bluuebunny/crossref_metadata_2025 huggingface dataset:
The relationship between brain‐age association and prediction: The impact of parameter selection
Authors: Zeighami Yashar , Evans Alan C.
Published: February 2022

Background

Association and prediction studies of brain age target the relationships between neuroanatomical changes across lifespan and behavioural or pathological phenotypes. However, the relationship between the two analyses has not been directly examined. Here we use brain resels (i.e. resolution elements) (Worsley et al. 1996) to directly compare age association and brain‐age prediction as a function of cortical thickness smoothing and parcellation parameters.

Method

Data included 608 healthy subjects (Age = 53.5218.07; Age range = 18‐88, 308 Female subjects) subjects with T1‐weighted MRI from the Cambridge Centre for Ageing and Neuroscience (https://www.cam‐can.org/index.php?content=dataset). CIVET pipeline (http://www.bic.mni.mcgill.ca/ServicesSoftware/CIVET) was used to extract cortical surfaces and calculate cortical thickness across the brain. We used 6 different diffusion based smoothing kernels (0, 5, 10, 20, 30, and 40 mm) and 5 different parcellation levels: 100, 200, 400, and 1000 parcels from Schaefer et al., 2018 multi‐level functional parcellation atlas as well as the entire cortex. For each level of smoothing and parcellation, age‐related correlations were calculated. Brain age was predicted using a linear regression model with 10‐fold cross validation, with principal components of cortical thickness data as predictors. To directly compare the correlation and prediction results, we calculated the brain resels for each smoothing parcellation parameter.

Result

Figure 1.A shows the correlation patterns across the brain as a function of smoothing and parcellation. Figure 2 shows age prediction error as a function of smoothing kernel, parcellation level, and number of principal components included. Larger smoothing kernels and brain parcels result in higher correlation values (Figure 1.B), but lower prediction accuracy (Figure 2). Figures 3.A and 3.B show mean age‐correlation value and age‐prediction error as a function of number of resels.

Conclusion

Our results demonstrate an opposite relationship between brain‐age association values and brain‐age prediction accuracy, and quantify how smoothing and parcellation parameters affect each of these analyses. These results highlight the importance of parameter selection for each analysis type and how they might affect the final results, and have significant implications for brain aging studies.
Optimal parameters for propagating gamma brain waves using flickering lights in human
Authors: Park Yeseung , Lee Kanghee , Kim Sang‐Su , Kim Do‐Won , Park Jaehyeok , Yoo Seunghyup , Kim Ki Woong
Published: February 2022

Background

Sensory stimulation with 40 Hz flickering light could entrain gamma oscillations leading to decreased amyloid β burden. However, the optimum parameters of a light source to promote brain gamma activity in humans have not suggested yet. We performed the study to investigate the optimal intensity and frequency of the flickering light stimulus (FLS) in young adults.

Method

We measured electroencephalography (EEG) during the FLS presented. We compared the event‐related synchronization (ERS) values of entrained gamma waves between four different luminance intensities (10, 100, 400, and 700 cd/m2) at 10 different flickering frequencies from 32Hz to 50Hz with an interval of 2Hz. Each frequency condition was comprised of 10 times repetition of 2‐sec with inter‐stimulus interval (ISI). We also examined the severity of six adverse effects in both experiments. Using the Granger causality, we compared the propagation of gamma waves in visual cortex to other brain regions between different luminance intensities and flickering frequencies.

Result

Entrained gamma activity started after the FLS onset, lasted during the FLS, and diminished after the FLS offset which was observed most highly at parietal area and steadily decreased from the parietal to the frontal area. Lights of higher luminance intensities (700cd/m2 and 400cd/m2) entrained stronger and more widely spread gamma waves than those of lower luminance intensities (100cd/m2 and 10cd/m2). Lights flickering at 34Hz ∼ 38Hz entrained stronger and more widely spread beyond visual cortex than those flickering at 40Hz ∼ 50Hz.

Conclusion

Optimal frequency of FLS for entraining brain gamma activity in human may be different from those in animals. Higher luminance with lower gamma frequency stimulus are effective to propagate the gamma activity to the frontal area.
MRI longitudinal and cross‐sectional monitoring of amyloid pathology in non‐human primates
Authors: Genovese Thomas S. , Ramadane Dina , Kingsley Charles , Nehete Pramod N. , Patel Akash G. , Leung Jonathan , Tibensky Miroslav , Rusinek Henry , Gray Stanton B. , Williams Lawrence E. , Zaim‐Wadghiri Youssef , Wisniewski Thomas , Scholtzova Henrieta
Published: February 2022

Background

The potential for using MRI technologies to visualize amyloid deposits has been increasingly recognized. The present study utilized a New World non‐human primate (NHP) model of amyloid pathology, squirrel monkey (SQM), which unlike other NHPs, develops age‐dependent abundant cerebral amyloid angiopathy (CAA). The transverse relaxation rate (R2*) has a linear correlation with iron content, a component of amyloid deposits and microhemorrhages. Here we assessed whether the region of interest (ROI)‐based quantitative R2* assessment is able to detect differences in SQM neuropathology between varying age cohorts as well as longitudinally. An additional focus was to examine the presence of naturally occurring ARIA‐E like pathologies in geriatric SQMs.

Method

Multi‐gradient echo (MGE) MRI datasets were acquired in three different SQM age cohorts at various stages of Aβ pathology development. The R2* maps were generated (Firevoxel parametric map tool) from each subject to enable ROI‐based quantitative R2* analyses. DAB‐enhanced histochemical iron stain (Meguro method), along with 6E10/4G8 immunohistochemistry, was used to identify iron‐positive Aβ deposits. Histological examination of neuroinflammation and microhemorrhages (Perls’ iron stain) was performed. T2‐w FLAIR images were acquired to assess the presence of ARIA‐E.

Result

MGE imaging was capable of depicting brain pathology differences between three SQM age cohorts (ages 5, 16, 21). Absolute quantitation of R2* values, defined by ROI circumventing the cortex, revealed significant age‐related differences in selected brain regions, with the highest R2* counts detected in 21yr old monkeys. The ability to longitudinally track pathology‐related increase in R2* values was further validated by MRIs performed at specific intervals post‐initial scans in our geriatric monkeys. Iron‐positive Aβ deposits and microhemorrhages detected by MRI were confirmed via matched histological sections. Subsequent histological evaluation demonstrated disease‐stage differences in microgliosis and astrocytosis. Moreover, ARIA‐E like T2‐w signal hyperintensities were detected in our oldest cohort. Neuropathological correlates of ARIA‐E‐related changes were characterized histologically.

Conclusion

The current study highlights the utility of MRI methodologies to monitor age‐dependent progression of Aβ‐related pathology, as well as the importance of the SQM model for future translational research on advancing therapeutic interventions targeting amyloid depositions.
Imaging measures of molecular pathology and neurodegeneration in dominantly‐inherited and sporadic early‐onset Alzheimer’s Disease
Authors: Iaccarino Leonardo , Llibre‐Guerra Jorge J. , Edwards Lauren , Mundada Nidhi , Strom Amelia , Tsoy Elena , Li Yan , Gordon Brian A. , Schindler Suzanne E. , Fagan Anne M. , Benzinger Tammie L.S. , Wang Guoqiao , Hassenstab Jason , Morris John C. , Xiong Chengjie , Perrin Richard J. , Soleimani‐Meigooni David N. , Miller Zachary A. , Kramer Joel H. , Rosen Howard J. , La Joie Renaud , Miller Bruce L. , Bateman Randall J. , Rabinovici Gil D.
Published: February 2022

Background

Approximately 5% of patients with Alzheimer’s Disease (AD) develop symptoms before age 65, with this early‐onset presentation attributed to either sporadic (sEOAD) or dominantly‐inherited (DIAD) etiology. Both sEOAD and DIAD are characterized by brain amyloid‐beta (Aβ) accumulation and neurodegeneration, but differences in topography and magnitude of these pathological changes are not fully elucidated.

Method

We included 108 sEOAD Aβ‐PET positive cases from the UCSF Alzheimer’s Disease Research Center (mean±standard deviation age 59.7±5.4 years) and 86 DIAD cases from the Dominantly Inherited Alzheimer Network (DIAN) study (age 45.5±9.5 years) with symptom onset before 65 years (see Table 1). All cases were symptomatic (clinical dementia rating [CDR] global ≥0.5) and underwent standard clinical and cognitive measures, 11C‐PiB‐PET (Aβ), 18F‐FDG‐PET (glucose metabolism) and structural MRI. PET scans were processed to obtain Standardized Uptake Value Ratio (SUVR, PIB50‐70, FDG30‐60) images. Warped PET SUVR and modulated, warped gray matter images were compared across the two cohorts with SPM12 after smoothing to ∼8mm3, covarying for age, CDR sum of boxes, years of education, APOE e4 status, and respective global biomarker score. A‐priori statistical threshold was set at p<0.001 uncorrected, with a Family Wise Error p<0.05 correction at the cluster‐level.

Result

sEOAD participants were older, more educated, had greater cognitive impairment, had higher Aβ burden and were more likely to be APOE ε4 carriers (see Table 1). sEOAD participants exhibited higher relative PIB‐PET binding in anterior temporal and frontal (mostly white matter) regions, as well as lower relative FDG‐PET binding and sMRI‐based volumes in temporoparietal regions. DIAD participants showed higher relative PIB‐PET binding in the medial occipital, thalami, basal ganglia (caudate nuclei and putamen) and medial/dorsal frontal regions. DIAD participants showed lower relative FDG‐PET binding mostly in the frontal and parietal white matter (see Figure 1).

Conclusion

Aβ pathology in DIAD was more likely to affect subcortical systems, whereas both Aβ pathology and neurodegeneration tended to be relatively more cortical and extensive in sEOAD. These results highlight EOAD heterogeneity and show that sporadic and inherited AD exhibit distinct regional vulnerabilities in neurodegeneration as well as differing topography and magnitude of biomarker abnormalities.
Home monitoring of vital signs and generation of alerts in a cohort of people living with dementia
Authors: David Michael , Barnaghi Payam , Nilforooshan Ramin , Rostill Helen , Soreq Eyal , Sharp David J , Scott Gregory
Published: February 2022

Background

People with dementia (PwD) are at increased risk of adverse medical events (e.g. infections and falls). These often cause clinical deterioration, and potentially preventable admissions. Remote home monitoring of vital signs using internet‐of‐things technology can identify risk factors for these events – something particular pertinent during the COVID‐19 pandemic. We present data from an on‐going UK Dementia Research Institute and Technology Integrated Health Management (DRI‐TIHM) project. We aim to define algorithms that generate automated alerts, like the hospital‐based NEWS system (Morgan, 1997, Clin Intensive Car), and provide more proactive care for PwD.

Method

PwD recorded their systolic/diastolic blood pressure (SBP/DBP), heart rate (HR), temperature (BTM), bodyweight (BW) and oxygen saturation (Sats) daily (figure 1) and data were collected centrally. A ‘monitoring team’ followed algorithms in response to alerts and advised medical attention if required. Events such as infections, were logged and correlated with the data. The dataset was then used to calculate the number of alerts that would have been raised if different thresholds were used.

Result

52 PwD living at home were included. Patients had a range of dementia diagnoses, most commonly Alzheimer’s disease. In total, 89,894 measurements were collected over 556 days (figure 2). During the pandemic, a sub‐group were given Sats probes and these produced a significant number of false positive results (figure 4f). On sub‐group analysis, PwD with Parkinson’s disease dementia had significantly lower SBP and DBP (p=0.004 and p=0.01 respectively, Mann‐Whitney U) (figure 3a), one of whom suffered from repeated falls (figure 3b).

Pilot data were used to set alert thresholds. Average values and number of alerts for each domain are shown (table 1). We then modelled the effect of different thresholds, based on NEWS, to the number of alerts generated (figure 4, table 2). This is informative in optimising sensitivity and specificity of alerts whilst considering the burden on the monitoring service.

Conclusion

Remote monitoring can be implemented for PwD. These data can be used to generate clinical alerts that may signify adverse medical outcomes. The thresholds need to be adjusted to optimise efficiency in the context of varying reliability of home monitoring devices.
Apolipoprotein L1 is increased in frontotemporal lobar degeneration postmortem brain tissue but not in cerebrospinal fluid
Authors: Hok‐A‐Hin Yanaika S. , Dijkstra Anke A. , Rabano Alberto , Hoozemans Jeroen J. , Castillo Lucia , Pijnenburg Yolande A.L. , Teunissen Charlotte E. , Del Campo Marta
Published: February 2022

Background

Frontotemporal Dementia (FTD) is a spectrum of heterogeneous disorders caused by frontal‐temporal lobar degeneration (FTLD). FTLD is characterized by brain protein aggregates of tau (FTLD‐Tau) or TDP43 (FTLD‐TDP) mainly. However, the clinicopathological heterogeneity across the FTLD spectrum makes ante‐mortem diagnosis of these FTLD pathological subtypes extremely challenging. Our recent proteomic analysis revealed apolipoprotein L1 (APOL1), involved in lipid metabolism and transport, as a potential cerebrospinal fluid (CSF) biomarker for FTLD. However, the association of APOL1 with the subtype of FTLD pathology is not known. Here, we aimed to characterize APOL1 expression in FTLD post‐mortem brain tissue with Tau or TDP pathology and validate its potential as a novel CSF biomarker for FTLD pathological subtypes.

Method

APOL1 immunoreactivity was analyzed in paraffin‐embedded post‐mortem frontal cortex of 18 FTLD cases (FTLD‐Tau: 12 and FTLD‐TDP: 6) and 9 non‐demented controls. APOL1 levels were measured in post‐mortem frontal cortex (44 FTLD cases (FTLD‐Tau: 21 and FTLD‐TDP: 23) and 9 controls) and in ante‐mortem CSF (27 FTD patients (FTLD‐Tau: 12 and FTLD‐TDP: 15) and 15 controls) by western blot analysis and a validated in‐house APOL1 ELISA. APOL1 levels between groups were evaluated either by analysis of covariance (corrected for center) or Kruskal‐Wallis test.

Result

Higher APOL1 immunoreactivity associated with neuronal and glia cells was observed in the frontal cortices of FTLD cases compared to controls (p<0.001, figure 1A). However, no differences were observed between the FTLD‐Tau and FTLD‐TDP subtypes. Western blot and ELISA analyses showed that APOL1 levels were increased in lysates from FTLD frontal cortex compared to controls (WB: p<0.001, figure 1B and ELISA: p<0.05, figure 1C), but were similar between the FTLD pathological subtypes. In CSF, we observed no changes in APOL1 between FTD patients and controls, nor between FTLD pathological subtypes.

Conclusion

In this study, we were not able to validate APOL1 as a CSF biomarker for FTD using the current immunoassay. However, we do show a strong involvement of APOL1 in FTLD pathology irrespective of FTLD subtype. Future research should explore the specific role of APOL1 in the pathogenesis of FTLD.
Enhancing dementia care during the Corona pandemic: Zooming from home
Authors: Brown Nancy L , Tziraki Chariklia , Cedar Tzippi
Published: February 2022

Background

The Covid‐19 pandemic has created social isolation across all age groups. Literature reports that persons with dementia experience significant social isolation resulting in stress and anxiety for their caregivers as well. Interactive communication technologies like Zoom have been employed to reduce the impact of the pandemic. However, we find no reports using this technology with persons with dementia. Our study used the Zoom platform to maintain social connectivity with 16 day center clients who represent an immigrant community identified with mild to moderate cognitive impairment. We hypothesize that by using technology which allows facial recognition and communication and by focusing on the meaning of home, these persons and their carers expressed positive emotional feelings and remained engaged with their social world despite what was going on around them.

Method

Online psychodrama sessions were conducted for 7 weeks, 1 hour each week during the COVID‐19 lockdown. Carers were instructed on using the tablet and preparations needed for the Zoom session. The session was video recorded following the ethics guidelines of the day center MELABEV and manually transcribed. NVivo software was used in the qualitative analysis.

Result

Five main themes emerged from this analysis: Emotions, Home/Family, Social Connectivity, Reminiscence with Objects, and Carers Participation. Clients demonstrated significant social interaction without inhibition in their participation and displayed emotional expressions of what home means to them. In contrast to recent literature, neither clients nor their caregivers exhibited anxiety, stress, depression, or security issues despite their social isolation. Despite cognitive limitations, the clients were engaged, connected, interacted, and communicated with one another in very personal ways.

Conclusion

Results support the notion that technology like Zoom offers an option for preventing social isolation and mitigating the negative impact of supporting someone with dementia during this pandemic and other crises. From a societal perspective, particularly during COVID‐19, the importance of making available technology to persons with dementia and seeing them socially connect and engage through a medium not part of their generation has far‐reaching implications not only for future research but also for policy considerations, mitigating social isolation and caregiver burden among a vulnerable population.
Exercise and carbohydrate‐restricted diet associates with improved cerebral blood flow
Authors: Heston Margo B. , Gaitán Julian M. , Ma Yue , Oh Jennifer M. , Jen Mu‐lan , Derynda Brittany R , Lose Sarah , Kozuch Michael P. , Johnson Kevin M. , Okonkwo Ozioma C. , Gretebeck Kimberlee A. , Gretebeck Randall J. , Bendlin Barbara B.
Published: February 2022

Background

Insulin resistance (IR) is linked to decreased cerebral blood flow (CBF), an Alzheimer’s disease risk factor. Previous findings of the Blood Flow Improvement Trial (BFiT, clinicaltrials.gov NCT03117829) demonstrate that reversing midlife IR associated with improved cognition, but it is unknown whether this also improves CBF. BFiT tested an exercise and carbohydrate‐restricted diet (CRD) to determine whether improving IR resulted in higher CBF.

Method

Twenty‐nine pre‐diabetic, cognitively unimpaired participants from the Wisconsin Alzheimer’s Disease Research Center were recruited in four phases (ns = 9, 7, 5, 8) into a stepped wedge cluster randomized trial. Participants engaged in 12 weeks of supervised aerobic exercise three times weekly, unsupervised exercise twice weekly, and behavioral classes once weekly for program adherence. Post‐intervention, participants were instructed to maintain the regimen for six additional months. At baseline (T1), 12 weeks (T2), and six months post‐intervention (T3), arterial spin labeling (ASL) images were obtained. CBF was calculated globally and in frontal and temporal regions of interest.

Intervention effects on regional CBF were tested through pairwise comparison of the three visits using random intercept three‐level mixed models, with visits nested within participants, and participants nested within groups. Age and sex were adjusted as covariates for each region, and models were tested with and without influential outliers. Tukey‐Kramer adjustment was applied to control for the inflation of type I error rate associated with multiple comparison.

Result

Of the 29 participants (Table 1) enrolled in the study, 23 completed the intervention, and 21 completed all measurements. Between T1 and T3, CBF showed significant bilateral increases in the middle temporal gyri and temporal poles (superior and middle areas), middle frontal gyri (orbital), superior frontal gyri (medial orbital), and precentral gyri (Figures 1, 2). No regions showed significant CBF increases (p<.05) between T1 and T2, or T2 and T3.

Conclusion

In a cognitively unimpaired cohort, an exercise and carbohydrate‐restricting intervention significantly improved CBF over the trial duration. This suggests that sustaining a CRD and exercise may improve CBF in people with impaired glucose regulation. Ongoing analysis of trial data will assess whether improved cerebral blood flow and cardiorespiratory fitness mediate observed enhancements in cognitive performance.
Early bio‐maker detection through novel data equilibration methods
Authors: Pal Prasanta , Brewer Judson A
Published: February 2022

Background

A novel adaptive universal set of algorithms are developed to map and differentiate normal and alzheimer patient MRI images into orthogonal complementary image spaces. This adaptive method greatly enhances the visual clarity of both (normal and alzheimer) images while providing with additional metric space of outlier image for further differentiation of features in the data sets. This enables us with extra handle to compare baseline and alzheimer MRI images with unprecedented clarity and robustness

Method

To observe multi‐scale features and its differences between baseline and disease condition MRI data sets (publicly available), we introduce a set of length scale kernels coupled with threshold parameters to transform the original image space to parametrically controlled equilibrium and out of equilibrium (or outlier) data sets. This forms the foundation of the new method of comparison through a novel method of outlier based orthogonal decomposition of image information space.

Result

While our new comparison method confirms the findings of published results, it adds additional layers of visual clarity for further discovery of the novel never before seen features. For the first time in the literature, we introduce the concept of equilibrium (and nonequilibrium) states from raw data acquired through sensors and demonstrate the efficacy of it in the context of early detection of AD biomarkers.

Conclusion

While historical methods of image difference works well for detecting crude biomarkers, there is a potential for a information loss and low contrast resolution. Our method overcomes those limitations by appropriately re‐mapping the raw data to equilibrium and nonequilibrium states. This makes the comparison between baseline and AD images much visually clear in those respective metric spaces.
Neuroanatomical mapping of artificial intelligence‐based classification of language in PPA
Authors: Rezaii Neguine , Carvalho Nicole , Brickhouse Michael , Loyer Emmaleigh , Wolff Phillip , Touroutoglou Alexandra , Wong Bonnie , Quimby Megan , Dickerson Brad C.
Published: February 2022

Background

Patients with Primary Progressive Aphasia (PPA) are usually subtyped into one of the three canonical subtypes (nfvPPA, svPPA, lvPPA) based on a neurological and cognitive assessment including their language characteristics typically measured from a battery of confrontational tests. While widely used, this classification system has been criticized, and also the approach makes assumptions about the features of language that are important to measure. Here we use methods from Artificial Intelligence to measure features of speech from naturalistic connected speech samples with the goal of determining how well this data‐driven approach matches independent clinical subtypes and how its results relate to neuroanatomical abnormalities measured from MRI.

Method

Language data was obtained from 78 PPA patients (28 nfvPPA, 26 lvPPA, 24 svPPA) describing the WAB Picnic Scene. A transformer model, RoBERTa, was used to measure similarities in language features, IVIS to perform dimensionality reduction, and nested k‐means to cluster language samples. We then examined the cortical atrophy patterns of these clusters of PPA patients versus healthy controls (N=25).

Result

Seven PPA clusters were identified with 88% agreement with the classic classification system. Individuals in Clusters 1 and 2 (mainly nfvPPA) exhibited speech dysfluency and reduced clausal complexity with atrophy in the left pars opercularis, superior and caudal middle frontal gyri. Those in Clusters 3 and 4 (predominantly lvPPA) exhibited difficulties in subject‐verb agreement, demonstratives and tense and shared atrophy in the superior and middle temporal and inferior parietal gyri. Individuals in Clusters 5‐7 (mainly svPPA) exhibited deficits in nouns/verbs access with atrophy in the left temporal pole and inferior and middle temporal gyri.

Conclusion

Data‐driven Artificial Intelligence methods applied to naturalistic speech samples from PPA patients identify clusters of patients that match well to clinical subtypes, and that exhibit cortical atrophy patterns typical of those subtypes. This suggests that PPA subtypes are natural kinds and that computational analysis of simple speech samples can be used to identify them.
Supervised machine learning method tailored for five brain MRI events is predictive of cognitive status
Authors: Thakar Darshit , Patel Raj , Ravindranath Vijayalakshmi , Tiwari Vivek
Published: February 2022

Background

Despite the large neuroanatomic measurements obtained from brain MRI segmentation, we do not have yet a definitive neuroanatomic or vascular feature/even that can precisely delineate a cognitively normal subject from cognitively impaired and Alzheimer’s disease (AD). Increasing lifespan of population accompanied with increased prevalence of cardiovascular risks across globe demands for precise early detection of AD and cognitive status (impaired or normal) in the aging individuals. Here, we have employed machine learning (ML) method on neuroanatomic volume and white matter hyperintensity (WMH) volume obtained from MRI analyses of data from National Alzheimer’s Coordinating Center (NACC) to identify participants as cognitively normal (CN), cognitively impaired with etiological diagnosis as AD and cognitively impaired (CI) subjects.

Method

Brain segmentation outputs for neuroanatomic‐volume and White matter hyperintensity (WMH) was obtained from NACC for 1290 unique subjects with total of 3684 longitudinal‐MRI. Supervised ML was performed using the MRI parameters for identifying the subjects as AD, CI, and CN. 50% of the MRI were used as training set while another 50% was used as test. Various combinations of neuroanatomic volume with WMH quantity were tested for accuracy of delineating the AD, CI and CN groups using random forest method. Furthermore, various ML methods such as XGB classifiers, classification tree, bagging classifier and simple classification were tested for accuracy using the optimized neuroanatomic volume and WMH.

Result

Random forest method converged with a combination of 5‐MRI features, intracranial, gray‐matter, cerebral CSF, hippocampus, and White‐matter hyperintensity volume with highest accuracy (83.3%) in identifying AD, CI, and CN subjects (Fig. 1). Inclusion of normal appearing white‐matter volume during the ML optimization of MRI features led to significant reduction in the accuracy. Simple random forest ML method showed highest accuracy using the optimized MRI features (Fig. 2).

Conclusion

All the neuroanatomic events obtained from brain MRI may not be specific in providing diagnostic features for evaluating brain health. Here we show that a combination of 5 MRI features that includes microvascular pathology and neuroanatomic volume may provide a specific and efficient non‐invasive imaging biomarker to evaluate brain health in aging population.
Regional amyloid accumulation predicts memory decline in initially cognitively unimpaired individuals
Authors: Collij Lyduine E. , Mastenbroek Sophie E , Salvadó Gemma , Wink Alle Meije , Visser Pieter Jelle , Barkhof Frederik , Van Berckel Bart N.M. , Alves Isadora Lopes
Published: February 2022

Background

The current shift towards (early) secondary intervention AD trial designs warrants the need for detection of subtle changes of both amyloid‐β (Aβ) burden and cognitive functioning. This study investigated the longitudinal trajectory of global and regional Aβ measurements and their value in predicting cognition in initially cognitively unimpaired (CU) subjects.

Method

We included 133 CU subjects with available longitudinal cognition (MMSE: 2‐13 assessments, 7.9±2.5 years; neuropsychological memory tasks: 2‐5 assessments, 4.0±1.9 years) and [11C]PiB PET imaging (2‐5 scans, 4.4±1.9 years) from the OASIS‐3 cohort. Baseline and annualized Aβ measures (DVR) were computed for a global composite and 4 clusters of regions, reflecting different stages of the amyloid accumulation process. Linear mixed effect models were used to examine the predictive value of Aβ measurements (i.e. Aβbaseline, Aβslope, and Aβbaseline*slope) on global cognition (MMSE) and several aspects of memory performance. All analyses were controlled for age, sex, years of education, and time between baseline PET and first cognitive assessment.

Result

Global baseline amyloid burden and slope were non‐linearly related (). This was also apparent in stages 1, 2, and 3 clusters, but less in stage 4 (). MMSE performance over time could only be predicted by Aβ burden and accumulation in cluster 2 (precuneus, lateral orbitofrontal (LOFC), and insula; β
baseline=‐0.37, p<.001; β
interaction=14.16, p<.05). Focusing on the precuneus ROI by itself significantly improved the model (βbaseline
=‐0.29, p<.001; βslope
=‐9.71, p<.05; βinteraction
=8.71, p<.01), where fast‐decliners were those at the plateau phase of accumulation (). Similarly, precuneal slope and the interaction term were both predictive of changes in immediate (βslope
=‐60.95, p<.05; βinteraction
=53.39, p<.05) and delayed episodic memory (βslope
=‐65.45, p<.05; βinteraction
=53.14, p<.05). In the Aβ‐ at baseline group (N=93), LOFC slope and the interaction term predicted changes in working (βslope
=‐172.0, p<.05; βinteraction
=‐147.2, p<.05) and semantic memory performance (βslope
=‐439,4, p<.01; βinteraction
=393.1, p<.01).

Conclusion

Quantifying longitudinal and regional changes in Aβ can improve the prediction of future cognitive functioning in initially CU individuals. For individuals with established amyloid pathology, longitudinal Aβ measures help to identify those subjects most likely to show cognitive decline within the short timelines of clinical trials.
Data‐driven evidence for three distinct patterns of amyloid‐β accumulation
Authors: Collij Lyduine E. , Salvadó Gemma , Wottschel Viktor , Schoenmakers Pierre , Mutti Martina , Aksman Leon M , Wink Alle Meije , van der Flier Wiesje M , Scheltens Philip , Visser Pieter Jelle , Van Berckel Bart N.M. , Barkhof Frederik , Haller Sven , Gispert Juan Domingo , Alves Isadora Lopes
Published: February 2022

Background

Amyloid burden staging models assume a single spatial‐temporal progression of amyloid accumulation across subjects, while disease heterogeneity suggests there might be subtypes with distinct trajectories. Here, we apply a data‐driven model which simultaneously resolves subtypes and stages (SuStaIn)1 to amyloid PET data to assess evidence for Aβ accumulation subtypes.

Method

Amyloid PET data of 3010 subjects () were pooled from ALFA+, EMIF‐AD, ABIDE, OASIS, and ADNI. SUVr was extracted for 17 regions. Next, GMM was applied to regional SUVr of cognitively unimpaired subjects per cohort, per tracer, to derive z‐scores. Then, we applied SuStaIn to baseline data to determine the optimal number of subtypes and the most probable subtype/stage per scan. Subtypes and stages were related to the proportion of APOE‐ε4 carriers and diagnostic groups, mean age, and Centiloid. The final model was also applied to longitudinal scans (>4 years after baseline) from ADNI and OASIS (N=519) for validation, where we assessed subtype stability and stage progression.

Result

SuStaIn identified three subtypes, referred to as Frontal, Parietal and Occipital based on the first regions to show abnormality (). This 3‐subtype model was preferred to a traditional one‐trajectory model () based on the Cross‐Validation Information Criteria. Most subjects displayed no amyloid (stage 0: N=1810, 60.1%) or abnormal amyloid levels across all regions (stage 17: N=282, 9.4%), challenging subtyping. Of the N=835 (27.7%) with strong subtype assignment (>50% probability), the majority was assigned to Frontal (55.0%), followed by Parietal (24.1%), and Occipital subtypes (21.0%). Statistically significant differences included lower age for the Parietal subtype (Frontal:71.9±8.3; Parietal:69.3±9.6; Occipital:72.1±8.1), and distinct proportions of APOE‐ε4 carriership (Frontal:61.8%, Parietal:57.1%, Occipital:49.4%) and subjects with dementia across subtypes (Frontal:19.7%, Parietal:19.1%, Occipital:31.0%). Older age, APOE‐ε4 carriership, and Centiloid burden were positively associated with stage independent of subtype. At follow‐up, most subjects (77.9%) maintained baseline subtype assignment, and 65.3% progressed to a later stage within their subtype.

Conclusion

While a one‐trajectory model recovers the established pattern of amyloid accumulation, SuStaIn identified three subtypes with distinct associations to AD risk factors. These initial results suggest subtype classification may have clinical relevance and/or improve risk assessment compared to previous staging models.
Differential gray matter connectivity correlates of CSF biomarkers: Results from the EPAD Cohort
Authors: Lorenzini Luigi , Ingala Silvia , Wottschel Viktor , Wink Alle Meije , Mutsaerts Henk‐Jan , Haller Sven , Blennow Kaj , Frisoni Giovanni B. , Chetelat Gaël , Payoux Pierre , Martinez‐Lage Pablo , Waldman Adam , Wardlaw Joanna M. , Ritchie Craig W. , Gispert Juan Domingo , Visser Pieter Jelle , Scheltens Philip , Tijms Betty M. , Barkhof Frederik
Published: February 2022

Background

Gray matter network (GMN) disruptions correlate with amyloid burden in the earliest stages of Alzheimer’s Disease (AD) pathology in cognitively unimpaired individuals. However, it remains unknown if and how hyperphosphorylated tau (p‐tau) influences GMNs. Here, we investigated the relation between GMNs and cerebrospinal fluid (CSF) p‐tau181 levels in non‐demented individuals from the European Prevention of Alzheimer Dementia (EPAD) cohort and evaluated whether this relationship is mediated by amyloid and Clinical Dementia Rating (CDR) status.

Method

We included 1198 participants from the EPAD v1500.0 release, who had both CSF biomarkers and structural MRI available. The cut‐off for amyloid‐β positivity (A+) was defined at <1000 pg/mL. Single‐subject network properties were extracted from 3D‐T1w MRI (Figure 1). Regional values were computed for 117 AAL atlas regions. Linear models were used to investigate main effects and interactions between amyloid status and p‐tau181 levels on global GMN measures. A three‐way interaction with CDR was modeled. Age, sex, site, total intracranial volume, and network size were included as covariates. Analyses were repeated for local network properties across AAL regions and FDR‐adjusted.

Result

Sample characteristics are provided in Table 1. A+ individuals had lower degree, clustering, gamma, and small world coefficients, and higher betweenness centrality (Figure 2). Higher p‐tau181 levels were associated with lower values of degree, betweenness centrality, lambda, and path length (Figure 3). Lambda, path length, and clustering showed an interaction effect of amyloid status and CDR on their relationship with p‐tau181 levels: A‐ individuals with CDR 0 had lower path length and lambda in association with tau, while A+ CDR 0.5 individuals with lower clustering coefficient values showed higher p‐tau181 (Figure 4). No associations were found for other GMN measures. Regional analysis showed a relationship of p‐tau181 with local path length in the precuneus (Figure 5).

Conclusion

GMN alterations show distinct associations with p‐tau181 levels, partially affected by amyloid and CDR status. Non‐amyloid related alterations of path length might be linked to axonal tau‐related changes. Clustering alterations seem instead to be linked to amyloid deposition and resulting local synaptic disconnectivity.
Clinical evaluation of SPARE‐TauAD, an AV‐1451‐derived tau index
Authors: Toledo Jon B. , Liu Hangfan , Rashid Tanweer , Habes Mohamad
Published: February 2022

Background

The deposition of abnormal proteins defines neurodegenerative diseases. Among these proteins, tau deposits define frontotemporal lobar degeneration (FTLD) tau, and together with Aβ, it defines the more prevalent Alzheimer’s disease (AD). PET scans with ligands binding AD tau neurofibrillary tangles (NFT) topographically quantify the amount of pathology. However, for clinical purposes, this information needs to be summarized into easily applicable and meaningful indices. Here we develop a machine learning‐derived tau PET index, the Spatial Pattern of Abnormality for Recognition of Tau in AD (SPARE‐TauAD).

Method

603 subjects were included in the study. Their clinical diagnoses were: 366 cognitively normal (CN), 177 mild cognitive impairment (MCI), and 60 dementia subjects. These subjects were classified as Aβ positive and negative based on CSF Aβ1‐42 levels or florbetapir PET summary composite. SPARE‐TauAD was derived using a support vector machine classifier comparing AV‐1451 PET scans in 141 Aβ negative CN subjects against 108 Aβ positive MCI and dementia subjects. We then evaluated its association with CSF t‐tau, global cognition (measured using ADAS‐Cog 13), clinical diagnosis, and clinical progression.

Result

SPARE‐TauAD and CSF t‐tau showed a moderate correlation (rho=0.51, p<0.0001). SPARE‐TauAD explained a larger variance of ADAS‐Cog13 scores (R2=0.60) compared to CSF t‐tau (R2=0.21) and the florbetapir PET summary composite (R2=0.23). Using 5‐fold cross‐validation in an independent sample of Aβ negative CN subjects (n=77) against Aβ positive MCI and dementia subjects (n=35 for CSF), SPARE‐TauAD showed higher balanced accuracy (79.6%) compared to CSF t‐tau (61.6%). SPARE‐TauAD was also associated with faster progression from CN to MCI/dementia (H.R.=6.83, p‐value<0.0001) and MCI to dementia (H.R.=3.43, p‐value<0.0001). Whereas CSF t‐tau was no associated with clinical progression.

Conclusion

SPARE‐TauAD showed, as expected, a moderate association with CSF t‐tau. However, it offered better cross‐sectional classification accuracy and correlation with cognitive scores. It also outperformed CSF t‐tau to predict longitudinal progression in this small with limited longitudinal follow‐up. One limitation is that the SPARE‐TauAD index has been developed in an AD MCI and dementia cohort. The used tau ligand, AV‐1451, has a greater affinity for NFT present in AD than tau pathology present in FTLD‐tau.
Microglial activation and atrophy in frontal cortex predict executive dysfunction in frontotemporal dementia
Authors: Malpetti Maura , Jones P. Simon , Hezemans Frank H. , Mak Elijah , Street Duncan , Passamonti Luca , Rittman Timothy , Cope Thomas E. , Bevan‐Jones W. Richard , Patterson Karalyn , Fryer Tim D. , Hong Young T. , Aigbirho Franklin I. , O'Brien John T. , Rowe James B.
Published: February 2022

Background

Frontotemporal dementia is clinically and neuropathologically heterogeneous, but atrophy, neuroinflammation, and executive dysfunction occur in each of the principal variants. Across the clinical spectrum of frontotemporal dementia, we assessed the predictive value of in vivo neuroimaging measures of grey‐matter volume (from structural MRI) and microglial activation (from [11C]PK11195 PET) on the rate of future executive decline. We hypothesised a detrimental effect of inflammation and atrophy severity on executive dysfunction progression.

Method

Thirty patients with frontotemporal dementia underwent a baseline multi‐modal imaging assessment, including [11C]PK11195 PET to index microglial activation and structural MRI for atrophy, as part of the Neuroimaging of Inflammation in Memory and Related Other Disorders (NIMROD) study. Cognitive impairments were assessed at baseline and serially for up to 5 years with the revised Addenbrooke's Cognitive Examination (ACE‐R). Regional grey‐matter volumes and [11C]PK11195 binding potentials were averaged in four regions of interest: left and right frontal and temporal lobes. Linear mixed models were applied to the longitudinal ACE‐R attention/executive sub‐score. Regional CSF‐corrected PET values and TIV‐corrected grey‐matter volumes were included in linear mixed models as predictors, with age and education as covariates. Specifically, negative associations of atrophy and inflammation with annual rate of executive decline were tested.

Result

Patients showed a mean 3.3‐point loss per year on the ACE‐R attention/executive sub‐score (p<0.001, Figure 1). Faster decline in ACE‐R was associated with reduced baseline grey‐matter volume of the left frontal lobe (beta=1.000, SE=0.285, p=0.000789, p‐FDR= 0.00316; Figure 2) and increased inflammation in frontal regions bilaterally (Left: beta=‐0.722, SE=0.251, p=0.00528, p‐FDR=0.0105, Figure 2; Right: Estimate=‐0.623, SE=0.256, p=0.0175, p‐FDR=0.0233). These associations remain significant when including both left frontal grey‐matter volume and [11C]PK11195 binding as predictors in the same model, and after controlling for baseline attention/executive scores. In these regions, grey‐matter volumes and inflammation levels were negatively correlated (left: r=‐0.414, p<0.001; right: r=‐0.374, p<0.001).

Conclusion

Imaging markers for atrophy and microglial activation provide useful and independent information to evaluate and stratify patients with frontotemporal dementia. This may improve cohort selection in clinical trials and highlights the potential for immunomodulatory treatment strategies in frontotemporal dementia.
[18F]RO948 tau PET in bvFTD due to C9orf72 and GRN mutations
Authors: Leuzy Antoine , Santillo Alexander , Smith Ruben , Groot Colin , Ossenkoppele Rik , Hansson Oskar
Published: February 2022

Background

The behavioral variant of frontotemporal dementia (bvFTD) is characterized by marked changes in personality and behaviour. Approximately 30% of cases are genetic in nature and most commonly due to autosomal dominant mutations in the chromosome 9 open reading frame 72 (C9orf72) and progranulin (GRN) genes resulting in TAR DNA‐binding protein 43 (TDP‐43) pathology. Several tau positron emission tomography (PET) studies using [18F]flortaucipir have shown conflicting results regarding tracer retention in bvFTD due to C9orf72 (bvFTD‐C9orf72) and GRN (bvFTD‐GRN) mutations. To date, no studies in bvFTD due to either mutation have been conducted using the novel tau tracer [18F]RO948.

Method

Eight patients meeting criteria for definite bvFTD were included from the Swedish BioFINDER‐2 study, including seven C9orf72 expansion carriers and one with a GRN mutation. Standardized uptake value ratio (SUVR) images of [18F]RO948 PET were created using 70‐90 post‐injection data and the inferior cerebellar cortex as reference region. Age and sex matched CU individuals (n=9) and patients with Alzheimer’s disease (AD) dementia (n=9) were included for comparison. [18F]RO948 retention in bvFTD mutation carriers was also assessed relative to a larger Aβ‐negative CU group (n=50) using age‐adjusted voxelwise t‐tests.

Result

BvFTD‐C9orf72 patients were on average 63 years of age (range 53‐72) and 57% were female. The bvFTD‐GRN patient was a 69‐year‐old male. Comparison of SUVR images showed that [18F]RO948 retention levels in bvFTD mutation carriers were similar to those seen in Aβ‐negative CU individuals (Figure 1). Voxelwise t‐tests showed no significant differences in comparison to the Aβ‐negative CU group. Similar findings were seen using a composite frontal region of interest (ROI) and when using the brainstem as reference instead of the inferior cerebellar cortex.

Conclusion

These preliminary findings suggest that [18F]RO948 signal is specific for AD‐type tau and does not capture TDP‐43 type pathology.
White matter hyperintensities and regional tau‐PET signal independently contribute to cognitive deficits in symptomatic patients on the Alzheimer’s disease continuum
Authors: Edwards Lauren , Iaccarino Leonardo , Tanner Jeremy A , Cobigo Yann , Pham Julie Q. , Rosen Howard J. , Soleimani‐Meigooni David N. , Strom Amelia , Wolf Amy , Kramer Joel H , Miller Bruce L. , Rabinovici Gil D. , La Joie Renaud
Published: February 2022

Background

We examined the associations of white matter hyperintensities (WMH), amyloid‐PET, and tau‐PET with multi‐domain cognitive performance in symptomatic patients on the Alzheimer’s disease (AD) continuum.

Method

119 amyloid‐PET‐positive patients diagnosed with MCI or AD dementia underwent 3‐Tesla structural MRI, 18F‐flortaucipir (tau)‐PET,11C‐PIB (amyloid)‐PET, and neuropsychological assessment. Standardized uptake value ratio (SUVR) flortaucipir‐ and PIB‐PET images were created using tracer‐specific reference regions and warped to template space. Patients were split based on availability of FLAIR‐MRI (Figure 1). The exploratory sample (n=50; no FLAIR) was used to run voxelwise models to identify regions where flortaucipir‐ and PIB‐PET were associated with episodic memory, executive, language, semantic memory, and visuospatial composite scores. In the validation sample (n=69), WMH were segmented from FLAIR and T1‐MRIs using a two‐step supervised algorithm. Linear regression models assessed the independent contributions of global WMH volume (corrected for intracranial volume and log‐transformed) and cognitive domain‐specific regional PET‐SUVR (derived in the exploratory sample) to each cognitive domain.

Result

The two samples had comparable demographics and clinical characteristics, with relatively young age (mean ∼65.5) and moderate impairment (mean MMSE ∼ 22, Table 1). In the exploratory sample, cognitive scores were associated with regional flortaucipir‐SUVR patterns (Figure 2); PIB‐SUVR was not robustly associated with cognition. In the validation sample, global WMH volume was inversely correlated with global PIB‐SUVR (r=‐.25, p=.04) but not global cortical flortaucipir‐SUVR (r=‐.18, p=.15). Older age predicted lower cortical flortaucipir‐SUVR (r=‐.70, p<.001) and greater WMH volume (r=.46, p<.001). Female sex was specifically associated with greater cortical flortaucipir‐SUVR (d=0.64, p=.01; psdsps

Conclusion

In patients at the early clinical stages of AD, tau‐PET and global WMH volume were not associated with each other, but independently contributed to cognitive impairment. These findings emphasize the clinical relevance of cerebrovascular injury in the context of AD pathology, even in younger patients.