bluuebunny/crossref_metadata_2025 huggingface dataset:
Plasma extracellular vesicle biomarkers for cognitive impairment in Parkinson’s disease
Authors: Blommer Joseph M. , Pitcher Toni , Mustapic Maja , Meissner Wassilios , Anderson Tim , Kapogiannis Dimitrios
Published: February 2022

Background

Parkinson’s Disease (PD) pathogenesis involves intraneuronal a‐synuclein accumulation, but also insulin resistance, characterized by decreased Tyr and increased Ser insulin receptor substrate‐1 (IRS‐1) phosphorylations. Besides motor symptoms, some PD patients develop mild cognitive impairment (PD‐MCI) or dementia (PD‐D), partly due to overlapping Alzheimer’s disease (AD) pathology. For PD prognosis, there is a need for biomarkers distinguishing PD with normal cognition (PD‐N) from PD‐MCI/D. Neuronal‐origin extracellular vesicles (NEVs) contain signaling and pathogenic proteins that may serve as biomarkers.

Method

From 104 PD‐N, 83 PD‐MCI, 39 PD‐D patients and 48 age/sex‐matched Controls, we immunocaptured plasma NEVs using anti‐L1CAM antibody. We measured biomarkers by immunoassays for: 1) PD and AD pathogenic proteins (a‐synuclein, Aβ42, total tau and p181‐tau) 2) insulin signaling mediators (pTyr20 and pSer312 IRS‐1). Particle concentration was measured by Nanoparticle Tracking Analysis and immunoblots were used to characterize NEV preparations.

Result

a‐synuclein was lower in PD compared to Controls (p = 0.005) and stepwise lower in PD‐MCI (p = 0.007) and PD‐D (p < 0.001) compared to PD‐N; it tended to decrease with increasing motor symptom severity by MDS‐UPDRS III (p = 0.06). Aβ42 trended towards being higher in PD‐MCI compared to PD‐N (p = 0.06). pTau181 was higher in PD patients compared to Controls (p = 0.003) and in PD‐MCI compared to PD‐N (p = 0.02). Total Tau was not different between groups. pTyr20‐IRS‐1 was lower in PD compared to Controls (p = 0.03) and in PD‐MCI compared to PD‐N (p = 0.01) and decreased with increasing motor symptom severity by MDS‐UPDRS III (p = 0.008). The ratio pSer312/pTyr20 IRS‐1 (indicating insulin resistance) was higher in PD patients compared to Controls (p = 0.02) and in PD‐MCI and PD‐D compared to PD‐N (p = 0.01).

Conclusion

PD patients with cognitive impairment exhibited lower NEV levels of a‐synuclein and pTyr20‐IRS‐1 and higher levels of pTau181 than cognitively intact PD patients. Additionally, a‐synuclein and IRS‐1pTyr20 were associated with PD motor symptom severity. Plasma NEVs offer novel biomarkers for PD and indicate Alzheimer's pathology and insulin resistance partially underly cognitive impairment in the disease.
Sparse canonical correlation analysis reveals relationships between TDP‐43 within the entorhinal cortex and fractional anisotropy across widespread white matter tracts
Authors: Heywood Ashley , Schneider Julie A. , Bennett David A. , Arfanakis Konstantinos , Beg Mirza Faisal , Wang Lei
Published: February 2022

Background

While research has focused on gray matter alterations in neurodegeneration, investigating the relationship between white matter and neuropathology allows for additional insight into disease effects on broad brain networks. TAR DNA‐binding protein 43 (TDP‐43), which has shown to be involved in various neurodegenerative disorders involving axonal damage including ALS, FTLD, and LATE, is associated with lower WM integrity. We used sparse canonical correlation analysis (SCCA) to explore the relationships between ante‐mortem WM integrity and post‐mortem TDP‐43.

Method

Diffusion weighted images were gathered on a 1.5T scanner and processed using TORTOISE in order to calculate fractional anisotropy (FA) in a sample of 70 older adults from two longitudinal cohort studies, the Religious Orders Study and Rush Memory and Aging Project. We registered the white matter ROIs from the John’s Hopkins University (JHU) DTI atlas to the study‐specific template using ANTS. Average FA was computed for each ROI and was included in the SCCA. A semi‐quantitative rating of TDP‐43 severity was assessed in 5 regions. Disease burden in each region and average FA within 48 ROIs were inputs for the SCCA. A fused lasso penalty based on permutation testing was employed to promote sparsity.

Result

The 70 subjects were 91.10 (SD=6.08) years old at death with a median interval from MRI to death of 3.11 years (SD=1.45). Sixty‐four percent were female, and 36% had dementia at their last study visit prior to death. TDP pathology was present in 47% of individuals. SCCA produced one canonical variable (Cor=0.36) which identified one regional pathology variable (TDP‐43 within the entorhinal cortex; Feature weight =‐1.0) and six FA ROIs: pontine crossing tract (0.597), splenium of corpus callosum (0.531), right anterior limb of internal capsule (0.001), superior corona radiata (0.411), and bilateral anterior corona radiata (Right: 0.115 and Left: 0.422).

Conclusion

Identified WM ROIs within the brainstem align with previous research within TDP‐43 related disorders, including those with motor neuron involvement such as FTLD‐U. Further, findings within bundles connecting parietal and temporal areas indicate the importance of TDP‐43 in broad brain networks which could relate to the deficits seen in memory and executive functions within FTLD and related disorders.
Unmet needs and health‐related quality of life for Alzheimer’s disease and related dementia caregivers during transition to long‐term care placement: A scoping review
Authors: Lee Kyungmi , Pickering Carolyn E
Published: February 2022

Background

Long‐term care placement is a transition in the caregiving trajectory that may have a crucial health‐related quality of life implications for many Alzheimer’s diseases and related dementia family caregivers. The lack of knowledge related to family caregivers’ needs and their health‐related quality of life outcomes surrounding long‐term care placement represents a gap in the field as it limits our ability to support caregiving families with appropriate interventions effectively. The objective of this study is to identify experiences, unmet needs, and health‐related quality of life for caregivers of persons with Alzheimer’s disease and related dementia as the process of transitioning into long‐term care placement.

Method

Scoping review of published literature. Electronic searches of PubMed, PsycINFO, Scopus, and CINAHL databases were conducted using keywords related to Alzheimer’s disease or related dementia, family caregiver, unmet needs, and health‐related quality of life. The literature search was performed in July 2020, with no specified date limits. The Arksey and O’Malley methodological framework guided the review. Studies were screened independently for inclusion by two persons.

Result

19 studies were organized around three major categories. First, caregiver experiences of pre and post long‐term care placement (n = 18, 95%): contexts of long‐term care placement (n = 10, 53%), distress and emotional responses (n = 9, 47%), and changes in relationships and responsibilities (n = 9, 47%). Second, caregivers’ unmet needs of surrounding long‐term care placement (n = 7, 37%): emotional concerns and support (n = 4, 21%) and knowledge, and information (n = 5, 26%). Third, caregivers’ health‐related quality of life during transitioning long‐term care placement (n=6, 32%): assistance from professional care (n=2, 11%), and physical and mental health (n=5, 26%).

Conclusion

Family caregivers are exposed to risk for adverse health outcomes even after the long‐term care placement of their care‐recipients. Family caregivers considering long‐term care placement need to be informed of what may change following long‐term care placement. We can suggest based on these findings that interventions may be to support caregivers during this transition with teaching skills, care planning, helping with conflict resolution, training in the use of communication strategies, and organizing services.
Development and evaluation of high‐resolution gray matter labels for the MIITRA atlas
Authors: Niaz Mohammad Rakeen , Wu Yingjuan , Ridwan Abdur Raquib , Qi Xiaoxiao , Bennett David A. , Arfanakis Konstantinos
Published: February 2022

Background

High resolution gray matter labels were constructed for the Multichannel Illinois Institute of Technology & Rush university Aging (MIITRA) atlas based on manually edited gray matter labels of the older adults included in the atlas. The performance of the new labels in labeling the gray matter of a separate group of older adults was evaluated.

Method

T1w images (400 images, 1mm isotropic) from the older adults included in the MIITRA atlas (50% male; 64.9‐98.9 age‐range; 54% white, 43% black) were processed with Freesurfer’s standard recon‐all pipeline, which segmented subcortical and cortical gray matter into 84 regions according to the Desikan Killiany atlas. The Freesurfer output for all images was manually edited. The ANTs‐derived transformations applied on individual T1w images to build the MIITRA T1w template were used to map the corresponding gray matter labels from raw space to exact physical locations in the final MIITRA space. The label in a 0.5mm isotropic voxel in MIITRA space was calculated using majority voting among all the labels that were mapped to that voxel. The performance of the MIITRA gray matter labels in segmentation of the gray matter of a separate group of 100 older adult individuals was evaluated in terms of label overlap, geometry, and dissimilarity when comparing the MIITRA labels warped to each individual’s space, to the respective manually edited reference labels.

Result

Examples of the MIITRA gray matter labels and corresponding confidence maps are shown in Figure 1. The measures of overlap were generally high, with an average Dice coefficient of 0.82±0.10, Jaccard coefficient of 0.70±0.13 (Fig. 2), sensitivity of 0.77±0.13, and specificity of 0.89±0.09 (Fig. 3). There was a high correlation in label geometry both in terms of the average volume (correlation coefficient=0.997, p‐value<10‐10) and in terms of the average surface area (correlation coefficient=0.988, p‐value<10‐10) (Fig. 4). The values of dissimilarity were low, with an average volume error of 0.18±0.18 and an average Hausdorff distance of 8.69±8.78 (Fig. 5).

Conclusion

The MIITRA gray matter labels, in combination with the high‐resolution T1w template of the atlas, allow segmentation of the gray matter of older adults that is in good agreement with the manually‐edited Freesurfer‐based segmentation.
Amyloid pathology, small‐vessel disease, atrophy, and cognition in normal adults with type 2 diabetes
Authors: Lesman‐Segev Orit H. , Golan Sapir , Ravona‐Springer Ramit , Livny Abigail , Lin Hung‐Mo , Ouyang Yuxia , Zadok Maya , Hoffmann Chen , Domachevsky Liran , Beeri Michal Schnaider
Published: February 2022

Background

Various factors contribute to cognitive decline in older adults with type 2 diabetes (T2D). We assessed the association between imaging metrics of brain pathology (including global atrophy, small vessel disease, and amyloid deposition) with cognitive functioning in older adults with T2D.

Method

Community‐dwelling, cognitively normal, older adults with T2D from the Israel Diabetes and Cognitive Decline Study with brain MRI and/or F18‐Flutemetamol amyloid‐PET were included. Gray matter (GM) and white matter hyperintensities (WMH) volume were extracted from high‐resolution T1‐weighted and fluid‐attenuated inversion recovery (FLAIR), respectively, using Statistical Parametric Mapping (SPM8). Amyloid PET was visually read and quantified using standardized uptake value ratio (SUVR) with the cerebellar gray and white matter as reference region. Global mean and lobar SUVR were extracted. Global cognitive functioning was assessed by neuropsychological testing and summarized into four domains including executive functions, attention, memory, and language, and an average of the four domains comprised global cognition. Linear regression models were used in a stepwise manner controlling for age, sex, education, HbA1c, and duration of T2D. MRI measures were also adjusted for intracranial volume.

Result

236 participants, 232 with MRI and 52 with amyloid‐PET were included, mean age 75 [66‐89], 39% females, 11 (21.1%) amyloid positive (Table 1). On average, participants had good glycemic control (mean HbA1C=6.7). An increase in global SUVR was associated with lower global cognition (Estimate=‐1.23, p=0.02). Additional adjustment for GM volume did not alter the results (Table 2). These results were driven by associations of SUVR with executive functioning (‐1.32, p=0.01), though a trend toward the same direction was also seen with attention (‐0.95, p=0.09), language (‐0.86, p=0.13), and memory (‐0.85, p=0.14) (Figure 1). Amyloid in all lobes contributed significantly to the associations (Table 2). No association was found between WMH volume and any of the cognitive outcomes (p‐values>0.21).

Conclusion

In our cohort of normal cognitive older adults with well controlled T2D, amyloid load but not small vessel disease nor glycemic control was associated with cognitive functioning. This association was not mediated by GM volume suggesting other neurobiological substrates underlying the effect of amyloid on cognition in this population.
Identifying multimodal imaging‐driven subtypes in mild cognitive impairment using deep multiview learning
Authors: Feng Yixue , Kim Mansu , Liu Kefei , Saykin Andrew J. , Moore Jason H. , Long Qi , Shen Li
Published: February 2022

Background

Multimodal neuroimaging data can provide complementary information that a single modality cannot about neurodegenerative diseases such as Alzheimer's disease (AD). Deep Generalized Canonical Correlation Analysis (DGCCA) is able to learn a shared feature representation from different views of data by applying non‐linear transformation using neural network. We utilize DGCCA to extract maximally correlated components from multi‐modal neuroimaging data to identify potential imaging‐driven MCI subtypes.

Method

We study 308 Mild Cognitive Impairment (MCI) participants (195 early MCI and 113 late MCI) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), each with voxel level features from FDG PET, amyloid PET (AV45) and structural MRI processed using voxel‐based morphometry (VBM). Six experimental settings are designed to compare single modality with multiview methods ‐ GCCA and DGCCA, see Figure 1. Agglomerative clustering was used to generated 2 clusters with features from each experiment. To investigate differences between the clusters, Wilcoxon rank‐sum tests are conducted on 11 baseline AD biomarkers including 5 cognitive assessments and 6 brain volume measures, from the ADNI QT‐PAD dataset http://www.pi4cs.org/qt‐pad‐challenge.

Result

Among the two multiview methods, DGCCA is able to explain 68.57% variance with 20 features, while GCCA explains 68.66% variance with 94 features. To evaluate the potential subtypes from clustering, the Calinski‐Harabasz (CH) score, Silhouette score and adjusted mutual information (AMI) score are computed, see Table 1. AV45 generates the best defined clusters, where DGCCA generates clusters with quality comparable to single modality features. In our QT analysis, clusters from FDG and DGCCA features show differential measure in all biomarkers where DGCCA learns from multimodal data, see Figure 2.

Conclusion

DGCCA is able to learn maximally correlated features from multimodal neuroimaging data with reduced dimensionality, and explain more variance than its linear counterpart GCCA. Cluster analysis shows these imaging‐driven MCI subtypes are different from the currently diagnosis with differential QT measures, by incorporating complementary information from 3 imaging modalities. DGCCA shows to be an effective feature learning method, and this multiview learning framework can identify potentially novel MCI subtypes to facilitate early detection of AD.
An exploratory study of caregiver burden amongst urban upper class adults in India during COVID‐19
Authors: Mondal Shreosi , Tandon Ravina , Dasgupta Jayashree
Published: February 2022

Background

The COVID pandemic has impacted caregivers of older adults globally and families have been wary of approaching hospitals due to increased risk of exposure. We explored reasons for help seeking and caregiver burden amongst a sample of consecutive urban upper class adults who approached a non‐hospital based organization providing elderly support in Delhi, India.

Methods

A detailed assessment was carried out by trained care specialists using a clinical interview, Hindi Mental Status examination, evaluation of independence in activities of daily living and caregiver burden using the Zarit Burden Interview (ZBI). The assessment was conducted online or in person depending on comfort of the family. Descriptive analysis was carried out to understand the caregiver profile and reasons for seeking help.

Results

Of the 39 adults assessed, majority had a primary diagnosis of dementia (80%). 10% had other psychiatric illness and 10% other neurological illness. 87% families preferred an in person assessment, stating that an online assessment would not be possible with their family member. Primary caregivers were mostly female (80%) and older adults (46%). The main reason for seeking help was inability to manage challenging behaviors at home (97%), followed by concerns about increased cognitive impairments during COIVD (80%), mood related disturbances (41%) and difficulties with activities of daily living (41%). Assessment using ZBI revealed 82% primary caregivers experienced mild to moderate caregiver burden, however, they felt that they were doing their duty and none spontaneously reported a need to seek any form of support for themselves.

Conclusion

Currently India does not have a public health system that supports dementia care and public awareness about management is limited. Our findings highlight that caregivers experience significant stress particularly managing challenging behaviors. Most caregivers are female older adults in whom caregiver burden may be more due to factors like role‐strain and limited independence. In absence of a supportive public health system, our findings also highlight the important role that non‐hospital based organizations play in bridging a gap for dementia care delivery, particularly during these COIVD times.
Patient‐tailored Alzheimer’s disease staging based on integrated biomarker timelines
Authors: yeon Kim Chae , Cho Hanna , Lee Wha Jin , Kim Sung‐Woo , Lyoo Chul Hyoung , Seong Joon‐Kyung
Published: February 2022

Background

Considerable evidence confirms the accumulation of fibrillar Amyloid‐β(Aβ) and aggregates of hyperphosphorylated tau as early Alzheimer’s Disease (AD) biomarker changes. However, the relationships between amyloid and tau within AD pathogenesis are not fully understood. Estimating the integrated order of these two biomarkers abnormality and identifying associations between two biomarkers in vivo could facilitate accurate prediction of patient‐tailored prognosis in early disease stage.

Method

We recruited 74 healthy controls, 75 MCI patients, and 38 AD patients with T1‐weighted magnetic resonance image (MRI) and two PET scans ([18F]Flortaucipir for tau and [18F]Florbetaben for Aβ) with about two‐year follow‐up data. All regional Aβ and regional tau were aligned simultaneously in the order of posterior probabilities of biomarkers becoming abnormal using the DEBM algorithm. All participants were then labeled with disease staging score based on the integrated biomarker timelines. We then explored the relationship between the disease score at baseline and the patient’s diagnosis in follow and annual change of CDR‐SB scores.

Result

Firstly, the integrated biomarker ordering shows a partially overlapped sequence of the Thal stage (in terms of the Aβ biomarker) and the Braak stage (in terms of the tau biomarker). Tau accumulates first within a region called the entorhinal cortex, then spreads out of that region. In the neocortical region (except the entorhinal cortex), the aggregation of amyloid precedes that of tau. Secondly, MCI patients’ stage at baseline matches well with the diagnosis labels at the same time point, and also significantly correlates to the change of CDR‐SB scores. Furthermore, MCI patients with higher disease stage scores at baseline have significantly higher chance to convert to AD at follow‐up.

Conclusion

In this study, we proposed in vivo temporal alterations of both regional amyloid and regional tau simultaneously. All biomarkers exhibited analogous trends to previous research. Amyloid aggregation generally occurs at early stages of the disease and seems to affect not tau seeding but initial tau spreading. Patient staging based on the integrated order of regional biomarker abnormality can help prediction of AD prognosis and future cognition change in early disease stage.
Cortical microstructure is associated with tau burden and predicts cognitive decline and clinical progression in healthy older adults
Authors: Rodriguez‐Vieitez Elena , Montal Victor , Sepulcre Jorge , Lois Cristina , Hanseeuw Bernard , Vilaplana Eduard , Schultz Aaron P. , Properzi Michael J , Scott Matthew R. , Amariglio Rebecca E. , Papp Kate V. , Marshall Gad A , Fortea Juan , Johnson Keith A. , Sperling Reisa A. , Vannini Patrizia
Published: February 2022

Background

Non‐invasive biomarkers of neuronal injury may be useful to detect cognitively‐normal individuals at risk of developing AD. A recent diffusion‐weighted imaging (DWI) method has allowed to assess microstructural properties of the brain's grey matter by means of cortical mean diffusivity (cMD) (Montal et al. Alz&Dem 14(3):340, 2018). Increased cMD is thought to reflect early neuronal injury that may precede macrostructural neurodegeneration. Here, we aimed to investigate the association of cMD with in vivo amyloid‐β and tau pathology in cognitively‐normal individuals, and to determine whether cMD can predict cognitive decline and clinical progression.

Method

196 cognitively‐normal participants from the Harvard Aging Brain Study (72.5±9.4 years; Table 1) underwent concurrent DWI, T1w‐MRI, 11C‐PIB‐PET, 18F‐flortaucipir (FTP)‐PET imaging and cognitive assessments at baseline. PIB‐PET was quantified using non‐PVC‐corrected Logan‐DVR, and FTP‐PET using PVC‐corrected SUVr; PET data were normalized to cerebellar grey‐matter. Longitudinal measures of Preclinical Alzheimer Cognitive Composite (PACC5) were available for n=186 individuals over a 3.72±1.96 yr follow‐up interval. Surface‐based image analysis (FreeSurfer 6.0) was performed to investigate vertex‐wise relationships between cMD and global amyloid‐β (PIB‐FLR), as well as tau (entorhinal, inferior‐temporal FTP). We assessed whether regional cMD predicted longitudinal PACC5 using linear mixed‐effects models, and progression to MCI using Cox proportional‐hazards regression.

Result

Entorhinal and inferior‐temporal tau, but not amyloid‐β, were associated with increases in surface‐based cMD in AD‐signature clusters (Fig. 1A); illustrated for middle‐temporal gyrus cMD (Fig. 1B). Correcting for demographics and baseline PACC5, increased cMD within AD‐signature regions‐of‐interest predicted the rate of subsequent cognitive decline, which remained significant after correcting for PIB‐FLR and regional cortical thickness; there was a synergistic interaction between cMD and PIB‐FLR on the slope of PACC5 decline (Fig. 2). From n=163 participants with clinical follow‐up data, 11/163 (6.7%) converted to MCI within 3.3±1.5 years. Dichotomized regional cMD (top‐tertile group being "high cMD") predicted conversion to MCI, illustrated for the middle‐temporal gyrus, hazard ratio HR[95% CI] = 5.21 [1.14‐23.75], p=0.03, corrected by age, sex and education (Fig. 3).

Conclusion

cMD is a promising technique to quantify cortical microstructural changes possibly related to tau‐induced neuronal injury. Its ability to predict short‐term cognitive decline and clinical progression suggests utility in clinical trials.
Ability of tau‐PET, phospho‐tau217, NfL and cortical thickness to predict short‐term cognitive decline in early symptomatic Alzheimer’s disease
Authors: Smith Ruben , Cullen Nicholas , Leuzy Antoine , Janelidze Shorena , Palmqvist Sebastian , Dage Jeffrey L , Borroni Edilio , Klein Gregory , Ossenkoppele Rik , Mattsson‐Carlgren Niklas , Stomrud Erik , Hansson Oskar
Published: February 2022

Background

Biomarkers for the prediction of cognitive decline in patients with mild cognitive impairment (MCI) due to Alzheimer’s disease (AD) and mild AD dementia are needed for inclusion of suitable patients in clinical trials. We therefore assessed the ability of tau‐PET, blood and cerebrospinal fluid (CSF) phospho‐Tau217 (pTau217), CSF neurofilament light (NfL) and cortical thickness to predict cognitive decline early symptomatic AD.

Method

73 amyloid‐β positive (CSF Aβ42/Aβ40<0.752) participants with MCI and mild AD dementia (MMSE ≥ 22) were assessed at baseline with cognitive testing, blood and cerebrospinal fluid (CSF)‐sampling, MRI and [18F]RO948 PET and were followed longitudinally with annual cognitive testing over 24 months. Slopes of change in MMSE and preclinical Alzheimer cognitive composite (PACC) were calculated over two years. We used linear regression models to assess the ability of biomarkers (plasma pTau217, CSF‐pTau217, temporal meta‐ROI [18F]RO948 PET standardized uptake value ratios (SUVR), CSF‐NfL and MRI “AD‐signature” cortical thickness) to predict cognitive decline both individually and in combination. The linear regression models were adjusted for age, sex, education, and baseline MMSE.

Result

All tested biomarkers individually showed significant associations with cognitive decline using both MMSE and PACC as outcome variables. For predicting longitudinal change in MMSE using individual biomarkers, [18F]RO948 SUVR showed the highest R2‐value (0.39, 95% CI [0.28‐0.67]) and best model fit (lowest Akaike Information Criterion score)(Table 1). Adding other biomarkers yielded a slightly higher R2‐value (0.44 [0.33‐0.63]), but did not improve the model fit. In a sensitivity analysis we performed a similar analysis in a subset of participants having undergone longitudinal testing with a modified PACC test battery (n=53). Results again showed the best performance for [18F]RO948 SUVRs, when tested alone, but with improved model fit and R2‐values with the addition of cortical thickness and CSF‐NfL data (Table 2).

Conclusion

Tau‐PET imaging outperformed CSF, plasma and MRI measures when predicting cognitive decline in prodromal AD and mild AD dementia. Specifically, tau‐PET provided the best prediction alone for change in MMSE and in combination with NfL and cortical thickness for change in PACC, indicating that it would be a suitable biomarker for inclusion in clinical trials.
Accumulation of amyloid‐β alters white matter integrity in cognitively unimpaired middle‐aged females
Authors: Xia Ying , Fazlollahi Amir , Dore Vincent , Bourgeat Pierrick , Raniga Parnesh , Martin Nick , Salvado Olivier , Rose Stephen , Lupton Michelle K. , Breakspear Michael , Fripp Jurgen ,   PISA (Prospective Imaging Study of Aging: Genes, Brain and Behaviour)
Published: February 2022

Background

The APOE‐ε4 allele is the strongest known genetic risk factor for Alzheimer’s disease (AD) and is associated with higher amyloid‐β (Aβ) deposition. White matter (WM) microstructural damages are known to occur early at the preclinical stage of AD. Although stable associations between APOE‐ε4 status and WM alternations have been reported in patients with AD and mild cognitive impairment, few studies have described WM differences in cognitively unimpaired (CU) subjects at risk of AD. We aim to investigate associations of APOE‐ε4 status and Aβ load with WM microstructural changes in mid‐age CU individuals.

Method

151 CU participants from the Prospective Imaging Study of Ageing (PISA) were included (aged 44‐66, 78% female, 77 APOE‐ε4 carriers (ε4+) and 74 non‐carriers (ε4‐)) and underwent Aβ PET and 3T MRI scans including multi‐shell diffusion‐weighted images. Aβ load was quantified in Centiloid (CL) on PET and Aβ+ was defined as CL ≥ 20. Tract based spatial statistics (TBSS) analysis was performed on fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AxD) to assess WM alternations associated with APOE‐ε4 status and/or Aβ load. All analyses were corrected for age and for multiple comparisons.

Result

A significant effect of gender, but not APOE‐ε4 or Aβ status was observed on WM integrity in the full cohort. When considering females only, APOE‐ε4 carriers showed regional increased MD in several right WM tracts. However, these differences were no longer significant when correcting for Aβ status. In contrast, significant WM alternations associated with Aβ+ status were found when correcting for APOE‐ε4 status. In this female‐only subset, widespread WM microstructural damages were observed in Aβ+ε4+ subjects (N=10) compared to Aβ‐ε4+ (N=51) and Aβ‐ε4‐ (N=54) subjects. No significant differences were observed between Aβ‐ε4+ and Aβ‐ε4‐ subjects. Similar differences were also observed in the global diffusion metrics of WM tracts.

Conclusion

These findings suggest that WM alternations associated with Aβ accumulation appear in mid‐life CU female subjects. Future studies in larger cohorts enriched for gender, APOE and Aβ status are required to clarify the relative contributions of APOE‐ε4 and Aβ status on WM microstructural damage.
Telephone support for dementia family caregivers during the COVID‐19 pandemic: Experiential differences in spouse and adult‐child caregivers
Authors: Lee Jung‐Ah , Ju Eunae , Tom Courtney , Tran Tiffany Marie
Published: February 2022

Background

Due to the COVID‐19 pandemic, family caregivers stayed home with their person with dementia (PWD) continuously for 24/7. They faced limited social activity with lack of essential services such as adult daycare and in‐home services. Social restrictions can worsen cognitive deterioration and increase behavioral problems of PWD, causing increased caregiver burden, distress, and loneliness. Caregiver research team developed a telephone support intervention with trained university students who provided emotional support, and COVID‐19 information. The objective of the study is to identify the different needs in caring between spousal caregivers and adult‐child caregivers for community‐dwelling PWD during this pandemic.

Methods

Family caregivers were recruited through our previous home‐visit family caregiver study. Trained bilingual university students conducted telephone support calls in English, Spanish, Korean or Vietnamese as preferred by caregiver participants, once a week during the 3 month of the early pandemic period. Students summarized each conversation in a call log for debriefing by a gerontology faculty. Thematic analysis using call logs was conducted and coded by two independent raters by using Dedoose, a qualitative data analysis tool. Similarities and differences between spousal caregivers and adult‐child caregivers were identified.

Results

14 spousal caregivers (11 were wives and 3 were husbands, mean age 67.4) and 11 adult‐child caregivers (daughters, mean age 49) participated in the study. Three themes were identified: (1) spousal caregivers had high sense of being left alone and isolated while adult‐child caregivers felt a greater responsibility for the family including PWD care, (2) both groups showed increased stress but for spouse caregivers it was due to worsening PWD behaviors, for adult‐child caregivers it was the restriction on social interaction and concerns about losing jobs, (3) similarities in adapting to the COVID‐19 safety recommendations and incorporating it into everyday life.

Conclusion

The findings showed an increase in stress and anxiety in both groups but the differences were: for spouse high level of loneness, difficulty with PWD behaviors; for adult‐child caregivers greater burden due to family and reduced social life. Both groups followed COVID‐19 safety protocol and highly appreciated the telephone‐based emotional support during the pandemic.
Identifying individuals with non‐AD co‐pathologies: A precision medicine approach to clinical trials in sporadic AD
Authors: Tosun Duygu , Ellis Ryan , Weiner Mike W. , Yardibi Ozlem , Simen Arthur , Schwarz Adam J.
Published: February 2022

Background

The presence of co‐pathologies such as TDP‐43, Lewy bodies (LB), and cerebral amyloid angiopathy (CAA) is common in older individuals with AD, even those pathologically confirmed to have amyloid‐β and tau pathology, and contributes to cognitive and functional decline. Treatments targeting just one pathology will thus have variable and reduced overall measurable efficacy compared with an assumed population with no co‐pathologies. Tools to identify individuals with non‐AD co‐pathologies would be enabling technologies for a precision medicine approach to clinical trials in sporadic AD.

In the absence of biomarkers to measure these co‐pathologies directly, our aim was to develop AI models to identify autopsy‐confirmed structural MRI‐based signatures of non‐AD degenerative brain pathologies, to facilitate participant selection for AD trials. This builds on the recent development of models to impute amyloid and tau positivity from structural MRI scans and associated clinical data.

Method

ADNI and NACC participants with ante‐mortem MRI and histopathologic assessments for scoring of neuritic plaques, staging of neurofibrillary tangles, LB, CAA, and TDP inclusions were included (Table 1). A multilabel classifier was trained on demographics, AD pathology, and MRI to jointly model positivity for TDP‐43, LB, and CAA. The leave‐one‐out validated model was applied to a separate ADNI cohort without neuropathologic assessments to assess the imputed prevalence of co‐pathologies at baseline and variance in cognitive decline and atrophy explained by baseline AD and non‐AD pathologies.

Result

When optimized for 90% overall NPV (Fig. 1), the multi‐label classifier identified 16.0% of ADNI Dementia participants as TDP‐43+, 54.8% LB+, and 17.8% CAA+ (Fig. 2). While co‐pathology positivity was rare in cognitively unimpaired, LB and CAA positivity were common in MCI. Although dependent upon clinical disease stage, imputed probability of being TDP‐43+ explained a significant percentage of variance in clinical outcomes measures in cognitively impaired participants (Fig. 3).

Conclusion

These initial results provide promising evidence that imputed co‐pathology burden via widely available imaging and clinical data can be used to impute the presence of non‐AD co‐pathologies and their contribution to cognitive decline in vivo. The primary limitation of this approach is the limited sample size in the autopsy cohorts for model development.
Automatic analysis and validation of digitized speech markers in Lewy body spectrum diseases with Alzheimer’s disease co‐pathology
Authors: Shellikeri Sanjana , Cho Sunghye , Liberman Mark Y. , Howard Erica , Balganorth Yvonne , Weintraub Daniel , Lee Eddie B. , Trojanowski John Q. , Irwin David J. , Grossman Murray , Nevler Naomi
Published: February 2022

Background

Lewy Body Spectrum Disorders (LBSD) are hallmarked by α‐synucleinopathy. Up to 50% of LBSD have co‐occurring Alzheimer’s Disease (AD) at autopsy and this is associated with earlier dementia onset, greater cognitive impairments, and reduced survival. In vivo identification of AD co‐pathology is currently achievable with invasive cerebrospinal fluid (CSF) AD biomarkers or costly molecular PET imaging. There remains a need for non‐invasive, inexpensive, and validated markers that can serve as screening tools for this purpose. We examined automated speech markers of a short semi‐structured natural speech sample in LBSD with and without neurobiologically‐validated AD co‐pathology.

Method

We analyzed digitized speech of Cookie Theft picture descriptions from 62 LBSD patients and 44 healthy controls (HC). AD co‐pathology was determined by neuropathological (25%) or CSF based diagnosis (75%): n=18 LBSD+AD (age= 73.7y (7.4), 67% Parkinson Disease (PD) /PD with Dementia (PDD), 33% Dementia with Lewy Bodies (DLB)); n=44 LBSD‐AD (age= 67.8y (6.5), 61% PD/PDD, 39% DLB). Speech samples were automatically parsed into voiced and silent segments and duration measures were extracted. Transcripts were processed for parts‐of‐speech usage and lexical‐semantic features. We conducted group comparisons of speech measures, examined their effects on determining pathologic group, and assessed relations with MRI cortical thickness.

Result

LBSD+AD and LBSD‐AD groups did not differ in disease duration, motor disease severity (UPDRS Part III), nor neuropsychological performance (overall and across individual cognitive domains). Both LBSD+AD and LBSD‐AD spoke in shorter speech segments and longer and more frequent pauses; and speaking rate was slower compared to HC. Compared to LBSD‐AD, speakers with LBSD+AD used shorter words (by phoneme count) acquired at a younger age, and produced more conjunctions per 100 words. The features showed excellent model fit for determining pathologic group (McFadden R2 = 0.23), but speech features did not distinguish between PDD and DLB. Reduced word age of acquisition related to atrophy in left and right temporal regions in LBSD+AD only.

Conclusion

Automated speech measures distinguished biologically‐confirmed LBSD+AD from LBSD‐AD regardless of clinical phenotype. Findings highlight the potential use of automated digitized speech analytics as a valid screening tool for AD co‐pathology in LBSD.
Accessibility of health care experienced by persons with dementia from ethnic minority groups and (in)formal caregivers: A scoping review
Authors: van Groenou Marjolein Broese , Duran Gozde , Van Hout Hein PJ
Published: February 2022

Background

the number of persons with dementia from ethnic minority backgrounds is increasing. However, ethnic minority groups use health care services less frequently compared to non‐migrants.

Method

We conducted a scoping review and used the theoretical framework developed by Levesque to provide an overview of the literature concerning access to health care for ethnic minority people with dementia and (in)formal caregivers. Our search strategy identified 28 empirical studies in the period 2008‐2019.

Result

Studies mentioned barriers in (1) the ability to perceive a need for care in terms of health literacy, health beliefs and trust and expectations; (2) the ability to seek care because of personal and social values and the lack of knowledge regarding health care options; (3) lack of person‐centered care as barrier to continue with professional health care. Studies also mentioned barriers experienced by professionals in (1) communication with ethnic minorities and knowledge about available resources for professionals; (2) cultural and social factors influencing the professionals’ attitudes towards ethnic minorities; (3) the appropriateness of care and lacking competencies to work with people with dementia from ethnic minority groups and informal caregivers.

Conclusion

Ethnic minority people with dementia and informal caregivers may benefit from improve their abilities to access health care. Health care professionals need to strengthen their competencies in order to facilitate access to health care for this group.
Regional cerebrovascular reactivity and cognitive performance among people with risk of cognitive decline
Authors: Kim Donghoon , Hughes Tim M. , Lipford Megan E. , Craft Suzanne , Baker Laura D. , Lockhart Samuel N. , Whitlow Christopher T. , Okonmah‐Obazee Stephanie , Hugenschmidt Christina E. , Bobinski Matthew , Jung Youngkyoo
Published: February 2022

Background

Cerebrovascular reactivity (CVR) is an indicator of the compensatory dilatory capacity of blood vessel in the brain in response to vasoactive stimuli. BOLD MRI‐measured CVR showed that CVR is correlated with cognition. However, BOLD signal is a complex combination of multiple parameters such as cerebral blood flow (CBF), cerebral blood volume, and oxygen metabolism. In this study, we directly measured CBF using dynamic arterial spin labeling (ASL) during a hypercapnia challenge and tested if regional CVR or CBF is related to cognitive performance among people with risk of cognitive decline.

Method

Seventy‐eight subjects (age: 69±7.18 years, M/F: 22/56; BMI: 27.29±5.12; years of education: 15.6 ±2.45; 12 Type 2 diabetes with 6 under treatment; 38 hypertension; 23 under treatment or 14 both; MMSE score: 28.41±1.43) enrolled in the Wake Forest Alzheimer’s Disease Research Center (ADRC) Clinical Core cohort underwent Pseudo‐continuous ASL during a 2‐minute baseline and a 2‐minute hypercapnic period with a RespirAct computer‐controlled gas blender, targeting 10mmHg higher end‐tidal CO2 level than the baseline while end‐tidal O2 level is maintained. Partial volume corrected voxel‐wise CVR was calculated (Figure 1). Multivariable linear regression analyses were performed to investigate the relationship between CBF or CVR and Mini‐Mental State Examination (MMSE) score in each ROI with adjustment for covariates: age, sex, race, BMI, years of education, hypertension/diabetic status, hypertension/diabetic medication status, and regional volume.

Result

Multivariable linear regression analysis of CVR in the whole brain gray and white matter were positively associated with MMSE score (gray matter: =0.662, p=0.003, white matter: =0.474, p=0.027) (Figure 2‐a and b). Lower MMSE scores were significantly associated with lower CVR (corrected p<0.05) in 26 regions out of 122 gray matter ROIs (Figure 2‐c and 3). There was no significant relationship between regional white matter CVR and MMSE and between baseline CBF and MMSE score.

Conclusion

Lower CVR in the whole brain gray and white matter and in the regional gray matter was related to lower MMSE score, while resting CBF showed no significant relationship with cognitive performance. Therefore, impaired CVR in the reported gray matter regions may be imaging biomarkers that predict cognitive performance.
Evaluation of an Arab American AD care intervention program in the United States
Authors: Ajrouch Kristine J , Janevic Mary , Alhamood Ammar J , Antonucci Toni C
Published: February 2022

Background

This initiative is part of a program of research designed to maximize the health and quality of life within the large Arab‐American community in Michigan through cultural/linguistic adaptations of the Alzheimer’s Association’s Living with Alzheimer’s education and support strategies program. Further, we aim to break new ground in terms of explicitly focusing on family systems as part of a caregiver support intervention.

Methods

10 families (two individuals from each, for a total of 20 individuals) signed up to attend the program. The program was offered twice virtually due to COVID‐19, delivered by bi‐lingual Arab American trainers. All participants were sent a link to an evaluation survey after completing the program (1=strongly disagree; 5=strongly agree) on: the usefulness of the program, the tip sheet, the language of delivery, and Alzheimer's Association resources. Descriptive analysis was conducted to ascertain rating frequency.

Results

Session 1 was delivered in English. Results showed that overall, all respondents agreed that the program was useful in that they learned something new and improved their caregiving skills. Half reported they neither agree/disagree about whether the program met their expectations with. Less than half reported they planned to use the Alzheimer’s Association resources available to them. Session 2 was delivered in Arabic. Results showed that overall, all respondents strongly agreed that the program was useful in that they learned something new and improved their caregiving skills. More than half strongly agreed the program met their expectations. More than half reported they planned to use the Alzheimer’s Association resources available to them. When asked “What would you change about this program” replies from both sessions asked to receive more strategies on how to deal with family members with Alzheimer’s. They also reported liking the Q&A time because that alleviated their feelings of the stigmatization of Alzheimer’s. As one said, “I felt at ease talking and sharing my experience with people who know what am I talking about.”

Conclusion

Identifying successful and challenging elements of the adapted intervention will enable the creation of a program tool kit, which will set the stage for full‐scale broader implementation in underserved diverse populations.
Brain structural alterations in cognitively unimpaired individuals with discordant amyloid‐β PET and CSF Aβ42 status: Findings using machine learning
Authors: Cumplido‐Mayoral Irene , Shekari Mahnaz , Salvadó Gemma , Operto Greg , Cacciaglia Raffaele , Falcon Carles , Niñerola‐Baizán Aida , Perissinotti Andrés , Minguillón Carolina , Fauria Karine , Suridjan Ivonne , Kollmorgen Gwendlyn , Molinuevo Jose , Zetterberg Henrik , Blennow Kaj , Suarez‐Calvet Marc , Vilaplana Verónica , Gispert Juan Domingo ,   ALFA Study,   ADNI study
Published: February 2022

Background

CSF Aβ42 is thought to show AD‐related alterations earlier than amyloid‐β PET. Therefore, cognitively unimpaired (CU) individuals with abnormal CSF Aβ42 and normal amyloid‐β PET are believed to be in the earliest stages of the AD continuum. In this work, we sought to detect structural cerebral alterations in CU individuals with discordant status in these amyloid‐β biomarkers using Machine Learning techniques.

Method

We included 498 CU individuals from the ALFA+ and ADNI studies with available MRI, amyloid‐β PET and CSF Aβ42 measurements, the latter measured with the exploratory Roche NeuroToolKit assays, a panel of automated robust prototype immunoassays. In addition, we calculated Centiloid (CL) values for the PET measurements. Individuals were categorized as CSF‐/PET‐, CSF+/PET‐ and CSF+/PET+ according to established cut‐offs (CSF Aβ42<1098pg/mL for ALFA+ and <880pg/mL for ADNI, and CL<17 for PET). We trained XGBoost classifiers to predict amyloid‐β positivity using as features age, sex, APOE‐ɛ4 status, brain volumes and cortical thicknesses, obtained with Freesurfer 6.0 and the Desikan‐Kiliany atlas. Relevant features for pairwise‐group classification were sought (CSF‐/PET‐ vs CSF+/PET‐; CSF+/PET‐ vs CSF+/PET+; CSF‐/PET‐ vs CSF+/PET+), calculating SHAP values to determine the most important features for prediction.

Result

With respect the CSF‐/PET‐ group, the CSF+/PET‐ showed decreased gray matter volumes in the anterior and posterior cingulate/precuneus and increases in the lateral ventricles and bilateral parahippocampal gyri, among other regions (Figure 1A). Unexpectedly, the posterior cingulate/precuneus showed the opposite effect in cortical thickness measurements. These patterns were similar but more prominent in the comparison between the CSF‐/PET‐ vs CSF+/PET+ group (Figure 1B). Finally, CSF+/PET‐ group was characterized, with respect the CSF+/PET+ group by higher volume of the bilateral supramarginal gyri and lower cortical thickness in the posterior cingulate/precuneus (Figure 1C). Regarding the other variables in the model, APOE‐ɛ4 status was the most predictive variable in models with respect the CSF‐/PET‐ group and age in the CSF+/PET‐ vs CSF+/PET+ comparison.

Conclusion

Our results show that model‐free machine learning techniques can detect complex brain morphological alterations in the earliest stages of the AD continuum. Interestingly, some regions showed increases in volume and/or cortical thickness which may reflect compensatory or inflammatory effects.