bluuebunny/crossref_metadata_2025 huggingface dataset:
Using an external control to contextualize efficacy data from patients with prodromal and mild Alzheimer’s disease treated with gantenerumab in SCarlet RoAD and Marguerite RoAD open‐label extension studies
Authors: Delmar Paul , Huang Zhiyue , Neve Anuja , Klein Gregory , Kerchner Geoffrey A. , Fontoura Paulo , Baudler Monika , Doody Rachelle S.
Published: December 2022

Background

Gantenerumab, a human monoclonal antibody targeting aggregated beta‐amyloid (Abeta), is a potential disease‐modifying treatment for early (prodromal‐to‐mild) Alzheimer’s disease (AD). SCarlet RoAD (SR) (NCT01224106) and Marguerite RoAD (MR) (NCT02051608) were two Phase III trials with open‐label extensions (OLEs), during which participants were treated with up to 1,200 mg/month of subcutaneous gantenerumab for up to 5 years. Substantial Abeta removal was confirmed without new or unexpected safety findings. This work aims to evaluate the gantenerumab treatment effect during the SR and MR uncontrolled OLE studies by using an external control group based on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort.

Method

Participants from the ADNI studies were weighted using the inverse probability of treatment weighting method1 to make their demographics and baseline characteristics more comparable to the patients in the OLE stages of the pooled SR and MR studies. In the weighted sample, the treatment effects of gantenerumab, per change from the OLE Baseline in Clinical Dementia Rating – Sum of Boxes (CDR‐SB), Alzheimer’s Disease Assessment Scale – Cognitive subscale 13 (ADAS‐Cog13), and Mini‐Mental State Exam (MMSE) at Weeks 104 and 156 were investigated by a mixed‐effect model of repeated measure.

Results

Applying inclusion and exclusion criteria from the ongoing GRADUATE gantenerumab trials (NCT03444870, NCT03443973) to the SR and MR OLE cohorts, 164 participants from the SR and MR OLE studies and 1,218 participants from ADNI were selected. After weighting, the demographics and baseline characteristics were comparable between the two populations. A comparison of relative reductions between the pooled participants in SR and MR OLE studies and weighted ADNI participants can be found in Table 1.

Conclusions

When comparing participants in the SR and MR OLE studies to a matched ADNI control group, a slower progression was observed with gantenerumab treatment. Specifically, gantenerumab showed effects on slowing cognitive decline in the SR and MR OLE studies compared with weighted ADNI participants on the CDR‐SB and ADAS‐Cog13 scales, although with a smaller effect on MMSE. The efficacy and safety of gantenerumab in early AD participants will be assessed in the two ongoing Phase III GRADUATE trials.

1. Austin PC & Stuart EA, 2015; Stat Med. 34:28
Multi‐modal Analysis and Modeling of Human Neurodegenerative Disease to Reveal Disease Mechanisms and Biomarkers
Authors: Marsh Samuel E , Murphy Sarah , Kamath Tushar , Gazestani Vahid , Therrien Martine , Dolan Michael John , Jereb Sasa , Reyes Miguel , Gobom Johan , Clish Clary , Hacohen Nir , Zetterberg Henrik , Leinonen Ville , Macosko Evan , Stevens Beth
Published: December 2022

Background

Microglia have emerged as key players in the pathogenesis of neurodegenerative conditions such as Alzheimer’s disease (AD), taking on distinct transcriptional and functional states. While the ability to profile complex tissues at single‐cell resolution in postmortem brain tissue provides insight into disease‐associated cellular states within the brain, more is required to understand how these changes modulate disease pathogenesis. Building on foundational transcriptomics, the advances in multi‐modal profiling of genomics and proteomics allows for a greater understanding of neuroimmune dysfunction in neurodegenerative disease.

Method

Transcriptomic datasets are often confounded by variability in collection and sequencing methodologies. We have optimized tissue dissociation and cell isolation protocols to avoid many of the pitfalls commonly found in bulk and single‐cell transcriptomic studies. Using these optimized protocols, we have begun assessing paired samples (blood, brain biopsy, and cerebrospinal fluid (CSF), from patients at risk for AD to understand neuroimmune changes in early‐phases of AD. We have also characterized the transcriptional and functional responses of human induced pluripotent stem cell (iPSC) microglia in response to a variety of neurodegenerative brain‐relevant challenges, including amyloid, apoptotic neurons and synaptic debris.

Result

Using scRNA‐seq on fresh mouse and human tissue we have identified a dissociation‐induced signature in microglia that is highly prevalent in current literature, and developed an experimental methodology to prevent this artifact. We have also identified a similar signature in post‐mortem tissue via snRNA‐seq that may be the result of acute‐pre/post‐mortem processes (Marsh et al., 2022). Powerfully, we also have cerebrospinal fluid (CSF) from the same patients, allowing us to correlate proteomic and transcriptomic analyses to determine the connections between disease‐associated transcriptomic cell states and analyte biomarkers. We can then use the iPSC microglia (iMGLs) to understand how altered transcriptomic states and biomarker profiles may alter microglial functions to elucidate mechanisms by which microglia contribute to disease pathogenesis.

Conclusion

Optimization of experimental and analysis methods along with extensive multi‐modal profiling of the same patients will lead to greater understanding of the neuroimmune landscape of neurodegenerative disease to better enable development of novel predictive biomarkers and therapeutic targets.
sTREM2 affects cytokine expression profiles in THP‐1 cell model.
Authors: Arsenault Ryan , Li Qiao , Zhang Wandong
Published: December 2022

Background

TREM2 is an innate immune receptor expressed on myeloid cells such as microglia and macrophages and is involved in several crucial cellular response pathways including activation and inflammation. TREM2 is cleaved from cell surface by ADAM10/17 releasing as soluble TREM2 (sTREM2) and is reported to be elevated in CSF of AD patients. The relationship between inflammation and sTREM2 remains largely uncharacterized.

Method

THP‐1 cells were used as a myeloid model. Cells were cultured and treated with different concentrations of human recombinant sTREM2 at 2‐, 4‐, 6‐, and 8‐hour time points. LPS was used as a positive control. RT‐qPCR was used to analyze the expression of several key inflammatory and anti‐inflammatory cytokines. A commercial monoclonal rat anti‐human TREM2 IgG antibody was pre‐incubated with sTREM2 before treatment to assess its ability to mitigate effects of sTREM2 in culture.

Result

LPS significantly stimulated the expression of TNF‐α, IL‐1β, and IL‐6 as compared to control at all time points, and IL‐10 to a lesser extent. 0.1µg/mL sTREM2 was capable of stimulating the expression of several key pro‐inflammatory cytokines such as TNF‐α, IL‐1β, and IL‐6 post‐treatment. 0.1µg/mL sTREM2 also stimulated the expression of anti‐inflammatory cytokines IL‐10 and CCL17 post treatment. 1.0µg/mL sTREM2 was also capable of stimulating the expression of these cytokines while seemingly affecting the expression of anti‐inflammatory cytokines more consistently. Pre‐incubation of sTREM2 with monoclonal antibody was sufficient at alleviating the expression of TNF‐α, IL‐10 and CCL‐17 induced by exogenous sTREM2. However, the expression of IL‐1β and IL‐6 were amplified following either treatment with antibody alone or sTREM2+antibody.

Conclusion

Exogenous sTREM2 at a lower concentration (0.1 µg/mL) seems to stimulate expression of several pro‐inflammatory cytokines, while sTREM2 at both a lower (0.1 µg/mL) and a higher concentration (1µg/mL) appear to stimulate the expression of anti‐inflammatory cytokines more consistently in our myeloid cell model. Possibly indicating that different concentrations of sTREM2 may have different effects on cytokine expression profiles in the cell model. Co‐incubation of sTREM2 with a monoclonal anti‐human TREM2 antibody was sufficient to neutralize the effects of sTREM2 on inducing the expression of some cytokines but promoted others.
Deciphering the clinico‐radiological heterogeneity of dysexecutive Alzheimer’s disease using unsupervised machine learning techniques
Authors: Corriveau‐Lecavalier Nick , Barnard Leland R , Lee Jeyeon , Botha Hugo , Graff‐Radford Jonathan , Machulda Mary M. , Knopman David S. , Lowe Val J. , Boeve Bradley F. , Petersen Ronald C. , Jack Clifford R. , Jones David T.
Published: December 2022

Background

Dysexecutive Alzheimer's disease (dAD) is a relatively early‐onset variant of AD primarily degrading core executive functions in the absence of predominant behavioral symptoms. Clinical observations suggest substantial variability in clinical, cognitive and neuroimaging profiles within this syndrome. In this presentation, we will discuss our ongoing work disentangling this heterogeneity using unsupervised machine learning techniques.

Method

We collected clinical, neuropsychological and multimodal imaging (MRI, FDG‐PET, amyloid‐PET, tau‐PET) data on 52 dAD patients assessed in our behavioral neurology clinic at Mayo Clinic Rochester. We first performed a spectral clustering analysis based on FDG‐PET to delineate latent patterns of network degeneration (referred as “eigenbrains”) and assessed the relationships between these eigenbrains and clinical and cognitive symptomatology. We then performed a hierarchical clustering on these eigenbrains to derive data‐driven subtypes of dAD. We compared clinical and cognitive data between subtypes, and then compared the imaging profiles to 52 amyloid‐negative age‐ and sex‐matched controls.

Result

Six eigenbrains explained approximatively 48% of the variance in FDG‐PET patterns and primarily reflected heteromodal to primary motor/sensory, left‐right hemispheric asymmetry, and anterior‐to‐posterior gradients of macro‐scale cortical organization (Fig 1). These eigenbrains differentially related to reported age at symptom onset, degree of clinical impairment, and performance on a wide range of cognitive domains (executive functions, episodic memory, and visuospatial). Hierarchical clustering revealed four dAD subtypes (diffuse, biparietal, left‐hemisphere, right‐hemisphere). These subtypes differed in reported age at symptom onset and cognitive profile, where the heteromodal‐diffuse subtype exhibited an overall worse clinical picture and the biparietal had a milder profile compared to other subtypes, which was not explained by disease duration. Additionally, spatial patterns of tau distribution and neurodegeneration overlapped with patterns of FDG‐PET hypometabolism in each subtype, whereas patterns of amyloid deposition were similar across subtypes (Figs 2 & 3).

Conclusion

Almost half of the variance in macro‐scale patterns of hypometabolism in this dAD cohort was accounted for by six eigenbrains. These eigenbrains captured the inter‐individual variability in age at symptom onset and cognitive impairment. Four dAD subtypes derived from these eigenbrains revealed meaningful differences in clinical, cognitive, and imaging profiles. Recognizing this heterogeneity has significant clinical implications for diagnosis, prognosis, and symptom monitoring.
A gene expression signature for Alzheimer’s from finger prick blood spotted on a filter paper card
Authors: Seligmann Bruce , Babic Milos , Scully Kathleen , Yeakley Joanne M , Sahagian Gregory
Published: December 2022

Background

There is an unmet need for a minimally invasive clinical test using samples collected by medical staff or by self‐collection to screen persons at risk for Alzheimer’s disease (AD) for initial diagnosis as well as for monitoring progression. Addressing this need is even more challenging for underserved and rural populations. Currently, use of whole blood has required venipuncture and RNA extraction. None‐the‐less, AD gene expression signatures using RNA extracted from whole blood have been reported by a number of groups. We have developed a direct, extraction‐free TempO‐Seq® assay of gene expression using blood from a finger prick spotted on filter paper. This novel method is perhaps the simplest and least invasive method of obtaining a blood sample and performing a test that can be used to identify a diagnostic Alzheimer’s signature.

Method

The targeted sequencing of the whole transcriptome via the TempO‐Seq® gene expression assay (Yeakley, PLosOne doi.org/10.1371/journal.pone.0178302) was adapted to utilize blood spotted on filter paper. Samples were obtained under an IRB‐approved protocol from normal volunteers and patients clinically diagnosed with AD or Parkinson’s disease (PD).

Result

A protocol that eliminated interference by components of whole blood with enzymes used in molecular biology assays was successfully implemented. This permitted a TempO‐Seq assay to be carried out without extraction of RNA from the filter paper blood spots. Highly expressed genes were attenuated to increase the sensitivity with which AD biomarker genes could be measured. The shelf‐life of blood spotted filter paper stored at room temperature was greater than 6 months. AD, PD, and normal control blood samples were assayed and a proposed gene expression signature for AD was identified.

Conclusion

Use of a simple gene expression‐based assay of blood from a finger prick spotted on filter paper to diagnose AD is feasible. The spotted blood sample is stable for months at room temperature, permitting self‐collection or assisted collection and mailing of samples for testing.
Menopause age and hormone therapy use moderate PET tau and amyloid association: findings from the Wisconsin Registry for Alzheimer Prevention
Authors: Coughlan Gillian T , Koscik Rebecca Langhough , Betthauser Tobey J , Boyle Rory Thomas , Jonaitis Erin M. , Wenzel Allen , Christian Bradley T , Gleason Carey E. , Klinger Hannah , Properzi Michael J , Schultz Aaron P. , Hanseeuw Bernard J , Rentz Dorene M. , Johnson Keith A. , Sperling Reisa A. , Johnson Sterling C. , Buckley Rachel F.
Published: December 2022

Background

Sex differences in tau deposition are apparent in clinically normal older adults. Abnormal β‐amyloid (Aβ) may strengthen this association between sex and tau. Whether hormone therapy (HT) and menopause influence this higher tau retention in women and whether this is contingent upon levels of Aβ burden is unclear. We examined differences in the cross‐sectional association between Aβ and regional tau deposition as a function of sex, HT‐exposure and age‐at‐menopause.

Method

Data were collected from 292 cognitively unimpaired individuals from the Wisconsin Registry for Alzheimer’s Disease (mean age 67.43; 193 women [66%]; 106 APOE ε4 carriers [37%]) who underwent dynamic0‐70 [C‐11] Pittsburgh Compound‐B [PiB] and [F‐18]‐MK‐6240 PET. The PiB distribution volume ratios (DVR) index reflects cortical Aβ burden. 90 [46.6%] women reported use of HT (past/current). Seven a priori tau regions previously demonstrating sex differences were selected (entorhinal cortex, amygdala, inferior temporal gyrus, middle and inferior temporooccipital gyri, superior parietal lobule and fusiform gyrus). Linear regressions (covarying current age) examined the sex*PiB‐DVR‐index interaction for each tau‐PET outcome and a preclinical Alzheimer’s cognitive composite (PACC). Similar models were examined in women alone for the same outcomes, investigating HT*PiB‐DVR‐index and age‐at‐menopause*PiB‐DVR‐index interactions (modeled separately).

Result

Women exhibited higher tau‐PET with an increasing PiB‐DVR‐index relative to men (FDR p’s: <0.002 in 5 of 7 tau regions; Fig 1). The HT*PiB‐DVR‐index analyses indicated that women with a higher PiB‐DVR‐index and self‐reported HT use exhibited higher tau in five regions (Fig2). Exploratory analyses suggested the HT*PiB‐DVR‐index interaction was strongest in women over the median current age (63.5years). The age‐at‐menopause* PiB‐DVR‐index interaction was significant in all regions and for the PACC, revealing subtle cognitive deficits in women with earlier age‐at‐menopause.and a higher PiB‐DVR‐index burden (Fig3).

Conclusion

Replicating previous studies, tau deposition was elevated in women compared with men. Hormone therapy use and earlier age‐at‐menopause influenced the association between Aβ and tau and between Aβ and cognition. Cognitively unimpaired women with elevated Aβ burden may be vulnerable to hormonal changes related to hormone therapy and early menopause and should be prioritized for future anti‐tauopathy clinical trials.
Differences in self and proxy assessments regarding motivation, quality of life and care dependency of people with dementia considering a technology‐based intervention
Authors: Zuschnegg Julia , Schüssler Sandra , Paletta Lucas , Holter Magdalena , Lodron Gerald , Orgel Thomas , Russegger Silvia , Schneeberger Michael , Fellner Maria , Steiner Josef , Pansy‐Resch Sandra , Prodromou Dimitrios , Brunsch Sebastian , Carnevale Lorenzo , Lammer Lara , Roller‐Wirnsberger Regina
Published: December 2022

Background

Self‐reported assessments of people with dementia (PwD) are sparsely used in research, which may be due to the progressive impairment of cognitive functioning and higher time expenditures for assessments. Proxy assessments by healthcare professionals or relatives are often used instead. The aim was to investigate whether a technology‐based intervention significantly influences self and proxy assessments of PwD’s quality of life (QoL), motivation, and care dependency.

Method

Data from the RCT of the project AMIGO were used. 32 community‐dwelling people with mild to moderate dementia and their relatives received either a humanoid social robot combined with a tablet‐based dementia training (IG) or a tablet‐based dementia training only (CG). Self and proxy versions of three standardized measurements (AES, DEMQoL, PAS) assessing motivation, QoL, and care dependency were used and analyzed using descriptive statistics and Wilcoxon signed‐rank tests.

Result

Compared with proxy assessments by relatives, PwD rated themselves better in all outcomes, regardless of group allocation or time points. At baseline, the median differences (MD) differed significantly between self and proxy assessments in IG and CG participants regarding PwDs’ motivation (16.0, p<0.001; 9.0, p<0.001) and care dependency (11.0, p = 0.014; 7.0, p = 0.002), while for QoL this was only the case in the CG (11.0, p = 0.035) and not in the IG (5.0, p = 0.139). After intervention, all outcomes in the IG and CG were significantly differently rated by PwD and relatives demonstrated by the MD for motivation (8.0, p<0.001; 12.0, p = 0.0101), QoL (16.0, p = 0.0023; 16.5, p = 0.030) and care dependency (12.0, p = 0.006; 4.5, p = 0.019).

Conclusion

There are significant differences of assessments between relatives and PwD, which could be due to a reduced illness insight of PwD, different foci of PwD and relatives on scale domains (e.g., psychosocial, physical), or an influence of relatives' attitudes and burden. However, QoL in the IG was not perceived differently at baseline, but after the intervention. This finding as well as the significant increase of self‐reported QoL, but the non‐significant proxy evaluation in the main study, highlight the PwDs’ ability to assess themselves and the necessity to involve them in research evaluations.
Algorithmic Fairness in Biomarker‐Based Machine Learning Models to Predict Alzheimer’s Dementia in Individuals with Mild Cognitive Impairment
Authors: Sahin Derya , Jessen Frank , Kambeitz Joseph ,   Alzheimer's Disease Neuroimaging Initiative (ADNI)
Published: December 2022

Background

With increasing availability of large‐scale data sets in biomedical research, machine learning (ML) algorithms rapidly gain importance for research and clinical practice. However, ML models bear the risk of increasing health disparities, whenever trained with imbalanced or biased data. Based on these ethical concerns the WHO guidelines on Artificial Intelligence for Healthcare recommend incorporating algorithmic fairness in ML models by design. Although research on biomarker detection and dementia risk prediction in Alzheimer’s disease increasingly employs ML algorithms, the fairness of these models has not been in focus to date.

Method

Using data from the Alzheimer’s Disease Neuroimaging Initiative database, we generated ML models to predict conversion to Alzheimer’s dementia in 1017 individuals with mild cognitive impairment. Two models were trained based on (1) biomarkers and (2) biomarkers and demographic features. Subsequently, fairness metrics were calculated to investigate prediction disparities in the trained models regarding sensitive attributes sex, education, race and ethnicity.

Result

The models did not show substantial differences in predictive performance. Compared to Non‐Hispanic‐White individuals, true positive rates for Hispanics and for Non‐White individuals were lower in the biomarker model. Inclusion of demographic features to the model led to a further drop of true positive rates and positive predictive values for both Hispanics and Non‐White individuals. None of the models showed any predictive disparities regarding sex and education, with both models having a slightly higher accuracy, positive predictive value, and negative predictive value for women and for individuals with lower educational attainment.

Conclusion

This study empirically demonstrates the potential ethical hazards of ML models for the prediction of conversion to Alzheimer’s dementia. While ML models exhibit fair prognostication when based on balanced data regarding sensitive attributes, underrepresentation of specific groups may lead to violations of fairness criteria with important implications for the clinical translation of these models. Such fairness disparities can be present in models based on only biological data and the inclusion of demographic information might exacerbate the predictive disparities in ML‐models.
Computerized cognitive interventions for preventing dementia in people with mild cognitive impairment: A systematic review with meta‐analyses
Authors: Zuschnegg Julia , Schoberer Daniela , Häussl Alfred , Russegger Silvia , Ploder Karin , Fellner Maria , Hofmarcher‐Holzhacker Maria , Roller‐Wirnsberger Regina , Paletta Lucas , Koini Marisa , Schüssler Sandra
Published: December 2022

Background

People with mild cognitive impairment (MCI) are faced with a higher risk of developing dementia, but with a "window of opportunity" for prevention and treatment. Computerized cognitive interventions (CCIs) might constitute a beneficial non‐pharmacological treatment approach. This systematic review evaluated evidence of CCIs performed individually with a computer, tablet‐PC, game consoles, virtual reality (VR), or augmented reality (AR) on cognition in community‐dwelling people with MCI.

Method

A systematic review and meta‐analyses of randomized controlled trials (RCTs) was performed. The systematic literature search was conducted in MEDLINE, CINAHL, Embase, Cochrane CENTRAL, IEEE Xplore Digital Library, ISI Web of Knowledge, Scopus and PsycINFO, and included an additional search for gray literature. The search was completed by backward citation tracking. The methodological quality of the included RCTs was independently assessed by two reviewers. Comparable studies were pooled using the random‐effects model.

Result

A total of 18 randomized controlled trials (RCTs) were identified. 12 RTCs were used for conducting meta‐analyses which showed significant effects of CCIs for people with MCI in memory (SMD 1.12, CI 95 % [0.08, 2.16]), working memory (SMD 0.85, CI 95 % [0.32, 1.38]), attention/concentration/processing speed (SMD 0.61, CI 95 % [0.21, 1.02]), executive functioning (SMD 0.96, CI 95 % [0.26, 1.66]), and language (SMD 1.63, CI 95 % [0.20, 3.06]), but no significant improvement in global cognition. Pooling follow‐up evaluations was not possible, but one of two studies showed continuing significant differences for the intervention group after 6 months post intervention in memory and working memory. CCIs were conducted predominantly with computers, followed by tablet‐PCs, VR, AR, and mixed reality.

Conclusion

This review demonstrated beneficial effects of CCIs on domain‐specific cognition in people with MCI. Therefore, CCIs might be a valuable treatment option to maintain cognition and prevent progression to dementia. However, further research is necessary, especially on CCIs applied with emerging technologies like VR or AR. Furthermore, various outcome measurements used in the studies were challenging for the pooling of study results, which highlights the need for a predefined set of important cognitive outcomes and tools for future RCTs.
Weighted Gene Co‐Expression Network Analysis for peripheral whole‐blood RNA sequencing in asymptomatic Alzheimer’s disease
Authors: Luckett Emma S. , Zielonka Magdalena , Schaeverbeke Jolien , Adamczuk Katarzyna , Van Laere Koen , Dupont Patrick , Cleynen Isabelle , Vandenberghe Rik
Published: December 2022

Background

Alzheimer’s disease (AD) blood‐based biomarkers are becoming widely researched. Their requirement in the asymptomatic phase of AD is high to determine individuals who are in the early stages of disease. We investigate gene network expression to better understand molecular changes in this asymptomatic phase.

Method

RNA was extracted and sequenced for 63 cognitively healthy Flemish Prevent AD Cohort KU Leuven (F‐PACK) participants (70 (56‐80) years) at baseline and follow‐up (interval: 4.6 (3.4‐8.59) years, 30 APOE4 carriers). Participants received amyloid‐PET and structural MRI at both timepoints. We performed weighted gene co‐expression network analysis (WGCNA) to identify networks of co‐expressed genes at baseline. These modules were correlated with traits of interest (APOE4 (present/absent) and amyloid rate of change ([follow‐up – baseline amyloid load], divided by time interval (years)) using Pearson’s correlation coefficient. Significantly correlated modules were functionally annotated using Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) in R. Potential hub genes were identified if the module contained genes with eigen‐based connectivity >0.7. These were visualised using STRING to create protein‐protein interaction networks. The top four hub genes (with highest Maximal Clique Centrality values) were then selected.

Result

A gene co‐expression network was built on 9,149 genes that passed the read count threshold (genes with >10 read counts in >90% of samples). From this co‐expression network, 22 co‐expression modules were constructed (Figure 1A) and correlated with traits of interest. For the tan module (including 188 genes) APOE4 carriership was significantly negatively correlated (p=0.03, r=‐0.22), whereas amyloid rate of change was significantly positively correlated (p=0.03, r=0.21). Top GO processes for this module included T cell activation and differentiation, and top KEGG pathways included T cell receptor signalling, and Th1 and Th2 cell differentiation. The top four hub genes were GZMA, NKG7, TBX21 and PRF1 (Figure 1B).

Conclusion

Baseline gene expression networks differ between APOE4 carrier status, and with respect to amyloid rate of change. This suggests there are network alterations in the asymptomatic phase of AD that can be detected in blood. These results may aid in development of targets for biomarker development or druggable targets for AD.
Using a digital assessment of multi‐day learning curves to detect preclinical AD
Authors: Weizenbaum Emma L , Soberanes Daniel , Hsieh Stephanie , Schneider Olivia R , Buckley Rachel F. , Properzi Michael J , Rentz Dorene M. , Johnson Keith A. , Sperling Reisa A. , Papp Kathryn V. , Amariglio Rebecca E.
Published: December 2022

Background

Unsupervised remote digital cognitive assessment makes frequent testing feasible and allows for measurement of learning across days on participants’ own devices. More rapid detection of diminished learning may provide a potentially valuable metric for clinical trials seeking to capture change over shorter intervals. Here, we assess whether clinically normal (CN) participants differ in their learning of the same stimuli across daily exposures depending on their β‐amyloid (Aβ) burden.

Method

The Boston Remote Assessment for Neurocognitive Health (BRANCH) (Papp et al., 2021) is a web‐based assessment administered over 7 consecutive days repeating the same stimuli each day to capture multi‐day‐learning‐curves (MDLC). The composite score includes accuracy on three cross‐modal associative memory tasks: face‐name, groceries‐prices, digits‐signs. Our sample consisted of 192 CN older adults enrolled in ongoing observational studies (mean age = 74.0, 63% female, 87% Caucasian, mean education = 16.6) who completed the tasks daily at home on their own digital devices. Participants had previously completed in‐clinic paper‐and‐pencil tests to compute a Preclinical Alzheimer’s Cognitive Composite (PACC‐5) as well as PET imaging with 11C‐Pittsburg Compound‐B to estimate globalAβ burden and classify participants as Aβ+ and Aβ‐. Mixed‐effects models controlling for age, sex, and education were used to observe the associations between Aβ status and BRANCH‐MDLC; and AUC analyses compared classification of amyloid using BRANCH‐MDLC vs. PACC‐5.

Result

Adherence was high with 95% of participants completing all seven days of consecutive assessment. Aβ+ status (n = 26) was associated with a lower BRANCH‐MDLC across 7‐days (t = ‐4.03, p<.001) compared with Aβ‐ status (n = 148). Amyloid status was not associated with difference in Day 1 BRANCH or PACC‐5 performance. Furthermore, BRANCH‐MDLC showed a significant ability to classify individuals as Aβ+ vs. Aβ‐ (AUC = 0.71, p = <.001) compared to a single‐timepoint pencil‐and‐paper composite (PACC‐5) (AUC = 0.52, p = 0.56).

Conclusion

Diminished task learning across seven days was associated with greater amyloid pathology, whereas Day 1 of BRANCH or an in‐person supervised one‐time neuropsychological assessment were not associated with elevated amyloid. These findings signal the value of measuring differences in learning across days as a means towards capturing biomarker‐associated memory decrements and identifying those in the preclinical stage of AD.
Neuroanatomy of dementia in Down Syndrome revealed using a voxel‐based morphometry approach to computed tomography
Authors: Zhang Linda , Sanchez Beatriz , Moldenhauer Fernando , de Asua Diego Real , Brudfors Mikael , Foulon Chris , del Ser Teodoro , Ashburner John , Nachev Parashkev , Strange Bryan A
Published: December 2022

Background

People with Down syndrome (DS) are more likely to develop Alzheimer’s disease than the general population, but comorbidities and variable intellectual disability complicate diagnosis and disease monitoring. Although neuroimaging may help elucidate the pathogenesis of dementia, studies using magnetic resonance imaging (MRI) in DS subjects with dementia are limited due to greater motion artefact in those with severe cognitive impairment. Computed tomography (CT) is faster, thus less impacted by motion, but poor tissue contrast makes analysis of cortical and subcortical changes difficult. In this study, we use CTseg, an algorithm able to robustly spatially normalise and segment CT scans, to analyse grey matter (GM) and white matter (WM) differences in 98 DS subjects with and without cognitive impairment due to dementia.

Methods

The CT scans of 120 DS patients from the Adult Down Syndrome unit at the Hospital Universitario La Princesa were selected. Dementia level was classified by retrospective review of medical records as 0 (cognitively stable), 1 (mild dementia), 2 (moderate dementia), or 3 (advanced dementia) according to the DSM‐V operational criteria. Premorbid functionality was assessed using Part 1 (“Level of ‘best’ ability”) of the Dementia Screening Questionnaire for Individuals with Intellectual Disabilities (DSQIID). Those with artefacts, faulty scans, or incidental brain findings were excluded, leaving a final sample of 98 subjects (mean age: 48±8.5 years; 45% female; 62 cognitively stable). CT scans were segmented into GM, WM, and cerebrospinal fluid using CTseg (https://github.com/WCHN/CTseg). Voxel‐based morphometry (VBM) analyses were carried out separately on smoothed and modulated GM and WM images, correlating with dementia level whilst controlling for age, sex, DSQIID, and total intracranial volume.

Results

GM volume was significantly negatively correlated with dementia level in the bilateral parahippocampal gyri, extending into hippocampus, and amygdalae. By contrast, significant WM reductions associated with dementia level were primarily parietal and occipitotemporal and right‐lateralised in the superior and inferior longitudinal fasciculi (p<0.001, FWE‐corrected).

Conclusions

Our study uses a novel algorithm that allows the analysis of CT scans using VBM methods, enabling the inclusion of a sizeable sample of DS subjects with dementia, a group difficult to study with neuroimaging due to practical constraints.
The cost burden of Alzheimer’s Disease on care partners
Authors: Hahn‐Pedersen Julie Hviid
Published: December 2022

Background

Alzheimer’s Disease (AD) has significant impact on care partners. We conducted a systematic literature review to assess the economic impact of AD with special attention to care partners and disease progression.

Method

A protocol was developed before searches in PubMed, Embase and PsycINFO were run November 2021 via the Silvi.ai‐platform. Conduct of the systematic literature review followed standard guidelines. Eligible studies were in English and provided data from earliest Jan 2011 – Nov 2021.

Result

Of 1043 identified hits, 25 studies were relevant for data extraction. AD costs were defined heterogeneously between studies, however most studies included AD drugs, out‐ and inpatient visits as well as non‐AD drugs (anti‐psychotics, supplements etc).

7 of the 25 studies specifically explored the cost burden of AD for care partners; hours needed to support the partner, loss of work productivity, and implications for future employability.

Monthly cost of caretaking was similar across studies and countries and varied between €643 ‐ €1050 for mild AD in Germany and Spain, €804‐ €1329 for moderate AD in France and Germany, to €1515 ‐ €2376 for severe AD in UK and Germany, respectively. The major cost driver was severity of the clinical status of the patient.

Only few studies reported on work impairment of care partners. A study comparing matched care partners vs. non‐care partner demonstrated significantly higher activity impairment (25.4% vs. 21.8%), greater absenteeism (5.4% vs.3.1%), presenteeism‐related impairment (22.7% vs. 18.4%), and overall work impairment (25.8% vs. 20.4%). Same pattern, showing an increase in work impairment with AD severity was seen across countries (US, Japan and EU5).

Conclusion

Most identified studies focused on the cost burden on society or patients. In 7 studies reporting cost impact on care partners, the cost burden was very similar across countries and health care systems. Cost impact on care partners increased from early to severe AD. In particular, work impairment increased significantly with AD severity. However, more research is needed to identify the true cost burden for care partners.
A Compendium Of Two Decades Of Economic Evaluations In Dementia And A Critique Of The Implied Use Of Resources
Authors: Trepel Dominic
Published: December 2022

Background

This paper presents a unified source of all health economic evaluations related to four categories of resource allocation in dementia (identification, pharmaceuticals, non‐pharmacological interventions and management strategies) and, for health professionals (i.e. non‐economists), we provides guided critiques of implied trade‐offs across varying allocation decisions.

Methods

To take stock of the entirety of economic evidence, we systematically review, and quality assess, all peer reviewed cost‐effectiveness analyses published since 1999. We provides in‐depth expert guidance, and objective critical appraisal, through the variety of implied inferences related to potential allocation decisions and avoid sources of underlying biased. We explain how to interpret, and differentiate between, the two common forms of economic evidence (i.e., trial‐based or model‐based cost effectiveness analysis). We illustrate strengths and weaknesses of our included studies and, towards informing optimal resource allocation, we detail the opportunities and threats in relation to quality of evidence.

Results

Since 1999, we found 127 published economic evaluations (identification, 20%; pharmaceuticals, 45%; non‐pharmacological approaches, 18% and; management strategies, 17%). Internationally, the top five countries producing economic evaluations in dementia were: UK (33%); USA (19%); the Netherlands (10%) Canada (7%) and; (jointly) Germany/Sweden (5%). Over time, production of economic evidence appears relatively flat (averaging 1 to 2 publications per category) but significant upsurges in pharmaceutical‐related studies occurred in 2005 (n = 5), 2010 (n = 8) and 2012 (n = 8). Reporting is generally found to meet objective international standards, however, our critique of model‐based techniques raises concerns. Examining funding sources, industry‐funded pharmaceutical studies appear more likely to report more favourable cost effectiveness results, with these exclusively simulation‐based studies often purporting more cost savings (as compared to publicly‐funded studies). Notwithstanding concerns, the sum of evidence indicates that, compared to usual dementia care, alternative resource allocation can often result in increased quality‐of‐life, whilst also reducing costs.

Conclusion

In contrast to competing disease areas, dementia research has experienced a relatively low production of economic evidence. Given the considerable economic changes created by dementia, and potential for economic benefit highlight here, increasing the inclusion of high quality economic evaluations alongside dementia‐related research is required.
Elevated tau‐PET signal predicts near‐term conversion to mild cognitive impairment in cognitively unimpaired older adults
Authors: Strikwerda‐Brown Cherie , St‐Onge Frederic , Binette Alexa Pichet , Ozlen Hazal , Buckley Rachel F. , Sperling Reisa A. , Johnson Keith A. , Poirier Judes , Breitner John , Villeneuve Sylvia ,   HABS Research Group, PREVENT‐AD Research Group
Published: December 2022

Background

National Institute on Aging‐Alzheimer’s Association workgroups have proposed biological research criteria to identify individuals with preclinical Alzheimer’s disease (AD). It remains unclear whether cognitively unimpaired individuals with abnormality in both amyloid (A) and tau (T) biomarkers will go on to develop a clinical AD syndrome. In two independent cohorts, we investigated whether elevated tau‐PET signal in persons with elevated amyloid‐PET predicts near‐term conversion to mild cognitive impairment (MCI). We also tested whether neurodegeneration (N), a non‐specific marker typical of later‐stage AD, improved such prediction.

Method

We studied 128 cognitively unimpaired participants from the parental history‐positive PREVENT‐AD cohort and 153 individuals from the Harvard Aging Brain Study. Participants had >1 year of clinical evaluation following tau‐PET scanning (PREVENT‐AD median follow‐up time = 3.21 years [1.51‐4.50]; HABS median=1.94 years [1.13‐5.42]). At the time of PET, participants were stratified as abnormal (+) or normal (‐) on global amyloid‐PET (A), a temporal tau‐PET meta‐ROI (T), and hippocampal volume (N). Tau‐PET scans were also visually inspected for significant neocortical binding.

Result

Within the A+T+ groups, 61.5% (8/13; PREVENT‐AD) and 45.5% (5/11; HABS) of participants converted to MCI during follow‐up, compared with <13% of participants in all other PET‐biomarker groups (Figures 1 & 2). In Cox regression models, hazard ratios for conversion to MCI in the A+T+ group vs. the other biomarker groups were all >5 (Figure 3). Importantly, the majority of the A+T+ “non‐converters” still showed longitudinal cognitive decline (80% in PREVENT‐AD and 50% in HABS), suggesting likely future clinical progression (Figures 4 and 5). By contrast, cognitive trajectories in the A+T‐, A‐T+, and A‐T‐ groups remained predominantly stable. Evidence of neurodegeneration increased MCI conversion rates in the A+T+ group to 75%, though ∼33% of A+T+N‐ individuals also progressed (Figure 6).

Conclusion

Among two cohorts of cognitively unimpaired older individuals, abnormality in both amyloid‐ and tau‐PET biomarkers was associated a dramatic increase in MCI progression within a short period of time as compared against individuals having only amyloid pathology or no pathology. These findings support the clinical prognostic relevance of a biological definition of AD in individuals without cognitive impairment.
Incorporating history into disparities research: A model for interdisciplinary collaboration and trust building
Authors: Smith Kylie M , Jeong Leanne , Hu William T. , Wharton Whitney
Published: December 2022

Background

Trust and mistrust of the healthcare system by Black and African American individuals is often cited as a primary barrier to willingness to access healthcare and low representation in clinical research. The United States Public Health Service Syphilis Study at Tuskegee is most often cited as the sole reason for this mistrust, however similar and widespread injustices, as well as the history of segregated health systems particularly in the stroke belt, laid the foundation for current health and research inequities. Medical discourses and practices positioned the Black or African American body as “inferior” and created disparities in research, diagnostic practices, and service provision.

Method

Our team collaborated with a historian of psychiatry and disability to document the historical factors that have created structural inequities in the South and beyond. The historian (KS) collected archival material related to Milledgeville Central State Hospital in Georgia including physical documents like annual reports, case studies, policies and procedures, and letters from patients. Annual reports which contained extensive diagnostic data were photocopied, computerized and analyzed to characterize patient diagnosis (mental, physical, age‐related), cause of death, and cost expended per patient, by race and gender.

Results

Our data documents the impact of segregated services, racist medical attitudes, abusive treatments, malpractices, physical labor exploitation, unlivable conditions, use of unapproved drugs, and involuntarily sterilizations in B/AA patients from 1956‐1970. Significant diagnostic disparities by race were obvious especially for “cerebral arteriosclerosis” and “schizophrenia”. Here we present data on first admissions diagnosis by age, gender, and race, as well as death rate and cause, and group level fiscal reports.

Conclusion

An analysis of historical data demonstrates clear linkages with current issues and practices. Addressing structural racism in research, education and service provision requires an honest reckoning with past practices that persist today. We demonstrate the ways that scientific teams can work with trained historians to unpack the consequences of past policies and set out a method and agenda for collaborative interdisciplinary research moving forward.
Investigating changes in fluid biomarkers in early Alzheimer’s disease: design of plasma biomarker analyses and a cerebrospinal fluid sub‐study in the evoke and evoke+ trials of semaglutide versus placebo
Authors: Cummings Jeffrey , Zetterberg Henrik , Atri Alireza , Hansen Charlotte Thim , Honore Julie Broe , Johannsen Peter , Knop Filip Krag , Raket Lars Lau , Sano Mary , Soininen Hilkka , Feldman Howard H.
Published: December 2022

Background

Several studies have generated data supporting a role for glucagon‐like peptide 1 receptor agonists (GLP‐1RA) in the treatment of Alzheimer’s disease (AD). For example, GLP‐1RAs reduced neuroinflammation and phospho‐tau accumulation, provided neuroprotective effects, and improved cognitive function in animal model studies. In patients with AD, GLP‐1RAs preserved cerebral glucose metabolism, favorably affected cognition and cortical volume, and in post‐hoc analyses of randomized clinical trials in type 2 diabetes, reduced cognitive impairment and dementia risk. The phase 3 evoke and evoke+ trials (NCT04777396 and NCT04777409, respectively) will assess the efficacy and safety of oral semaglutide (a GLP‐1RA) versus placebo in early AD. Here, we describe how fluid biomarkers will be investigated.

Method

Participants in the randomized double‐blind, placebo‐controlled evoke and evoke+ trials (N=1,840 per trial) will be randomized 1:1 to oral semaglutide 14 mg once‐daily or matched placebo for 156 weeks. The primary endpoint is change in Clinical Dementia Rating Scale – Sum of Boxes score from baseline to week 104. In both studies, fluid biomarkers will be measured in plasma (all participants [except those in China]) and cerebrospinal fluid (CSF) (a sub‐set of participants). For plasma biomarkers, blood samples will be collected at baseline (week 0) and weeks 52, 104, and 156. For CSF biomarkers, samples will be collected before randomization and at week 78, aiming for around 210 consenting participants (Figure). In each trial, participants will be stratified by CSF sub‐study participation (yes/no) to ensure 1:1 randomization in the sub‐study population. The range of biomarkers analyzed will encompass markers of AD, neuroinflammation, neurodegeneration, blood–brain barrier integrity, oxidative stress, and vascular health (Table).

Result

Results from the plasma biomarker analyses and CSF sub‐study of the evoke and evoke+ trials are expected in 2025.

Conclusion

These analyses of the evoke and evoke+ studies will investigate the effects of semaglutide on fluid biomarkers in participants with early AD. The analyses will provide insights into the mechanism of action of semaglutide on neuroinflammation and neurodegeneration (and the relationship between the two) in this population.