Predicting Fazekas scores from automatic segmentations of white matter signal abnormalities

Frontoparietal atrophy trajectories in cognitively unimpaired elderly individuals using longitudinal Bayesian clustering

INTRODUCTION

Frontal and/or parietal atrophy has been reported during aging. To disentangle the heterogeneity previously observed, this study aimed to uncover different clusters of grey matter profiles and trajectories within cognitively unimpaired individuals.

METHODS

Structural magnetic resonance imaging (MRI) data of 307 Aβ-negative cognitively unimpaired individuals were modelled between ages 60-85 from three cohorts worldwide. We applied unsupervised clustering using a novel longitudinal Bayesian approach and characterized the clusters' cerebrovascular and cognitive profiles.

RESULTS

Four clusters were identified with different grey matter profiles and atrophy trajectories. Differences were mainly observed in frontal and parietal brain regions. These distinct frontoparietal grey matter profiles and longitudinal trajectories were differently associated with cerebrovascular burden and cognitive decline.

DISCUSSION

Our findings suggest a conciliation of the frontal and parietal theories of aging, uncovering coexisting frontoparietal GM patterns. This could have important future implications for better stratification and identification of at-risk individuals.

Cerebrovascular and Alzheimer's disease biomarkers in dementia with Lewy bodies and other dementias

Co-pathologies are common in dementia with Lewy bodies and other dementia disorders. We investigated cerebrovascular and Alzheimer's disease co-pathologies in patients with dementia with Lewy bodies in comparison with patients with mild cognitive impairment, Alzheimer's disease, mixed dementia, vascular dementia or Parkinson's disease with dementia and cognitively unimpaired participants. We assessed the association of biomarkers of cerebrovascular and Alzheimer's disease co-pathologies with medial temporal atrophy and global cognitive performance. Additionally, we evaluated whether the findings were specific to dementia with Lewy bodies. We gathered a multi-cohort dataset of 4549 participants (dementia with Lewy bodies = 331, cognitively unimpaired = 1505, mild cognitive impairment = 1489, Alzheimer's disease = 708, mixed dementia = 268, vascular dementia = 148, Parkinson's disease with dementia = 120) from the MemClin Study, Karolinska Imaging in Dementia Study, Gothenburg H70 Birth Cohort Studies and the European DLB Consortium. Cerebrovascular co-pathology was assessed with visual ratings of white matter hyperintensities using the Fazekas scale through structural imaging. Alzheimer's disease biomarkers of β-amyloid and phosphorylated tau were assessed in the cerebrospinal fluid for a subsample (N = 2191). Medial temporal atrophy was assessed with visual ratings and global cognition with the mini-mental state examination. Differences and associations were assessed through regression models, including interaction terms. In dementia with Lewy bodies, 43% had a high white matter hyperintensity load, which was significantly higher than that in cognitively unimpaired (14%), mild cognitive impairment (26%) and Alzheimer's disease (27%), but lower than that in vascular dementia (62%). In dementia with Lewy bodies, white matter hyperintensities were associated with medial temporal atrophy, and the interaction term showed that this association was stronger than that in cognitively unimpaired and mixed dementia. However, the association between white matter hyperintensities and medial temporal atrophy was non-significant when β-amyloid was included in the model. Instead, β-amyloid predicted medial temporal atrophy in dementia with Lewy bodies, in contrast to the findings in mild cognitive impairment where medial temporal atrophy scores were independent of β-amyloid. Dementia with Lewy bodies had the lowest performance on global cognition, but this was not associated with white matter hyperintensities. In Alzheimer's disease, global cognitive performance was lower in patients with more white matter hyperintensities. We conclude that white matter hyperintensities are common in dementia with Lewy bodies and are associated with more atrophy in medial temporal lobes, but this association depended on β-amyloid-related pathology in our cohort. The associations between biomarkers were overall stronger in dementia with Lewy bodies than in some of the other diagnostic groups.

Age-related white matter change disease predicts long-term cerebrovascular morbidity following carotid endarterectomy

PURPOSE

Cerebrovascular diseases remain a critical focus of medical research due to their substantial impact on global health. Carotid stenosis, often associated with atherosclerosis and advancing age, profoundly affects cerebral blood supply and white matter integrity. This study aims to assess how age-related white matter changes (ARWMC) score, applied to cortex and Basal Ganglia, relates to cardiovascular and cerebrovascular events in patients who underwent carotid endarterectomy (CEA).

METHODS

Ninety patients undergoing CEA with regional anesthesia were prospectively enrolled from January 2012 to January 2022, and a post hoc analysis of patients with preoperative cerebral CT scans were reviewed, stratified by ARWMC score. Survival analysis and multivariate Cox regression were employed to assess time-dependent variables and independent predictors.

RESULTS

A median follow-up of 51 months (Inter-quartile range [IQR [ [38.8-63.2] months) revealed higher ARWMC grades in the basal ganglia independently associated with significantly increased stroke risk (HR=5.070, 95% CI: 1.509-17.031, P=0.009), acute heart failure (HR=19.066, 95% CI: 2.038-178.375, P=0.01), major adverse cardiovascular events (MACE) (HR=2.760, 95% CI: 1.268-6.009, P=0.011), and all-cause mortality (HR=2.497, 95% CI:1.009-6.180, P=0.048). Polyvascular disease and chronic kidney disease emerged as additional predictors of MACE.

CONCLUSION

Higher grades of ARWMC score in the basal ganglia were related to a significant increase in the risk of adverse cardiovascular events, such as stroke, MACE, AHF and all-cause mortality. This study suggests that ARWMC may have potential as a possible predictor of long-term cardio- and cerebrovascular events in patients undergoing CEA.

Potential role of blood pressure variability and plasma neurofilament light in the mechanism of comorbidity between Alzheimer's disease and cerebral small vessel disease

INTRODUCTION

Long-term blood pressure variability (BPV) and plasma neurofilament light (pNfL) have been identified as potential biomarkers for Alzheimer's disease (AD) and cerebral small vessel disease (CSVD). However, the relationship between BPV, pNfL, and their association with the comorbidity of AD and CSVD remains unknown.

METHODS

Participants with normal cognition and mild cognitive impairment from the Alzheimer's Disease Neuroimaging Initiative study were included in the data analysis. Linear mixed-effects regression models and causal mediation analyses were conducted to investigate the relationship among BPV, pNfL, comorbidity-related brain structural changes (hippocampal atrophy and white matter hyperintensities [WMH]), and cognitive function.

RESULTS

BPV was associated with pNfL, volumes of hippocampus and WMH, and cognition. pNfL mediated the effects of BPV on brain structural changes and cognition.

DISCUSSION

Our findings suggest a potential role of BPV and pNfL in the mechanism of comorbidity between AD and CSVD, underscoring the importance of BPV intervention in the general population.

HIGHLIGHTS

Individuals with both Alzheimer's disease (AD) and cerebral small vessel disease (CSVD) pathologies had elevated blood pressure variability (BPV) and plasma neurofilament light (pNfL). The association between different components of BPV and brain structural changes may vary. BPV was associated with pNfL levels independent of average blood pressure. pNfL mediated the effects of BPV on comorbidity-related brain structural changes and cognitive performance.

Superagers Resist Typical Age-Related White Matter Structural Changes

Superagers are elderly individuals with the memory ability of people 30 years younger and provide evidence that age-related cognitive decline is not inevitable. In a sample of 64 superagers (mean age, 81.9; 59% women) and 55 typical older adults (mean age, 82.4; 64% women) from the Vallecas Project, we studied, cross-sectionally and longitudinally over 5 years with yearly follow-ups, the global cerebral white matter status as well as region-specific white matter microstructure assessment derived from diffusivity measures. Superagers and typical older adults showed no difference in global white matter health (total white matter volume, Fazekas score, and lesions volume) cross-sectionally or longitudinally. However, analyses of diffusion parameters revealed the better white matter microstructure in superagers than in typical older adults. Cross-sectional differences showed higher fractional anisotropy (FA) in superagers mostly in frontal fibers and lower mean diffusivity (MD) in most white matter tracts, expressed as an anteroposterior gradient with greater group differences in anterior tracts. FA decrease over time is slower in superagers than in typical older adults in all white matter tracts assessed, which is mirrored by MD increases over time being slower in superagers than in typical older adults in all white matter tracts except for the corticospinal tract, the uncinate fasciculus, and the forceps minor. The better preservation of white matter microstructure in superagers relative to typical older adults supports resistance to age-related brain structural changes as a mechanism underpinning the remarkable memory capacity of superagers, while their regional aging pattern is in line with the last-in-first-out hypothesis.

Multi-pathological contributions toward atrophy patterns in the Alzheimer's disease continuum

Introduction

Heterogeneity in downstream atrophy in Alzheimer's disease (AD) is predominantly investigated in relation to pathological hallmarks (Aβ, tau) and co-pathologies (cerebrovascular burden) independently. However, the proportional contribution of each pathology in determining atrophy pattern remains unclear. We assessed heterogeneity in atrophy using two recently conceptualized dimensions: typicality (typical AD atrophy at the center and deviant atypical atrophy on either extreme including limbic predominant to hippocampal sparing patterns) and severity (overall neurodegeneration spanning minimal atrophy to diffuse typical AD atrophy) in relation to Aβ, tau, and cerebrovascular burden.

Methods

We included 149 Aβ + individuals on the AD continuum (cognitively normal, prodromal AD, AD dementia) and 163 Aβ- cognitively normal individuals from the ADNI. We modeled heterogeneity in MRI-based atrophy with continuous-scales of typicality (ratio of hippocampus to cortical volume) and severity (total gray matter volume). Partial correlation models investigated the association of typicality/severity with (a) Aβ (global Aβ PET centiloid), tau (global tau PET SUVR), cerebrovascular (total white matter hypointensity volume) burden (b) four cognitive domains (memory, executive function, language, visuospatial composites). Using multiple regression, we assessed the association of each pathological burden and typicality/severity with cognition.

Results

(a) In the AD continuum, typicality (r = -0.31, p < 0.001) and severity (r = -0.37, p < 0.001) were associated with tau burden after controlling for Aβ, cerebrovascular burden and age. Findings imply greater tau pathology in limbic predominant atrophy and diffuse atrophy. (b) Typicality was associated with memory (r = 0.49, p < 0.001) and language scores (r = 0.19, p = 0.02). Severity was associated with memory (r = 0.26, p < 0.001), executive function (r = 0.24, p = 0.003) and language scores (r = 0.29, p < 0.001). Findings imply better cognitive performance in hippocampal sparing and minimal atrophy patterns. Beyond typicality/severity, tau burden but not Aβ and cerebrovascular burden explained cognition.

Conclusion

In the AD continuum, atrophy-based severity was more strongly associated with tau burden than typicality after accounting for Aβ and cerebrovascular burden. Cognitive performance in memory, executive function and language domains was explained by typicality and/or severity and additionally tau pathology. Typicality and severity may differentially reflect burden arising from tau pathology but not Aβ or cerebrovascular pathologies which need to be accounted for when investigating AD heterogeneity.

A multi-site study on sex differences in cortical thickness in non-demented Parkinson's disease

Clinical, cognitive, and atrophy characteristics depending on sex have been previously reported in Parkinson's disease (PD). However, though sex differences in cortical gray matter measures in early drug naïve patients have been described, little is known about differences in cortical thickness (CTh) as the disease advances. Our multi-site sample comprised 211 non-demented PD patients (64.45% males; mean age 65.58 ± 8.44 years old; mean disease duration 6.42 ± 5.11 years) and 86 healthy controls (50% males; mean age 65.49 ± 9.33 years old) with available T1-weighted 3 T MRI data from four international research centers. Sex differences in regional mean CTh estimations were analyzed using generalized linear models. The relation of CTh in regions showing sex differences with age, disease duration, and age of onset was examined through multiple linear regression. PD males showed thinner cortex than PD females in six frontal (bilateral caudal middle frontal, bilateral superior frontal, left precentral and right pars orbitalis), three parietal (bilateral inferior parietal and left supramarginal), and one limbic region (right posterior cingulate). In PD males, lower CTh values in nine out of ten regions were associated with longer disease duration and older age, whereas in PD females, lower CTh was associated with older age but with longer disease duration only in one region. Overall, male patients show a more widespread pattern of reduced CTh compared with female patients. Disease duration seems more relevant to explain reduced CTh in male patients, suggesting worse prognostic over time. Further studies should explore sex-specific cortical atrophy trajectories using large longitudinal multi-site data.

In vivo microstructural heterogeneity of white matter and cognitive correlates in aging using tissue compositional analysis of diffusion magnetic resonance imaging

BACKGROUND

Age-related cognitive decline is linked to changes in the brain, particularly the deterioration of white matter (WM) microstructure that accelerates after the age of 60. WM deterioration is associated with mild cognitive impairment and dementia, but the origin and role of white matter signal abnormalities (WMSA) seen in standard MRI remain debated due to their heterogeneity. This study explores the potential of single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD), a novel technique that models diffusion data in terms of gray matter (TG ), white matter (Tw ), and cerebrospinal fluid (TC ), to differentiate WMSA from normal-appearing white matter and better understand the interplay between changes in WM microstructure and decline in cognition.

METHODS

A total of 189 individuals from the GENIC cohort were included. MRI data, including T1-weighted and diffusion images, were obtained. Preprocessing steps were performed on the diffusion MRI data, followed by the SS3T-CSD. WMSA were segmented using FreeSurfer. Statistical analyses were conducted to assess the association between age, WMSA volume, 3-tissue signal fractions (Tw , TG , and TC ), and neuropsychological variables.

RESULTS

Participants above 60 years old showed worse cognitive performance and processing speed compared to those below 60 (p < .001). Age was negatively associated with Tw in normal-appearing white matter (p < .001) and positively associated with TG in both WMSA (p < .01) and normal-appearing white matter (p < .001). Age was also significantly associated with WMSA volume (p < .001). Higher processing speed was associated with lower Tw and higher TG , in normal-appearing white matter (p < .01 and p < .001, respectively), as well as increased WMSA volume (p < .001). Similarly, lower MMSE scores correlated with lower Tw and higher TG in normal-appearing white matter (p < .05). High cholesterol and hypertension were associated with higher WMSA volume (p < .05).

CONCLUSION

The microstructural heterogeneity within normal-appearing white matter and WMSA is associated with increasing age and cognitive variation, in cognitively unimpaired individuals. Furthermore, the 3-tissue signal fractions are more specific to potential white matter alterations than conventional MRI measures such as WMSA volume. These findings also support the view that the WMSA volumes may be more influenced by vascular risk factors than the 3-tissue metrics. Finally, the 3-tissue metrics were able to capture associations with cognitive tests and therefore capable of capturing subtle pathological changes in the brain in individuals who are still within the normal range of cognitive performance.

Biomarkers of Alzheimer's Disease and Cerebrovascular Disease in Relation to Depressive Symptomatology in Individuals With Subjective Cognitive Decline

BACKGROUND

Subjective cognitive decline (SCD) has gained recent interest as a potential harbinger of neurodegenerative diseases such as Alzheimer's disease (AD) and cerebrovascular disease (CVD). In addition, SCD can be related to depressive symptomatology. However, the association between AD and CVD biomarkers, depressive symptomatology, and SCD is still unclear. We investigated the association of AD and CVD biomarkers and depressive symptomatology with SCD in individuals with subjective memory complaints (SCD-memory group) and individuals with subjective concentration complaints (SCD-concentration group).

METHODS

We recruited a population-based cohort of 217 individuals (all aged 70 years, 53% female participants, 119 SCD-memory individuals, 23 SCD-concentration individuals, and 89 controls). AD and CVD were assessed through cerebrospinal fluid levels of the Aβ42/40 ratio and phosphorylated tau, and white matter signal abnormalities on magnetic resonance imaging, respectively. Associations between biomarkers, depressive symptomatology, and SCD were tested via logistic regression and correlation analyses.

RESULTS

We found a significant association between depressive symptomatology with SCD-memory and SCD-concentration. Depressive symptomatology was not associated with AD and CVD biomarkers. Both the phosphorylated tau biomarker and depressive symptomatology predicted SCD-memory, and the Aβ42/40 ratio and depressive symptomatology predicted SCD-concentration.

CONCLUSIONS

The role of depressive symptomatology in SCD may differ depending on the stage within the spectrum of preclinical AD (as determined by amyloid-beta and tau positivity), and does not seem to reflect AD pathology. Our findings contribute to the emerging field of subclinical depressive symptomatology in SCD and clarify the association of different types of subjective complaints with distinct syndromic and biomarker profiles.

The Association of Body Mass Index with Cognition and Alzheimer's Disease Biomarkers in the Elderly with Different Cognitive Status: A Study from the Alzheimer's Disease Neuroimaging Initiative Database

Background

The association of body mass index (BMI) with cognition and Alzheimer's disease (AD) biomarkers of the elderly remains inconclusive.

Objective

To investigate the relationship between BMI and cognition as well as AD biomarkers in the elderly with different cognitive status.

Methods

Participants with cognitively normal (CN) were included as the CN group. Participants with mild cognitive impairment and mild dementia were included as the cognitive impairment (CI) group. The relationship between BMI and AD biomarkers (cerebrospinal fluid Aβ42 and p-tau181, hippocampal volume [HV]), global cognition (Mini-Mental State Examination [MMSE]), memory, and executive function were explored.

Results

In the CI group, BMI was associated with MMSE (β= 0.03, p = 0.009), Aβ42 (β= 0.006, p = 0.029), p-tau181/Aβ42 ratio (β= -0.001, p = 0.011), and HV (β= 0.05, p < 0.001). However in the CN group, BMI exhibited associations with p-tau181 (β= 0.012, p = 0.014) and memory composite score (β= -0.04, p = 0.038), but not with p-tau181/Aβ42 ratio and HV. Moreover, mediation analysis showed that in the CI group, the positive effect of BMI on HV and MMSE score was partially mediated by diastolic blood pressure.

Conclusion

The association of BMI with cognition and AD biomarkers varies across different cognitive status. In particular, a lower BMI was associated with worse cognition, higher Aβ burden, and lower HV in individuals with CI. Clinical practice should strengthen the monitoring and management of BMI in patients with AD.

White matter abnormalities mediate the association between masticatory dysfunction and cognition among older adults

BACKGROUND

Masticatory parameters, such as reduced number of teeth and posterior contacts, have been shown to be associated with reduced cognitive status. The underlying mechanisms that affect these associations, are however, not well understood.

OBJECTIVES

The study aims to investigate the association between masticatory dysfunction and cognition and explore the mediating effect of brain structure.

METHODS

In this cross-sectional study, 45 older adults with subjective masticatory dysfunction (mean age 72.3 ± 4.0 years) were included. Mini-Mental State Examination score <25, brain trauma, neurological disease, neurodegenerative disorders, depression or poor Swedish language skills were criteria for exclusion. Cognitive functions (executive function and episodic memory) and masticatory dysfunction defined by functional occluding status (FOS; the number of occluding units and number of remaining teeth) were analysed with partial correlation models. Structural magnetic resonance imaging was performed on 28 feasible participants. Multiple regression analyses were performed to evaluate the predictive value of brain structure and white matter hypointensities (WM-hypo) on cognitive functions. A mediation analysis was applied to assess significant predictor/s of the association between FOS and cognition.

RESULTS

Both episodic memory and executive functions were positively correlated with FOS. WM-hypo predicted cognitive status (executive function, p ≤ .01). WM-hypo mediated 66.6% (p = 0.06) of the association between FOS and executive functions.

CONCLUSION

Associations between FOS and cognitive functions are reported, where FOS, a potential modifiable risk factor, was related to both episodic memory and executive functions. The mediating effect of WM-hypo on the association between FOS and executive functions highlights the impact of the vascularisation of the brain on the link between mastication and cognition. The present study provides increased knowledge that bridges the gap between masticatory dysfunction and cognition.

Brain-derived neurotrophic factor gene polymorphism affects cognitive function and neurofilament light chain level in patients with subcortical ischaemic vascular dementia

Objective

To investigate the effects of brain-derived neurotrophic factor (BDNF) gene polymorphism on cognitive function, neuroimaging and blood biological markers in patients with subcortical ischaemic vascular dementia (SIVD).

Methods

A total of 81 patients with SIVD were included. According to their BDNF gene polymorphism, the participants were divided into the Val/Val (n = 26), Val/Met (n = 35), and Met/Met (n = 20) groups. A comprehensive neuropsychological evaluation and multimodal brain MRI scan were performed. MRI markers for small vessel disease were visually rated or quantitatively analysed. Moreover, 52 patients were further evaluated with blood marker assays, including amyloid beta (Aβ), phosphorylated tau at threonine-181 (P-tau181), glial fibrillary acidic protein (GFAP), total tau (T-tau) and neurofilament light chain (NfL).

Results

There were no significant differences in demographics, disease duration or MRI markers of small vessel disease between the three groups. Compared with the Val/Val and Val/Met groups, the Met/Met group showed worse performance in the verbal fluency test and higher levels of plasma NfL.

Conclusion

The rs6265 polymorphism of the BDNF gene is associated with semantic language fluency in patients with SIVD. The Met genotype may be a risk factor for cognitive impairment and neuronal injury.

Associations between dietary patterns and dementia-related neuroimaging markers

BACKGROUND

The exploration of associations between dietary patterns and dementia-related neuroimaging markers can provide insights on food combinations that may impact brain integrity.

METHODS

Data were derived from the Swedish Gothenburg H70 Birth Cohort Study (n = 610). Three dietary patterns were obtained using principal component analysis. Magnetic resonance imaging markers included cortical thickness, an Alzheimer's disease (AD) signature score, small vessel disease, and white matter microstructural integrity. Adjusted linear/ordinal regression analyses were performed.

RESULTS

A high-protein and alcohol dietary pattern was negatively associated with cortical thickness in the whole brain (Beta: -0.011; 95% confidence interval [CI]: -0.018 to -0.003), and with an Alzheimer's disease cortical thickness signature score (Beta: -0.013; 95% CI: -0.024 to -0.001). A positive association was found between a Mediterranean-like dietary pattern and white matter microstructural integrity (Beta: 0.078; 95% CI: 0.002-0.154). No associations were found with a Western-like dietary pattern.

DISCUSSION

Dietary patterns may impact brain integrity through neurodegenerative and vascular pathways.

HIGHLIGHTS

Certain dietary patterns were associated with dementia-related neuroimaging markers. A Mediterranean dietary pattern was positively associated with white matter microstructure. A high-protein and alcohol pattern was negatively associated with cortical thickness.

Brain MRI correlations with disease burden and biomarkers in Fabry disease

OBJECTIVE

To quantitatively evaluate cerebral small vessel disease (CSVD) in brain magnetic resonance imaging (MRI) and its correlation with disease burden and markers in Fabry disease, a rare X-linked lysosomal storage disease.

METHODS

We collected brain MRI data from seventy-one Chinese patients with Fabry disease. CSVD was evaluated using an age-related white matter change rating scale, Fazekas scale, enlarged perivascular spaces grading scale, lacunar infarction scale, Microbleed Anatomical Rating Scale, global cortical atrophy scale, and small-vessel disease score. Factors associated with MRI lesions, including sex, clinical subtype, disease severity, disease burden, genotype, and biomarkers, were also analyzed.

RESULTS

Of 71 patients, 16 (22.5%) experienced ischemic stroke. The incidences of lacunar infarctions, white matter hyperintensities, and cerebral microbleeds were 55%, 62%, and 33%, respectively. The abnormal MRI group had later disease onset, longer disease duration, and a higher Mainz Severity Score Index (p < 0.05) than the normal MRI group. Patients with more severe clinical phenotypes also had higher CVSD-related scores. Sex and GLA mutational type were not closely associated with brain MRI lesions. Of the disease markers, the Mainz Severity Score Index and plasma globotriaosylsphingosine (Lyso-Gb3) were closely correlated with the majority of the MRI scores, whereas α-galactosidase A activity was not.

CONCLUSION

Brain MRI revealed progressive lacunar infarctions, white matter hyperintensities, and decreased brain volume in patients with Fabry disease. Brain MRI lesions were closely related to onset-age; disease duration, severity, burden; and plasma Lyso-Gb3. However, they were not associated with sex, α-galactosidase A activity, or GLA mutation type.

Diagnostic accuracy of brain age prediction in a memory clinic population and comparison with clinically available volumetric measures

The aim of this study was to assess the diagnostic validity of a deep learning-based method estimating brain age based on magnetic resonance imaging (MRI) and to compare it with volumetrics obtained using NeuroQuant (NQ) in a clinical cohort. Brain age prediction was performed on minimally processed MRI data using deep convolutional neural networks and an independent training set. The brain age gap (difference between chronological and biological age) was calculated, and volumetrics were performed in 110 patients with dementia (Alzheimer's disease, frontotemporal dementia (FTD), and dementia with Lewy bodies), and 122 with non-dementia (subjective and mild cognitive impairment). Area-under-the-curve (AUC) based on receiver operating characteristics and logistic regression analyses were performed. The mean age was 67.1 (9.5) years and 48.7% (113) were females. The dementia versus non-dementia sensitivity and specificity of the volumetric measures exceeded 80% and yielded higher AUCs compared to BAG. The explained variance of the prediction of diagnostic stage increased when BAG was added to the volumetrics. Further, BAG separated patients with FTD from other dementia etiologies with > 80% sensitivity and specificity. NQ volumetrics outperformed BAG in terms of diagnostic discriminatory power but the two methods provided complementary information, and BAG discriminated FTD from other dementia etiologies.

Vascular cognitive impairment - Past, present, and future challenges

Vascular cognitive impairment (VCI) is a lifelong process encompassing a broad spectrum of cognitive disorders, ranging from subtle or mild deficits to prodromal and fully developed dementia, originating from cerebrovascular lesions such as large and small vessel disease. Genetic predisposition and environmental exposure to risk factors such as unhealthy lifestyles, hypertension, cardiovascular disease, and metabolic disorders will synergistically interact, yielding biochemical and structural brain changes, ultimately culminating in VCI. However, little is known about the pathological processes underlying VCI and the temporal dynamics between risk factors and disease mechanisms (biochemical and structural brain changes). This narrative review aims to provide an evidence-based summary of the link between individual vascular risk/disorders and cognitive dysfunction and the potential structural and biochemical pathophysiological processes. We also discuss some key challenges for future research on VCI. There is a need to shift from individual risk factors/disorders to comorbid vascular burden, identifying and integrating imaging and fluid biomarkers, implementing a life-course approach, considering possible neuroprotective influences of positive life exposures, and addressing biological sex at birth and gender differences. Finally, this review highlights the need for future researchers to leverage and integrate multidimensional data to advance our understanding of the mechanisms and pathophysiology of VCI.

Purpose in life promotes resilience to age-related brain burden in middle-aged adults

BACKGROUND

Disease-modifying agents to counteract cognitive impairment in older age remain elusive. Hence, identifying modifiable factors promoting resilience, as the capacity of the brain to maintain cognition and function with aging and disease, is paramount. In Alzheimer's disease (AD), education and occupation are typical cognitive reserve proxies. However, the importance of psychological factors is being increasingly recognized, as their operating biological mechanisms are elucidated. Purpose in life (PiL), one of the pillars of psychological well-being, has previously been found to reduce the deleterious effects of AD-related pathological changes on cognition. However, whether PiL operates as a resilience factor in middle-aged individuals and what are the underlying neural mechanisms remain unknown.

METHODS

Data was obtained from 624 middle-aged adults (mean age 53.71 ± 6.9; 303 women) from the Barcelona Brain Health Initiative cohort. Individuals with lower (LP; N = 146) and higher (HP; N = 100) PiL rates, according to the division of this variable into quintiles, were compared in terms of cognitive status, a measure reflecting brain burden (white matter lesions; WMLs), and resting-state functional connectivity, examining system segregation (SyS) parameters using 14 common brain circuits.

RESULTS

Neuropsychological status and WMLs burden did not differ between the PiL groups. However, in the LP group, greater WMLs entailed a negative impact on executive functions. Subjects in the HP group showed lower SyS of the dorsal default-mode network (dDMN), indicating lesser segregation of this network from other brain circuits. Specifically, HP individuals had greater inter-network connectivity between specific dDMN nodes, including the frontal cortex, the hippocampal formation, the midcingulate region, and the rest of the brain. Greater functional connectivity in some of these nodes positively correlated with cognitive performance.

CONCLUSION

Expanding previous findings on AD pathology and advanced age, the present results suggest that higher rates of PiL may promote resilience against brain changes already observable in middle age. Furthermore, having a purposeful life implies larger functional integration of the dDMN, which may potentially reflect greater brain reserve associated to better cognitive function.

SERS "hot spot" enhance-array assay for misfolded SOD1 correlated with white matter lesions and aging

Misfolding of superoxide dismutase-1 (SOD1) has been correlated with many neurodegenerative diseases, such as Amyotrophic lateral sclerosis's and Alzheimer's among others. However, it is unclear whether misfolded SOD1 plays a role in another neurodegenerative disease of white matter lesions (WMLs). In this study, a sensitive and specific method based on SERS technique was proposed for quantitative detection of misfolded SOD1 content in WMLs. To fabricate the double antibodysandwich substrates for SERS detection, gold nanostars modified with capture antibody were immobilized on glass substrates to prepare active SERS substrates, and then SERS probes conjugated with a Raman reporter and a specific target antibody were coupled with active SERS substrates. This SERS substrates had been employed for quantitative detection of misfolded SOD1 levels in WMLs and exhibited excellent stability, reliability, and accuracy. Moreover, experimental results indicated that the level of misfolded SOD1 increased with the increase in age and the degree of WMLs. Hence, misfolded SOD1 may be a potential blood marker for WMLs and aging. Meanwhile, SERS-based gold nanostars have great clinical application potential in the screening, diagnosis and treatment of WMLs.

Superficial white matter microstructure affects processing speed in cerebral small vessel disease

White matter hyperintensities (WMH) are a typical feature of cerebral small vessel disease (CSVD), which contributes to about 50% of dementias worldwide. Microstructural alterations in deep white matter (DWM) have been widely examined in CSVD. However, little is known about abnormalities in superficial white matter (SWM) and their relevance for processing speed, the main cognitive deficit in CSVD. In 141 CSVD patients, processing speed was assessed using Trail Making Test Part A. White matter abnormalities were assessed by WMH burden (volume on T2-FLAIR) and diffusion MRI measures. SWM imaging measures had a large contribution to processing speed, despite a relatively low SWM WMH burden. Across all imaging measures, SWM free water (FW) had the strongest association with processing speed, followed by SWM mean diffusivity (MD). SWM FW was the only marker to significantly increase between two subgroups with the lowest WMH burdens. When comparing two subgroups with the highest WMH burdens, the involvement of WMH in the SWM was accompanied by significant differences in processing speed and white matter microstructure. Mediation analysis revealed that SWM FW fully mediated the association between WMH volume and processing speed, while no mediation effect of MD or DWM FW was observed. Overall, results suggest that the SWM has an important contribution to processing speed, while SWM FW is a sensitive imaging marker associated with cognition in CSVD. This study extends the current understanding of CSVD-related dysfunction and suggests that the SWM, as an understudied region, can be a potential target for monitoring pathophysiological processes.

Diagnostic value of plasma D-dimer and serum lipoprotein phospholipase A2 in patients with cerebral small vessel disease and their association with severity of the disease

OBJECTIVE

To determine the diagnostic value of plasma D-dimer (DD) and serum lipoprotein phospholipase A2 (Lp-PLA2) in patients with cerebral small vessel disease (CSVD) and their association with severity of the disease.

METHODS

In this retrospective analysis, 84 patients with CSVD treated in Shangqiu First People's Hospital from February 2020 to November 2021 were included in the study group, and 75 healthy individuals were assigned into the control group. The DD and Lp-PLA2 levels in the two groups were compared, and the diagnostic value of the two in CSVD was evaluated via receiver operating characteristic (ROC) curves. Patients were assigned to a mild group or a severe group based on Fazekas scale scores. Then, the two groups were compared in terms of the DD and Lp-PLA2 levels, and the association of the two with the severity of CSVD was determined through ROC curves. With the Montreal cognitive assessment (MoCA) scale, the patients were assigned to a cognitive impairment group or a non-cognitive impairment group. Then the two groups were compared in terms of the DD and Lp-PLA2 levels, and the association of the two with the cognitive function of CSVD patients was also determined by ROC curves.

RESULTS

The research group showed higher DD and Lp-PLA2 levels than the control group; the severe group showed higher DD and Lp-PLA2 levels than the mild group; the cognitive impairment group showed higher DD and Lp-PLA2 levels than the non-cognitive impairment group (all P < 0.001). The areas under the curves (AUCs) of DD and Lp-PLA2 in CSVD diagnosis were 0.902 and 0.907, respectively; the AUCs of DD and Lp-PLA2 in CSVD severity determination were 0.747 and 0.704, respectively; the AUCs of DD and Lp-PLA2 in cognitive impairment diagnosis were 0.736 and 0.725, respectively.

CONCLUSION

Plasma DD and Lp-PLA2 possess good diagnostic value in patients with CSVD, and also has certain clinical value in diagnosing patients' severity and cognitive impairment.

Diagnostic performance of deep learning-based automatic white matter hyperintensity segmentation for classification of the Fazekas scale and differentiation of subcortical vascular dementia

Purpose

To validate the diagnostic performance of commercially available, deep learning-based automatic white matter hyperintensity (WMH) segmentation algorithm for classifying the grades of the Fazekas scale and differentiating subcortical vascular dementia.

Methods

This retrospective, observational, single-institution study investigated the diagnostic performance of a deep learning-based automatic WMH volume segmentation to classify the grades of the Fazekas scale and differentiate subcortical vascular dementia. The VUNO Med-DeepBrain was used for the WMH segmentation system. The system for segmentation of WMH was designed with convolutional neural networks, in which the input image was comprised of a pre-processed axial FLAIR image, and the output was a segmented WMH mask and its volume. Patients presented with memory complaint between March 2017 and June 2018 were included and were split into training (March 2017–March 2018, n = 596) and internal validation test set (April 2018–June 2018, n = 204).

Results

Optimal cut-off values to categorize WMH volume as normal vs. mild/moderate/severe, normal/mild vs. moderate/severe, and normal/mild/moderate vs. severe were 3.4 mL, 9.6 mL, and 17.1 mL, respectively, and the AUC were 0.921, 0.956 and 0.960, respectively. When differentiating normal/mild vs. moderate/severe using WMH volume in the test set, sensitivity, specificity, and accuracy were 96.4%, 89.9%, and 91.7%, respectively. For distinguishing subcortical vascular dementia from others using WMH volume, sensitivity, specificity, and accuracy were 83.3%, 84.3%, and 84.3%, respectively.

Conclusion

Deep learning-based automatic WMH segmentation may be an accurate and promising method for classifying the grades of the Fazekas scale and differentiating subcortical vascular dementia.

The value of mobile magnetic resonance imaging in early warning for stroke: A prospective case-control study

Aims

To evaluate the predictive value of mobile magnetic resonance imaging (MRI) in screening stroke.

Methods

This was a prospective case-control study performed on healthy residents over 40 years old in remote rural areas of northern China between May 2019 and May 2020. Multivariate logistic regression and receiver operator characteristic curve (ROC) analysis were used to evaluate the screening model.

Results

A total of 1,224 patients (500 [40.8%] men) enrolled, including 56 patients who suffered from stroke (aged 64.05 ± 7.27). The individuals who developed stroke were significantly older (P < 0.001), had a significantly higher occurrence of heart disease (P = 0.015), diabetes (P = 0.005), dyslipidemia (P = 0.009), and significantly increased waist circumference (P = 0.02), systolic blood pressure (SBP) (P = 0.003), glycosylated hemoglobin (HbA1c) level (P = 0.007), triglyceride (TG) level (P = 0.025), low density lipoprotein cholesterol (LDL-c) level (P = 0.04), and homocysteine (HCY) level (P < 0.001). Multivariate logistic regression analysis showed that age (OR = 1.055, 95% CI: 1.017–1.094, P = 0.004), HCY (OR = 1.029, 95% CI: 1.012–1.047, P = 0.001) and mobile MRI (OR = 4.539, 95% CI: 1.726–11.939, P = 0.002) were independently associated with stroke. The area under the curve (AUC) of the combined model including national screening criteria, mobile MRI results, and stroke risk factors was 0.786 (95% CI: 0.721–0.851), with a sensitivity of 69.6% and specificity of 80.4%.

Conclusion

Mobile MRI can be used as a simple and easy means to screen stroke.

Higher-resolution quantification of white matter hypointensities by large-scale transfer learning from 2D images on the JPSC-AD cohort

White matter lesions (WML) commonly occur in older brains and are quantifiable on MRI, often used as a biomarker in Aging research. Although algorithms are regularly proposed that identify these lesions from T2‐fluid‐attenuated inversion recovery (FLAIR) sequences, none so far can estimate lesions directly from T1‐weighted images with acceptable accuracy. Since 3D T1 is a polyvalent and higher‐resolution sequence, it could be beneficial to obtain the distribution of WML directly from it. However a serious difficulty, both for algorithms and human, can be found in the ambiguities of brain signal intensity in T1 images. This manuscript shows that a cross‐domain ConvNet (Convolutional Neural Network) approach can help solve this problem. Still, this is non‐trivial, as it would appear to require a large and varied dataset (for robustness) labelled at the same high resolution (for spatial accuracy). Instead, our model was taught from two‐dimensional FLAIR images with a loss function designed to handle the super‐resolution need. And crucially, we leveraged a very large training set for this task, the recently assembled, multi‐sites Japan Prospective Studies Collaboration for Aging and Dementia (JPSC‐AD) cohort. We describe the two‐step procedure that we followed to handle such a large number of imperfectly labeled samples. A large‐scale accuracy evaluation conducted against FreeSurfer 7, and a further visual expert rating revealed that WML segmentation from our ConvNet was consistently better. Finally, we made a directly usable software program based on that trained ConvNet model, available at https://github.com/bthyreau/deep-T1-WMH.

Plasma and CSF NfL are differentially associated with biomarker evidence of neurodegeneration in a community-based sample of 70-year-olds

Neurofilament light protein (NfL) in cerebrospinal fluid (CSF) and plasma (P) are suggested to be interchangeable markers of neurodegeneration. However, evidence is scarce from community-based samples. NfL was examined in a small-scale sample of 287 individuals from the Gothenburg H70 Birth cohort 1944 study, using linear models in relation to CSF and magnetic resonance imaging (MRI) biomarker evidence of neurodegeneration. CSF-NfL and P-NfL present distinct associations with biomarker evidence of Alzheimer's disease (AD) pathology and neurodegeneration. P-NfL was associated with several markers that are characteristic of AD, including smaller hippocampal volumes, amyloid beta (Aβ)42, Aβ42/40, and Aβ42/t-tau (total tau). CSF-NfL demonstrated associations with measures of synaptic and neurodegeneration, including t-tau, phosphorylated tau (p-tau), and neurogranin. Our findings suggest that P-NfL and CSF-NfL may exert different effects on markers of neurodegeneration in a small-scale community-based sample of 70-year-olds.

Parsing heterogeneity within dementia with Lewy bodies using clustering of biological, clinical, and demographic data

BACKGROUND

Dementia with Lewy bodies (DLB) includes various core clinical features that result in different phenotypes. In addition, Alzheimer's disease (AD) and cerebrovascular pathologies are common in DLB. All this increases the heterogeneity within DLB and hampers clinical diagnosis. We addressed this heterogeneity by investigating subgroups of patients with similar biological, clinical, and demographic features.

METHODS

We studied 107 extensively phenotyped DLB patients from the European DLB consortium. Factorial analysis of mixed data (FAMD) was used to identify dimensions in the data, based on sex, age, years of education, disease duration, Mini-Mental State Examination (MMSE), cerebrospinal fluid (CSF) levels of AD biomarkers, core features of DLB, and regional brain atrophy. Subsequently, hierarchical clustering analysis was used to subgroup individuals based on the FAMD dimensions.

RESULTS

We identified 3 dimensions using FAMD that explained 38% of the variance. Subsequent hierarchical clustering identified 4 clusters. Cluster 1 was characterized by amyloid-β and cerebrovascular pathologies, medial temporal atrophy, and cognitive fluctuations. Cluster 2 had posterior atrophy and showed the lowest frequency of visual hallucinations and cognitive fluctuations and the worst cognitive performance. Cluster 3 had the highest frequency of tau pathology, showed posterior atrophy, and had a low frequency of parkinsonism. Cluster 4 had virtually normal AD biomarkers, the least regional brain atrophy and cerebrovascular pathology, and the highest MMSE scores.

CONCLUSIONS

This study demonstrates that there are subgroups of DLB patients with different biological, clinical, and demographic characteristics. These findings may have implications in the diagnosis and prognosis of DLB, as well as in the treatment response in clinical trials.

Association of Plasma Oligomerized Amyloid-β and Cerebral White Matter Lesions in a Health Screening Population

BACKGROUND

Cerebral white matter lesions (WML) are related to a higher risk of vascular and Alzheimer's dementia. Moreover, oligomerized amyloid-β (OAβ) can be measured from blood for dementia screening.

OBJECTIVE

We aimed to investigate the relationship of plasma OAβ levels with clinical and radiological variables in a health screening population.

METHODS

WML, other volumetric parameters of magnetic resonance images, cognitive assessment, and plasma OAβ level were evaluated.

RESULTS

Ninety-two participants were analyzed. The majority of participants' clinical dementia rating was 0 or 0.5 (96.7%). White matter hyperintensities (WMH) increased with age, but OAβ levels did not (r2 = 0.19, p < 0.001, r2 = 0.03, p = 0.10, respectively). No volumetric data, including cortical thickness/hippocampal volume, showed any significant correlation with OAβ. Log-WMH volume was positively correlated with OAβ (r = 0.24, p = 0.02), and this association was significant in the periventricular area. White matter signal abnormalities from 3D-T1 images were also correlated with the OAβ in the periventricular area (p = 0.039). Multivariate linear regression showed that log-WMH values were independently associated with OAβ (B = 0.879 (95% confidence interval 0.098 -1.660, p = 0.028)). Higher tertiles of WMH showed higher OAβ levels than lower tertiles showed (p = 0.044). Using a cutoff of 0.78 ng/mL, the high OAβ group had a larger WMH volume, especially in the periventricular area, than the low OAβ group (p = 0.036).

CONCLUSION

Both WML and plasma OAβ levels can be early markers for neurodegeneration in the healthcare population. The lesions, especially in the periventricular area, might be related to amyloid pathogenesis, which strengthens the importance of WML in the predementia stage.

The influence of white matter hyperintensities severity on functional brain activity in cerebral small vessel disease: An rs-fMRI study

OBJECTIVE

To investigate relationships between the severity of white matter hyperintensities (WMH), functional brain activity, and cognition in cerebral small vessel disease (CSVD) based on resting-state functional magnetic resonance imaging (rs-fMRI) data.

METHODS

A total of 103 subjects with CSVD were included. The amplitude of low frequency fluctuations (ALFF), regional homogeneity (ReHo), functional connectivity (FC) and their graph properties were applied to explore the influence of WMH burden on functional brain activity. We also investigated whether there are correlations between different functional brain characteristics and cognitive assessments. Finally, we selected disease-related rs-fMRI features in combination with ensemble learning to classify CSVD patients with low WMH load and with high WMH load.

RESULTS

The high WMH load group demonstrated significantly abnormal functional brain activity based on rs-MRI data, relative to the low WMH load group. ALFF and graph properties in specific brain regions were significantly correlated with patients' cognitive assessments in CSVD. Moreover, altered rs-fMRI signal can help predict the severity of WMH in CSVD patients with an overall accuracy of 92.23%.

CONCLUSIONS

This study provided a comprehensive analysis and evidence for a pattern of altered functional brain activity under different WMH load in CSVD based on rs-fMRI data, enabling accurately individual prediction of status of WMH.

Atrial Fibrillation, Stroke, and Silent Cerebrovascular Disease: A Population-based MRI Study

Background and Objectives

Atrial fibrillation (AF) has been associated with cognitive decline and dementia. However, the mechanisms behind these associations are not clear. Examination of cerebrovascular pathology on MRI may shed light on how AF affects the brain. This study aimed to determine whether AF is associated with a broad range of cerebrovascular diseases beyond the well-known association with symptomatic stroke, including silent infarcts and markers of small vessel disease, i.e., cerebral microbleeds (CMBs), white matter hyperintensities (WMHs), and lacunes, in a population-based sample of 70-year-olds.

Methods

Data were obtained from the Gothenburg H70 Birth Cohort Studies, in which individuals are invited based on birthdate. This study has a cross-sectional design and includes individuals born in 1944 who underwent structural brain MRI in 2014 to 2017. AF diagnoses were based on self-report, ECG, and register data. Symptomatic stroke was based on self-report, proxy interviews, and register data. Brain infarcts and CMBs were assessed by a radiologist. WMH volumes were measured on fluid-attenuated inversion recovery images with the Lesion Segmentation Tool. Multivariable logistic regression was used to study the association between AF and infarcts/CMBs, and multivariable linear regression was used to study the association between AF and WMHs.

Results

A total of 776 individuals were included, and 65 (8.4%) had AF. AF was associated with symptomatic stroke (odds ratio [OR] 4.5, 95% confidence interval [CI] 2.1–9.5) and MRI findings of large infarcts (OR 5.0, 95% CI 1.5–15.9), lacunes (OR 2.7, 95% CI 1.2–5.6), and silent brain infarcts (OR 3.5; 95% CI 1.6–7.4). Among those with symptomatic stroke, individuals with AF had larger WMH volumes (0.0137 mL/total intracranial volume [TIV], 95% CI 0.0074–0.0252) compared to those without AF (0.0043 mL/TIV, 95% CI 0.0029–0.0064). There was no association between AF and WMH volumes among those without symptomatic stroke. In addition, AF was associated to CMBs in the frontal lobe.

Discussion

AF was associated with a broad range of cerebrovascular pathologies. Further research is needed to establish whether cerebrovascular MRI markers can be added to current treatment guidelines to further personalize anticoagulant treatment in patients with AF and to further characterize the pathogenetic processes underlying the associations between AF and cerebrovascular diseases, as well as dementia.

Cerebrovascular Disease and Depressive Symptomatology in Individuals With Subjective Cognitive Decline: A Community-Based Study

Subjective cognitive decline (SCD) may be the first sign of Alzheimer's disease (AD), but it can also reflect other pathologies such as cerebrovascular disease or conditions like depressive symptomatology. The role of depressive symptomatology in SCD is controversial. We investigated the association between depressive symptomatology, cerebrovascular disease, and SCD. We recruited 225 cognitively unimpaired individuals from a prospective community-based study [mean age (SD) = 54.64 (10.18); age range 35-77 years; 55% women; 123 individuals with one or more subjective cognitive complaints, 102 individuals with zero complaints]. SCD was assessed with a scale of 9 memory and non-memory subjective complaints. Depressive symptomatology was assessed with established questionnaires. Cerebrovascular disease was assessed with magnetic resonance imaging markers of white matter signal abnormalities (WMSA) and mean diffusivity (MD). We combined correlation, multiple regression, and mediation analyses to investigate the association between depressive symptomatology, cerebrovascular disease, and SCD. We found that SCD was associated with more cerebrovascular disease, older age, and increased depressive symptomatology. In turn, depressive symptomatology was not associated with cerebrovascular disease. Variability in MD was mediated by WMSA burden, presumably reflecting cerebrovascular disease. We conclude that, in our community-based cohort, depressive symptomatology is associated with SCD but not with cerebrovascular disease. In addition, depressive symptomatology did not influence the association between cerebrovascular disease and SCD. We suggest that therapeutic interventions for depressive symptomatology could alleviate the psychological burden of negative emotions in people with SCD, and intervening on vascular risk factors to reduce cerebrovascular disease should be tested as an opportunity to minimize neurodegeneration in SCD individuals from the community.

Cholinergic basal forebrain and hippocampal structure influence visuospatial memory in Parkinson's disease

Visuospatial impairment in Parkinson's disease (PD) heralds the onset of a progressive dementia syndrome and might be associated with cholinergic dysfunction. It remains unclear however, whether degeneration of the cholinergic basal forebrain is directly related to cognitive decline, or whether relationships between this region and cognitive function are mediated by closely related brain structures such as those in the medial temporal lobe. To evaluate relationships between structure of the cholinergic basal forebrain, medial temporal lobe and cognition, 27 PD patients without dementia and 20 controls underwent neuropsychological assessment and MRI. Volumes of the cholinergic basal forebrain nuclei, the entorhinal cortex, the hippocampus and its subfields were measured. Regression models utilised basal forebrain and hippocampal volumetric measures to predict cognitive performance. In PD, visuospatial memory (but not verbal memory or executive function) was correlated with hippocampal volume, particularly CA2-3, and basal forebrain subregion Ch1-2, but not Ch4. In addition, hippocampal volume was correlated with Ch1-2 in PD. The relationship between Ch1-2 and visuospatial memory was mediated by CA2-3 integrity. There were no correlations between cognitive and volumetric measures in controls. Our data imply that the integrity of the cholinergic basal forebrain is associated with subregional hippocampal volume. Additionally, a relationship between visuospatial function and cholinergic nuclei does exist, but is fully mediated by variations in hippocampal structure. These findings are consistent with the recent hypothesis that forebrain cholinergic system degeneration results in cognitive deficits via cholinergic denervation, and subsequent structural degeneration, of its target regions.

Circulating Angiotensin-(1-7) Is Reduced in Alzheimer's Disease Patients and Correlates With White Matter Abnormalities: Results From a Pilot Study

Introduction

Alzheimer’s disease (AD) is the leading cause of dementia worldwide. Despite the extensive research, its pathophysiology remains largely unelucidated. Currently, more attention is being given to the disease’s vascular and inflammatory aspects. In this context, the renin-angiotensin system (RAS) emerges as a credible player in AD pathogenesis. The RAS has multiple physiological functions, conducted by its two opposing axes: the classical, led by Angiotensin II (Ang II), and the alternative, driven by Angiotensin-(1–7) [Ang-(1–7)]. These peptides were shown to interact with AD pathology in animal studies, but evidence from humans is scarce. Only 20 studies dosed RAS molecules in AD patients’ bloodstream, none of which assessed both axes simultaneously. Therefore, we conducted a cross-sectional, case-control exploratory study to compare plasma levels of Ang II and Ang-(1–7) in AD patients vs. age-matched controls. Within each group, we searched for correlations between RAS biomarkers and measures from magnetic resonance imaging (MRI).

Methods

We evaluated patients with AD (n = 14) and aged-matched controls (n = 14). Plasma Ang II and Ang-(1–7) were dosed using ELISA. Brain MRI was performed in a 3 Tesla scan, and a three-dimensional T1-weighted volumetric sequence was obtained. Images were then processed by FreeSurfer to calculate: (1) white matter hypointensities (WMH) volume; (2) volumes of hippocampus, medial temporal cortex, and precuneus. Statistical analyses used non-parametrical tests (Mann-Whitney and Spearman).

Results

Ang-(1–7) levels in plasma were significantly lower in the AD patients than in controls [median (25th–75th percentiles)]: AD [101.5 (62.43–126.4)] vs. controls [209.3 (72–419.1)], p = 0.014. There was no significant difference in circulating Ang II. In the AD patients, but not in controls, there was a positive and significant correlation between Ang-(1–7) values and WMH volumes (Spearman’s rho = 0.56, p = 0.038). Ang-(1–7) did not correlate with cortical volumes in AD or in controls. Ang II did not correlate with any MRI variable in none of the groups.

Conclusion

If confirmed, our results strengthen the hypothesis that RAS alternative axis is downregulated in AD, and points to a possible interaction between Ang-(1–7) and cerebrovascular lesions in AD.

Brain Atrophy Subtypes and the ATN Classification Scheme in Alzheimer's Disease

INTRODUCTION

We investigated the association between atrophy subtypes of Alzheimer's disease (AD), the ATN classification scheme, and key demographic and clinical factors in 2 cohorts with different source characteristics (a highly selective research-oriented cohort, the Alzheimer's Disease Neuroimaging Initiative [ADNI]; and a naturalistic heterogeneous clinically oriented cohort, Karolinska Imaging Dementia Study [KIDS]).

METHODS

A total of 382 AD patients were included. Factorial analysis of mixed data was used to investigate associations between AD subtypes based on brain atrophy patterns, ATN profiles based on cerebrospinal fluid biomarkers, and age, sex, Mini Mental State Examination (MMSE), cerebrovascular disease (burden of white matter signal abnormalities, WMSAs), and APOE genotype.

RESULTS

Older patients with high WMSA burden, belonging to the typical AD subtype and showing A+T+N+ or A+T+N- profiles clustered together and were mainly from ADNI. Younger patients with low WMSA burden, limbic-predominant or minimal atrophy AD subtypes, and A+T-N- or A+T-N+ profiles clustered together and were mainly from KIDS. APOE ε4 carriers more frequently showed the A+T-N- and A+T+N- profiles.

CONCLUSIONS

Our findings align with the recent framework for biological subtypes of AD: the combination of risk factors, protective factors, and brain pathologies determines belonging of AD patients to distinct subtypes.

Comparing different approaches for operationalizing subjective cognitive decline: impact on syndromic and biomarker profiles

Subjective cognitive decline (SCD) has been proposed as a risk factor for future cognitive decline and dementia. Given the heterogeneity of SCD and the lack of consensus about how to classify this condition, different operationalization approaches still need to be compared. In this study, we used the same sample of individuals to compare  different SCD operationalization approaches. We included 399 cognitively healthy individuals from a community-based cohort. SCD was assessed through nine questions about memory and non-memory subjective complaints. We applied four approaches to operationalize SCD: two hypothesis-driven approaches and two data-driven approaches. We characterized the resulting groups from each operationalization approach using multivariate methods on comprehensive demographic, clinical, cognitive, and neuroimaging data. We identified two main phenotypes: an amnestic phenotype characterized by an Alzheimer's Disease (AD) signature pattern of brain atrophy; and an anomic phenotype, which was mainly related to cerebrovascular pathology. Furthermore, language complaints other than naming helped to identify a subgroup with subclinical cognitive impairment and difficulties in activities of daily living. This subgroup also showed an AD signature pattern of atrophy. The identification of SCD phenotypes, characterized by different syndromic and biomarker profiles, varies depending on the operationalization approach used. In this study we discuss how these findings may be used in clinical practice and research.

Cholinergic white matter pathways make a stronger contribution to attention and memory in normal aging than cerebrovascular health and nucleus basalis of Meynert

The integrity of the cholinergic system plays a central role in cognitive decline both in normal aging and neurological disorders including Alzheimer's disease and vascular cognitive impairment. Most of the previous neuroimaging research has focused on the integrity of the cholinergic basal forebrain, or its sub-region the nucleus basalis of Meynert (NBM). Tractography using diffusion tensor imaging data may enable modelling of the NBM white matter projections. We investigated the contribution of NBM volume, NBM white matter projections, small vessel disease (SVD), and age to performance in attention and memory in 262 cognitively normal individuals (39-77 years of age, 53% female). We developed a multimodal MRI pipeline for NBM segmentation and diffusion-based tracking of NBM white matter projections, and computed white matter hypointensities (WM-hypo) as a marker of SVD. We successfully tracked pathways that closely resemble the spatial layout of the cholinergic system as seen in previous post-mortem and DTI tractography studies. We found that high WM-hypo load was associated with older age, male sex, and lower performance in attention and memory. A high WM-hypo load was also associated with lower integrity of the cholinergic system above and beyond the effect of age. In a multivariate model, age and integrity of NBM white matter projections were stronger contributors than WM-hypo load and NBM volume to performance in attention and memory. We conclude that the integrity of NBM white matter projections plays a fundamental role in cognitive aging. This and other modern neuroimaging methods offer new opportunities to re-evaluate the cholinergic hypothesis of cognitive aging.