sncRNAs signature exhibited better predictive performance than the conventional model plus ATN status (C-statistic: 0.849 [95% CI, 0.808 to 0.890]). When ATN was included in this model, the prediction further improved to 0.875 (95% CI, 0.840 to 0.910). The miRNA-target interaction network and functional analysis, including GO and KEGG pathway enrichment analysis, suggested that the miRNAs in both signatures are involved in neuronal pathways associated with AD.

CONCLUSIONS

The AD-related sncRNA signature holds promise in predicting AD conversion, providing insights into early AD development and potential targets for prevention.

Systematic proteomics in Autosomal dominant Alzheimer's disease reveals decades-early changes of CSF proteins in neuronal death, and immune pathways

Background

To date, there is no high throughput proteomic study in the context of Autosomal Dominant Alzheimer's disease (ADAD). Here, we aimed to characterize early CSF proteome changes in ADAD and leverage them as potential biomarkers for disease monitoring and therapeutic strategies.

Methods

We utilized Somascan® 7K assay to quantify protein levels in the CSF from 291 mutation carriers (MCs) and 185 non-carriers (NCs). We employed a multi-layer regression model to identify proteins with different pseudo-trajectories between MCs and NCs. We replicated the results using publicly available ADAD datasets as well as proteomic data from sporadic Alzheimer's disease (sAD). To biologically contextualize the results, we performed network and pathway enrichment analyses. Machine learning was applied to create and validate predictive models.

Findings

We identified 125 proteins with significantly different pseudo-trajectories between MCs and NCs. Twelve proteins showed changes even before the traditional AD biomarkers (Aβ42, tau, ptau). These 125 proteins belong to three different modules that are associated with age at onset: 1) early stage module associated with stress response, glutamate metabolism, and mitochondria damage; 2) the middle stage module, enriched in neuronal death and apoptosis; and 3) the presymptomatic stage module was characterized by changes in microglia, and cell-to-cell communication processes, indicating an attempt of rebuilding and establishing new connections to maintain functionality. Machine learning identified a subset of nine proteins that can differentiate MCs from NCs better than traditional AD biomarkers (AUC>0.89).

Interpretation

Our findings comprehensively described early proteomic changes associated with ADAD and captured specific biological processes that happen in the early phases of the disease, fifteen to five years before clinical onset. We identified a small subset of proteins with the potentials to become therapy-monitoring biomarkers of ADAD MCs.

Funding

Proteomic data generation was supported by NIH: RF1AG044546.

Cerebrospinal fluid shotgun proteomics identifies distinct proteomic patterns in cerebral amyloid angiopathy rodent models and human patients

Cerebral amyloid angiopathy (CAA) is a form of small vessel disease characterised by the progressive deposition of amyloid β protein in the cerebral vasculature, inducing symptoms including cognitive impairment and cerebral haemorrhages. Due to their accessibility and homogeneous disease phenotypes, animal models are advantageous platforms to study diseases like CAA. Untargeted proteomics studies of CAA rat models (e.g. rTg-DI) and CAA patients provide opportunities for the identification of novel biomarkers of CAA. We performed untargeted, data-independent acquisition proteomic shotgun analyses on the cerebrospinal fluid of rTg-DI rats and wild-type (WT) littermates. Rodents were analysed at 3 months (n = 6/10), 6 months (n = 8/8), and 12 months (n = 10/10) for rTg-DI and WT respectively. For humans, proteomic analyses were performed on CSF of sporadic CAA patients (sCAA) and control participants (n = 39/28). We show recurring patterns of differentially expressed (mostly increased) proteins in the rTg-DI rats compared to wild type rats, especially of proteases of the cathepsin protein family (CTSB, CTSD, CTSS), and their main inhibitor (CST3). In sCAA patients, decreased levels of synaptic proteins (e.g. including VGF, NPTX1, NRXN2) and several members of the granin family (SCG1, SCG2, SCG3, SCG5) compared to controls were discovered. Additionally, several serine protease inhibitors of the SERPIN protein family (including SERPINA3, SERPINC1 and SERPING1) were differentially expressed compared to controls. Fifteen proteins were significantly altered in both rTg-DI rats and sCAA patients, including (amongst others) SCG5 and SERPING1. These results identify specific groups of proteins likely involved in, or affected by, pathophysiological processes involved in CAA pathology such as protease and synapse function of rTg-DI rat models and sCAA patients, and may serve as candidate biomarkers for sCAA.

Plasma metabolites distinguish dementia with Lewy bodies from Alzheimer's disease: a cross-sectional metabolomic analysis

Background

In multifactorial diseases, alterations in the concentration of metabolites can identify novel pathological mechanisms at the intersection between genetic and environmental influences. This study aimed to profile the plasma metabolome of patients with dementia with Lewy bodies (DLB) and Alzheimer's disease (AD), two neurodegenerative disorders for which our understanding of the pathophysiology is incomplete. In the clinical setting, DLB is often mistaken for AD, highlighting a need for accurate diagnostic biomarkers. We therefore also aimed to determine the overlapping and differentiating metabolite patterns associated with each and establish whether identification of these patterns could be leveraged as biomarkers to support clinical diagnosis.

Methods

A panel of 630 metabolites (Biocrates MxP Quant 500) and a further 232 metabolism indicators (biologically informative sums and ratios calculated from measured metabolites, each indicative for a specific pathway or synthesis; MetaboINDICATOR) were analyzed in plasma from patients with probable DLB (n = 15; age 77.6 ± 8.2 years), probable AD (n = 15; 76.1 ± 6.4 years), and age-matched cognitively healthy controls (HC; n = 15; 75.2 ± 6.9 years). Metabolites were quantified using a reversed-phase ultra-performance liquid chromatography column and triple-quadrupole mass spectrometer in multiple reaction monitoring (MRM) mode, or by using flow injection analysis in MRM mode. Data underwent multivariate (PCA analysis), univariate and receiving operator characteristic (ROC) analysis. Metabolite data were also correlated (Spearman r) with the collected clinical neuroimaging and protein biomarker data.

Results

The PCA plot separated DLB, AD and HC groups (R2 = 0.518, Q2 = 0.348). Significant alterations in 17 detected metabolite parameters were identified (q ≤ 0.05), including neurotransmitters, amino acids and glycerophospholipids. Glutamine (Glu; q = 0.045) concentrations and indicators of sphingomyelin hydroxylation (q = 0.039) distinguished AD and DLB, and these significantly correlated with semi-quantitative measurement of cardiac sympathetic denervation. The most promising biomarker differentiating AD from DLB was Glu:lysophosphatidylcholine (lysoPC a 24:0) ratio (AUC = 0.92; 95%CI 0.809-0.996; sensitivity = 0.90; specificity = 0.90).

Discussion

Several plasma metabolomic aberrations are shared by both DLB and AD, but a rise in plasma glutamine was specific to DLB. When measured against plasma lysoPC a C24:0, glutamine could differentiate DLB from AD, and the reproducibility of this biomarker should be investigated in larger cohorts.

Revision of Alzheimer's diagnostic criteria or relocation of the Potemkin village

The recently announced revision of the Alzheimer's disease (AD) diagnostic ATN classification adds to an already existing disregard for clinical assessment the rejection of image-based in vivo assessment of the brain's condition. The revision suggests that the diagnosis of AD should be based solely on the presence of cerebral amyloid-beta and tau, indicated by the "A" and "T". The "N", which stands for neurodegeneration - detected by imaging - should no longer be given importance, except that A+ ± T + = AD with amyloid PET being the main method for demonstrating A+ . We believe this is an artificial and misleading suggestion. It is artificial because it relies on biomarkers whose significance remains obscure and where the detection of "A" is based on a never-validated PET method using a tracer that marks much more than amyloid-beta. It is misleading because many patients without dementia will be falsely classified as having AD, but nonetheless candidates for passive immunotherapy, which may be more harmful than beneficial, and sometimes fatal.

Plasma neurofilament light chain predicts Alzheimer's disease in patients with subjective cognitive decline and mild cognitive impairment: A cross-sectional and longitudinal study

BACKGROUND AND PURPOSE

We aimed to evaluate the accuracy of plasma neurofilament light chain (NfL) in predicting Alzheimer's disease (AD) and the progression of cognitive decline in patients with subjective cognitive decline (SCD) and mild cognitive impairment (MCI).

METHODS

This longitudinal cohort study involved 140 patients (45 with SCD, 73 with MCI, and 22 with AD dementia [AD-D]) who underwent plasma NfL and AD biomarker assessments (cerebrospinal fluid, amyloid positron emission tomography [PET], and 18 F-fluorodeoxyglucose-PET) at baseline. The patients were rated according to the amyloid/tau/neurodegeneration (A/T/N) system and followed up for a mean time of 2.72 ± 0.95 years to detect progression from SCD to MCI and from MCI to AD. Forty-eight patients (19 SCD, 29 MCI) also underwent plasma NfL measurements 2 years after baseline.

RESULTS

At baseline, plasma NfL detected patients with biomarker profiles consistent with AD (A+/T+/N+ or A+/T+/N-) with high accuracy (area under the curve [AUC] 0.82). We identified cut-off values of 19.45 pg/mL for SCD and 20.45 pg/mL for MCI. During follow-up, nine SCD patients progressed to MCI (progressive SCD [p-SCD]), and 14 MCI patients developed AD dementia (progressive MCI [p-MCI]). The previously identified cut-off values provided good accuracy in identifying p-SCD (80% [95% confidence interval 65.69: 94.31]). The rate of NfL change was higher in p-MCI (3.52 ± 4.06 pg/mL) compared to non-progressive SCD (0.81 ± 1.25 pg/mL) and non-progressive MCI (-0.13 ± 3.24 pg/mL) patients. A rate of change lower than 1.64 pg/mL per year accurately excluded progression from MCI to AD (AUC 0.954).

CONCLUSION

Plasma NfL concentration and change over time may be a reliable, non-invasive tool to detect AD and the progression of cognitive decline at the earliest stages of the disease.

Harmonization of CSF and imaging biomarkers in Alzheimer's disease: Need and practical applications for genetics studies and preclinical classification

In Alzheimer's disease (AD) research, cerebrospinal fluid (CSF) Amyloid beta (Aβ), Tau and pTau are the most accepted and well validated biomarkers. Several methods and platforms exist to measure those biomarkers, leading to challenges in combining data across studies. Thus, there is a need to identify methods that harmonize and standardize these values. We used a Z-score based approach to harmonize CSF and amyloid imaging data from multiple cohorts and compared GWAS results using this approach with currently accepted methods. We also used a generalized mixture model to calculate the threshold for biomarker-positivity. Based on our findings, our normalization approach performed as well as meta-analysis and did not lead to any spurious results. In terms of dichotomization, cutoffs calculated with this approach were very similar to those reported previously. These findings show that the Z-score based harmonization approach can be applied to heterogeneous platforms and provides biomarker cut-offs consistent with the classical approaches without requiring any additional data.

Using Neuroimaging to Study Cerebral Amyloid Angiopathy and Its Relationship to Alzheimer's Disease

Cerebral amyloid angiopathy (CAA) is characterized by amyloid-β aggregation in the media and adventitia of the leptomeningeal and cortical blood vessels. CAA is one of the strongest vascular contributors to Alzheimer's disease (AD). It frequently co-occurs in AD patients, but the relationship between CAA and AD is incompletely understood. CAA may drive AD risk through damage to the neurovascular unit and accelerate parenchymal amyloid and tau deposition. Conversely, early AD may also drive CAA through cerebrovascular remodeling that impairs blood vessels from clearing amyloid-β. Sole reliance on autopsy examination to study CAA limits researchers' ability to investigate CAA's natural disease course and the effect of CAA on cognitive decline. Neuroimaging allows for in vivo assessment of brain function and structure and can be leveraged to investigate CAA staging and explore its associations with AD. In this review, we will discuss neuroimaging modalities that can be used to investigate markers associated with CAA that may impact AD vulnerability including hemorrhages and microbleeds, blood-brain barrier permeability disruption, reduced cerebral blood flow, amyloid and tau accumulation, white matter tract disruption, reduced cerebrovascular reactivity, and lowered brain glucose metabolism. We present possible areas for research inquiry to advance biomarker discovery and improve diagnostics.

Plasma Phosphorylated Tau 231 Increases at One-Year Intervals in Cognitively Unimpaired Subjects

Background

Plasma biomarkers of Alzheimer's disease (AD) constitute a non-invasive tool for diagnosing and classifying subjects. They change even in preclinical stages, but it is necessary to understand their properties so they can be helpful in a clinical context.

Objective

With this work we want to study the evolution of p-tau231 plasma levels in the preclinical stages of AD and its relationship with both cognitive and imaging parameters.

Methods

We evaluated plasma phosphorylated (p)-tau231 levels in 146 cognitively unimpaired subjects in sequential visits. We performed a Linear Mixed-effects Model to analyze their rate of change. We also correlated their baseline levels with cognitive tests and structural and functional image values. ATN status was defined based on cerebrospinal fluid biomarkers.

Results

Plasma p-tau231 showed a significant rate of change over time. It correlated negatively with memory tests only in amyloid-positive subjects. No significant correlations were found with any imaging measures.

Conclusions

Increases in plasma p-tau231 can be detected at one-year intervals in cognitively healthy subjects. It could constitute a sensitive marker for detecting early signs of neuronal network impairment by amyloid.

Dementia Ideal Care: Ecosystem Map of Best Practices and Care Pathways Enhanced by Technology and Community

Background

Globally, much work has been done by nonprofit, private, and academic groups to develop best practices for the care of people living with dementia (PLWD), including Alzheimer's disease. However, these best practices reside in disparate repositories and tend to focus on one phase of the patient journey or one relevant group.

Objective

To fill this gap, we developed a Dementia Ideal Care Map that everyone in the dementia ecosystem can use as an actionable tool for awareness, policy development, funding, research, training, service delivery, and technology design. The intended audience includes (and not limited to) policymakers, academia, industry, technology developers, health system leaders, clinicians, social service providers, patient advocates, PLWD, their families, and communities at large.

Methods

A search was conducted for published dementia care best practices and quality measures, which were then summarized in a visual diagram. The draft diagram was analyzed to identify barriers to ideal care. Then, additional processes, services, technologies, and quality measures to overcome those challenges were brainstormed. Feedback was then obtained from experts.

Results

The Dementia Ideal Care Map summarizes the ecosystem of over 200 best practices, nearly 100 technology enablers, other infrastructure, and enhanced care pathways in one comprehensive diagram. It includes psychosocial interventions, care partner support, community-based organizations; awareness, risk reduction; initial detection, diagnosis, ongoing medical care; governments, payers, health systems, businesses, data, research, and training.

Conclusions

Dementia Ideal Care Map is a practical tool for planning and coordinating dementia care. This visualized ecosystem approach can be applied to other conditions.

Aqueous and Plasma Levels of Phosphorylated Tau 181 in Individuals with Normal Cognition

Background

Plasma and cerebrospinal fluid (CSF) levels of p-tau181 have been associated with Alzheimer's disease (AD). The retina and vitreous have shown measurable quantities of phosphorylated tau 181 (p-tau181). The aqueous humor, which can be collected during cataract surgery, may have measurable concentrations of p-tau181.

Objective

To determine whether p-tau181 is detectable in the aqueous humor and if so, whether it is associated with other measures that might be consistent with AD such as higher plasma p-tau181 concentration and lower Montreal Cognitive Assessment (MoCA-BLIND version 7.1) score.

Methods

Aqueous humor samples, blood samples, and MoCA-BLIND scores were collected from patients who did not carry a clinical diagnosis of cognitive impairment at the time of cataract surgery. Aqueous p-tau181 concentrations and plasma p-tau181 concentrations were then measured using ultra-sensitive single-molecule assay ELISA technology. A rank-transformed mixed-effects multivariate regression model was used to determine associations between aqueous concentrations, plasma concentrations, and MoCA-BLIND scores.

Results

16 eyes of 16 participants were enrolled with an average age of 71.6. Average MoCA-BLIND score was 20.6/22, average aqueous p-tau181 concentration was 6.4 pg/mL, and average plasma p-tau181 concentration was 3.1 pg/mL. Higher plasma p-tau181 was significantly associated with higher aqueous p-tau181 (p = 0.02). Aqueous p-tau181 and plasma p-tau181 were negatively associated with MoCA-BLIND scores (p = 0.005 and p = 0.001 respectively) in these patients.

Conclusions

Aqueous p-tau181 is positively correlated with plasma p-tau181 and is negatively correlated with MoCA-BLIND scores. Further study in individuals with mild cognitive impairment or AD characterized by cerebrospinal fluid and volumetric MRI metrics may yield further insights.

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.

The heritability of blood-based biomarkers related to risk of Alzheimer's disease in a population-based sample of early old-age men

INTRODUCTION

Despite their increased application, the heritability of Alzheimer's disease (AD)-related blood-based biomarkers remains unexplored.

METHODS

Plasma amyloid beta 40 (Aβ40), Aβ42, the Aβ42/40 ratio, total tau (t-tau), and neurofilament light (NfL) data came from 1035 men 60 to 73 years of age (μ = 67.0, SD = 2.6). Twin models were used to calculate heritability and the genetic and environmental correlations between them.

RESULTS

Additive genetics explained 44% to 52% of Aβ42, Aβ40, t-tau, and NfL. The Aβ42/40 ratio was not heritable. Aβ40 and Aβ42 were genetically near identical (rg  = 0.94). Both Aβ40 and Aβ42 were genetically correlated with NfL (rg  = 0.35 to 0.38), but genetically unrelated to t-tau.

DISCUSSION

Except for Aβ42/40, plasma biomarkers are heritable. Aβ40 and Aβ42 share mostly the same genetic influences, whereas genetic influences on plasma t-tau and NfL are largely unique in early old-age men. The absence of genetic associations between the Aβs and t-tau is not consistent with the amyloid cascade hypothesis.

AT(N) biomarker profiles and Alzheimer's disease symptomology in Down syndrome

INTRODUCTION

Down syndrome (DS) is a genetic cause of early-onset Alzheimer's disease (AD). The National Institute on Aging-Alzheimer's Association AT(N) Research Framework is a staging model for AD biomarkers but has not been assessed in DS.

METHOD

Data are from the Alzheimer's Biomarker Consortium-Down Syndrome. Positron emission tomography (PET) amyloid beta (Aβ; 15 mCi of [11 C]Pittsburgh compound B) and tau (10 mCi of [18 F]AV-1451) were used to classify amyloid (A) -/+ and tau (T) +/-. Hippocampal volume classified neurodegeneration (N) -/+. The modified Cued Recall Test assessed episodic memory.

RESULTS

Analyses included 162 adults with DS (aged M = 38.84 years, standard deviation = 8.41). Overall, 69.8% of participants were classified as A-/T-/(N)-, 11.1% were A+/T-/(N)-, 5.6% were A+/T+/(N)-, and 9.3% were A+/T+/(N)+. Participants deemed cognitively stable were most likely to be A-T-(N)- and A+T-(N)-. Tau PET (T+) most closely aligning with memory impairment and AD clinical status.

DISCUSSION

Findings add to understanding of AT(N) biomarker profiles in DS.

HIGHLIGHTS

Overall, 69.8% of adults with Down syndrome (DS) aged 25 to 61 years were classified as amyloid (A)-/tau (T)-/neurodegeneration (N)-, 11.1% were A+/T-/(N)-, 5.6% were A+/T+/(N)-, and 9.3% were A+/T+/(N)+. The AT(N) profiles were associated with clinical Alzheimer's disease (AD) status and with memory performance, with the presence of T+ aligned with AD clinical symptomology. Findings inform models for predicting the transition to the prodromal stage of AD in DS.

A Continuous Extension of Gene Set Enrichment Analysis Using the Likelihood Ratio Test Statistics Identifies Vascular Endothelial Growth Factor as a Candidate Pathway for Alzheimer's Disease via ITGA5

BACKGROUND

Alzheimer's disease (AD) involves brain neuropathologies such as amyloid plaque and hyperphosphorylated tau tangles and is accompanied by cognitive decline. Identifying the biological mechanisms underlying disease onset and progression based on quantifiable phenotypes will help understand disease etiology and devise therapies.

OBJECTIVE

Our objective was to identify molecular pathways associated with hallmark AD biomarkers and cognitive status, accounting for variables such as age, sex, education, and APOE genotype.

METHODS

We introduce a pathway-based statistical approach, extending the gene set likelihood ratio test to continuous phenotypes. We first analyzed independently each of the three phenotypes (amyloid-β, tau, cognition) using continuous gene set likelihood ratio tests to account for covariates, including age, sex, education, and APOE genotype. The analysis involved 634 subjects with data available for all three phenotypes, allowing for the identification of common pathways.

RESULTS

We identified 14 pathways significantly associated with amyloid-β; 5 associated with tau; and 174 associated with cognition, which showed a larger number of pathways compared to biomarkers. A single pathway, vascular endothelial growth factor receptor binding (VEGF-RB), exhibited associations with all three phenotypes. Mediation analysis showed that among the VEGF-RB family genes, ITGA5 mediates the relationship between cognitive scores and pathological biomarkers.

CONCLUSIONS

We presented a new statistical approach linking continuous phenotypes, gene expression across pathways, and covariates like sex, age, and education. Our results reinforced VEGF RB2's role in AD cognition and demonstrated ITGA5's significant role in mediating the AD pathology-cognition connection.

Contactin 5 and Apolipoproteins Interplay in Alzheimer's Disease

Background

Apolipoproteins and contactin 5 are proteins associated with Alzheimer's disease (AD) pathophysiology. Apolipoproteins act on transport and clearance of cholesterol and phospholipids during synaptic turnover and terminal proliferation. Contactin 5 is a neuronal membrane protein involved in key processes of neurodevelopment.

Objective

To investigate the interactions between contactin 5 and apolipoproteins in AD, and the role of these proteins in response to neuronal damage.

Methods

Apolipoproteins (measured by Luminex), contactin 5 (measured by Olink's proximity extension assay), and cholesterol (measured by liquid chromatography mass spectrometry) were assessed in the cerebrospinal fluid (CSF) and plasma of cognitively unimpaired participants (n = 93). Gene expression was measured using polymerase chain reaction in the frontal cortex of autopsied-confirmed AD (n = 57) and control subjects (n = 31) and in the hippocampi of mice following entorhinal cortex lesions.

Results

Contactin 5 positively correlated with apolipoproteins B (p = 5.4×10-8), D (p = 1.86×10-4), E (p = 2.92×10-9), J (p = 2.65×10-9), and with cholesterol (p = 0.0096) in the CSF, and with cholesterol (p = 0.02), HDL (p = 0.0143), and LDL (p = 0.0121) in the plasma. Negative correlations were seen between CNTN5, APOB (p = 0.034) and APOE (p = 0.015) mRNA levels in the brains of control subjects. In the mouse model, apoe and apoj gene expression increased during the reinnervation phase (p <  0.05), while apob (p = 0.023) and apod (p = 0.006) increased in the deafferentation stage.

Conclusions

Extensive interactions were observed between contactin 5 and apolipoproteins and cholesterol, possibly due to neuronal damage. The alterations in gene expression of apolipoproteins suggest a role in axonal, terminal, and synaptic remodeling in response to entorhinal cortex damage.

Visual Functions Are Associated with Biomarker Changes in Alzheimer's Disease

Background

While various biomarkers of Alzheimer's disease (AD) have been associated with general cognitive function, their association to visual-perceptive function across the AD spectrum warrant more attention due to its significant impact on quality of life. Thus, this study explores how AD biomarkers are associated with decline in this cognitive domain.

Objective

To explore associations between various fluid and imaging biomarkers and visual-based cognitive assessments in participants across the AD spectrum.

Methods

Data from participants (N = 1,460) in the Alzheimer's Disease Neuroimaging Initiative were analyzed, including fluid and imaging biomarkers. Along with the Mini-Mental State Examination (MMSE), three specific visual-based cognitive tests were investigated: Trail Making Test (TMT) A and TMT B, and the Boston Naming Test (BNT). Locally estimated scatterplot smoothing curves and Pearson correlation coefficients were used to examine associations.

Results

MMSE showed the strongest correlations with most biomarkers, followed by TMT-B. The p-tau181/Aβ1-42 ratio, along with the volume of the hippocampus and entorhinal cortex, had the strongest associations among the biomarkers.

Conclusions

Several biomarkers are associated with visual processing across the disease spectrum, emphasizing their potential in assessing disease severity and contributing to progression models of visual function and cognition.

Risk, protective, and biomarkers of dementia in Indigenous peoples: A systematic review

INTRODUCTION

Dementia is an emergent health priority for Indigenous peoples worldwide, yet little is known about disease drivers and protective factors.

METHODS

Database searches were conducted in March 2022 to identify original publications on risk, protective, genetic, neuroradiological, and biological factors related to dementia and cognitive impairment involving Indigenous peoples.

RESULTS

Modifiable risk factors featured across multiple studies include childhood adversity, hearing loss, low education attainment, unskilled work history, stroke, head injury, epilepsy, diabetes, hypertension, hyperlipidemia, depression, low BMI, poor mobility, and continence issues. Non-modifiable risk factors included increasing age, sex, and genetic polymorphisms. Education, ex-smoking, physical and social activity, and engagement with cultural or religious practices were highlighted as potential protective factors. There is a paucity of research on dementia biomarkers involving Indigenous peoples.

DISCUSSION

Greater understanding of modifiable factors and biomarkers of dementia can assist in strength-based models to promote healthy ageing and cognition for Indigenous peoples.

[Use of modern classification systems for complex diagnostics of Alzheimer's disease]

OBJECTIVE

To compare the content of β-amyloid (Aβ) peptides Aβ40, Aβ42, total and threonine phosphorylated 181 tau-protein in cerebrospinal fluid (CSF) of patients with the clinical diagnosis of Alzheimer's disease (AD).

MATERIAL AND METHODS

The study was performed on 64 patients with a diagnosis of dementia and MMSE scores of 24 or lower. All patients underwent lumbar puncture. Aβ40, Aβ42, Aβ42/40 ratio, total tau, phosphorylated tau at threonine 181 were determined in the CSF using a multiplex assay according to the manufacturer's protocol, the concentration was determined in pkg/ml.

RESULTS

The preliminary diagnosis of AD was made in 3 patients (5%). As a result of the study of protein content in the CSF, signs of AD were detected in 48 (75%) people. The findings suggest that the diagnosis of AD is made 10-14 times less frequently than it should be according to the World Health Organization data. The discrepancy between clinical diagnosis and laboratory findings is confirmed by our study.

CONCLUSION

Differences in the therapy of dementias and the development of new drugs targeting specific links in the pathogenesis of different types of dementias require accurate and complete diagnosis of dementias, especially AD, as the most common type of dementia.

White matter integrity is associated with cognition and amyloid burden in older adult Koreans along the Alzheimer's disease continuum

BACKGROUND

White matter (WM) microstructural changes in the hippocampal cingulum bundle (CBH) in Alzheimer's disease (AD) have been described in cohorts of largely European ancestry but are lacking in other populations.

METHODS

We assessed the relationship between CBH WM integrity and cognition or amyloid burden in 505 Korean older adults aged ≥ 55 years, including 276 cognitively normal older adults (CN), 142 with mild cognitive impairment (MCI), and 87 AD patients, recruited as part of the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's disease (KBASE) at Seoul National University.

RESULTS

Compared to CN, AD and MCI subjects showed significantly higher RD, MD, and AxD values (all p-values < 0.001) and significantly lower FA values (left p ≤ 0.002, right p ≤ 0.015) after Bonferroni adjustment for multiple comparisons. Most tests of cognition and mood (p < 0.001) as well as higher medial temporal amyloid burden (p < 0.001) were associated with poorer WM integrity in the CBH after Bonferroni adjustment.

CONCLUSION

These findings are consistent with patterns of WM microstructural damage previously reported in non-Hispanic White (NHW) MCI/AD cohorts, reinforcing existing evidence from predominantly NHW cohort studies.

Verifying and refining early statuses in Alzheimer's disease progression: a possibility from deep feature comparison

Defining the early status of Alzheimer's disease is challenging. Theoretically, the statuses in the Alzheimer's disease continuum are expected to share common features. Here, we explore to verify and refine candidature early statuses of Alzheimer's disease with features learned from deep learning. We train models on brain functional networks to accurately classify between amnestic and non-amnestic mild cognitive impairments and between healthy controls and mild cognitive impairments. The trained models are applied to Alzheimer's disease and subjective cognitive decline groups to suggest feature similarities among the statuses and identify informative subpopulations. The amnestic mild cognitive impairment vs non-amnestic mild cognitive impairments classifier believes that 71.8% of Alzheimer's disease are amnestic mild cognitive impairment. And 73.5% of subjective cognitive declines are labeled as mild cognitive impairments, 88.8% of which are further suggested as "amnestic mild cognitive impairment." Further multimodal analyses suggest that the amnestic mild cognitive impairment-like Alzheimer's disease, mild cognitive impairment-like subjective cognitive decline, and amnestic mild cognitive impairment-like subjective cognitive decline exhibit more Alzheimer's disease -related pathological changes (elaborated β-amyloid depositions, reduced glucose metabolism, and gray matter atrophy) than non-amnestic mild cognitive impairments -like Alzheimer's disease, healthy control-like subjective cognitive decline, and non-amnestic mild cognitive impairments -like subjective cognitive decline. The test-retest reliability of the subpopulation identification is fair to good in general. The study indicates overall similarity among subjective cognitive decline, amnestic mild cognitive impairment, and Alzheimer's disease and implies their progression relationships. The results support "deep feature comparison" as a potential beneficial framework to verify and refine early Alzheimer's disease status.

Prediction of misfolded proteins spreading in Alzheimer's disease using machine learning and spreading models

The pervasive impact of Alzheimer's disease on aging society represents one of the main challenges at this time. Current investigations highlight 2 specific misfolded proteins in its development: Amyloid-$\beta$ and tau. Previous studies focused on spreading for misfolded proteins exploited simulations, which required several parameters to be empirically estimated. Here, we provide an alternative view based on 2 machine learning approaches which we compare with known simulation models. The first approach applies an autoregressive model constrained by structural connectivity, while the second is based on graph convolutional networks. The aim is to predict concentrations of Amyloid-$\beta$ 2 yr after a provided baseline. We also evaluate its real-world effectiveness and suitability by providing a web service for physicians and researchers. In experiments, the autoregressive model generally outperformed state-of-the-art models resulting in lower prediction errors. While it is important to note that a comprehensive prognostic plan cannot solely rely on amyloid beta concentrations, their prediction, achieved by the discussed approaches, can be valuable for planning therapies and other cures, especially when dealing with asymptomatic patients for whom novel therapies could prove effective.

Neurotheranostics: The Next Frontier for Health Span

With an aging U.S. population, advancements in the treatment of Alzheimer disease (AD) and other neurodegenerative diseases are key to the maximization of health span. The recent approval of 2 antiamyloid antibodies, which decrease brain amyloid load, places us on the cusp of breakthrough therapies that target the mechanism of the disease rather than just treating the symptoms. Although the trials that led to these approvals studied patients with mild early symptoms, multiple ongoing trials have enrolled cognitively normal patients screened for AD biomarkers including risk factors for amyloid positivity, family history, and genetic markers. Thus, amyloid PET can help identify an at-risk population that can be enrolled for antiamyloid therapy to prevent AD symptoms from ever developing. In this review, we examine the paradigm of neurotheranostics and how PET biomarkers of amyloid, tau, inflammation, and neurodegeneration could characterize the pathologic stage of AD and therefore allow for personalized therapy.

Toward a Unified Classification System for Brain-Mind Disorders: Putting Calls for Integrated Clinical Neuroscience Into Action

Dividing the brain-mind into the specialized fields of neurology and psychiatry has produced many granular advantages, but these silos have imposed barriers to comprehensively understanding and contextualizing the fundamentals governing mental life and its maladies. Scientific inquiry into these fundamentals cannot reach its full potential without interdigitating the boundaries of two specialties of the same organ for both scholarship and clinical practice. We propose that to truly integrate disorders of the brain and the mind for research and clinical care, we must carefully reexamine the classification of its disorders (nosology) as an instrument to develop a coherent pathological and psychological framework. We call on professional organizations from neurology, psychiatry, behavioral neurology, neuropsychiatry, neuropsychology, and other relevant subspecialties (eg, geriatric psychiatry) to convene a multidisciplinary task force to define the current classification principles of their subspecialties and work toward developing an integrated nosology. The effect of a shared classification system, which we acknowledge is a difficult proposition philosophically and politically, would have transformative potential across educational, clinical, scientific, programmatic, and sociocultural realms. If accomplished, this initiative would provide a definitive step toward reducing stigma (and promoting reimbursement parity) for the full spectrum of complex brain disorders (regardless of traditional neurologic vs psychiatric conceptualizations).

Atrophy, hypometabolism and implication regarding pathology in late-life major depression with suspected non-alzheimer pathophysiology (SNAP)

BACKGROUND

A substantial proportion of individuals with late-life major depression could be classified as having a suspected non-Alzheimer disease pathophysiology (SNAP), as indicated by a negative test for the biomarker β-amyloid (Aβ-) but a positive test for neurodegeneration (ND+). This study investigated the clinical features, characteristic patterns of brain atrophy and hypometabolism, and implications regarding pathology in this population.

METHODS

Forty-six amyloid-negative patients with late-life major depressive disorder (MDD) patients, including 23 SNAP (Aβ-/ND+) and 23 Aβ-/ND- MDD subjects, and 22 Aβ-/ND-healthy control subjects were included in this study. Voxel-wise group comparisons between the SNAP MDD, Aβ-/ND- MDD and control subjects were performed, adjusting for age, gender and level of education. For exploratory comparisons, 8 Aβ+/ND- and 4 Aβ+/ND + MDD patients were included in the Supplementary Material.

RESULTS

The SNAP MDD patients had atrophy extending to regions outside the hippocampus, predominately in the medial temporal, dorsomedial and ventromedial prefrontal cortex; hypometabolism involving a large portion of the lateral and medial prefrontal cortex in addition to the bilateral temporal, parietal and precuneus cortex within typical Alzheimer disease regions were observed. Metabolism ratios of the inferior to the medial temporal lobe were significantly elevated in the SNAP MDD patients. We further discussed the implications with regards to underlying pathologies.

CONCLUSION

The present study demonstrated characteristic patterns of atrophy and hypometabolism in patients with late-life major depression with SNAP. Identifying individuals with SNAP MDD may provide insights into currently unspecified neurodegenerative processes. Future refinement of neurodegeneration biomarkers is essential in order to identify potential pathological correlates while in vivo reliable pathological biomarkers are not forthcoming.

[The new age of neurodegenerative diseases. The basis of the new approaches]

The detection by biomarkers of the pathophysiological and molecular processes involved in misfolding protein diseases making it possible to delineate the natural history of these processes. The great majority of protein misfolding diseases have a prolonged preclinical phase, in which the biological changes are patent. The clinical manifestations (i.e., phenotypes) do not have a univocal correspondence with the underlying pathology, despite the fact that pathological eponyms have been used for the description of the clinical syndromes, which has favored diagnostic inaccuracy. In order to perform an adequate clinical management, we must know the 3 planes that currently define the most common neurodegenerative processes. Diagnostic accuracy will be a prerequisite for new therapies aimed at modifying the course of brain protein misfolding diseases.

APOE ε4's impact on response to amyloid therapies in early symptomatic Alzheimer's disease: Analyses from multiple clinical trials

INTRODUCTION

Apolipoprotein E (APOE) ε4 may interact with response to amyloid-targeting therapies.

METHODS

Aggregate data from trials enrolling participants with amyloid-positive, early symptomatic Alzheimer's disease (AD) were analyzed for disease progression.

RESULTS

Pooled analysis of potentially efficacious antibodies lecanemab, aducanumab, solanezumab, and donanemab shows slightly better efficacy in APOE ε4 carriers than in non-carriers. Carrier and non-carrier mean (95% confidence interval) differences from placebo using Clinical Dementia Rating Scale-Sum of Boxes (CDR-SB) were -0.30 (-0.478, -0.106) and -0.20 (-0.435, 0.042) and AD Assessment Scale-Cognitive subscale (ADAS-Cog) values were -1.01 (-1.577, -0.456) and -0.80 (-1.627, 0.018), respectively. Decline in the APOE ε4 non-carrier placebo group was equal to or greater than that in carriers across multiple scales. Probability of study success increases as the representation of the carrier population increases.

DISCUSSION

We hypothesize that APOE ε4 carriers have same or better response than non-carriers to amyloid-targeting therapies and similar or less disease progression with placebo in amyloid-positive trials.

HIGHLIGHTS

Amyloid-targeting therapies had slightly greater efficacy in apolipoprotein E (APOE) ε4 carriers. Clinical decline is the same/slightly faster in amyloid-positive APOE ε4 non-carriers. Prevalence of non-carriers in trial populations could impact outcomes.

Gaussian Process-based prediction of memory performance and biomarker status in ageing and Alzheimer's disease-A systematic model evaluation

Neuroimaging markers based on Magnetic Resonance Imaging (MRI) combined with various other measures (such as genetic covariates, biomarkers, vascular risk factors, neuropsychological tests etc.) might provide useful predictions of clinical outcomes during the progression towards Alzheimer's disease (AD). The use of multiple features in predictive frameworks for clinical outcomes has become increasingly prevalent in AD research. However, many studies do not focus on systematically and accurately evaluating combinations of multiple input features. Hence, the aim of the present work is to explore and assess optimal combinations of various features for MR-based prediction of (1) cognitive status and (2) biomarker positivity with a multi-kernel learning Gaussian process framework. The explored features and parameters included (A) combinations of brain tissues, modulation, smoothing, and image resolution; (B) incorporating demographics & clinical covariates; (C) the impact of the size of the training data set; (D) the influence of dimensionality reduction and the choice of kernel types. The approach was tested in a large German cohort including 959 subjects from the multicentric longitudinal study of cognitive impairment and dementia (DELCODE). Our evaluation suggests the best prediction of memory performance was obtained for a combination of neuroimaging markers, demographics, genetic information (ApoE4) and CSF biomarkers explaining 57% of outcome variance in out-of-sample predictions. The highest performance for Aβ42/40 status classification was achieved for a combination of demographics, ApoE4, and a memory score while usage of structural MRI further improved the classification of individual patient's pTau status.

Differential effects of sleep on brain structure and metabolism at the preclinical stages of AD

INTRODUCTION

Poor sleep quality is associated with cognitive outcomes in Alzheimer's disease (AD). We analyzed the associations between self-reported sleep quality and brain structure and function in cognitively unimpaired (CU) individuals.

METHODS

CU adults (N = 339) underwent structural magnetic resonance imaging, lumbar puncture, and the Pittsburgh Sleep Quality Index (PSQI) questionnaire. A subset (N = 295) performed [18F] fluorodeoxyglucose positron emission tomography scans. Voxel-wise associations with gray matter volumes (GMv) and cerebral glucose metabolism (CMRGlu) were performed including interactions with cerebrospinal fluid (CSF) AD biomarkers status.

RESULTS

Poorer sleep quality was associated with lower GMv and CMRGlu in the orbitofrontal and cingulate cortices independently of AD pathology. Self-reported sleep quality interacted with altered core AD CSF biomarkers in brain areas known to be affected in preclinical AD stages.

DISCUSSION

Poor sleep quality may impact brain structure and function independently from AD pathology. Alternatively, AD-related neurodegeneration in areas involved in sleep-wake regulation may induce or worsen sleep disturbances. Highlights Poor sleep impacts brain structure and function independent of Alzheimer's disease (AD) pathology. Poor sleep exacerbates brain changes observed in preclinical AD. Sleep is an appealing therapeutic strategy for preventing AD.

Functional connectivity changes in mild cognitive impairment: A meta-analysis of M/EEG studies

OBJECTIVE

Early synchrony alterations have been observed through electrophysiological techniques in Mild Cognitive Impairment (MCI), which is considered the intermediate phase between healthy aging (HC) and Alzheimer's disease (AD). However, the documented direction (hyper/hypo-synchronization), regions and frequency bands affected are inconsistent. This meta-analysis intended to elucidate existing evidence linked to potential neurophysiological biomarkers of AD.

METHODS

We conducted a random-effects meta-analysis that entailed the unbiased inclusion of Non-statistically Significant Unreported Effect Sizes ("MetaNSUE") of electroencephalogram (EEG) and magnetoencephalogram (MEG) studies investigating functional connectivity changes at rest along the healthy-pathological aging continuum, searched through PubMed, Scopus, Web of Science and PsycINFO databases until June 2023.

RESULTS

Of the 3852 articles extracted, we analyzed 12 papers, and we found an alpha synchrony decrease in MCI compared to HC, specifically between temporal-parietal (d = -0.26) and frontal-parietal areas (d = -0.25).

CONCLUSIONS

Alterations of alpha synchrony are present even at MCI stage.

SIGNIFICANCE

Synchrony measures may be promising for the detection of the first hallmarks of connectivity alterations, even at the prodromal stages of the AD, before clinical symptoms occur.

Speech and language markers of neurodegeneration: a call for global equity

In the field of neurodegeneration, speech and language assessments are useful for diagnosing aphasic syndromes and for characterizing other disorders. As a complement to classic tests, scalable and low-cost digital tools can capture relevant anomalies automatically, potentially supporting the quest for globally equitable markers of brain health. However, this promise remains unfulfilled due to limited linguistic diversity in scientific works and clinical instruments. Here we argue for cross-linguistic research as a core strategy to counter this problem. First, we survey the contributions of linguistic assessments in the study of primary progressive aphasia and the three most prevalent neurodegenerative disorders worldwide-Alzheimer's disease, Parkinson's disease, and behavioural variant frontotemporal dementia. Second, we address two forms of linguistic unfairness in the literature: the neglect of most of the world's 7000 languages and the preponderance of English-speaking cohorts. Third, we review studies showing that linguistic dysfunctions in a given disorder may vary depending on the patient's language and that English speakers offer a suboptimal benchmark for other language groups. Finally, we highlight different approaches, tools and initiatives for cross-linguistic research, identifying core challenges for their deployment. Overall, we seek to inspire timely actions to counter a looming source of inequity in behavioural neurology.

Traumatic brain injury and Alzheimer's Disease biomarkers: A systematic review of findings from amyloid and tau positron emission tomography (PET)

Traumatic brain injury (TBI) has been discussed as a risk factor for Alzheimer's disease (AD) due to its association with dementia risk and earlier cognitive symptom onset. However, the mechanisms behind this relationship are unclear. Some studies have suggested TBI may increase pathological protein deposition in an AD-like pattern; others have failed to find such associations. This review covers literature that uses positron emission tomography (PET) of amyloid-β and/or tau to examine subjects with history of TBI who are at risk for AD due to advanced age. A comprehensive literature search was conducted on January 9, 2023, and 24 resulting citations met inclusion criteria. Common methodological concerns included small samples, limited clinical detail about subjects' TBI, recall bias due to reliance on self-reported TBI, and an inability to establish causation. For both amyloid and tau, results were widespread but inconsistent. The regions which showed the most compelling evidence for increased amyloid deposition were the cingulate gyrus, cuneus/precuneus, and parietal lobe. Evidence for increased tau was strongest in the medial temporal lobe, entorhinal cortex, precuneus, and frontal, temporal, parietal, and occipital lobes. However, conflicting findings across most regions of interest in both amyloid- and tau-PET studies indicate the critical need for future work in expanded samples and with greater clinical detail to offer a clearer picture of the relationship between TBI and protein deposition in older subjects at risk for AD.

Fully automated production of [11C]PiB for clinical use on Trasis-AllinOne synthesizer module

Pittsburgh compound B ([11C]PiB) was the first broadly applied radiotracer with specificity for amyloid-β (Aβ) peptide aggregates in the brain and has since been established as the gold standard for positron emission tomography (PET) employed for clinical in vivo imaging of Aβ plaques, used for imaging applications of Alzheimer's disease (AD), related dementia, and other tauopathies. The use of [11C]PiB for routine PET studies is dependent on the production capabilities of each radiochemistry laboratory, subsequently a continuous effort is made to develop suitable and sustainable methods on a variety of auto synthesis platforms. Here we report a fully automated, multi-step radio synthesis, purification, and reformulation of [11C]PiB for PET imaging using the Trasis AllinOne synthesis unit, a commonly used commercial radiochemistry module. We performed three validation runs to evaluate the reproducibility and to verify that the acceptable criteria were met for the release of clinical-grade [11C]PiB using a Trasis AllinOne auto radiosynthesis unit. Solid phase supported radiolabeling was performed through the capture of precursor (6-OH-BTA-0) on a C18 solid phase extraction (SPE) cartridge and subsequent flushing of gaseous [11C]Methyl triflate(MeOTf) through the Sep-Pak for carbon-11 (11C) N-methylation. Starting with 92.5 GBq [11C]CO2, [11C]PiB synthesis was completed in approximately 25 min after cyclotron end of bombardment with an injectable dose >7.0 GBq at end of the synthesis. The radiopharmaceutical product met all quality control criteria and specifications for use in human studies.

Alzheimer's Disease CSF Biomarkers as Possible Indicators of Tap-Test Response in Idiopathic Normal Pressure Hydrocephalus

The aim of the present study is the evaluation of established Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers in patients with idiopathic normal-pressure hydrocephalus (iNPH), both individually and as a total profile, and the investigation of their use as potential predictors of Tap-test responsiveness. Fifty-three patients with iNPH participated in the study. Aβ42, Aβ40, total Tau and phospho-Tau proteins were measured in duplicate with double-sandwich ELISA assays. Clinical evaluation involved a 10 m timed walk test before an evacuative lumbar puncture (LP) and every 24 h for three consecutive days afterwards. Neuropsychological assessment involved a mini-mental state examination, frontal assessment battery, 5-word test and CLOX drawing test 1 and 2, which were also performed before and 48 h after LP. Response in the Tap-test was defined as a 20% improvement in gait and/or a 10% improvement in neuropsychological tests. The Aβ42/Aβ40 ratio was found to be significantly higher in Tap-test responders than non-responders. Total Tau and phospho-Tau CSF levels also differed significantly between these two groups, with Tap-test responders presenting with lower levels compared to non-responders. Regarding the AD CSF biomarker profile (decreased amyloid and increased Tau proteins levels), patients with a non-AD profile were more likely to have a positive response in the Tap-test than patients with an AD profile.

Patterns of Glucose Metabolism in [ 18 F]FDG PET Indicate Regional Variability and Neurodegeneration in the Progression of Alzheimer's Dementia

In disorders of cognitive impairment, such as Alzheimer's disease, neurodegeneration is the final common pathway of disease progression. Modulating, reversing, or preventing disease progression is a clinical imperative most likely to succeed following accurate and explanatory understanding of neurodegeneration, requiring enhanced consistency with quantitative measurements and expanded interpretability of complex data. The on-going study of neurodegeneration has robustly demonstrated the advantages of accumulating large amounts of clinical data that include neuroimaging, motiving multi-center studies such as the Alzheimer's Disease Neuroimaging Initiative (ADNI). Demonstrative advantages also arise from highly multivariate analysis methods, and this work reports advances provided by non-negative matrix factorization (NMF). NMF revealed patterns of covariance for glucose metabolism, estimated by positron emission tomography of [ 18 F]fluorodeoxyglucose, in 243 healthy normal participants of ADNI. Patterns for glucose metabolism provided cross-sectional inferences for 860 total participants of ADNI with and without cerebral amyloidosis and clinical dementia ratings (CDR) ranging 0-3. Patterns for glucose metabolism were distinct in number and topography from patterns identified in previous studies of structural MRI. They were also distinct from well-establish topographies of resting-state neuronal networks mapped by functional magnetic resonance imaging. Patterns for glucose metabolism identified significant topographical landmarks relating age, sex, APOE ε4 alleles, amyloidosis, CDR, and neurodegeneration. Patterns involving insular and orbitofrontal cortices, as well as midline regions of frontal and parietal lobes demonstrated the greatest neurodegeneration with progressive Alzheimer's dementia. A single pattern for the lateral parietal and posterior superior temporal cortices demonstrated preserved glucose metabolism for all diagnostic groups, including Alzheimer's dementia. Patterns correlated significantly with topical terms from the Neurosynth platform, thereby providing semantic representations for patterns such as attention, memory, language, fear/reward, movement and motor planning. In summary, NMF is a data-driven, principled, supervised statistical learning method that provides interpretable patterns of neurodegeneration. These patterns can help inform the understanding and treatment of Alzheimer's disease.

Highlights

▪ Data-driven non-negative matrix factorization (NMF) identified 24 canonical patterns of spatial covariance of cerebral glucose metabolism. The training data comprised healthy older participants (CDR = 0 without amyloidosis) cross-sectionally drawn from ADNI. ▪ In healthy participants, mean SUVRs for specific patterns in precuneus, lateral parietal cortex, and subcortical areas including superficial white matter and striatum, demonstrated increasing glucose metabolism with advancing age. ▪ In asymptomatic participants with amyloidosis , glucose metabolism increased compared to those who were asymptomatic without amyloid , particularly in medial prefrontal cortex, frontoparietal cortex, occipital white, and posterior cerebellar regions. ▪ In symptomatic participants with amyloidosis , insular cortex, medial frontal cortex, and prefrontal cortex demonstrated the most severe losses of glucose metabolism with increasing CDR. Lateral parietal and posterior superior temporal cortices retained glucose metabolism even for CDR > 0.5. ▪ NMF models of glucose metabolism are consistent with models arising from principal components, or eigenbrains, while adding additional regional interpretability. ▪ NMF patterns correlated with regions catalogued in Neurosynth. Following corrections for spatial autocorrelations, NMF patterns revealed meta-analytic identifications of patterns with Neurosynth topics of fear/reward, attention, memory, language, and movement with motor planning. Patterns varied with degrees of cognitive impairment.

Hippocampal subfield associations with memory depend on stimulus modality and retrieval mode

Hippocampal atrophy is a well-known feature of age-related memory decline, and hippocampal subfields may contribute differently to this decline. In this cross-sectional study, we investigated the associations between hippocampal subfield volumes and performance in free recall and recognition memory tasks in both verbal and visual modalities in older adults without dementia. We collected MRIs from 97 (41 males) right-handed participants aged over 60. We segmented the right and left hippocampi into (i) dentate gyrus and cornu ammonis 4 (DG/CA4); (ii) CA2 and CA3 (CA2/CA3); (iii) CA1; (iv) strata radiatum, lacunosum and moleculare; and (v) subiculum. Memory was assessed with verbal free recall and recognition tasks, as well as visual free recall and recognition tasks. Amyloid-β and hippocampal tau positivity were assessed using [18F]AZD4694 and [18F]MK6240 PET tracers, respectively. The verbal free recall and verbal recognition performances were positively associated with CA1 and strata radiatum, lacunosum and moleculare volumes. The verbal free recall and visual free recall were positively correlated with the right DG/CA4. The visual free recall, but not verbal free recall, was also associated with the right CA2/CA3. The visual recognition was not significantly associated with any subfield volume. Hippocampal tau positivity, but not amyloid-β positivity, was associated with reduced DG/CA4, CA2/CA3 and strata radiatum, lacunosum and moleculare volumes. Our results suggest that memory performances are linked to specific subfields. CA1 appears to contribute to the verbal modality, irrespective of the free recall or recognition mode of retrieval. In contrast, DG/CA4 seems to be involved in the free recall mode, irrespective of verbal or visual modalities. These results are concordant with the view that DG/CA4 plays a primary role in encoding a stimulus' distinctive attributes, and that CA2/CA3 could be instrumental in recollecting a visual memory from one of its fragments. Overall, we show that hippocampal subfield segmentation can be useful for detecting early volume changes and improve our understanding of the hippocampal subfields' roles in memory.

Alzheimer Disease Biomarkers: Moving from CSF to Plasma for Reliable Detection of Amyloid and tau Pathology

BACKGROUND

Development of validated biomarkers to detect early Alzheimer disease (AD) neuropathology is needed for therapeutic AD trials. Abnormal concentrations of "core" AD biomarkers, cerebrospinal fluid (CSF) amyloid beta1-42, total tau, and phosphorylated tau correlate well with neuroimaging biomarkers and autopsy findings. Nevertheless, given the limitations of established CSF and neuroimaging biomarkers, accelerated development of blood-based AD biomarkers is underway.

CONTENT

Here we describe the clinical significance of CSF and plasma AD biomarkers to detect disease pathology throughout the Alzheimer continuum and correlate with imaging biomarkers. Use of the AT(N) classification by CSF and imaging biomarkers provides a more objective biologically based diagnosis of AD than clinical diagnosis alone. Significant progress in measuring CSF AD biomarkers using extensively validated highly automated assay systems has facilitated their transition from research use only to approved in vitro diagnostics tests for clinical use. We summarize development of plasma AD biomarkers as screening tools for enrollment and monitoring participants in therapeutic trials and ultimately in clinical care. Finally, we discuss the challenges for AD biomarkers use in clinical trials and precision medicine, emphasizing the possible ethnocultural differences in the levels of AD biomarkers.

SUMMARY

CSF AD biomarker measurements using fully automated analytical platforms is possible. Building on this experience, validated blood-based biomarker tests are being implemented on highly automated immunoassay and mass spectrometry platforms. The progress made developing analytically and clinically validated plasma AD biomarkers within the AT(N) classification scheme can accelerate use of AD biomarkers in therapeutic trials and routine clinical practice.

Plasma Biomarkers of Alzheimer Disease in Women With and Without HIV

Importance

Blood-based biomarkers associated with increased risk of Alzheimer disease (AD) are understudied in people living with and without HIV, particularly women.

Objective

To determine whether baseline or 1-year changes in plasma amyloid-β40 (Aβ40), Aβ42, ratio of Aβ42 to Aβ40, total tau (t-tau), phosphorylated tau 231 (p-tau231), glial fibrillary acidic protein (GFAP), and/or neurofilament light chain (NFL) are associated with neuropsychological performance (NP) among women living with HIV (WLWH) and women living without HIV (WLWOH).

Design, Setting, and Participants

This longitudinal, prospective, cohort study with 1-year repeated clinical measures (NP only measured once) and biospecimen collection occurred between 2017 and 2019. Participants were women aged 40 years or older from 10 clinical research sites in cities across the US that were part of the Women's Interagency HIV Study. Data analysis was conducted from April to December 2022.

Exposure

Laboratory-confirmed HIV status and AD biomarkers.

Main Outcomes and Measures

Sociodemographically adjusted NP T-scores (attention and working memory, executive function, processing speed, memory, learning, verbal fluency, motor function, and global performance) were the primary outcomes. Baseline and 1-year fasting plasma Aβ40, Aβ42, t-tau, p-tau231, GFAP, and NFL levels were measured and analyzed using multivariable linear regression.

Results

The study consisted of 307 participants (294 aged ≥50 years [96%]; 164 African American or Black women [53%]; 214 women with a high school education or higher [70%]; 238 women who were current or former smokers [78%]; and 236 women [77%] who were overweight or obese [body mass index >25]) including 209 WLWH and 98 WLWOH. Compared with WLWOH at baseline, WLWH performed worse on learning (mean [SD] T-score 47.8 [11.3] vs 51.4 [10.5]), memory (mean [SD] T-score 48.3 [11.6] vs 52.4 [10.2]), verbal fluency (mean [SD] T-score 48.3 [9.8] vs 50.7 [8.5]), and global (mean [SD] T-score 49.2 [6.8] vs 51.1 [5.9]) NP assessments. Baseline median Aβ40, GFAP, and NFL levels were higher among WLWH vs WLWOH. There were no differences in 1-year biomarker change by HIV serostatus. Lower learning, memory, and motor NP were associated with 1-year Aβ40 increase; lower learning and motor with Aβ42 increase; lower motor with p-tau231 increase; and lower processing speed, verbal fluency and motor with NFL increase in the entire sample. Among WLWH, a 1-year increase in Aβ40 from baseline to follow-up was associated with worse learning, memory, and global NP; a 1-year increase in t-tau with worse executive function; and a 1-year increase in NFL with worse processing speed. Among WLWOH, a 1-year increase in Aβ40 and Aβ42 were associated with poorer memory performance and NFL was associated with poorer motor performance.

Conclusions and Relevance

These findings suggest that increases in certain plasma AD biomarkers are associated with NP in WLWH and WLWOH and may be associated with later onset of AD, and measuring these biomarkers could be a pivotal advancement in monitoring aging brain health and development of AD among women with and without HIV.

Nuclear Imaging Data-Driven Classification of Parkinson's Disease

BACKGROUND

Parkinson's disease (PD) is a heterogeneous neurodegenerative disorder characterized by motor and nonmotor symptoms. Several features have prognostic importance and have been used as key indicators for identifying clinical subtypes. However, the symptom-based classification approach has limitations with respect to the stability of the obtained subtypes.

OBJECTIVES

The purpose of this study was to identify subtypes of PD using nuclear imaging biomarkers targeting the cardiac sympathetic nervous and nigro-striatal systems and to compare patterns of cortical morphological change among obtained subtypes.

METHODS

We performed unbiased hierarchical cluster analysis using 123 I-metaiodobenzylguanidine cardiac scintigraphy and 123 I-N-(3-fluoropropyl)-2β-carbomethoxy-3β-(4-iodophenyl) nortropane single photon emission computed tomography data for 56 patients with PD. We compared clinical characteristics and the patterns of cortical atrophy in the obtained clusters.

RESULTS

Three clusters were identified and showed distinct characteristics in onset ages and dopamine-replacement therapy and deep brain stimulation requirements. According to the characteristics, clusters were classified into two subtypes, namely, "cardio-cortical impairment (CC)" and "dopaminergic-dominant dysfunction (DD)" subtype. The three clusters were named according to subtype and time since onset in which 14 patients were classified as "early DD," 25 as "advanced DD," and 17 as "early CC." Compared with the early DD subtype, the early CC subtype showed parietal-dominant diffuse cortical atrophy and the advanced DD subtype showed left-side predominant mild cortical atrophy.

CONCLUSIONS

Nuclear imaging biomarker-based classification can be used to identify clinically and pathologically relevant PD subtypes with distinct disease trajectories. © 2023 International Parkinson and Movement Disorder Society.

Novel fluid biomarkers for mild cognitive impairment: A systematic review and meta-analysis

Mild cognitive impairment (MCI) is a well-established prodromal stage of dementia (e.g., Alzheimer's disease) that is often accompanied by early signs of neurodegeneration. To facilitate a better characterization of the underlying pathophysiology, we assessed the available literature to evaluate potential fluid biomarkers in MCI. Peer-reviewed articles that measured cerebrospinal fluid (CSF) and/or peripheral biomarkers of neuronal injury (total-tau [T-tau], neurofilament light chain [NfL], heart-type fatty acid binding protein [HFABP], neuron-specific enolase, ubiquitin C-terminal hydrolase L1) and/or astroglial pathology (glial fibrillary acidic protein [GFAP], S100 calcium-binding protein B) in MCI and healthy controls were assessed. Group differences were summarized by standardized mean differences (SMDs) and 95% confidence intervals calculated using a random-effects model. Heterogeneity was quantified using I2. A total of 107 studies were included in the meta-analysis and 10 studies were qualitatively reviewed. In CSF, concentrations of NfL (SMD = 0.69 [0.56, 0.83]), GFAP (SMD = 0.41 [0.07, 0.75]), and HFABP (SMD = 0.57 [0.26, 0.89]) were elevated in MCI. In blood, increased concentrations of T-tau (SMD = 0.19 [0.09, 0.29]), NfL (SMD = 0.41 [0.32, 0.49]), and GFAP (SMD = 0.39 [0.23, 0.55]) were found in MCI. Heterogeneity that was identified in all comparisons was explored using meta-regression and subgroup analysis. Elevated NfL and GFAP can be detected in both CSF and peripheral blood. Monitoring these biomarkers in clinical settings may provide important insight into underlying neurodegenerative processes in MCI.

Supported decision making: Facilitating the self-determination of persons living with Alzheimer's and related diseases

Decision-making capacity describes the ability to make a particular decision at a given time. People with Mild Cognitive Impairment (MCI) and mild stage dementia typically experience an associated erosion of their decisional abilities. Many could be said to have marginal capacity. These individuals are in a liminal space between adequate and inadequate capacity. Too often, marginal capacity is overlooked as a category: individuals are classified either as having capacity and being able to make decisions independently or as lacking capacity and needing a surrogate to make decisions for them. These approaches can, respectively, result in under- or overprotection of individuals with marginal capacity. A promising alternative approach is supported decision making. In supported decision making, a person with marginal capacity identifies a trusted person or network of persons to aid them in making their own decisions. Supported decision making is recognized by law in a growing number of states; it is important for geriatricians to be familiar with the concept, as they are increasingly likely to encounter it in their practice. Even in states where supported decision making is not formally recognized, it can be practiced informally, helping patients, care partners, and clinicians strike an appropriate balance between respecting autonomy and recognizing vulnerability. In this article, we describe supported decision making, discuss its ethical and legal foundations, and identify steps by which geriatricians can incorporate it into their practice.

Grey matter volume and CSF biomarkers predict neuropsychological subtypes of MCI

There is increasing evidence of different subtypes of individuals with mild cognitive impairment (MCI). An important line of research is whether neuropsychologically-defined subtypes have distinct patterns of neurodegeneration and cerebrospinal fluid (CSF) biomarker composition. In our study, we demonstrated that MCI participants of the ADNI database (N = 640) can be discriminated into 3 coherent neuropsychological subgroups. Our clustering approach revealed amnestic MCI, mixed MCI, and cluster-derived normal subgroups. Furthermore, classification modeling revealed that specific predictive features can be used to differentiate amnestic and mixed MCI from cognitively normal (CN) controls: CSF Aβ142 concentration for the former and CSF Aβ1-42 concentration, tau concentration as well as grey matter atrophy (especially in the temporal and occipital lobes) for the latter. In contrast, participants from the cluster-derived normal subgroup exhibited an identical profile to CN controls in terms of cognitive performance, brain structure, and CSF biomarker levels. Our comprehensive data analytics strategy provides further evidence that multimodal neuropsychological subtyping is both clinically and neurobiologically meaningful.

Biostatistical Estimation of Tau Threshold Hallmarks (BETTH) Algorithm for Human Tau PET Imaging Studies

A methodology for determining tau PET thresholds is needed to confidently detect early tau deposition. We compared multiple threshold-determining methods in participants who underwent either 18F-flortaucipir or 18F-MK-6240 PET scans. Methods: 18F-flortaucipir (n = 798) and 18F-MK-6240 (n = 216) scans were processed and sampled to obtain regional SUV ratios. Subsamples of the cohorts were based on participant diagnosis, age, amyloid-β status (positive or negative), and neurodegeneration status (positive or negative), creating older-adult (age ≥ 55 y) cognitively unimpaired (amyloid-β-negative, neurodegeneration-negative) and cognitively impaired (mild cognitive impairment/Alzheimer disease, amyloid-β-positive, neurodegeneration-positive) groups, and then were further subsampled via matching to reduce significant differences in diagnostic prevalence, age, and Mini-Mental State Examination score. We used the biostatistical estimation of tau threshold hallmarks (BETTH) algorithm to determine sensitivity and specificity in 6 composite regions. Results: Parametric double receiver operating characteristic analysis yielded the greatest joint sensitivity in 5 of the 6 regions, whereas hierarchic clustering, gaussian mixture modeling, and k-means clustering all yielded perfect joint specificity (2.00) in all regions. Conclusion: When 18F-flortaucipir and 18F-MK-6240 are used, Alzheimer disease-related tau status is best assessed using 2 thresholds, a sensitivity one based on parametric double receiver operating characteristic analysis and a specificity one based on gaussian mixture modeling, delimiting an uncertainty zone indicating participants who may require further evaluation.

Comparing machine learning-derived MRI-based and blood-based neurodegeneration biomarkers in predicting syndromal conversion in early AD

INTRODUCTION

We compared the machine learning-derived, MRI-based Alzheimer's disease (AD) resemblance atrophy index (AD-RAI) with plasma neurofilament light chain (NfL) level in predicting conversion of early AD among cognitively unimpaired (CU) and mild cognitive impairment (MCI) subjects.

METHODS

We recruited participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) who had the following data: clinical features (age, gender, education, Montreal Cognitive Assessment [MoCA]), structural MRI, plasma biomarkers (p-tau181 , NfL), cerebrospinal fluid biomarkers (CSF) (Aβ42, p-tau181 ), and apolipoprotein E (APOE) ε4 genotype. We defined AD using CSF Aβ42 (A+) and p-tau181 (T+). We defined conversion (C+) if a subject progressed to the next syndromal stage within 4 years.

RESULTS

Of 589 participants, 96 (16.3%) were A+T+C+. AD-RAI performed better than plasma NfL when added on top of clinical features, plasma p-tau181 , and APOE ε4 genotype (area under the curve [AUC] = 0.832 vs. AUC = 0.650 among CU, AUC = 0.853 vs. AUC = 0.805 among MCI) in predicting A+T+C+.

DISCUSSION

AD-RAI outperformed plasma NfL in predicting syndromal conversion of early AD.

HIGHLIGHTS

AD-RAI outperformed plasma NfL in predicting syndromal conversion among early AD. AD-RAI showed better metrics than volumetric hippocampal measures in predicting syndromal conversion. Combining clinical features, plasma p-tau181 and apolipoprotein E (APOE) with AD-RAI is the best model for predicting syndromal conversion.

A Systematic Review of tACS Effects on Cognitive Functioning in Older Adults Across the Healthy to Dementia Spectrum

Transcranial alternating current stimulation (tACS) is a form of noninvasive brain stimulation that has experienced rapid growth within the aging population over the past decade due to its potential for modulating cognitive functioning across the "intact" to dementia spectrum. For this reason, we performed a systematic review of the literature to evaluate the efficacy of tACS on cognitive functioning in older adults, including those with cognitive impairment. Our review was completed in June 2023 using Psych INFO, Embase, PubMed, and Cochrane databases. Out of 479 screened articles, 21 met inclusion criteria and were organized according to clinical diagnoses. Seven out of nine studies targeted cognitively intact older adults and showed some type of cognitive improvement after stimulation, whereas nine out of twelve studies targeted clinical diagnoses and showed improved cognitive performance to varying degrees. Studies showed considerable heterogeneity in methodology, stimulation parameters, participant characteristics, choice of cognitive task, and analytic strategy, all of which reinforce the need for standardized reporting of tACS methods. Through this heterogeneity, multiple patterns are described, such as disease progression influencing tACS effects and the need for individualized tailoring. For clinical translation, it is imperative that the field (a) better understand the physiological effects of tACS in these populations, especially in respect to biomarkers, (b) document a causal relationship between tACS delivery and neurophysiological/cognitive effects, and (c) systematically establish dosing parameters (e.g., amplitude, stimulation frequency, number and duration of sessions, need for booster/maintenance sessions).