bluuebunny/crossref_metadata_2025 huggingface dataset:
Dementia caregivers identify challenges and facilitators to attending health care visits
Authors: Gately Megan E , Muccini Sarah , McLaren Jaye E , Moo Lauren R
Published: December 2021

Background

The 2020 National Research Summit on Care, Services, and Supports for Persons with Dementia and Their Caregivers identified the need for person‐centered dementia care throughout the care continuum. Challenges include adapting health care to meet the complex needs of persons with dementia and their caregivers across a variety of settings.

Method

To understand dementia caregivers’ experience of the health care system, we conducted qualitative interviews with twenty‐four middle‐to‐older age caregivers of community‐dwelling people with dementia. Data were analyzed using conventional content analysis whereby the coding team sought to identify barriers and facilitators to person‐centered dementia care.

Result

We identified three categories and associated sub‐categories related to caregiver experience: 1) Preparing for the Visit, with sub‐categories Physical Challenges and Emotional Preparation; 2) Visit‐Related Time and Travel, with sub‐categories General Travel Challenges, Physical Limitations, Cognitive Limitations, and Benefits; and, 3) In‐visit Experience, with sub‐categories Physical Challenges and Emotional Preparation. Preparing for visit statements revealed barriers, such as patient resistance to attending visits due to not understanding the need. Visit‐related time and travel statements reflected a balance of challenges and facilitators, including general challenges such as traffic and dementia‐specific challenges such as patient agitation around visit wait times. Facilitators reflected the benefit of visits as opportunities for social participation. In‐visit experience statements reflected a mix of challenges and facilitators. Challenges included person with dementia difficulty participating in the health care visit due to poor insight and inability to answer questions, while facilitators included caregivers’ positive engagement with the care team. Across categories, caregivers assumed high‐level responsibility to accommodate for person with dementia physical and cognitive challenges.

Conclusion

Categories underscore the complexity of health care management for a person with dementia both in and around actual clinic appointments, highlighting both challenges related to person with dementia cognitive deficits and perceived benefits related to visits as opportunities for social participation and accessing resources. This study offers relevant insights about tailoring health care to accommodate for person with dementia deficits while supporting their caregivers.
Building relationships to enhance person‐centered care through emotion‐focused care
Authors: Abbott Katherine M , Heid Allison R , Spector Abby , Heppner Alex , VanHaitsma Kimberly S
Published: December 2021

Background

The way we respond emotionally to others can impact how we provide care. Research has shown that employees with high emotional intelligence (EI) know what they are feeling, stop to think before they act, and have strategies for appropriately managing negative feelings and promoting positive feelings. These characteristics are vital to care team members whose entire day involves interacting with other people. Working with people is a double‐edged sword: it can be incredibly rewarding, but people also can bring out negative emotions – frustration, disappointment, anger, shame, and resentment. The ability to identify and manage emotions is particularly important for care team members who work with people living with dementia. While people living with moderate to severe dementia have lost much of their cognitive capacity, feelings remain intact far into the disease process. Care team members recognize that their job is not just to take care of residents’ physical needs; rather, it is to take care of the whole person – body, mind, and soul. Improving quality of life means being concerned about the whole person, and emotional well‐being in particular. We have developed an interactive, on‐line, self‐paced course for all people providing care to others with the specific goal of increasing awareness of emotions and helping to identify emotions in others. The training is supported by research indicating that individuals who can better manage their own emotions are better positioned to manage behaviors and emotions in others. The central concept of the training is to build individuals’ capacity for recognizing and managing their emotions and the emotions of others to enhance person‐centered care. While the course is relevant to any person who is a caregiver, it focuses on the context of providing care to an individual with dementia. The training is available to individuals at no cost due to generous grant funding. The goal of this presentation is to introduce the concept of EI, particularly as it applies to caregivers and then review how to access and navigate the course.
High frequency of functional cognitive decline among patients with low education
Authors: Borelli Wyllians Vendramini , de Senna Priscylla Nunes , Chaves Marcia L Fagundes , Castilhos Raphael Machado
Published: December 2021

Background

Functional cognitive decline (FCD) has been increasingly described as a blind spot of dementia care. Psychological distress, affective symptoms and disturbed self‐perception comprehend the most common causes of FCD. Herein, we aim to identify the frequency of FCD in a tertiary memory clinic from a very low education setting.

Method

A retrospective analysis was conducted to identify new referrals to our tertiary memory clinic (Porto Alegre, southern Brazil) over a 6‐year period (2014 ‐ 2020). All individuals referred from the primary care setting of the public health system in this time period were included in this analysis. Patients underwent a diagnostic protocol including neurologic evaluation, cognitive screening, neuroimaging (CT or MRI) and laboratory testing. FCD was defined as patients with cognitive complaints/objective cognitive decline associated with psychological distress and affective symptoms, without evidence of underlying neurodegenerative disease. Data is shown in median [interquartile range].

Result

A total of 474 patients (287 females, median age 72 [65‐78]) with a median of 5 [0‐10] years of education were referred to our memory clinic within the period from 2014 to 2020. FCD was the second more frequent final diagnosis (95, 19.8%), only behind of dementia due to Alzheimer's disease (106, 22.4%); other diagnosis were less frequent: Mild Cognitive Impairment (49, 10.3%), Subjective Cognitive Decline (35, 7.4%), Vascular dementia (34, 7.2%), Mixed‐type dementia (24, 5.1%), behavioral variant Frontotemporal Dementia (5, 1.1%), and other types (36, 7.6%). Patients with FCD were younger (69 [63‐75] vs. 74 [67‐78], p<0.001), and showed higher Geriatric Depression Scale (GDS‐15) than non‐FCD individuals (9 [5‐12] vs. 5 [2‐8], p<0.001). The education level did not differ (p>0.05).

Conclusion

Functional Cognitive Decline was the second most frequent diagnosis among patients with very low education in a tertiary memory clinic. FCD individuals were younger, showed increased depressive symptoms than non‐FCD patients. Taken altogether with Subjective Cognitive Decline, functional disorders account for the majority of consultations referred to this tertiary setting. Public health strategies including the primary care setting may greatly improve early diagnosis and treatment to these patients.
Changed behaviours associated with cognitive decline: Views of people living with dementia, families and healthcare professionals
Authors: Burley Claire V , Chenoweth Lynnette , Casey Anne‐Nicole S , Brodaty Henry
Published: December 2021

Background

Changed behaviours associated with cognitive decline (also known as neuropsychiatric symptoms (NPS), behavioural and psychological symptoms of dementia (BPSD), and responsive behaviours) occur in up to 90‐percent of people living with dementia (PLWD). They strongly correlate with functional and cognitive impairment and contribute to approximately 30‐percent of overall dementia costs. Decisions regarding care and strategies for changed behaviours are often determined by families and healthcare professionals and are not inclusive of PLWD. This is the first study that investigates terminology used to describe changed behaviours associated with cognitive decline from the perspective of PLWD, families/care partners and healthcare professionals. PLWD, families/care partners and healthcare professionals participated in semi‐structured interviews. A thematic iterative approach was used to code the data and identify common themes until theoretical saturation was reached (∼25 participants per group). Themes were compared between groups. Data were analysed deductively in relation to pre‐existing terminology regarding changed behaviours in cognitive decline, and inductively to discover new ideas on use of such terminology as perceived by PLWD and others. Thirty‐four volunteers have been interviewed so far: 16 PLWD, mean age 70yrs, mean Mini‐Mental State Examination score 26, and 18 family members/care partners. Preliminary analysis indicates that terms used by PLWD and families differ to terms used in existing professional frameworks (e.g., ‘disinhibition’ described as ‘loss of filter’ and ‘agitation/ aggression’ as ‘frustration’ or ‘lower tolerance’. Full results from PLWD, families/care partners and healthcare professionals will be presented (∼75 participants). This is the first report from PLWD themselves on their preferences for the terminology describing changed behaviours previously described as BPSD or NPS, suggesting a reconceptualization of changed behaviours may assist, e.g., from ‘agitated/ hard to handle’ to being frustrated with cognitive decline, discriminatory behaviour and insufficient support systems, and ‘having delusions/ false beliefs’ to thinking about and re‐experiencing previous traumatic events. In better understanding changed behaviours, families and professionals will be able to respond in a way that is helpful for PLWD. An integrated understanding of all views and factors involved will assist in better understanding changed behaviours, improve language use and the quality of care and support.
Anti‐inflammation as one of the mechanisms in the improvement of cognitive function by probiotic Bifidobacterium breve strain
Authors: Ohno Kazuya , Bernier Francois , Katsumata Noriko , Shimizu Takashi , Xiao Jin‐Zhong
Published: December 2021

Background

Recently, the gut‐brain axis has received a lot of attention as some probiotics have been reported to have a beneficial effect on CNS diseases. Our previous studies show that the probiotic strain, Bifidobacterium breve MCC1274 (synonym B. breve A1), improves memory scores in Alzheimer’s disease model and human subjects with self‐reported memory complaints. Furthermore, in a trial with healthy adults with MCI (Mild Cognitive Impairment), we found that B. breve MCC1274 significantly improved the cognitive function [1]. In the present study, we investigated the association of blood parameters with the improvement of cognitive function by B. breve MCC1274.

Method

In a double blind, randomized placebo‐controlled trial, healthy adults aged 50‐79 years with MCI consumed probiotic capsules (2x1010 CFU/day) or placebo capsules for 16 weeks. Cognitive function was measured before and after the intervention using RBANS (Repeatable Battery for the Assessment of Neuropsychological Status) and JMCIS (Japanese version of MCI Screen) as neuropsychological tests. Hematological and biological blood parameters were measured to assess the safety and elucidate the possible action mechanism.

Result

Out of 80 participants, 79 subjects completed the study and after 16 weeks intervention, RBANS total score was significantly improved in the probiotic group in particular with significant improvement in domain scores of immediate memory, visuospatial/constructional, and delayed memory. Hematological and biological blood parameters showed no significant differences between the two groups. Interestingly, however, a significant correlation was found between the changes in blood HbA1c and RBANS total score in B. breve MCC1274 group (ρ=‐0.4218, p=0.0067). A stratified analysis based on baseline HbA1c with a median value (5.4%) showed a more remarkable benefit on the cognitive function by the probiotic consumption in the higher median subgroup (Fig 1). As many studies have reported an association between HbA1c and inflammation‐related dementia, this data suggests the mechanism of action of the probiotics may involve reducing inflammation.

Conclusion

The present data shows that B. breve MCC1274 improves cognitive function by reducing inflammation in healthy adults with MCI and may be a potential strategy for preventing dementia. Reference: (1) Xiao et al. Journal of Alzheimer’s Disease, 2020.
Apolipoprotein E4‐driven effects on inflammatory and neurotrophic factors in peripheral extracellular vesicles from cognitively impaired not demented participants converted to Alzheimer’s disease
Authors: Kheder Mohamed Raâfet Ben , Haddad Mohamed , Laurin Danielle , Ramassamy Charles
Published: December 2021

Background

In brain, extracellular vesicles (EVs) play an essential role in neuron‐glia interface and ensure the crosstalk between the brain and the periphery. Only a few studies have demonstrated the apolipoprotein E4 variant (APOE ε4)‐driven dysfunction of EVs pathway and the risk to develop Alzheimer’s disease (AD). To better understand the role of APOE ε4 in pre‐clinical AD, we determined levels of pathogenic, neurotrophic and inflammatory proteins in peripheral EVs (pEVs) and in plasma from cognitively impaired‐not demented (CIND) participants stratified upon the absence (APOE ε4‐) or the presence (APOE ε4+) of the ε4 allele of APOE.

Method

Levels of 15 neurodegenerative, neurotrophic and neuroinflammatory proteins were quantified in pEVs by the multiplex Luminex assay and compared to their plasma levels from cognitively normal and CIND participants

Result

For the first time, several neurotrophic and inflammatory markers including LCN‐2, S100B, ANGPTL‐4, NPTX‐2 and α‐synuclein were evidenced in pEVs. Some proteins such as α‐Syn, NPTX‐2 and S100B were enriched in pEVs as compared to plasma. APOE ε4+ was associated with differential regulation of 7 markers and compromised the release of pEVs formed by an endosomal route. The pentraxin‐2/α‐synuclein ratio measured in pEVs was able to predict AD 5 years before the onset among APOE ε4+ CIND individuals. Discussion: Our findings suggest an alteration of the endosomal pathway in APOE ε4+ carriers and that pEVs pentraxin‐2/α‐synuclein ratio could serve as a useful early biomarker for AD susceptibility.

Conclusion

The findings reported herein provide a comprehensive insight and enhance our knowledge on the emerging role of ApoE4 in abnormal pEVs cargo proteins processing and the identification of blood‐based biomarkers.
E2511, a novel small compound TrkA allosteric modulator, induces a specific trophic signaling via direct binding to TrkA, and can reverse the loss of choline acetyltransferase (ChAT) positive neurons in transgenic models of AD
Authors: Tomioka Takeyasu , Moriyama Yoshiyuki , Hiramatsu Naoki , Kosasa Takashi , Kondo Keita , Wakita Hisashi
Published: December 2021

Background

Loss of cholinergic neurons in Alzheimer’s disease (AD) is an early pathogenic event correlated with cognitive impairment. Nerve growth factor (NGF) plays a major role in the maintenance and function of cholinergic neurons. Decrease in NGF‐Tropomyosin receptor kinase A (TrkA) induced trophic signaling contributes to cholinergic neurodegeneration and cognitive decline during the course of AD. The activation of the trophic signaling could be a promising therapy for AD, reinnervating basal forebrain cholinergic neurons. We provide evidence that our novel small compound E2511 is TrkA allosteric modulator showing an increase in specific trophic signaling via direct binding to TrkA.

Method

E2511 was characterized in several in vitro assays such as NMR assay for detecting binding to TrkA and biochemical studies for evaluating the phosphorylation level of TrkA in each site using rat primary septal neurons. The in vivo effects of the compound on TrkA signaling were investigated in human Tau P301S transgenic mice (Tau tg mice) by biochemical studies such as western blot analysis, while assessing whether the compound induces hyperalgesia in behaviour studies and pain‐related signaling in normal and pain model rats. Moreover, the trophic effect of the compound on cholinergic neurons was investigated in Tau tg mice.

Result

E2511 enhanced phosphorylation level of TrkA in the presence of NGF via direct binding to TrkA in rat primary neurons, and phosphorylation level of each site of TrkA induced by the compound was different from that of NGF. In vivo experiments demonstrated that oral administration of E2511 elevated trophic signaling in the septum, while induction of hyperalgesia was not detected. Furthermore, chronic administration of E2511 reversed the loss of ChAT‐positive cells in Tau tg mice by therapeutic treatment.

Conclusion

E2511 enhances specific trophic signaling by altering TrkA signaling as specific allosteric modulator via direct binding to TrkA, and E2511 shows the reinnervative effect on cholinergic neurons through activation of TrkA signaling without induction of NGF‐like adverse effect.
Rationale and design of the NEwTON study: A prospective cohort study of patients at risk of chronic traumatic encephalopathy
Authors: van Amerongen Suzan , Vijverberg Everard G.B. , Pijnenburg Yolande A.L. , Scheltens Philip
Published: December 2021

Background

Traumatic brain injury increases the risk of neurodegenerative diseases later in life. Repetitive head injury, more specific in contact sports, is associated with cognitive, neurobehavioral and motor impairments in the light of a unique neurodegenerative disorder: chronic traumatic encephalopathy (CTE). Yet, the clinical presentation, risk factors and diagnostic biomarkers of CTE have remained unclear. The general objective of the NEwTON study is to establish a prospective cohort of patients with high risk of CTE, to further study the link between repetitive head injury and neurodegeneration. We aim to phenotype the study population, identify potential biomarkers and measure clinical progression.

Method

NEwTON is a prospective cohort study which aims to recruit approximately 80 patients at risk of CTE (features of the traumatic encephalopathy syndrome, Montenigro 2014) and healthy control subjects. Inclusion criteria are: history of repetitive head injury (contact sports, military service, other exposure), progressive cognitive and/or neurobehavioral symptoms, age 45‐75 years and symptom duration of ≥12 months. The control group will consist of age‐matched healthy participants without history of significant traumatic brain injury or participation in contact sports/professional military service. Subjects are invited to participate after diagnostic screening at our memory clinic or recruited by advertisement.

Result

Patients will undergo comprehensive baseline screening, including neurological examination, neuropsychological tests, questionnaires and brain magnetic resonance imaging (MRI) for anatomical imaging, diffusion tensor imaging (DTI), resting state functional MRI (rsfMRI) and Quantitative Susceptibility Mapping (QSM). Questionnaires include topics on life‐time head injury, subjective cognitive change and neuropsychiatric symptoms. Blood and cerebrospinal fluid will be stored in the NEwTON biobank. Patients will be informed about our brain donation program in collaboration with the Netherlands Brain Brank. Testing for control subjects will be limited to baseline neuropsychological tests, blood draw and MRI. Patient follow‐up will take place annually and includes neuropsychological assessment, questionnaires and blood draw.

Conclusion

The NEwTON study will contain the first cohort in the Netherlands with prospective observational data of patients with high risk of CTE. This study design will be an umbrella protocol and it is expected that other sub‐studies will use this cohort in the future.
Sex differences in the relation between subjective memory complaints, impairments in instrumental activities of daily living, and risk of dementia
Authors: Abdulrahman Hanna , Richard Edo , van Gool Willem A , van Charante Eric P Moll , van Dalen Jan Willem
Published: December 2021

Background

Older people with symptoms of subjective memory complaints (SMC) and impairments in instrumental activities of daily living (IADL) have an increased risk of developing dementia. The predictive value of SMC and IADL‐impairments may be modified by sex. This could have consequences for personalized risk prediction and prognosis.

Methods

From the Prevention of Dementia by Intensive Vascular care study (preDIVA), 3495 community‐dwelling older people, aged 70‐78 years (mean=74.3±2.5) without dementia, were investigated over a median follow‐up of 6.7 years. SMC at baseline were assessed using the memory question from the 15‐item Geriatric Depression Scale. IADL‐impairments were assessed using the Academic Medical Center Linear Disability Score (ALDS). Potential sex‐differences in the predictive value of SMC and IADL‐impairments for incident dementia were assessed using Cox regression models with an interaction term for sex*ALDS_SMC.

Results

Women with isolated SMC (HR=2.10,95%CI=0.94‐4.69) and SMC combined with IADL‐impairments (HR=2.96,95%CI=1.66‐5.28) were at greater risk of developing dementia than men (HR=1.51,95%CI=0.83‐2.75; HR=1.24,95%CI=0.59‐2.61 respectively), but these differences were not significant (p‐interaction=0.67 and 0.13). Isolated IADL‐impairments were associated with a significantly higher risk of mortality (HR=1.36,95%CI=1.09‐1.68), and a lower risk of dementia (HR=0.70,95%CI=0.48‐1.00). These associations were particularly prominent in men, but were not significantly different compared to women (p‐interaction=0.25 and 0.83).

Conclusion

SMC increase dementia risk, especially when occurring together with IADL‐impairments. This relation may be somewhat stronger in women. Isolated IADL‐impairments do not increase dementia risk. Competing mortality risk may strongly influence these associations, especially in men, suggesting it is essential to assess when comparing sex‐differences in dementia risk.
Slow waves contribute to memory consolidation only in older adults without sleep‐disordered breathing
Authors: Champetier Pierre , André Claire , Rehel Stéphane , Ourry Valentin , Landeau Brigitte , Mézenge Florence , de Flores Robin , De la Sayette Vincent , Chetelat Gaël , Rauchs Géraldine ,   Medit‐Ageing Research Group
Published: December 2021

Background

Sleep‐dependent memory consolidation, which is thought to rely on the dialogue between the hippocampus and the medial prefrontal cortex (mPFC) during NREM sleep, is mediated by slow waves (SW) and sleep spindles. Some studies indicate that this process is impaired in ageing but also in sleep‐disordered breathing (SDB), a very common sleep disorder in ageing. In this study, we investigated sleep‐dependent memory consolidation in older adults with or without SDB and explored the underlying mechanisms.

Method

Baseline data of 57 cognitively unimpaired older adults (mean age ± SD: 68.6 ± 3.3 years) from the Age‐Well cohort were analysed. Participants underwent a structural MRI scan to obtain mPFC and hippocampal grey matter volumes, and performed a visuospatial memory task until reaching a learning criterion of 66.6% of correct answers. Post‐learning sleep was monitored using polysomnography, and delayed recall was probed the next morning. An overnight change in memory performance (OCMP) was computed as follows: (recall performance – learning performance) / learning performance. SW, slow and fast spindles during N2 and N3 sleep were automatically detected using the SleepTrip toolbox. Based on the standard apnea‐hypopnea index (AHI) cutoff of 15 events/h, participants were classified as having SDB (SDB+, n=47) or not (SDB‐, n=10).

Result

There was no between‐group difference in OCMP, as well as in amplitude, duration and frequency of SW, slow and fast spindles (p>0.05). However, we found a significant group by SW density interaction after controlling for age, sex, education, total sleep time and trait‐anxiety (p=0.03). Thus, a positive association was only found between SW density and OCMP in the SDB‐ group (p=0.02; Fig 1). No correlation was found between slow or fast spindle density and OCMP in either group. Finally, mPFC and hippocampal volumes did not differ between SDB+ and SDB‐ participants (p>0.05), but SW density positively correlated with the volume of the mPFC (p=0.01; Fig 2).

Conclusion

Our findings suggest that the contribution of SW to sleep‐dependent memory consolidation is impaired in participants with SDB and incriminate the mPFC. We plan to conduct connectivity and SW‐spindle coupling analyses to unravel the functional substrates of this deficit.
Antihypertensive drug classes and incident dementia: Findings from the PreDIVA observational extension study
Authors: Schroevers Jakob L , Eggink Esmé , Hoevenaar‐Blom Marieke P , Richard Edo , van Dalen Jan Willem , van Middelaar Tessa , van Gool Willem A , van Charante Eric P Moll
Published: December 2021

Background

Midlife hypertension is a risk factor for all‐cause dementia. Treatment of hypertension with antihypertensive medication (AHM) may therefore be a promising strategy to delay or prevent dementia. Recent reports have suggested that AHM are associated with differential effects on dementia risk, due to class‐specific mechanisms. In this study, we assess the association between different AHM‐classes and incident dementia, using data from the preDIVA observational extension (POE) study.

Method

All participants who reported use of AHM at baseline were included in the analyses. We distinguished angiotensin‐converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARBs), beta‐blockers, calcium channel blockers (CCBs), and diuretics. Data on incident dementia was collected during the randomised phase at 2, 4, 6‐8 and, after discontinuation of the intervention, 10‐12 years after baseline. Cox proportional hazards regression was used to study the association between use of different AHM‐classes, compared with use of any other AHM class, and incident dementia. A post‐hoc analysis was performed, dividing follow‐up time in two periods (preDIVA median follow‐up acting as cut‐off point) to account for the effect of time between exposure and dementia.

Result

1953 participants who reported AHM use at baseline were included, with a mean age of 74.5 (±2.5) and a mean systolic blood pressure of 156.4 mmHg (±21.5). After a median follow‐up of 10.4 years (IQR 6.7‐11.0), 228 (11.7%) participants had developed dementia. Adjusted hazard ratios (HR) for dementia were 1.07 (95%CI 0.80‐1.42) for ACE inhibitors, 0.75 (95%CI 0.53‐1.06) for ARBs, 1.00 (95%CI 0.77‐1.31) for beta‐blockers, 0.92 (95%CI 0.68‐1.24) for CCBs, and 1.02 (95%CI 0.78‐1.33) for diuretics. ARBs and CCBs were inversely associated with dementia during the first time period (HR 0.46, 95%CI 0.25‐0.84 and HR 0.62, 95%CI 0.38‐0.99 respectively), which was not apparent anymore during the second one.

Conclusion

Despite short‐term beneficial associations of CCBs and ARBs and a promising HR for ARBs also after longer follow‐up, associations between any AHM‐class and incident dementia were not convincing after complete follow‐up. These findings are possibly best explained by the long follow‐up in older participants with high mortality‐ and dementia rates, possibly attenuating AHM‐class effects on dementia incidence.
Dual pathogenic mutations in SQSTM1 and C9orf72 as a cause of frontotemporal dementia
Authors: Benotmane Hanya
Published: December 2021

Background

Hexanucleotide repeat expansions in the C9orf72 gene have been found to be the leading genetic cause of both familial frontotemporal dementia (FTD) and motor neuron disease (MND). However there are a number of other genetic causes of both FTD and MND including, less commonly, mutations in sequestosome 1 (SQSTM1) which codes for the cargo protein p62. Occasionally, people with FTD or MND have been described with dual pathogenic mutations, although this is rare.

Method

We describe the clinical and imaging features of a woman who presented with FTD and motor neurone involvement who was found to carry both a pathogenic C9orf72 expansion and a deleterious c.1185dup, p.Glu396* heterozygous SQSTM1 mutation.

Result

Symptoms started at the age of 60 with change in personality and impaired behaviour followed at the age of 63 by prosopagnosia and semantic impairment. Brain magnetic resonance imaging showed right‐sided predominant temporal more than frontal lobe atrophy, and she was initially diagnosed with behavioural variant FTD. However at the age of 66 she developed asymmetrical limb weakness and stiffness, with upper motor neurone features only on examination, suggestive of primary lateral sclerosis (PLS). She deteriorated rapidly over the next couple of years, although never developed lower motor neurone features when subsequently examined. She died at the age of 69.

Conclusion

The co‐presence of both a SQSTM1 mutation and C9orf72 expansion is rare. It remains unclear which mutation accounts for which of the features seen. Focal right temporal lobe atrophy is more common with SQSTM1 mutations, but PLS is uncommon with both mutations. It may be therefore that it is the dual mutations together that explain the altered phenotype. It is paramount to better understand the roles which SQSTM1 and C9orf72 mutations have on cellular pathways and how their combination results in rare phenotypes.
Artificial neural network visualization methods reveal diagnostically relevant brain regions to detect Alzheimer’s disease: The first step towards comprehensive artificial intelligence
Authors: Dyrba Martin , Hanzig Moritz , Buerger Katharina , Cantré Daniel , Düzel Emrah , Heneka Michael T. , Laske Christoph , Perneczky Robert , Peters Oliver , Priller Josef , Schneider Anja , Spottke Annika , Wagner Michael , Weber Marc‐André , Wiltfang Jens , Jessen Frank , Teipel Stefan J. ,   DELCODE
Published: December 2021

Background

Although deep learning approaches achieve high diagnostic accuracy for detecting Alzheimer’s disease (AD) based on MRI scans, they are rarely applied in clinical research due to a lack of suitable methods for model comprehensibility and interpretability. Recent advances in convolutional neural networks (CNN) visualization algorithms may help to overcome these problems.

Method

We implemented a CNN model structure, trained it on 662 T1‐weighted MRI scans obtained from ADNI in a twentyfold cross‐validation procedure, and validated it on 1655 cases from three independent samples. Various CNN visualization algorithms were compared, which generated relevance maps indicating the contribution of individual image areas for detecting AD. We developed an interactive web application to display the 3D relevance maps and interactively change various visualization parameters. We assessed the clinical utility of relevance maps by comparing hippocampus relevance scores with hippocampus volume.

Result

Across the three independent validation datasets (Fig. 1), group separation showed high accuracy for AD dementia versus controls (AUC≥0.92) and moderate accuracy for amnestic mild cognitive impairment (MCI) versus controls (AUC≥0.73). Relevance maps obtained from Layer‐wise Relevance Propagation (LRP) provided a high spatial resolution and strongest focus (Fig. 2 & Fig. 3). LRP maps indicated that hippocampal atrophy was the most informative factor for AD detection (Fig. 4), with additional contributions from atrophy in other cortical and subcortical regions. Relevance scores within the hippocampus were highly correlated with hippocampal volumes (median: r=‐0.81, Fig. 5). The relevance maps of individual patients revealed additional clusters in the frontal and occipital lobe, which may be an indicator of model overfitting or potential bias of the training sample. When comparing the twenty cross‐validation models, stronger focus of the models on irrelevant areas was associated with lower accuracy to detect MCI.

Conclusion

The relevance maps highlighted atrophy in regions that we had hypothesized a priori, which strengthens the overall comprehensibility and validity of the CNN models.
Detecting amyloid positivity in early Alzheimer disease using plasma biomarkers
Authors: Janelidze Shorena , Palmqvist Sebastian , Leuzy Antoine , Stomrud Erik , Verberk Inge M.W. , Zetterberg Henrik , Ashton Nicholas J. , Mattsson‐Carlgren Niklas , Pesini Pedro , Sarasa Leticia , Allué Jose A. , Teunissen Charlotte E. , Dage Jeffrey L. , Blennow Kaj , Hansson Oskar
Published: December 2021

Background

Recent data suggest that blood biomarkers of amyloid‐β (Aβ) pathology (Aβ42/Aβ40), tau pathology (phosphorylated tau [P‐tau]) and neurodegeneration (neurofilament light [NfL]) in Alzheimer disease (AD) become abnormal very early in the disease course, albeit with different dynamics; Aβ42/Aβ40 starts to change first followed next by P‐tau and then by NfL.

Method

We studied the usefulness of plasma AD biomarkers measured using mass spectrometry (Aβ42/Aβ40) and immunoassays (P‐tau217 and NfL) to identify abnormal brain Aβ status (according to CSF Aβ42/Aβ40 or Aβ‐PET) in a total of 895 participants with early disease (cognitively unimpaired individuals [CU] and patients with mild cognitive impairment [MCI]) from two independent cohorts (BioFINDER‐1 and BioFINDER‐2). CSF Aβ42/Aβ40 measures were available in all study participants; 159 (26.9%) CU and 175 (57.6%) MCI were CSF Aβ42/Aβ40‐positive. Out of 858 subjects who underwent Aβ‐PET imaging, 142 (24.0%) CU and 169 (55.6%) MCI were Aβ‐PET positive.

Result

In CU, a combination of plasma Aβ42/Aβ40 and plasma P‐tau217 accurately detected abnormal CSF Aβ42/Aβ40 status (BioFINDER‐2, area under the curve [AUC]=0.86; BioFINDER‐1, AUC=0.83) with no significant difference in the accuracy compared with the model including all 3 plasma biomarkers (BioFINDER‐2, AUC=0.87, p=0.62; BioFINDER‐1, AUC=0.84, p=0.57). In MCI patients, plasma P‐tau217 alone showed high discriminative accuracy (BioFINDER‐2, AUC=0.88; BioFINDER‐1, AUC=0.86) which was not significantly different from the discriminative accuracy of the model combining all 3 plasma biomarkers (BioFINDER‐2, AUC=0.88, p=0.94; BioFINDER‐1, AUC=0.88, p=0.29). Adding APOE ε4 status improved model fit but did not significantly change the AUCs of the models. The results were similar when using Aβ‐PET as the outcome.

Conclusion

These findings suggest that different plasma biomarkers are not equally useful along the AD continuum. In the preclinical phase, plasma Aβ42/Aβ40 and plasma P‐tau217 would be needed to accurately detect abnormal brain Aβ status whereas in prodromal AD plasma P‐tau217 might alone be sufficient.
Clustering biomarkers in dominantly inherited Alzheimer’s disease
Authors: Luckett Patrick H. , Chen Charles D. , Gordon Brian A. , McDade Eric , Benzinger Tammie L.S. , Bateman Randall J. , Ances Beau M.
Published: December 2021

Background

Numerous biomarkers exist for potentially studying autosomal dominant Alzheimer disease (ADAD) pathology. Understanding the relationships between biomarkers and disease progression can inform patient care and clinical trials. We utilized machine learning‐based clustering and feature selection to identify an optimal subset of biomarkers reflective of disease stage and pathology.

Method

Cross sectional clinical and neuropsychological evaluation (Clinical Dementia Rating (CDR), Geriatric Depression Scale (GDS), Mini‐Mental State Exam (MMSE)), structural magnetic resonance imaging (AD cortical signature), amyloid measures (amyloid positron emission tomography (PET) and CSF Aβ42 and 40), tau measures (CSF total tau and phosphorylated tau isoforms pT181, pT205, pT202, and pT217), and neurodegeneration measures (fluorodeoxyglucose (FDG) PET, serum NFL, CSF neurogranin, SNAP‐25, VILLIP‐1) and neuroinflammation (CSF YKL‐40) were acquired in 130 mutation carriers (MC) and 79 non‐carriers (NC) from the Dominantly Inherited Alzheimer Network observational study (Table 1). Hierarchical clustering was used to group biomarkers. Decision tree‐based feature selection identified biomarkers that were the strongest predictors of mutation status and estimated years to symptom onset (EYO).

Result

Figure 1 shows the absolute value correlation matrix used for hierarchical clustering. Figure 2 shows the dendrogram of the clustering results. FDG, GDS, and Aβ40 were the least similar to other biomarkers. Aβ42 and 42/40 ratio, PET amyloid, cortical signature, CDR, MMSE, and NFL were similar. With the exception of YKL‐40, the “emerging” biomarkers (neurogranin, VILLIP‐1, SNAP‐25) clustered together. Total tau and tau isoforms were grouped together. Feature selection identified YKL‐40, pT205, and pT217 as the strongest predictors of EYO in MCs (Figure 3). YKL‐40 had the highest correlation with EYO (.59,p‐value<.001), suggesting a possible role of persistent increasing neuroinflimation. With regard to mutation status, the strongest predictors were measures related to amyloid, including Aβ42/40 ratio, amyloid PET PIB, and pT217 (Figure 4).

Conclusion

Understanding the relationships biomarkers have with each other, as well as understanding which biomarkers are most reflective of disease processes, is vital for patient care and clinical trials. In this study, we have identified groups of biomarkers that are most similar to each other, as well as identified which biomarkers are most reflective of EYO and mutation status in ADAD.
Subclinical but high level of glycemia and platelet activity are associated with decreased structural and functional integrity in Alzheimer’s disease‐sensitive brain regions
Authors: Palix Cassandre , Felisatti Francesca , Kuhn Elizabeth , Mézenge Florence , Landeau Brigitte , Gonneaud Julie , Quillard Anne , Chocat Anne , De la Sayette Vincent , Vivien Denis , Martinaud Olivier , Chetelat Gaël , Poisnel Géraldine
Published: December 2021

Background

There is an increasing research focus on type 2 diabetes (T2D) as a risk factor for Alzheimer’s disease (AD) (Lee, 2018). T2D is a disease characterized notably by hyperglycemia and platelet hyper‐reactivity (Schneider, 2009). However, relatively little is known about subclinical but high levels of glycemia and platelet reactivity in the context of ageing and AD. The aim of this study was to investigate the association between glycemia and platelet level, size and activity (platelet count and mean platelet volume (MPV)) and neuroimaging markers of ageing and AD.

Method

107 cognitively unimpaired adults (18‐84 years old) from the IMAP+ study (Caen) were included, comprising 23 amyloid‐negative older adults (Aβ‐ controls) and 48 amyloid‐positive patients with mild cognitive impairment or dementia (Aβ+ patients). Participants underwent blood tests to dose glycemic and platelet indices, structural MRI, FDG‐PET and amyloid‐PET assessments. Multiple regressions were performed between blood indices and neuroimaging data and inter‐group comparisons of blood indices were assessed between Aβ+ patients and Aβ‐ controls.

Result

Compared to Aβ‐ controls, Aβ+ patients showed no difference in glycemia levels but had lower platelet count and higher MPV. Increased MPV was associated with entorhinal and perirhinal cortex atrophy in Aβ+ patients (fig.B) while platelet count was not associated with any neuroimaging data. High glycemia levels were associated with both atrophy of the right hippocampus and posterior cingulate cortex (PCC) and hypometabolism in the precuneus, cuneus, PCC, angular cortex and medial temporal gyrus in cognitively unimpaired adults (fig.A). None of the blood indices were associated with amyloid‐PET.

Conclusion

Both high glycemia and MPV levels were associated with atrophy and/or hypometabolism in AD‐sensitive brain regions, notably the entorhinal cortex, hippocampus and posterior cingulate cortex. These results suggest that subclinical but high levels of glycemia and MPV could be associated with more vulnerability in brain regions sensitive to AD but not at the same stage, while amyloid deposition does not appear to be involved at these stages. Our findings highlight the importance of monitoring these blood indices as risk factors early in the context of AD prevention.
Analysing behavioural changes in people with dementia using in‐home monitoring technologies
Authors: Rezvani Roonak , Kouchaki Samaneh , Nilforooshan Ramin , Sharp David J , Barnaghi Payam
Published: December 2021

Background

Behavioural changes and neuropsychiatric symptoms such as agitation are common in people with dementia. These symptoms impact the quality of life of people with dementia and can increase the stress on caregivers. This study aims to identify the likelihood of having agitation in people affected by dementia (i.e., patients and carers) using routinely collected data from in‐home monitoring technologies. We have used a digital platform and analytical methods, developed in our previous study, to generate alerts when changes occur in the digital markers collected using in‐home sensing technologies (i.e., vital signs, environmental and activity data). A care monitoring team use the platform and interact with participants and caregivers when an alert is generated.

Method

We have used connected sensory devices to collect environmental markers, including Passive Infra‐Red (PIR), smart power plugs for monitoring home appliance use, motion and door sensors. The environmental marker data have been aggregated within each hour and used to train an agitation risk analysis model. We have trained a model using data collected from 88 homes (∼6 months of data from each home). The proposed model has two components: a self‐supervised transformation learning and an ensemble classification model for agitation likelihood. Ten different neural network encoders are learned to create pseudo‐labels using the samples from the unlabelled data. We use these pseudo‐labels to train a classification model with a convolutional block and a decision layer. The trained convolutional block is then used to learn a latent representation of the data for an ensemble classification block.

Results

Comparing with baseline models such as LSTM network, Bidirectional LSTM (BiLSTM) network, VGG, ResNet, Inception, Random Forest (RF), Support Vector Machine (SVM) and Gaussian Process (GP) classifiers, the proposed model performs better in sensitivity (recall) and area under the precision‐recall curve with at most 40% improvement. The recall measure using the 10‐fold cross‐validation technique is 61%.

Conclusion

This method can support early interventions and help develop new pathways to support people affected by dementia. A limitation in our current study is that the environmental and movement data is at the home level and not personalised.
From brain volumes to subgroup classification in genetic mutation carriers for frontotemporal dementia: A cluster analysis in the GENFI study
Authors: Bocchetta Martina , Todd Emily G. , Nicholas Jennifer M. , Heller Carolin , Swift Imogen J. , Peakman Georgia , Cash David M. , Convery Rhian S. , Russell Lucy L. , Thomas David L. , Iglesias Juan Eugenio , van Swieten John C. , Jiskoot Lize C. , Seelaar Harro , Borroni Barbara , Galimberti Daniela , Sanchez‐Valle Raquel , Laforce Robert , Moreno Fermin , Synofzik Matthis , Graff Caroline , Masellis Mario , Tartaglia Maria Carmela , Rowe James B. , Vandenberghe Rik , Finger Elizabeth , Tagliavini Fabrizio , Mendonca Alexandre , Santana Isabel , Butler Christopher , Ducharme Simon , Gerhard Alexander , Danek Adrian , Levin Johannes , Otto Markus , Sorbi Sandro , Ber Isabelle Le , Pasquier Florence , Rohrer Jonathan D. ,   Genetic Frontotemporal dementia Initiative (GENFI)
Published: December 2021

Background

Genetic frontotemporal dementia (FTD) is highly heterogeneous, with carriers of mutations in the same gene manifesting different phenotypes. Using in vivo MR images from the Genetic FTD Initiative (GENFI), we aimed to identify subgroups within the same genetic group whose brains were affected differently.

Method

Cortical and subcortical volumes of interest were generated using automated parcellation methods on volumetric 3T T1‐weighted MRI scans for 479 carriers (198 GRN, 202 C9orf72, and 79 MAPT mutation carriers). W‐scores for 85 volumes of interest were computed from a linear regression model carried out on 298 non‐carrier cognitively normal controls adjusting for the effect of age, sex, total intracranial volume and scanner type. Cluster analyses with the Ward agglomerating method were performed on all w‐scores while considering the three genetic groups independently. The identified clusters were then compared for age, estimated years from onset, global and sum of boxes scores of the CDR® plus NACC FTLD (at baseline and after one year), neurofilament light chain (NfL) levels in the plasma and w‐scores in brain regions typically showing early atrophy (Kruskal‐Wallis test).

Result

We identified three clusters among the GRN mutation carriers and four in the MAPT and C9orf72 groups, which were all significantly different for the variables reported in the Table (p‐value<0.003). For all three genetic groups, one cluster was formed by patients with a clinical diagnosis of FTD, with more extensive atrophy and increased disease severity. For the remaining clusters, there seemed to be an association with disease severity for MAPT and GRN mutation carriers but not so for C9orf72 expansion carriers where clinical scores were not clearly associated with a specific cluster.

Conclusion

By only looking at regional brain volumes, we were able to detect different clusters within carriers of mutations in the same gene, with C9orf72 expansion carriers being the most heterogenous group. Further investigations with specific cognitive, clinical and biomarkers correlates, including further follow‐up visits, are needed.