Structural progression of Alzheimer’s disease over decades: the MRI staging scheme

WDR49-Positive Astrocytes Mark Severity of Neurodegeneration in Frontotemporal Lobar Degeneration and Alzheimer's Disease

A subpopulation of astrocytes expressing WD Repeat Domain 49 (WDR49) was recently identified in frontotemporal lobar degeneration (FTLD) with GRN pathogenic variants. This is the first study to investigate their expression and relation to pathology in other FTLD subtypes and Alzheimer's disease (AD). In a postmortem cohort of TDP-43 proteinopathies (12 GRN, 11 C9orf72, 9 sporadic TDP-43), tauopathies (13 MAPT, 8 sporadic tau), 10 AD, and four controls, immunohistochemistry and immunofluorescence were performed for WDR49 and pathological inclusions on frontal, temporal, and occipital cortical sections. WDR49-positive cell counts (adjusted per mm2) were examined and related to digitally quantified percentage areas of TDP-43/tau pathology and semiquantitative scores of neurodegeneration. Quantitative colocalization analysis of WDR49 and pathological inclusions was done. WDR49-positive astrocytes were present across FTLD subtypes and AD in the brain parenchyma and (peri-)vascular space, with distinct morphological patterns, and were particularly enriched in gray matter. In controls, sporadic WDR49-positive cells were found enveloping vessels. WDR49-positive astrocytes were most abundant in the frontal cortex (FC) of GRN cases and temporal cortex in GRN, AD, and sporadic primary tauopathy. In the occipital cortex, only a few cells were found across groups. WDR49-positive astrocyte counts positively correlated with the severity of neurodegeneration and TDP-43 pathology but not tauopathy. Furthermore, in frontotemporal cortices, WDR49 partly colocalized with TDP-43 (14%-21%) and tau (31%-45%). In conclusion, WDR49 is a marker for a subset of astrocytes with different morphologies across FTLD and AD, reflecting the severity of neurodegeneration. These astrocytes may become activated in neurodegeneration in response to pathological damage and migrate from the vessel wall to the parenchyma.

Clinical phenotypes of Alzheimer's disease: investigating atrophy patterns and their pathological correlates

BACKGROUND

In Alzheimer's disease (AD), MRI atrophy patterns can distinguish between amnestic (typical) and non-amnestic (atypical) clinical phenotypes and are increasingly used for diagnosis and outcome measures in clinical trials. However, understanding how protein accumulation and other key features of neurodegeneration influence these imaging measurements, are lacking. The current study aimed to assess regional MRI patterns of cortical atrophy across clinical AD phenotypes, and their association with amyloid-beta (Aβ), phosphorylated tau (pTau), neuro-axonal degeneration and microvascular deterioration.

METHODS

Post-mortem in-situ 3DT1 3 T-MRI data was obtained from 33 AD (17 typical, 16 atypical) and 16 control brain donors. Additionally, ante-mortem 3DT1 3 T-MRI scans of brain donors were collected if available. Regional volumes were obtained from MRI scans using an atlas based parcellation software. Eight cortical brain regions were selected from formalin-fixed right hemispheres of brain donors and then immunostained for Aβ, pTau, neurofilament light, and collagen IV. Group comparisons and volume-pathology associations were analyzed using linear mixed models corrected for age, sex, post-mortem delay, and intracranial volume.

RESULTS

Compared to controls, both typical and atypical AD showed volume loss in the temporo-occipital cortex, while typical AD showed additional volume loss in the parietal cortex. Posterior cingulate volume was lower in typical AD compared to atypical AD (- 6.9%, p = 0.043). In AD, a global positive association between MRI cortical volume and Aβ load (βs = 0.21, p = 0.010), and a global negative association with NfL load (βs = - 0.18, p = 0.018) were observed. Regionally, higher superior parietal gyrus volume was associated with higher Aβ load in typical AD (βs = 0.47, p = 0.004), lower middle frontal gyrus volume associated with higher NfL load in atypical AD (βs = - 0.50, p < 0.001), and lower hippocampal volume associated with higher COLIV load in typical AD (βs = - 1.69, p < 0.001). Comparing post-mortem with ante-mortem scans showed minimal volume differences at scan-intervals within 2 years, highlighting the translational aspect of this study.

CONCLUSION

For both clinical phenotypes, cortical volume is affected by Aβ and neuro-axonal damage, but in opposing directions. Differences in volume-pathology relationships between clinical phenotypes are region-specific. The findings of this study could improve the interpretation of MRI datasets in heterogenous AD cohorts, both in research and clinical settings.

Allogeneic mesenchymal stem cell therapy with laromestrocel in mild Alzheimer's disease: a randomized controlled phase 2a trial

Alzheimer's disease (AD) is characterized by progressive cognitive decline, severe brain atrophy and neuroinflammation. We conducted a randomized, double-blind, placebo-controlled, parallel-group phase 2a clinical trial that tested the safety and efficacy of laromestrocel, a bone-marrow-derived, allogeneic mesenchymal stem-cell therapy, in slowing AD clinical progression, atrophy and neuroinflammation. Participants across ten centers in the United States were randomly assigned 1:1:1:1 to four infusion groups: group 1 (placebo; four monthly infusions, n = 12); group 2 (25 million cells, one infusion followed by three monthly infusions of placebo, n = 13); group 3 (25 million cells; four monthly doses, n = 13); and group 4 (100 million cells; four monthly doses, n = 11). The study met its primary end point of safety; the rate of treatment-emergent serious adverse events within 4 weeks of any infusion was similar in all four groups: group 1, 0% (95% CI 0-26.5%); group 2, 7.7% (95% CI 0.2-36%); group 3, 7.7% (95% CI 0.2-36%) and group 4, 9.1% (95% CI 0.2-41.3%). Additionally, there were no reported infusion-related reactions, hypersensitivities or amyloid-related imaging abnormalities. Laromestrocel improved clinical assessments at 39 weeks compared to placebo, as measured by a composite AD score (secondary end point was met: group 2 versus placebo change: 0.38; 95% CI -0.06-0.82), Montreal cognitive assessment and the Alzheimer's Disease Cooperative Study Activities of Daily Living. At 39 weeks, Laromestrocel slowed the decline of whole brain volume compared to placebo (n = 10) by 48.4% for all treatment groups combined (groups 2-4: P = 0.005; n = 32) and left hippocampal volume by 61.9% (groups 2-4, P = 0.021; n = 32), and reduced neuroinflammation as measured by diffusion tensor imaging. The change in bilateral hippocampal atrophy correlated with the change in mini-mental state exam scores (R = 0.41, P = 0.0075) in all study patients (N = 42). Collectively these results support safety of single and multiple doses of laromestrocel treatment for mild AD and provide indications of efficacy in combating decline of brain volume and potentially cognitive function. Larger-scale clinical trials of laromestrocel in AD are warranted. ClinicalTrials.gov registration: NCT05233774 .

Utilization of precision medicine digital twins for drug discovery in Alzheimer's disease

Alzheimer's disease (AD) presents significant challenges in drug discovery and development due to its complex and poorly understood pathology and etiology. Digital twins (DTs) are recently developed virtual real-time representations of physical entities that enable rapid assessment of the bidirectional interaction between the virtual and physical domains. With recent advances in artificial intelligence (AI) and the growing accumulation of multi-omics and clinical data, application of DTs in healthcare is gaining traction. Digital twin technology, in the form of multiscale virtual models of patients or organ systems, can track health status in real time with continuous feedback, thereby driving model updates that enhance clinical decision-making. Here, we posit an additional role for DTs in drug discovery, with particular utility for complex diseases like AD. In this review, we discuss salient challenges in AD drug development, including complex disease pathology and comorbidities, difficulty in early diagnosis, and the current high failure rate of clinical trials. We also review DTs and discuss potential applications for predicting AD progression, discovering biomarkers, identifying new drug targets and opportunities for drug repurposing, facilitating clinical trials, and advancing precision medicine. Despite significant hurdles in this area, such as integration and standardization of dynamic medical data and issues of data security and privacy, DTs represent a promising approach for revolutionizing drug discovery in AD.

Effects of exercise on cognition and Alzheimer's biomarkers in a randomized controlled trial of adults with mild cognitive impairment: The EXERT study

INTRODUCTION

The EXERT study (Exercise in Adults with Mild Memory Problems) was a Phase 3, multicenter, randomized controlled trial that examined effects of exercise on cognition and other measures of brain health in sedentary older adults with amnestic mild cognitive impairment (MCI).

METHODS

Participants were randomized to moderate-high intensity aerobic training (AX) or low-intensity stretching/balance/range of motion (SBR) for 18 months. Exercise was supervised for the first 12 months. Assessments were administered at baseline and every 6 months. The primary outcome was a global cognitive composite.

RESULTS

A total of 296 participants were enrolled, and intervention adherence was high (supervised session attendance: AX = 81%, SBR = 87%). Intervention effects on cognition did not differ for AX and SBR (regression = -0.078, standard error [SE] = 0.074; p = 0.3). Notably, there was no 12 month  cognition decline for either group, and mean 12 month  hippocampal volume loss for both groups was low at 0.51%.

DISCUSSION

Exercise intensity did not differentially affect cognitive trajectory. Intervention delivery was successful (high adherence) and cognition remained stable over 12 months  for both MCI groups, an association that warrants further study.

HIGHLIGHTS

Exercise in Adults with Mild Memory Problems (EXERT) was a large multisite randomized controlled trial of moderate-high intensity aerobic training versus lower-intensity flexibility and balance exercise in sedentary older adults with amnestic mild cognitive impairment (MCI). A sensitive and validated measure of global cognitive function, the Alzheimer's Disease Assessment Scale-Cognition supplemented with tests of executive function (ADAS-Cog-Exec), was used to assess intervention efficacy with 12 months of supervised exercise. There was no intervention group difference on the 12-month cognitive trajectory of the ADAS-Cog-Exec. Intervention delivery was successful (high adherence), and cognition remained stable over 12 months for both exercise groups. Regular supported moderate-high or lower-intensity exercise may stall decline in adults with amnestic MCI, but further investigation is needed.

Cerebrovascular burden and neurodegeneration linked to 15-year odor identification decline in older adults

Background

The mechanisms underlying olfactory decline in aging need further investigation. Noticeably, the longitudinal relationship of biological markers with olfaction remains underexplored. We investigated whether baseline levels and progression of microvascular lesions and brain atrophy are associated with odor identification (OID) decline.

Methods

The association between structural MRI markers and OID decline was examined in participants from the SNAC-K MRI study who were free from dementia at baseline (n = 401, mean age = 70.2 years, 60% females). OID was repeatedly assessed over 15 years. Presence of lacunes, white matter hyperintensities (WMH), perivascular spaces (PVS), and lateral ventricular, hippocampal, amygdalar, and total gray matter (GM) volumes were assessed up to 6 years, concurrent with the first 6 years of olfactory assessments.

Results

Higher PVS count and lower hippocampal and GM volumes at baseline were associated with accelerated OID decline (pFWE  < 0.05). Longitudinally (n = 225), presence of lacunes at follow-up, faster WMH volume and PVS count increases, faster lateral ventricular enlargement, and faster hippocampal, amygdalar, and GM atrophy were associated with accelerated OID decline (p FWE < 0.05).

Conclusion

Olfactory decline is related to both increased cerebrovascular burden and accelerated brain atrophy over time.

Evaluation of altered cell-cell communication between glia and neurons in the hippocampus of 3xTg-AD mice at two time points

Alzheimer's disease (AD) is the most common form of dementia and is characterized by progressive memory loss and cognitive decline, affecting behavior, speech, and motor abilities. The neuropathology of AD includes the formation of extracellular amyloid-β plaques and intracellular neurofibrillary tangles of phosphorylated tau, along with neuronal loss. Although neuronal loss is an AD hallmark, cell-cell communication between neuronal and non-neuronal cell populations maintains neuronal health and brain homeostasis. To study changes in cell-cell communication during disease progression, we performed snRNA-sequencing of the hippocampus from female 3xTg-AD and wild-type littermates at 6 and 12 months. We inferred differential cell-cell communication between 3xTg-AD and wild-type mice across time points and between senders (astrocytes, microglia, oligodendrocytes, and OPCs) and receivers (excitatory and inhibitory neurons) of interest. We also assessed the downstream effects of altered glia-neuron communication using pseudobulk differential gene expression, functional enrichment, and gene regulatory analyses. We found that glia-neuron communication is increasingly dysregulated in 12-month 3xTg-AD mice. We also identified 23 AD-associated ligand-receptor pairs that are upregulated in the 12-month-old 3xTg-AD hippocampus. Our results suggest increased AD association of interactions originating from microglia. Signaling mediators were not significantly differentially expressed but showed altered gene regulation and transcription factor activity. Our findings indicate that altered glia-neuron communication is increasingly dysregulated and affects the gene regulatory mechanisms in neurons of 12-month-old 3xTg-AD mice.

Mild Behavioral Impairment and cognitive functions: A systematic review and meta-analysis

Mild behavioral impairment (MBI) represents a recently introduced diagnostic concept that focuses on behavioral and personality changes occurring in late life and associated with cognitive decline. Nevertheless, the relationship between these dimensions remains unclear. This systematic review and meta-analysis aim to analyze the relationship between MBI and cognitive functioning. The review process was conducted according to the PRISMA-Statement. Restrictions were made, selecting the studies published in peer-review journals, including at least one cognitive measure and presenting the measurement of MBI. Studies that included participants with neurological disorders, dementia, or psychiatric disorders or that only did a neuroimaging or genetic study were excluded. Twenty-two studies were included in the systematic review, while in the meta-analysis seventeen studies featured data to be included in the analyses. The results were classified according to the following cognitive domains: global cognitive functioning, memory, language, attention executive functions, visuospatial skills, and processing speed. In the quantitative analysis, only global cognitive functioning, executive function, attention, and memory were evaluated. The results of both qualitative and quantitative analysis indicate that individuals with MBI exhibited diminished performance on cognitive tasks when compared to those without MBI symptoms. These results are stronger when evaluating the various domains individually (particularly memory and executive functions) than when a global assessment was made. These findings highlight the potential role of MBI symptoms as early indicators of neurodegenerative processes, reinforcing the necessity for comprehensive assessments that encompass both behavioral and cognitive evaluations. The early detection of these symptoms in prodromal phases can be very useful for the development of non-pharmacological interventions and may provide relevant guidelines for clinicians in the management and diagnosis of neurodegenerative disorders.

Extracellular vesicles contribute to the beneficial effects of exercise training in APP/PS1 mice

Exercise improves cognitive function in Alzheimer's disease (AD) via mechanism that are not fully clear. Here, we first examined the effect of voluntary exercise training (VET) on energy metabolism and cognitive function in the APP/PS1 transgenic mouse (Tg) model of familial AD. Next, we profiled extracellular vesicles (EVs) and examined whether they may play a role in the protective effects of VET via intranasal administration of EVs, purified from the blood of sedentary (sEV) and/or acutely exercised (eEV) donor wild-type mice into APP/PS1Tg mice. We show that VET reduced resting energy expenditure (REE) and improved cognition in APP/PS1 Tg mice. Administration of eEV, but not sEV, also reduced REE, but had no effect on cognition. Taken together, these data show that exercise is effective intervention to improve symptoms of AD in APP/PS1Tg mice. In addition, eEVs mediate some of these effects, implicating EVs in the treatment of age-related neurodegenerative diseases.

Volume Changes in Brain Subfields of Patients with Alzheimer's Disease After Transcranial Ultrasound Stimulation

Background/Objectives: Alzheimer's disease (AD) is characterized by progressive brain atrophy marked by cognitive decline and memory loss, which significantly affect patients' quality of life. Transcranial ultrasound stimulation (TUS) is a potential physical treatment for AD patients. However, the specific brain regions stimulated by TUS and its therapeutic effects remain unclear. Methods: In this study, magnetic resonance imaging (MRI) and FreeSurfer segmentation were employed to assess alterations in the brain volume of AD patients after TUS. Results: Our findings revealed significant volume increases in the corpus callosum (CC) and lateral orbitofrontal cortex (lOFC) in the TUS group. Moreover, the volumetric changes in the CC were strongly correlated with improvements in the Mini-Mental State Examination score, which is a widely used measure of cognitive function of AD patients. Conclusions: TUS has the potential to alleviate disease progression and offers a non-invasive therapeutic approach to the improvement of cognitive function in AD patients.

Compositional brain scores capture Alzheimer's disease-specific structural brain patterns along the disease continuum

INTRODUCTION

Traditional multivariate methods for neuroimaging studies overlook the interdependent relationship between brain features. This study addresses this gap by analyzing relative brain volumetric patterns to capture how Alzheimer's disease (AD) and genetics influence brain structure along the disease continuum.

METHODS

This study analyzed data from participants across the AD continuum from the Alzheimer's and Families (ALFA) and Alzheimer's Disease Neuroimaging Initiative (ADNI) studies. Compositional data analysis (CoDA) was exploited to examine relative brain volumetric variations that (1) were linked to different AD stages compared to cognitively unimpaired amyloid-β-negative (CU A-) individuals and (2) varied by AD genetic risk.

RESULTS

Disease stage-specific compositional brain scores were identified, differentiating CU A- individuals from those in more advanced stages. Genetic risk-stratified models revealed a broader genetic landscape affecting brain morphology in AD, beyond the well-known apolipoprotein E ε4 allele.

DISCUSSION

CoDA emerges as an alternative multivariate framework to deepen understanding of AD-related structural changes and support targeted interventions for those at higher genetic risk.

HIGHLIGHTS

Compositional data analysis (CoDA) revealed the relative variation of brain region volumes, captured in compositional brain scores, capable of discerning between cognitively unimpaired amyloid-β-negative individuals and subjects within other disease-stage groups along the Alzheimer's disease (AD) continuum. CoDA also uncovered the genetic vulnerability of specific brain regions at each stage of the disease along the continuum. CoDA is capable of integrating magnetic resonance imaging data from two different cohorts without stringent requirements for harmonization. This translates as an advantage, compared to traditional methods, and strengthens the reliability of cross-study comparisons by standardizing the data despite different labeling agreements, facilitating collaborative and large-scale research. The algorithm is sensitive to AD-specific effects, as the main compositional brain scores display little overlap with the age-specific compositional brain score. CoDA provides a more accurate analysis of brain imaging data addressing its compositional nature, which can influence the development of targeted approaches, opening new avenues for enhancing brain health.

Synapse vulnerability and resilience underlying Alzheimer's disease

Synapse preservation is key for healthy cognitive ageing, and synapse loss represents a critical anatomical basis of cognitive dysfunction in Alzheimer's disease (AD), predicting dementia onset, severity, and progression. Synapse loss is viewed as a primary pathologic event, preceding neuronal loss and brain atrophy in AD. Synapses may, therefore, represent one of the earliest and clinically most meaningful targets of the neuropathologic processes driving AD dementia. The synapse loss in AD is highly selective and targets particularly vulnerable synapses while leaving others, termed resilient, largely unaffected. Yet, the anatomic and molecular hallmarks of the vulnerable and resilient synapse populations and their association with AD neuropathologic changes (e.g. amyloid-β plaques and tau tangles) and memory dysfunction remain poorly understood. Characterising the selectively vulnerable and resilient synapses in AD may be key to understanding the mechanisms of cognitive preservation versus loss and enable the development of robust biomarkers and disease-modifying therapies for dementia.

Controversies and insights into PTBP1-related astrocyte-neuron transdifferentiation: neuronal regeneration strategies for Parkinson's and Alzheimer's disease

Promising therapeutic strategies are being explored to replace or regenerate the neuronal populations that are lost in patients with neurodegenerative disorders. Several research groups have attempted direct reprogramming of astrocytes into neurons by manipulating the expression of polypyrimidine tract-binding protein 1 (PTBP1) and claimed putative converted neurons to be functional, which led to improved disease outcomes in animal models of several neurodegenerative disorders. However, a few other studies reported data that contradict these claims, raising doubt about whether PTBP1 suppression truly reprograms astrocytes into neurons and the therapeutic potential of this approach. This review discusses recent advances in regenerative therapeutics including stem cell transplantations for central nervous system disorders, with a particular focus on Parkinson's and Alzheimer's diseases. We also provide a perspective on this controversy by considering that astrocyte heterogeneity may be the key to understanding the discrepancy in published studies, and that certain subpopulations of these glial cells may be more readily converted into neurons.

Heterogeneity of cerebral atrophic rate in mild cognitive impairment and its interactive association with proteins related to microglia activity on longitudinal cognitive changes

BACKGROUND

Heterogeneity of cerebral atrophic rate commonly exists in mild cognitive impairment (MCI), which may be associated with microglia-involved neuropathology and have an influence on cognitive outcomes.

OBJECTIVE

We aim to explore the heterogeneity of cerebral atrophic rate among MCI and its association with plasma proteins related to microglia activity, with further investigation of their interaction effects on long-term cognition.

SUBJECTS

A total of 630 MCI subjects in the ADNI database were included, of which 260 subjects were available with baseline data on plasma proteins.

METHODS

Group-based multi-trajectory modeling (GBMT) was used to identify the latent classes with heterogeneous cerebral atrophic rates. Associations between latent classes and plasma proteins related to microglia activity were investigated with generalized linear models. Linear mixed effect models (LME) were implemented to explore the interaction effects between proteins related to microglia activity and identified latent classes on longitudinal cognitive changes.

RESULTS

Two latent classes were identified and labeled as the slow-atrophy class and the fast-atrophy class. Associations were found between such heterogeneity of atrophic rates and plasma proteins related to microglia activity, especially AXL receptor tyrosine kinase (AXL), CD40 antigen (CD40), and tumor necrosis factor receptor-like 2 (TNF-R2). Interaction effects on longitudinal cognitive changes showed that higher CD40 was associated with faster cognitive decline in the slow-atrophy class and higher AXL or TNF-R2 was associated with slower cognitive decline in the fast-atrophy class.

CONCLUSIONS

Heterogeneity of atrophic rates at the MCI stage is associated with several plasma proteins related to microglia activity, which show either protective or adverse effects on long-term cognition depending on the variability of atrophic rates.

Age-related alterations in human cortical microstructure across the lifespan: Insights from high-gradient diffusion MRI

The human brain undergoes age-related microstructural alterations across the lifespan. Soma and Neurite Density Imaging (SANDI), a novel biophysical model of diffusion MRI, provides estimates of cell body (soma) radius and density, and neurite density in gray matter. The goal of this cross-sectional study was to assess the sensitivity of high-gradient diffusion MRI toward age-related alterations in cortical microstructure across the adult lifespan using SANDI. Seventy-two cognitively unimpaired healthy subjects (ages 19-85 years; 40 females) were scanned on the 3T Connectome MRI scanner with a maximum gradient strength of 300mT/m using a multi-shell diffusion MRI protocol incorporating 8 b-values and diffusion time of 19 ms. Intra-soma signal fraction obtained from SANDI model-fitting to the data was strongly correlated with age in all major cortical lobes (r = -0.69 to -0.60, FDR-p < 0.001). Intra-soma signal fraction (r = 0.48-0.63, FDR-p < 0.001) and soma radius (r = 0.28-0.40, FDR-p < 0.04) were significantly correlated with cortical volume in the prefrontal cortex, frontal, parietal, and temporal lobes. The strength of the relationship between SANDI metrics and age was greater than or comparable to the relationship between cortical volume and age across the cortical regions, particularly in the occipital lobe and anterior cingulate gyrus. In contrast to the SANDI metrics, all associations between diffusion tensor imaging (DTI) and diffusion kurtosis imaging metrics and age were low to moderate. These results suggest that high-gradient diffusion MRI may be more sensitive to underlying substrates of neurodegeneration in the aging brain than DTI and traditional macroscopic measures of neurodegeneration such as cortical volume and thickness.

Structural and molecular characterization of astrocyte and vasculature connectivity in the mouse hippocampus and cortex

The relation of astrocytic endfeet to the vasculature plays a key functional role in the neuro-glia-vasculature unit. We characterize the spatial organization of astrocytes and the structural aspects that facilitate their involvement in molecular exchanges. Using double transgenic mice, we performed co-immunostaining, confocal microscopy, and three-dimensional digital segmentation to investigate the biophysical and molecular organization of astrocytes and their intricate endfoot network at the micrometer level in the isocortex and hippocampus. The results showed that hippocampal astrocytes had smaller territories, reduced endfoot dimensions, and fewer contacts with blood vessels compared with those in the isocortex. Additionally, we found that both connexins 43 and 30 have a higher density in the endfoot and the former is overexpressed relative to the latter. However, due to the limitations of the method, further studies are needed to determine the exact localization on the endfoot. The quantitative information obtained in this study will be useful for modeling the interactions of astrocytes with the vasculature.

Unveiling DNA methylation in Alzheimer's disease: a review of array-based human brain studies

The intricacies of Alzheimer's disease pathogenesis are being increasingly illuminated by the exploration of epigenetic mechanisms, particularly DNA methylation. This review comprehensively surveys recent human-centered studies that investigate whole genome DNA methylation in Alzheimer's disease neuropathology. The examination of various brain regions reveals distinctive DNA methylation patterns that associate with the Braak stage and Alzheimer's disease progression. The entorhinal cortex emerges as a focal point due to its early histological alterations and subsequent impact on downstream regions like the hippocampus. Notably, ANK1 hypermethylation, a protein implicated in neurofibrillary tangle formation, was recurrently identified in the entorhinal cortex. Further, the middle temporal gyrus and prefrontal cortex were shown to exhibit significant hypermethylation of genes like HOXA3, RHBDF2, and MCF2L, potentially influencing neuroinflammatory processes. The complex role of BIN1 in late-onset Alzheimer's disease is underscored by its association with altered methylation patterns. Despite the disparities across studies, these findings highlight the intricate interplay between epigenetic modifications and Alzheimer's disease pathology. Future research efforts should address methodological variations, incorporate diverse cohorts, and consider environmental factors to unravel the nuanced epigenetic landscape underlying Alzheimer's disease progression.

Increased expression of the proapoptotic presenilin associated protein is involved in neuronal tangle formation in human brain

Presenilin-associated protein (PSAP) is a mitochondrial proapoptotic protein as established in cell biology studies. It remains unknown whether it involves in neurodegenerative diseases. Here, we explored PASP expression in adult and aged human brains and its alteration relative to Alzheimer-disease (AD)-type neuropathology. In pathology-free brains, light PASP immunoreactivity (IR) occurred among largely principal neurons in the cerebrum and subcortical structures. In the brains with AD pathology, enhanced PSAP IR occurred in neuronal and neuritic profiles with a tangle-like appearance, with PSAP and pTau protein levels elevated in neocortical lysates relative to control. Neuronal/neuritic profiles with enhanced PSAP IR partially colocalized with pTau, but invariably with Amylo-Glo labelled tangles. The neuronal somata with enhanced PASP IR also showed diminished IR for casein kinase 1 delta (Ck1δ), a marker of granulovacuolar degeneration; and diminished IR for sortilin, which is normally expressed in membrane and intracellular protein sorting/trafficking organelles. In old 3xTg-AD mice with β-amyloid and pTau pathologies developed in the brain, PSAP IR in the cerebral sections exhibited no difference relative to wildtype mice. These findings indicate that PSAP upregulation is involved in the course of tangle formation especially in the human brain during aging and in AD pathogenesis.

Longitudinal accelerated brain age in mild cognitive impairment and Alzheimer's disease

Introduction

Brain age is a machine learning-derived estimate that captures lower brain volume. Previous studies have found that brain age is significantly higher in mild cognitive impairment and Alzheimer's disease (AD) compared to healthy controls. Few studies have investigated changes in brain age longitudinally in MCI and AD. We hypothesized that individuals with MCI and AD would show heightened brain age over time and across the lifespan. We also hypothesized that both MCI and AD would show faster rates of brain aging (higher slopes) over time compared to healthy controls.

Methods

We utilized data from an archival dataset, mainly Alzheimer's disease Neuroimaging Initiative (ADNI) 1 with 3Tesla (3 T) data which totaled 677 scans from 183 participants. This constitutes a secondary data analysis on existing data. We included control participants (healthy controls or HC), individuals with MCI, and individuals with AD. We predicted brain age using a pre-trained model and tested for accuracy. We investigated cross-sectional differences in brain age by group [healthy controls or HC, mild cognitive impairment (MCI), and AD]. We conducted longitudinal modeling of age and brain age by group using time from baseline in one model and chronological age in another model.

Results

We predicted brain age with a mean absolute error (MAE) < 5 years. Brain age was associated with age across the study and individuals with MCI and AD had greater brain age on average. We found that the MCI group had significantly higher rates of change in brain age over time compared to the HC group regardless of individual chronologic age, while the AD group did not differ in rate of brain age change.

Discussion

We replicated past studies that showed that MCI and AD had greater brain age than HC. We additionally found that this was true over time, both groups showed higher brain age longitudinally. Contrary to our hypothesis, we found that the MCI, but not the AD group, showed faster rates of brain aging. We essentially found that while the MCI group was actively experiencing faster rates of brain aging, the AD group may have already experienced this acceleration (as they show higher brain age). Individuals with MCI may experience higher rates of brain aging than AD and controls. AD may represent a homeostatic endpoint after significant neurodegeneration. Future work may focus on individuals with MCI as one potential therapeutic option is to alter rates of brain aging, which ultimately may slow cognitive decline in the long-term.

Integrating longitudinal mental health data into a staging database: harnessing DDI-lifecycle and OMOP vocabularies within the INSPIRE Network Datahub

Background

Longitudinal studies are essential for understanding the progression of mental health disorders over time, but combining data collected through different methods to assess conditions like depression, anxiety, and psychosis presents significant challenges. This study presents a mapping technique allowing for the conversion of diverse longitudinal data into a standardized staging database, leveraging the Data Documentation Initiative (DDI) Lifecycle and the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) standards to ensure consistency and compatibility across datasets.

Methods

The "INSPIRE" project integrates longitudinal data from African studies into a staging database using metadata documentation standards structured with a snowflake schema. This facilitates the development of Extraction, Transformation, and Loading (ETL) scripts for integrating data into OMOP CDM. The staging database schema is designed to capture the dynamic nature of longitudinal studies, including changes in research protocols and the use of different instruments across data collection waves.

Results

Utilizing this mapping method, we streamlined the data migration process to the staging database, enabling subsequent integration into the OMOP CDM. Adherence to metadata standards ensures data quality, promotes interoperability, and expands opportunities for data sharing in mental health research.

Conclusion

The staging database serves as an innovative tool in managing longitudinal mental health data, going beyond simple data hosting to act as a comprehensive study descriptor. It provides detailed insights into each study stage and establishes a data science foundation for standardizing and integrating the data into OMOP CDM.

Machine Learning-Driven Prediction of Brain Age for Alzheimer's Risk: APOE4 Genotype and Gender Effects

Background: Alzheimer's disease (AD) is a leading cause of dementia, and it is significantly influenced by the apolipoprotein E4 (APOE4) gene and gender. This study aimed to use machine learning (ML) algorithms to predict brain age and assess AD risk by considering the effects of the APOE4 genotype and gender. Methods: We collected brain volumetric MRI data and medical records from 1100 cognitively unimpaired individuals and 602 patients with AD. We applied three ML regression models-XGBoost, random forest (RF), and linear regression (LR)-to predict brain age. Additionally, we introduced two novel metrics, brain age difference (BAD) and integrated difference (ID), to evaluate the models' performances and analyze the influences of the APOE4 genotype and gender on brain aging. Results: Patients with AD displayed significantly older brain ages compared to their chronological ages, with BADs ranging from 6.5 to 10 years. The RF model outperformed both XGBoost and LR in terms of accuracy, delivering higher ID values and more precise predictions. Comparing the APOE4 carriers with noncarriers, the models showed enhanced ID values and consistent brain age predictions, improving the overall performance. Gender-specific analyses indicated slight enhancements, with the models performing equally well for both genders. Conclusions: This study demonstrates that robust ML models for brain age prediction can play a crucial role in the early detection of AD risk through MRI brain structural imaging. The significant impact of the APOE4 genotype on brain aging and AD risk is also emphasized. These findings highlight the potential of ML models in assessing AD risk and suggest that utilizing AI for AD identification could enable earlier preventative interventions.

Evaluation of altered cell-cell communication between glia and neurons in the hippocampus of 3xTg-AD mice at two time points

Alzheimer's disease (AD) is the most common form of dementia and is characterized by progressive memory loss and cognitive decline, affecting behavior, speech, and motor abilities. The neuropathology of AD includes the formation of extracellular amyloid-β plaque and intracellular neurofibrillary tangles of phosphorylated tau, along with neuronal loss. While neuronal loss is an AD hallmark, cell-cell communication between neuronal and non-neuronal cell populations maintains neuronal health and brain homeostasis. To study changes in cellcell communication during disease progression, we performed snRNA-sequencing of the hippocampus from female 3xTg-AD and wild-type littermates at 6 and 12 months. We inferred differential cell-cell communication between 3xTg-AD and wild-type mice across time points and between senders (astrocytes, microglia, oligodendrocytes, and OPCs) and receivers (excitatory and inhibitory neurons) of interest. We also assessed the downstream effects of altered glia-neuron communication using pseudobulk differential gene expression, functional enrichment, and gene regulatory analyses. We found that glia-neuron communication is increasingly dysregulated in 12-month 3xTg-AD mice. We also identified 23 AD-associated ligand-receptor pairs that are upregulated in the 12-month-old 3xTg-AD hippocampus. Our results suggest increased AD association of interactions originating from microglia. Signaling mediators were not significantly differentially expressed but showed altered gene regulation and TF activity. Our findings indicate that altered glia-neuron communication is increasingly dysregulated and affects the gene regulatory mechanisms in neurons of 12-month-old 3xTg-AD mice.

The current status and challenges of olfactory dysfunction study in Alzheimer's Disease

Olfactory functioning involves multiple cognitive processes and the coordinated actions of various neural systems. Any disruption at any stage of this process may result in olfactory dysfunction, which is consequently widely used to predict the onset and progression of diseases, such as Alzheimer's Disease (AD). Although the underlying mechanisms have not yet been fully unraveled, apparent changes were observed in olfactory brain areas form patients who suffer from AD by means of medical imaging and electroencephalography (EEG). Olfactory dysfunction holds significant promise in detecting AD during the preclinical stage preceding mild cognitive impairment (MCI). Owing to the strong specificity, olfactory tests are prevalently applied for screening in community cohorts. And combining olfactory tests with other biomarkers may further establish an optimal model for AD prediction in studies of specific olfactory dysfunctions and improve the sensitivity and specificity of early AD diagnosis.

An estimate of the longitudinal pace of aging from a single brain scan predicts dementia conversion, morbidity, and mortality

To understand how aging affects functional decline and increases disease risk, it is necessary to develop accurate and reliable measures of how fast a person is aging. Epigenetic clocks measure aging but require DNA methylation data, which many studies lack. Using data from the Dunedin Study, we introduce an accurate and reliable measure for the rate of longitudinal aging derived from cross-sectional brain MRI: the Dunedin Pace of Aging Calculated from NeuroImaging or DunedinPACNI. Exporting this measure to the Alzheimer's Disease Neuroimaging Initiative and UK Biobank neuroimaging datasets revealed that faster DunedinPACNI predicted participants' cognitive impairment, accelerated brain atrophy, and conversion to diagnosed dementia. Underscoring close links between longitudinal aging of the body and brain, faster DunedinPACNI also predicted physical frailty, poor health, future chronic diseases, and mortality in older adults. Furthermore, DunedinPACNI followed the expected socioeconomic health gradient. When compared to brain age gap, an existing MRI aging biomarker, DunedinPACNI was similarly or more strongly related to clinical outcomes. DunedinPACNI is a "next generation" MRI measure that will be made publicly available to the research community to help accelerate aging research and evaluate the effectiveness of dementia prevention and anti-aging strategies.

A "glympse" into neurodegeneration: Diffusion MRI and cerebrospinal fluid aquaporin-4 for the assessment of glymphatic system in Alzheimer's disease and other dementias

The glymphatic system (GS) is a whole-brain perivascular network, consisting of three compartments: the periarterial and perivenous spaces and the interposed brain parenchyma. GS dysfunction has been implicated in neurodegenerative diseases, particularly Alzheimer's disease (AD). So far, comprehensive research on GS in humans has been limited by the absence of easily accessible biomarkers. Recently, promising non-invasive methods based on magnetic resonance imaging (MRI) along with aquaporin-4 (AQP4) quantification in the cerebrospinal fluid (CSF) were introduced for an indirect assessment of each of the three GS compartments. We recruited 111 consecutive subjects presenting with symptoms suggestive of degenerative cognitive decline, who underwent 3 T MRI scanning including multi-shell diffusion-weighted images. Forty nine out of 111 also underwent CSF examination with quantification of CSF-AQP4. CSF-AQP4 levels and MRI measures-including perivascular spaces (PVS) counts and volume fraction (PVSVF), white matter free water fraction (FW-WM) and mean kurtosis (MK-WM), diffusion tensor imaging analysis along the perivascular spaces (DTI-ALPS) (mean, left and right)-were compared among patients with AD (n = 47) and other neurodegenerative diseases (nAD = 24), patients with stable mild cognitive impairment (MCI = 17) and cognitively unimpaired (CU = 23) elderly people. Two runs of analysis were conducted, the first including all patients; the second after dividing both nAD and AD patients into two subgroups based on gray matter atrophy as a proxy of disease stage. Age, sex, years of education, and scanning time were included as confounding factors in the analyses. Considering the whole cohort, patients with AD showed significantly higher levels of CSF-AQP4 (exp(b) = 2.05, p = .005) and FW-WM FW-WM (exp(b) = 1.06, p = .043) than CU. AQP4 levels were also significantly higher in nAD in respect to CU (exp(b) = 2.98, p < .001). CSF-AQP4 and FW-WM were significantly higher in both less atrophic AD (exp(b) = 2.20, p = .006; exp(b) = 1.08, p = .019, respectively) and nAD patients (exp(b) = 2.66, p = .002; exp(b) = 1.10, p = .019, respectively) compared to CU subjects. Higher total (exp(b) = 1.59, p = .013) and centrum semiovale PVS counts (exp(b) = 1.89, p = .016), total (exp(b) = 1.50, p = .036) and WM PVSVF (exp(b) = 1.89, p = .005) together with lower MK-WM (exp(b) = 0.94, p = .006), mean and left ALPS (exp(b) = 0.91, p = .043; exp(b) = 0.88, p = .010 respectively) were observed in more atrophic AD patients in respect to CU. In addition, more atrophic nAD patients exhibited higher levels of AQP4 (exp(b) = 3.39, p = .002) than CU. Our results indicate significant changes in putative MRI biomarkers of GS and CSF-AQP4 levels in AD and in other neurodegenerative dementias, suggesting a close interaction between glymphatic dysfunction and neurodegeneration, particularly in the case of AD. However, the usefulness of some of these biomarkers as indirect and standalone indices of glymphatic activity may be hindered by their dependence on disease stage and structural brain damage.

A Holistic Analysis of Alzheimer's Disease-Associated lncRNA Communities Reveals Enhanced lncRNA-miRNA-RBP Regulatory Triad Formation Within Functionally Segregated Clusters

Recent studies on the regulatory networks implicated in Alzheimer's disease (AD) evince long non-coding RNAs (lncRNAs) as crucial regulatory players, albeit a poor understanding of the mechanism. Analyzing differential gene expression in the RNA-seq data from the post-mortem AD brain hippocampus, we categorized a list of AD-dysregulated lncRNA transcripts into functionally similar communities based on their k-mer profiles. Using machine-learning-based algorithms, their subcellular localizations were mapped. We further explored the functional relevance of each community through AD-dysregulated miRNA, RNA-binding protein (RBP) interactors, and pathway enrichment analyses. Further investigation of the miRNA-lncRNA and RBP-lncRNA networks from each community revealed the top RBPs, miRNAs, and lncRNAs for each cluster. The experimental validation community yielded ELAVL4 and miR-16-5p as the predominant RBP and miRNA, respectively. Five lncRNAs emerged as the top-ranking candidates from the RBP/miRNA-lncRNA networks. Further analyses of these networks revealed the presence of multiple regulatory triads where the RBP-lncRNA interactions could be augmented by the enhanced miRNA-lncRNA interactions. Our results advance the understanding of the mechanism of lncRNA-mediated AD regulation through their interacting partners and demonstrate how these functionally segregated but overlapping regulatory networks can modulate the disease holistically.

Alteration in amygdala subfield volumes and their association with cognition in mild cognitive impairment

BACKGROUND

The amygdala has an important role in cognitive and affective functions. The involvement of amygdala and related limbic structures is implicated in many aspects of memory and emotion in mild cognitive impairment (MCI). In the present study, we aimed to compare the volumetric measurements of amygdala and its subfields as well as their association with cognitive functions in stable MCI (sMCI).

METHODS

We performed Addenbrooke's cognitive examination III (ACE-III) test, as well as high-resolution T1-weighted images from 31 participants with sMCI and 31 age-matched healthy controls. The amygdala subfield volumes were extracted using Freesurfer software, and group differences were assessed using general linear model (GLM) with age, gender, education and estimated intracranial volume (ICV) as covariates. Partial correlation was also calculated between cognitive scores and volumes of amygdala subfields in healthy controls and sMCI participants controlling for estimated ICV.

RESULTS

sMCI participants exhibited significantly reduced volumes in most of the right amygdala subfields, including basal nucleus, accessory basal nucleus, central nucleus, medial nucleus, corticoamygdaloid transition area, and whole amygdala, as well as significantly reduced right amygdala/hippocampus ratio compared to healthy controls. In addition, our results revealed statistically significant positive correlations between ACE memory scores and the volumes of right central nucleus, right medial nucleus, right cortical nucleus, and the right whole amygdala, in sMCI.

CONCLUSIONS

Our findings revealed volumetric reductions in most of the right amygdala subfields along with its association with the memory functions in sMCI. These findings provide valuable insights into the underlying anatomical factors contributing to neurocognitive symptoms in MCI.

Dual sensitivity-enhanced microring resonance-based integrated microfluidic biosensor for Aβ42 detection

Sensitive, accurate, and straightforward biosensors are pivotal in the battle against Alzheimer's disease, particularly in light of the escalating patient population. These biosensors enable early adjunctive diagnosis, thereby facilitating prompt intervention, alleviating socioeconomic burdens, and preserving individual well-being. In this study, we introduce the development of a highly sensitive add-drop dual-microring resonant microfluidic sensing chip boasting a sensitivity of 188.11 nm/RIU, marking a significant 20.7% enhancement over single microring systems. Leveraging ultra-thin Parylene C for streamlined antibody immobilization and non-destructive removal, this platform facilitates the precise quantification of the Alzheimer's disease biomarker Aβ42. Employing an immune sensing strategy that amplifies and captures antigen signals using Au-labeled antibodies, we achieve an exceptional limit of detection of 9.02 pg/mL. The designed microring-based microfluidic biosensor chip exhibits outstanding specificity and sensitivity for Aβ42 in serum samples, offering a promising avenue for the early adjunctive diagnosis of Alzheimer's disease.

Aberrant cortical morphology patterns are associated with cognitive impairment in patients with chronic heart failure

A mounting body of evidences suggests that patients with chronic heart failure (HF) frequently experience cognitive impairments, but the neuroanatomical mechanism underlying these impairments remains elusive. In this retrospective study, 49 chronic HF patients and 49 healthy controls (HCs) underwent brain structural MRI scans and cognitive assessments. Cortical morphology index (cortical thickness, complexity, sulcal depth and gyrification) were evaluated. Correlations between cortical morphology and cognitive scores and clinical variables were explored. Logistic regression analysis was employed to identify risk factors for predicting 3-year major adverse cardiovascular events. Compared with HCs, patients with chronic HF exhibited decreased cognitive scores (p < .001) and decreased cortical thickness, sulcal depth and gyrification in brain regions involved cognition, sensorimotor, autonomic nervous system (family-wise error correction, all p values <.05). Notably, HF duration and New York Heart Association (NYHA) demonstrated negative correlations with abnormal cortex morphology, particularly HF duration and thickness in left precentral gyrus (r = -.387, p = .006). Cortical morphology characteristics exhibited positive associations with global cognition, particularly cortical thickness in left pars opercularis (r = .476, p < .001). NYHA class is an independent risk factor for adverse outcome (p = .001). The observed correlation between abnormal cortical morphology and global cognition suggested that cortical morphology may serve as a promising imaging biomarker and provide insights into neuroanatomical underpinnings of cognitive impairment in patients with chronic HF.

Dynamic Evolution of Infarct Volumes at MRI in Ischemic Stroke Due to Large Vessel Occlusion

BACKGROUND AND OBJECTIVES

The typical infarct volume trajectories in stroke patients, categorized as slow or fast progressors, remain largely unknown. This study aimed to reveal the characteristic spatiotemporal evolutions of infarct volumes caused by large vessel occlusion (LVO) and show that such growth charts help anticipate clinical outcomes.

METHODS

We conducted a secondary analysis from prospectively collected databases (FRAME, 2017-2019; ETIS, 2015-2022). We selected acute MRI data from anterior LVO stroke patients with witnessed onset, which were divided into training and independent validation datasets. In the training dataset, using Gaussian mixture analysis, we classified the patients into 3 growth groups based on their rate of infarct growth (diffusion volume/time-to-imaging). Subsequently, we extrapolated pseudo-longitudinal models of infarct growth for each group and generated sequential frequency maps to highlight the spatial distribution of infarct growth. We used these charts to attribute a growth group to the independent patients from the validation dataset. We compared their 3-month modified Rankin scale (mRS) with the predicted values based on a multivariable regression model from the training dataset that used growth group as an independent variable.

RESULTS

We included 804 patients (median age 73.0 years [interquartile range 61.2-82.0 years]; 409 men). The training dataset revealed nonsupervised clustering into 11% (74/703) slow, 62% (437/703) intermediate, and 27% (192/703) fast progressors. Infarct volume evolutions were best fitted with a linear (r = 0.809; p < 0.001), cubic (r = 0.471; p < 0.001), and power (r = 0.63; p < 0.001) function for the slow, intermediate, and fast progressors, respectively. Notably, the deep nuclei and insular cortex were rapidly affected in the intermediate and fast groups with further cortical involvement in the fast group. The variable growth group significantly predicted the 3-month mRS (multivariate odds ratio 0.51; 95% CI 0.37-0.72, p < 0.0001) in the training dataset, yielding a mean area under the receiver operating characteristic curve of 0.78 (95% CI 0.66-0.88) in the independent validation dataset.

DISCUSSION

We revealed spatiotemporal archetype dynamic evolutions following LVO stroke according to 3 growth phenotypes called slow, intermediate, and fast progressors, providing insight into anticipating clinical outcome. We expect this could help in designing neuroprotective trials aiming at modulating infarct growth before EVT.

Atrophy links lower novelty-related locus coeruleus connectivity to cognitive decline in preclinical AD

INTRODUCTION

Animal research has shown that tau pathology in the locus coeruleus (LC) is associated with reduced norepinephrine signaling, lower projection density to the medial temporal lobe (MTL), atrophy, and cognitive impairment. We investigated the contribution of LC-MTL functional connectivity (FCLC-MTL) on cortical atrophy across Braak stage regions and its impact on cognition.

METHODS

We analyzed functional magnetic resonance imaging and amyloid beta (Aβ) positron emission tomography data from 128 cognitively normal participants, associating novelty-related FCLC-MTL with longitudinal atrophy and cognition with and without Aβ moderation.

RESULTS

Cross-sectionally, lower FCLC-MTL was associated with atrophy in Braak stage II regions. Longitudinally, atrophy in Braak stage 2 to 4 regions related to lower baseline FCLC-MTL at elevated levels of Aβ, but not to other regions. Atrophy in Braak stage 2 regions mediated the relation between FCLC-MTL and subsequent cognitive decline.

DISCUSSION

FCLC-MTL is implicated in Aβ-related cortical atrophy, suggesting that LC-MTL connectivity could confer neuroprotective effects in preclinical AD.

HIGHLIGHTS

Novelty-related functional magnetic resonance imaging (fMRI) LC-medial temporal lobe (MTL) connectivity links to longitudinal Aβ-dependent atrophy. This relationship extended to higher Braak stage regions with increasing Aβ burden. Longitudinal MTL atrophy mediated the LC-MTL connectivity-cognition relationship. Our findings mirror the animal data on MTL atrophy following NE signal dysfunction.

Cortical thickness and grey-matter volume anomaly detection in individual MRI scans: Comparison of two methods

Over the past decades, morphometric analysis of brain MRI has contributed substantially to the understanding of healthy brain structure, development and aging as well as to improved characterisation of disease related pathologies. Certified commercial tools based on normative modeling of these metrics are meanwhile available for diagnostic purposes, but they are cost intensive and their clinical evaluation is still in its infancy. Here we have compared the performance of "ScanOMetrics", an open-source research-level tool for detection of statistical anomalies in individual MRI scans, depending on whether it is operated on the output of FreeSurfer or of the deep learning based brain morphometry tool DL + DiReCT. When applied to the public OASIS3 dataset, containing patients with Alzheimer's disease (AD) and healthy controls (HC), cortical thickness anomalies in patient scans were mainly detected in regions that are known as predilection areas of cortical atrophy in AD, regardless of the software used for extraction of the metrics. By contrast, anomaly detections in HCs were up to twenty-fold reduced and spatially unspecific using both DL + DiReCT and FreeSurfer. Progression of the atrophy pattern with clinical dementia rating (CDR) was clearly observable with both methods. DL + DiReCT provided results in less than 25 min, more than 15 times faster than FreeSurfer. This difference in computation time might be relevant when considering application of this or similar methodology as diagnostic decision support for neuroradiologists.

Exploring intricate connectivity patterns for cognitive functioning and neurological disorders: incorporating frequency-domain NC method into fMRI analysis

This study extends the application of the frequency-domain new causality method to functional magnetic resonance imaging analysis. Strong causality, weak causality, balanced causality, cyclic causality, and transitivity causality were constructed to simulate varying degrees of causal associations among multivariate functional-magnetic-resonance-imaging blood-oxygen-level-dependent signals. Data from 1,252 groups of individuals with different degrees of cognitive impairment were collected. The frequency-domain new causality method was employed to construct directed efficient connectivity networks of the brain, analyze the statistical characteristics of topological variations in brain regions related to cognitive impairment, and utilize these characteristics as features for training a deep learning model. The results demonstrated that the frequency-domain new causality method accurately detected causal associations among simulated signals of different degrees. The deep learning tests also confirmed the superior performance of new causality, surpassing the other three methods in terms of accuracy, precision, and recall rates. Furthermore, consistent significant differences were observed in the brain efficiency networks, where several subregions defined by the multimodal parcellation method of Human Connectome Project simultaneously appeared in the topological statistical results of different patient groups. This suggests a significant association between these fine-grained cortical subregions, driven by multimodal data segmentation, and human cognitive function, making them potential biomarkers for further analysis of Alzheimer's disease.

Exploration of neuroanatomical characteristics to differentiate prodromal Alzheimer's disease from cognitively unimpaired amyloid-positive individuals

Differentiating clinical stages based solely on positive findings from amyloid PET is challenging. We aimed to investigate the neuroanatomical characteristics at the whole-brain level that differentiate prodromal Alzheimer's disease (AD) from cognitively unimpaired amyloid-positive individuals (CU A+) in relation to amyloid deposition and regional atrophy. We included 45 CU A+ participants and 135 participants with amyloid-positive prodromal AD matched 1:3 by age, sex, and education. All participants underwent 18F-florbetaben positron emission tomography and 3D structural T1-weighted magnetic resonance imaging. We compared the standardized uptake value ratios (SUVRs) and volumes in 80 regions of interest (ROIs) between CU A+ and prodromal AD groups using independent t-tests, and employed the least absolute selection and shrinkage operator (LASSO) logistic regression model to identify ROIs associated with prodromal AD in relation to amyloid deposition, regional atrophy, and their interaction. After applying False Discovery Rate correction at < 0.1, there were no differences in global and regional SUVR between CU A+ and prodromal AD groups. Regional volume differences between the two groups were observed in the amygdala, hippocampus, entorhinal cortex, insula, parahippocampal gyrus, and inferior temporal and parietal cortices. LASSO logistic regression model showed significant associations between prodromal AD and atrophy in the entorhinal cortex, inferior parietal cortex, both amygdalae, and left hippocampus. The mean SUVR in the right superior parietal cortex (beta coefficient = 0.0172) and its interaction with the regional volume (0.0672) were also selected in the LASSO model. The mean SUVR in the right superior parietal cortex was associated with an increased likelihood of prodromal AD (Odds ratio [OR] 1.602, p = 0.014), particularly in participants with lower regional volume (OR 3.389, p < 0.001). Only regional volume differences, not amyloid deposition, were observed between CU A+ and prodromal AD. The reduced volume in the superior parietal cortex may play a significant role in the progression to prodromal AD through its interaction with amyloid deposition in that region.

Vulnerability of Thalamic Nuclei at CSF Interface During the Entire Course of Multiple Sclerosis

BACKGROUND AND OBJECTIVES

Thalamic atrophy can be used as a proxy for neurodegeneration in multiple sclerosis (MS). Some data point toward thalamic nuclei that could be affected more than others. However, the dynamic of their changes during MS evolution and the mechanisms driving their differential alterations are still uncertain.

METHODS

We paired a large cohort of 1,123 patients with MS with the same number of healthy controls, all scanned with conventional 3D-T1 MRI. To highlight the main atrophic regions at the thalamic nuclei level, we validated a segmentation strategy consisting of deep learning-based synthesis of sequences, which were used for automatic multiatlas segmentation. Then, through a lifespan-based approach, we could model the dynamics of the 4 main thalamic nuclei groups.

RESULTS

All analyses converged toward a higher rate of atrophy for the posterior and medial groups compared with the anterior and lateral groups. We also demonstrated that focal MS white matter lesions were associated with atrophy of groups of nuclei when specifically located within the associated thalamocortical projections. The volumes of the most affected posterior group, but also of the anterior group, were better associated with clinical disability than the volume of the whole thalamus.

DISCUSSION

These findings point toward the thalamic nuclei adjacent to the third ventricle as more susceptible to neurodegeneration during the entire course of MS through potentiation of disconnection effects by regional factors. Because this information can be obtained even from standard T1-weighted MRI, this paves the way toward such an approach for future monitoring of patients with MS.

Loss of spontaneous vasomotion precedes impaired cerebrovascular reactivity and microbleeds in a mouse model of cerebral amyloid angiopathy

Background

Cerebral amyloid angiopathy (CAA) is a cerebral small vessel disease in which amyloid-β accumulates in vessel walls. CAA is a leading cause of symptomatic lobar intracerebral hemorrhage and an important contributor to age-related cognitive decline. Recent work has suggested that vascular dysfunction may precede symptomatic stages of CAA, and that spontaneous slow oscillations in arteriolar diameter (termed vasomotion), important for amyloid-β clearance, may be impaired in CAA.

Methods

To systematically study the progression of vascular dysfunction in CAA, we used the APP23 mouse model of amyloidosis, which is known to develop spontaneous cerebral microbleeds mimicking human CAA. Using in vivo 2-photon microscopy, we longitudinally imaged unanesthetized APP23 transgenic mice and wildtype littermates from 7 to 14 months of age, tracking amyloid-β accumulation and vasomotion in individual pial arterioles over time. MRI was used in separate groups of 12-, 18-, and 24-month-old APP23 transgenic mice and wildtype littermates to detect microbleeds and to assess cerebral blood flow and cerebrovascular reactivity with pseudo-continuous arterial spin labeling.

Results

We observed a significant decline in vasomotion with age in APP23 mice, while vasomotion remained unchanged in wildtype mice with age. This decline corresponded in timing to initial vascular amyloid-β deposition (∼8-10 months of age), although was more strongly correlated with age than with vascular amyloid-β burden in individual arterioles. Declines in vasomotion preceded the development of MRI-visible microbleeds and the loss of smooth muscle actin in arterioles, both of which were observed in APP23 mice by 18 months of age. Additionally, evoked cerebrovascular reactivity was intact in APP23 mice at 12 months of age, but significantly lower in APP23 mice by 24 months of age.

Conclusions

Our findings suggest that a decline in spontaneous vasomotion is an early, potentially pre-symptomatic, manifestation of CAA and vascular dysfunction, and a possible future treatment target.

Staging of progressive supranuclear palsy-Richardson syndrome using MRI brain charts for the human lifespan

Brain charts for the human lifespan have been recently proposed to build dynamic models of brain anatomy in normal aging and various neurological conditions. They offer new possibilities to quantify neuroanatomical changes from preclinical stages to death, where longitudinal MRI data are not available. In this study, we used brain charts to model the progression of brain atrophy in progressive supranuclear palsy-Richardson syndrome. We combined multiple datasets (n = 8170 quality controlled MRI of healthy subjects from 22 cohorts covering the entire lifespan, and n = 62 MRI of progressive supranuclear palsy-Richardson syndrome patients from the Four Repeat Tauopathy Neuroimaging Initiative (4RTNI)) to extrapolate lifetime volumetric models of healthy and progressive supranuclear palsy-Richardson syndrome brain structures. We then mapped in time and space the sequential divergence between healthy and progressive supranuclear palsy-Richardson syndrome charts. We found six major consecutive stages of atrophy progression: (i) ventral diencephalon (including subthalamic nuclei, substantia nigra, and red nuclei), (ii) pallidum, (iii) brainstem, striatum and amygdala, (iv) thalamus, (v) frontal lobe, and (vi) occipital lobe. The three structures with the most severe atrophy over time were the thalamus, followed by the pallidum and the brainstem. These results match the neuropathological staging of tauopathy progression in progressive supranuclear palsy-Richardson syndrome, where the pathology is supposed to start in the pallido-nigro-luysian system and spreads rostrally via the striatum and the amygdala to the cerebral cortex, and caudally to the brainstem. This study supports the use of brain charts for the human lifespan to study the progression of neurodegenerative diseases, especially in the absence of specific biomarkers as in PSP.

Respiratory Dysfunction in Alzheimer's Disease-Consequence or Underlying Cause? Applying Animal Models to the Study of Respiratory Malfunctions

Alzheimer's disease (AD) is a neurodegenerative brain disease that is the most common cause of dementia among the elderly. In addition to dementia, which is the loss of cognitive function, including thinking, remembering, and reasoning, and behavioral abilities, AD patients also experience respiratory disturbances. The most common respiratory problems observed in AD patients are pneumonia, shortness of breath, respiratory muscle weakness, and obstructive sleep apnea (OSA). The latter is considered an outcome of Alzheimer's disease and is suggested to be a causative factor. While this narrative review addresses the bidirectional relationship between obstructive sleep apnea and Alzheimer's disease and reports on existing studies describing the most common respiratory disorders found in patients with Alzheimer's disease, its main purpose is to review all currently available studies using animal models of Alzheimer's disease to study respiratory impairments. These studies on animal models of AD are few in number but are crucial for establishing mechanisms, causation, implementing potential therapies for respiratory disorders, and ultimately applying these findings to clinical practice. This review summarizes what is already known in the context of research on respiratory disorders in animal models, while pointing out directions for future research.

Vulnerability of the Hippocampus to Insults: Links to Blood-Brain Barrier Dysfunction

The hippocampus is a critical brain substrate for learning and memory; events that harm the hippocampus can seriously impair mental and behavioral functioning. Hippocampal pathophysiologies have been identified as potential causes and effects of a remarkably diverse array of medical diseases, psychological disorders, and environmental sources of damage. It may be that the hippocampus is more vulnerable than other brain areas to insults that are related to these conditions. One purpose of this review is to assess the vulnerability of the hippocampus to the most prevalent types of insults in multiple biomedical domains (i.e., neuroactive pathogens, neurotoxins, neurological conditions, trauma, aging, neurodegenerative disease, acquired brain injury, mental health conditions, endocrine disorders, developmental disabilities, nutrition) and to evaluate whether these insults affect the hippocampus first and more prominently compared to other brain loci. A second purpose is to consider the role of hippocampal blood-brain barrier (BBB) breakdown in either causing or worsening the harmful effects of each insult. Recent research suggests that the hippocampal BBB is more fragile compared to other brain areas and may also be more prone to the disruption of the transport mechanisms that act to maintain the internal milieu. Moreover, a compromised BBB could be a factor that is common to many different types of insults. Our analysis indicates that the hippocampus is more vulnerable to insults compared to other parts of the brain, and that developing interventions that protect the hippocampal BBB may help to prevent or ameliorate the harmful effects of many insults on memory and cognition.

Advancing Diagnostics and Patient Care: The Role of Biomarkers in Radiology

The integration of biomarkers into medical practice has revolutionized the field of radiology, allowing for enhanced diagnostic accuracy, personalized treatment strategies, and improved patient care outcomes. This review offers radiologists a comprehensive understanding of the diverse applications of biomarkers in medicine. By elucidating the fundamental concepts, challenges, and recent advancements in biomarker utilization, it will serve as a bridge between the disciplines of radiology and epidemiology. Through an exploration of various biomarker types, such as imaging biomarkers, molecular biomarkers, and genetic markers, I outline their roles in disease detection, prognosis prediction, and therapeutic monitoring. I also discuss the significance of robust study designs, blinding, power and sample size calculations, performance metrics, and statistical methodologies in biomarker research. By fostering collaboration between radiologists, statisticians, and epidemiologists, I hope to accelerate the translation of biomarker discoveries into clinical practice, ultimately leading to improved patient care.

Investigating the synergistic effects of hormone replacement therapy, apolipoprotein E and age on brain health in the UK Biobank

Global prevalence of Alzheimer's Disease has a strong sex bias, with women representing approximately two-thirds of the patients. Yet, the role of sex-specific risk factors during midlife, including hormone replacement therapy (HRT) and their interaction with other major risk factors for Alzheimer's Disease, such as apolipoprotein E (APOE)-e4 genotype and age, on brain health remains unclear. We investigated the relationship between HRT (i.e., use, age of initiation and duration of use) and brain health (i.e., cognition and regional brain volumes). We then consider the multiplicative effects of HRT and APOE status (i.e., e2/e2, e2/e3, e3/e3, e3/e4 and e4/e4) via a two-way interaction and subsequently age of participants via a three-way interaction. Women from the UK Biobank with no self-reported neurological conditions were included (N = 207,595 women, mean age = 56.25 years, standard deviation = 8.01 years). Generalised linear regression models were computed to quantify the cross-sectional association between HRT and brain health, while controlling for APOE status, age, time since attending centre for completing brain health measure, surgical menopause status, smoking history, body mass index, education, physical activity, alcohol use, ethnicity, socioeconomic status, vascular/heart problems and diabetes diagnosed by doctor. Analyses of structural brain regions further controlled for scanner site. All brain volumes were normalised for head size. Two-way interactions between HRT and APOE status were modelled, in addition to three-way interactions including age. Results showed that women with the e4/e4 genotype who have used HRT had 1.82% lower hippocampal, 2.4% lower parahippocampal and 1.24% lower thalamus volumes than those with the e3/e3 genotype who had never used HRT. However, this interaction was not detected for measures of cognition. No clinically meaningful three-way interaction between APOE, HRT and age was detected when interpreted relative to the scales of the cognitive measures used and normative models of ageing for brain volumes in this sample. Differences in hippocampal volume between women with the e4/e4 genotype who have used HRT and those with the e3/e3 genotype who had never used HRT are equivalent to approximately 1-2 years of hippocampal atrophy observed in typical health ageing trajectories in midlife (i.e., 0.98%-1.41% per year). Effect sizes were consistent within APOE e4/e4 group post hoc sensitivity analyses, suggesting observed effects were not solely driven by APOE status and may, in part, be attributed to HRT use. Although, the design of this study means we cannot exclude the possibility that women who have used HRT may have a predisposition for poorer brain health.

Neurofilament light chain concentration mediates the association between regional medial temporal lobe structure and memory in adults with Down syndrome

INTRODUCTION

Virtually all people with Down syndrome (DS) develop neuropathology associated with Alzheimer's disease (AD). Atrophy of the hippocampus and entorhinal cortex (EC), as well as elevated plasma concentrations of neurofilament light chain (NfL) protein, are markers of neurodegeneration associated with late-onset AD. We hypothesized that hippocampus and EC gray matter loss and increased plasma NfL concentrations are associated with memory in adults with DS.

METHODS

T1-weighted structural magnetic resonance imaging (MRI) data were collected from 101 participants with DS. Hippocampus and EC volume, as well as EC subregional cortical thickness, were derived. In a subset of participants, plasma NfL concentrations and modified Cued Recall Test scores were obtained. Partial correlation and mediation were used to test relationships between medial temporal lobe (MTL) atrophy, plasma NfL, and episodic memory.

RESULTS

Hippocampus volume, left anterolateral EC (alEC) thickness, and plasma NfL were correlated with each other and were associated with memory. Plasma NfL mediated the relationship between left alEC thickness and memory as well as hippocampus volume and memory.

DISCUSSION

The relationship between MTL gray matter and memory is mediated by plasma NfL levels, suggesting a link between neurodegenerative processes underlying axonal injury and frank gray matter loss in key structures supporting episodic memory in people with DS.

Trajectories and contributing factors of neural compensation in healthy and pathological aging

Neural degeneration is a hallmark of healthy aging and can be associated with specific cognitive impairments. However, neural degeneration per se is not matched by unremitting declines in cognitive abilities. Instead, middle-aged and older adults typically maintain surprisingly high levels of cognitive functioning, suggesting that the human brain can adapt to structural degeneration by neural compensation. Here, we summarize prevailing theories and recent empirical studies on neural compensation with a focus on often neglected contributing factors, such as lifestyle, metabolism and neural plasticity. We suggest that these factors moderate the relationship between structural integrity and neural compensation, maintaining psychological well-being and behavioral functioning. Finally, we discuss that a breakdown in neural compensation may pose a tipping point that distinguishes the trajectories of healthy vs pathological aging, but conjoint support from psychology and cognitive neuroscience for this alluring view is still scarce. Therefore, future experiments that target the concomitant processes of neural compensation and associated behavior will foster a comprehensive understanding of both healthy and pathological aging.

Improving Clinical Trials of Antioxidants in Alzheimer's Disease

Maintaining diversity in drug development in research into Alzheimer's disease (AD) is necessary to avoid over-reliance on targeting AD neuropathology. Treatments that reduce or prevent the generation of oxidative stress, frequently cited for its causal role in the aging process and AD, could be useful in at-risk populations or diagnosed AD patients. However, in this review, it is argued that clinical research into antioxidants in AD could provide more useful feedback as to the therapeutic value of the oxidative stress theory of AD. Improving comparability between randomized controlled trials (RCTs) is vital from a waste-reduction and priority-setting point of view for AD clinical research. For as well as attempting to improve meaningful outcomes for patients, RCTs of antioxidants in AD should strive to maximize the extraction of clinically useful information and actionable feedback from trial outcomes. Solutions to maximize information flow from RCTs of antioxidants in AD are offered here in the form of checklist questions to improve ongoing and future trials centered around the following dimensions: adhesion to reporting guidelines like CONSORT, biomarker enrichment, simple tests of treatment, and innovative trial design.

Synaptic density affects clinical severity via network dysfunction in syndromes associated with frontotemporal lobar degeneration

There is extensive synaptic loss from frontotemporal lobar degeneration, in preclinical models and human in vivo and post mortem studies. Understanding the consequences of synaptic loss for network function is important to support translational models and guide future therapeutic strategies. To examine this relationship, we recruited 55 participants with syndromes associated with frontotemporal lobar degeneration and 24 healthy controls. We measured synaptic density with positron emission tomography using the radioligand [11C]UCB-J, which binds to the presynaptic vesicle glycoprotein SV2A, neurite dispersion with diffusion magnetic resonance imaging, and network function with task-free magnetic resonance imaging functional connectivity. Synaptic density and neurite dispersion in patients was associated with reduced connectivity beyond atrophy. Functional connectivity moderated the relationship between synaptic density and clinical severity. Our findings confirm the importance of synaptic loss in frontotemporal lobar degeneration syndromes, and the resulting effect on behaviour as a function of abnormal connectivity.

Detection of APP gene recombinant in human blood plasma

The pathogenesis of Alzheimer's disease (AD) is believed to involve the accumulation of amyloid-β in the brain, which is produced by the sequential cleavage of amyloid precursor protein (APP) by β-secretase and γ-secretase. Recently, analysis of genomic DNA and mRNA from postmortem brain neurons has revealed intra-exonic recombinants of APP (gencDNA), which have been implicated in the accumulation of amyloid-β. In this study, we computationally analyzed publicly available sequence data (SRA) using probe sequences we constructed to screen APP gencDNAs. APP gencDNAs were detected in SRAs constructed from both genomic DNA and RNA obtained from the postmortem brain and in the SRA constructed from plasma cell-free mRNA (cf-mRNA). The SRA constructed from plasma cf-mRNA showed a significant difference in the number of APP gencDNA reads between SAD and NCI: the p-value from the Mann-Whitney U test was 5.14 × 10-6. The transcripts were also found in circulating nucleic acids (CNA) from our plasma samples with NGS analysis. These data indicate that transcripts of APP gencDNA can be detected in blood plasma and suggest the possibility of using them as blood biomarkers for Alzheimer's disease.

Lifespan neurodegeneration of the human brain in multiple sclerosis

Atrophy related to multiple sclerosis (MS) has been found at the early stages of the disease. However, the archetype dynamic trajectories of the neurodegenerative process, even prior to clinical diagnosis, remain unknown. We modeled the volumetric trajectories of brain structures across the entire lifespan using 40,944 subjects (38,295 healthy controls and 2649 MS patients). Then, we estimated the chronological progression of MS by assessing the divergence of lifespan trajectories between normal brain charts and MS brain charts. Chronologically, the first affected structure was the thalamus, then the putamen and the pallidum (around 4 years later), followed by the ventral diencephalon (around 7 years after thalamus) and finally the brainstem (around 9 years after thalamus). To a lesser extent, the anterior cingulate gyrus, insular cortex, occipital pole, caudate and hippocampus were impacted. Finally, the precuneus and accumbens nuclei exhibited a limited atrophy pattern. Subcortical atrophy was more pronounced than cortical atrophy. The thalamus was the most impacted structure with a very early divergence in life. Our experiments showed that lifespan models of most impacted structures could be an important tool for future preclinical/prodromal prognosis and monitoring of MS.

Smaller grey matter volume in the central olfactory system in mild cognitive impairment

One of the major challenges in the diagnosis of Alzheimer's disease (AD) is to increase the specificity of the early diagnosis. While episodic memory impairment is a sensitive AD marker, other measures are needed to improve diagnostic specificity. A promising biomarker might be a cerebral atrophy of the central olfactory processing areas in the early stages of the disease since an impairment of olfactory identification is present at the clinical stage of AD. Our goal was therefore, (1) to evaluate the grey matter volume (GMV) of central olfactory processing regions in prodromal AD and (2) to assess its association with episodic memory. We included 34 cognitively normal healthy controls (HC), 92 individuals with subjective cognitive decline (SCD), and 40 with mild cognitive impairment (MCI). We performed regions of interest analysis (ROI) using two different approaches, allowing to extract GMV from (1) atlas-based anatomical ROIs and from (2) functional and non-functional subregions of these ROIs (olfactory ROIs and non-olfactory ROIs). Participants with MCI exhibited smaller olfactory ROIs GMV, including significant reductions in the piriform cortex, amygdala, entorhinal cortex, and left hippocampus compared to other groups (p ≤ 0.05, corrected). No significant effect was found regarding anatomical or non-olfactory ROIs GMV. The left hippocampus olfactory ROI GMV was correlated with episodic memory performance (p < 0.05 corrected). Limbic/medial-temporal olfactory processing areas are specifically atrophied at the MCI stage, and the degree of atrophy might predict cognitive decline in AD early stages.

Structural degeneration of the nucleus basalis of Meynert in mild cognitive impairment and Alzheimer's disease - Evidence from an MRI-based meta-analysis

Recent models of Alzheimer's disease (AD) suggest that neuropathological changes of the medial temporal lobe, especially entorhinal cortex, are preceded by degenerations of the cholinergic Nucleus basalis of Meynert (NbM). Evidence from imaging studies in humans, however, is limited. Therefore, we performed an activation-likelihood estimation meta-analysis on whole brain voxel-based morphometry (VBM) MRI data from 54 experiments and 2581 subjects in total. It revealed, compared to healthy older controls, reduced gray matter in the bilateral NbM in AD, but only limited evidence for such an effect in patients with mild cognitive impairment (MCI), which typically precedes AD. Both patient groups showed less gray matter in the amygdala and hippocampus, with hints towards more pronounced amygdala effects in AD. We discuss our findings in the context of studies that highlight the importance of the cholinergic basal forebrain in learning and memory throughout the lifespan, and conclude that they are partly compatible with pathological staging models suggesting initial and pronounced structural degenerations within the NbM in the progression of AD.

Genome-Wide Association Analysis across Endophenotypes in Alzheimer's Disease: Main Effects and Disease Stage-Specific Interactions

The underlying genetic susceptibility for Alzheimer's disease (AD) is not yet fully understood. The heterogeneous nature of the disease challenges genetic association studies. Endophenotype approaches can help to address this challenge by more direct interrogation of biological traits related to the disease. AD endophenotypes based on amyloid-β, tau, and neurodegeneration (A/T/N) biomarkers and cognitive performance were selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort (N = 1565). A genome-wide association study (GWAS) of quantitative phenotypes was performed using an SNP main effect and an SNP by Diagnosis interaction (SNP × DX) model to identify disease stage-specific genetic effects. Nine loci were identified as study-wide significant with one or more A/T/N endophenotypes in the main effect model, as well as additional findings significantly associated with cognitive measures. These nine loci include SNPs in or near the genes APOE, SRSF10, HLA-DQB1, XKR3, and KIAA1671. The SNP × DX model identified three study-wide significant genetic loci (BACH2, EP300, and PACRG-AS1) with a neuroprotective effect in later AD stage endophenotypes. An endophenotype approach identified novel genetic associations and provided insight into the molecular mechanisms underlying the genetic associations that may otherwise be missed using conventional case-control study designs.