bluuebunny/crossref_metadata_2025 huggingface dataset:
What words and concepts do people enrolled in research registries use to describe them?
Authors: Harkins Kristin , Maloney Erin , Bleakley Amy , Langbaum Jessica B
Published: December 2021

Background

Research registries have been developed as a strategy to accelerate enrollment into Alzheimer’s disease studies. However, there remains a need to increase both total enrollment and diversity of race and gender among registry enrollees and study participants. The goal of this study was to learn how enrollees describe registries with a focus on identifying preferred terminology in order to improve outreach and recruitment efforts.

Method

Individuals enrolled in two registries (Penn Memory Center Brain Health Research Registry and Banner Alzheimer’s Institute Alzheimer’s Prevention Registry) were invited to complete an anonymous online survey. Items included demographic characteristics and open‐ended questions about how they would describe a brain health research registry. Data were collected December 2020 through January 2021 from 1,741 respondents who completed the survey. Respondents were primarily non‐Hispanic White (75.8%) and female (58.4%). To ensure diverse representation in the analysis and allow comparisons by race and gender, equally sized (n=49) random samples of respondents (Hispanic/Latinx; non‐White; non‐Hispanic White females; non‐Hispanic White males) were selected for coding and analysis in NVivo. The University of Pennsylvania IRB approved this study.

Results

Respondents use a wide range of terminology to describe registries (“pool,” “bank of names,” “roster,” “clearinghouse,” “gathering place,” “database,” “hub of communication,” “compendium,” “online community”) and the people enrolled in them (“volunteers,” “participants,” “members of the public,” “willing,” “interested”). Some describe participation as providing basic contact information, while others note features such as bloodwork, genetic tests, and periodic online tests and surveys. Respondents describe registries as allowing them to find, be notified of, or “matched” to studies. They frequently discuss registries as contributing to scientific knowledge and aiding development of preventions, treatments, and/or cures. Some also indicate that registries keep them informed about brain health. Voluntariness and data protection/privacy are mentioned less frequently. A small portion gave vague responses, indicated that they did not know what a registry is, or did not answer.

Conclusion

Terms and concepts that respondents use to describe registries vary and differ from those typically used by researchers. Applying respondent‐driven language and notions to outreach and recruitment efforts may facilitate more diverse and representative registry enrollment.
Gut microbiome‐related metabolites in plasma are associated with general cognition
Authors: Ahmad Shahzad , Arnold Matthias , Hankemeier Thomas , Ghanbari Mohsen , Uitterlinden André G. , Kraaij Robert , Van Duijn Cornelia M. , Kaddurah‐Daouk Rima F. , Kastenmüller Gabi , Ikram M. Arfan
Published: December 2021

Background

Increasing evidence suggests a role for gut microbiome in pathogenesis of neurological disorders including Alzheimer’s disease. Gut bacteria produce a large number of metabolites that become part of the human blood metabolome. We hypothesized that the effect of gut microbiome on Alzheimer’s disease is through certain metabolites derived or influenced by the gut microbiota. Identifying metabolites associated with gut microbiota as well as with general cognition may help to discover new targets for drugs and prevention.

Method

We profiled plasma samples of 1146 participants of the Rotterdam study for 1387 metabolites using a non‐targeted metabolomics platform. After preprocessing and quality control, plasma levels of 964 metabolites were available for analysis of 1040 participants. Gut microbiome information was available for participants based on 16sRNA sequencing (microbial taxa = 190). We evaluated the gut‐microbial association with metabolite levels in plasma using linear regression adjusting for age, sex, body mass index, medication use, and technical covariates. We further assessed these gut microbiota associated metabolites for association of metabolites with general cognition (G‐factor) using linear regression. Multiple testing correction was performed based on the false discovery rate (FDR) by Benjamini Hochberg (FDR<0.05).

Result

We found significant association of 400 metabolites (Grouped into xenobiotics, lipids, amino acids, peptides, co‐factor and vitamins, carbohydrates, energy and partially characterized molecules) with various gut microbial taxa. Among the gut‐microbiota‐associated metabolites, eleven also showed significant associations with general cognition after multiple testing. Among these associations, higher ergothioneine (xenobiotic) levels showed the most significant association with better cognition (β = 0.012, P = 6.40x10‐7). Ergothioneine showed significant association with genus RuminococcaceaeUCG003 (id 11361) (β = 0.064, P = 5.94x10‐5) and genus Romboutsia (id 11347) (β = 0.042, P = 1.98x10‐4), suggesting an implication of these genera in cognitive function mediated by ergothioneine.

Conclusion

Our study provides evidence for the association between gut microbiota and plasma metabolites of diverse biochemical groups, which also associates with cognition in a population‐based cohort. Further, studies are warranted to elucidate the complex relationship of gut microbiota, diet, genome, human metabolome, and cognition.
Baseline structural MRI and plasma biomarkers predict longitudinal structural atrophy and cognitive decline in early AD
Authors: Xie Long , Das Sandhitsu R. , Wisse Laura , Ittyerah Ranjit , de Flores Robin , Yushkevich Paul A. , Wolk David A.
Published: December 2021

Background

In clinical trials targeting early Alzheimer’s disease (AD), recruiting participants that are more likely to progress over the course of the trials is crucial to success. Molecular and neurodegenerative markers obtained through PET or in cerebrospinal fluid have significant prognostic value, but they are costly or invasive. In this study, we hypothesize that a combination of plasma and structural MRI biomarkers, which overcome these limitations, are predictive of longitudinal progression measured by atrophy and cognitive decline in early AD, providing a more feasible solution.

Methods

Longitudinal 3 Tesla T1‐weighted MRI and cognitive measurements [logical memory, delayed recall and clinical dementia rating sum‐of‐boxes] of 662 cognitively normal (CN) and MCI participants [divided into β‐amyloid positive/negative (A+/A‐)] from ADNI were included (Table 1). Anterior/posterior hippocampus, entorhinal cortex, Brodmann areas (BA) 35 and 36, and parahippocampal cortex were segmented in baseline MRI. Annualized change rates of BA35 thickness [the first region of neurofibrillary tangle pathology] and cognitive measurements were estimated using linear modeling. In each diagnostic group and A+/A‐ subgroups, stepwise linear regression model with age, gender, education and intracranial volume as fixed variables and all baseline MRI and plasma measurements [neurofilament light chain (NfL), pTau‐181] was implemented to investigate their predictive power for each longitudinal measure. In addition, the area under the curve (AUC) of each model in discriminating the first and last terciles of each longitudinal measurement was reported.

Results

Baseline plasma and structural biomarkers provided complementary information in predicting longitudinal atrophy and cognitive decline in controls and MCI (Table 2, Figure 1). These relationships were maintained (albeit with some differences in most predicted measures) when limited to A+ subgroups (preclinical and prodromal AD, Table 4) with AUCs ranging from 0.70‐0.84. Interestingly, baseline structural measures are consistently included in all the models.

Conclusions

We demonstrated that baseline plasma and MRI biomarkers provide complementary information in predicting brain atrophy and cognitive decline. This indicates the combination of these biomarkers, which are relatively easy to obtain, may have important use for recruitment in clinical trials and practice. Additionally, the effect in A‐ CN indicates the potential use of our structural biomarker in predicting normal age‐related decline.
Spermidine supplementation and diffusion weighted imaging in subjective cognitive decline
Authors: Wurdack Katharina , Schwarz Claudia , Benson Gloria , Horn Nora , Antonenko Daria , Hofer Sebastian , Wirth Miranka , Sigrist Stephan , Madeo Frank , Flöel Agnes
Published: December 2021

Background

Subjective Cognitive Decline (SCD) may represent an early, pre‐clinical manifestation of Alzheimer’s disease (Jessen et al., 2014), possibly accompanied by detrimental changes in white matter (WM) microstructure (Brueggen et al., 2019). Neuroprotective effects of increased external supply of spermidine were demonstrated in aged animal models (Madeo et al., 2018). This study investigated the effects of a 12‐month spermidine‐rich dietary supplementation on diffusion weighted imaging (DWI) parameters of central WM tracts in older persons with SCD.

Method

The monocentre, randomised, double‐blind, placebo‐controlled phase IIb SmartAge trial (clinicaltrial.gov: NCT03094546, Wirth et al., 2019) investigates the effects of a 12‐month dietary spermidine supplementation in SCD. Baseline and follow‐up DWI data were available for 72 SCDs (mean age 69±5 years; 38 placebo, 34 spermidine). Fractional anisotropy (FA) and mean diffusivity (MD) of central WM tracts were obtained through Tract Based Spatial Statistics. The interaction effect of intervention group and time was examined through analysis of variance. Exploratory analyses of within‐group changes from baseline to follow‐up were conducted using paired t‐tests. Correction for voxelwise multiple testing was applied.

Result

No statistically significant interaction effect of time and intervention group (spermidine vs. placebo) was present for FA and MD in central WM tracts. Exploratory within‐group analyses in the placebo group revealed a decrease of FA in areas comprising tracts within the limbic system and the MTL (right more than left), and an increase of FA in a small region of the right occipital lobe. Widespread increases of MD in the placebo group were observed in the right hemisphere and to a lesser extent in central regions of the left hemisphere. Within the spermidine group, no significant changes in FA or MD were present.

Conclusion

While our analyses did not show an interaction effect, we found detrimental within‐group changes in FA and MD from baseline to follow‐up in the placebo group but not in the spermidine group. Our findings thus suggest a potential beneficial influence of dietary spermidine supplementation on WM microstructure in SCD, to be followed up in future larger and longer‐lasting intervention studies.
NRG1/ErbB4 signaling and its role on the development and progression of Alzheimer's disease
Authors: García‐Colomo Alejandra , Nebreda Alberto , de Frutos Jaisalmer , Losada María Luisa Delgado , Higes Ramón López , Cuesta Pablo , Vilca Brenda Chino , Dolado Alberto Marcos , Maestú Fernando
Published: December 2021

Background

Alzheimer’s disease (AD) is a complex disease; various etiopathogenic mechanisms, like genetics and cognitive reserve, affect its development and progression across the continuum. Neuregulin‐1 (NRG‐1) /ErbB4 signaling has been recently studied regarding its possible role in the development of AD. To our knowledge, the schizophrenia (SZ) risk SNPs rs6994992 (NRG‐1) and rs839523 (ErbB4) have never been explored in association to AD, but the risk alleles have been associated with structural, functional and cognitive alterations in SZ and healthy individuals. Some of these alterations are similar to those experienced by AD patients, over 40% of which evolve to experience psychotic symptoms. This subset of patients experience a more rapid cognitive decline, greater functional impairment, etc., which contribute to a greater level of distress for family and caregivers.

Method

The sample consisted of 584 Spanish individuals: 161 were diagnosed with mild cognitive impairment (MCI; age = 76.66±5.37). The remaining 423 were healthy controls (HC; age = 65.88±8.80).

Participants underwent a neuropsychological evaluation, a MEG scan, a magnetic resonance imaging scan, and were genotyped for the rs6994992 and rs839523 SNPs.

Result

Preliminary results show a significant interaction between the NRG1 risk allele and the diagnosis in the MMSE score (figure 1); the risk allele had no effect in HC, but in MCI those with the risk allele had a significantly worse performance. Linear models were performed for the prediction of the MMSE score, including either the NRG1 or ErbB4 SNP, the diagnosis, cognitive reserve and age. Significant interactions with the SNPs were found for both, including a three‐way interaction between the diagnosis, cognitive reserve.

Conclusion

These preliminary findings could indicate that the SZ risk alleles have a negative influence in the AD continuum over cognition and, potentially, over structural and functional parameters. This effect could be modulated by cognitive activity across the lifespan.
Associations between CSF proteins and medial temporal lobe atrophy across the AD continuum
Authors: Ekblad Laura L. , Visser Pieter Jelle , Tijms Betty M.
Published: December 2021

Background

Cortical atrophy is a typical feature of Alzheimer´s disease (AD). The biological processes that associate with or possibly lead to atrophy remain largely unexplored. We hypothesized that disease stage would modulate the associations between cerebrospinal fluid (CSF) proteins and regional cortical thickness in individuals with abnormal CSF beta‐amyloid.

Method

Cognitively normal (CN), mild cognitive impairment (MCI) and AD individuals were selected from ADNI, based on abnormal CSF beta‐amyloid (<192 ng/l). All examined individuals had cortical thickness measurements and CSF proteomic data available (measured with MRM and RBM). Correlations between 217 CSF proteins and cortical thickness in 34 cortical regions (averaged over the left and right hemispheres) were analyzed with linear models, adjusted for age and sex. Interactions for diagnosis were evaluated for each protein‐cortical thickness association. Protein enrichment analysis was performed with Cytoscape ClueGO.

Result

We included 197 individuals (32 CN; 104 MCI; 61 AD) with a mean age 74.8 (SD 7.1) years, 41.6 % women.Cortical thickness declined according to disease progression in 28 brain regions, most significantly in the entorhinal cortex (ANOVA p‐value <0.0001), the middle temporal gyrus (p<0.0001) and the inferior temporal cortex (p<0.0001). 9 proteins, including phospho‐tau and BACE activity, showed interactions for diagnosis in the entorhinal cortex, 12 in the middle temporal gyrus and 19 inferior temporal cortex. These proteins were associated with beta‐amyloid metabolic process, dendritic cell differentiation, and oligodendrocyte development in ClueGO enrichment analyses. A consistent finding was that higher levels of the majority of these CSF proteins correlated with lower cortical thickness in CN, and that these correlations were attenuated with disease progression.

Conclusion

Alterations in the levels of CSF proteins are associated with cortical atrophy in the medial temporal regions, and the biological processes underlying cortical atrophy seem to begin already in the preclinical stage of AD. These results suggest that therapies targeted at preventing cortical atrophy would need to be initiated already in the CN stage.
Examining possible gender differences in the association between education and late‐life cognitive function in the LifeAfter90 Study, a large multiethnic cohort of the oldest‐old
Authors: Gilsanz Paola , Corrada Maria M , Mungas Dan M , Glymour M Maria , Kawas Claudia H , Lam Jennifer O , Vieira Katharine E , Peterson Rachel L , Eng Chloe W , Quesenberry Charles P , Whitmer Rachel A
Published: December 2021

Background

Educational attainment predicts late‐life cognitive ability and dementia. Historically, women have had fewer educational opportunities than men. We examine if the association between educational attainment and cognitive level and decline differ by gender.

Method

LifeAfter90 is an ongoing cohort of long‐time members of an integrated healthcare delivery system ≥90 years old without a dementia diagnosis at recruitment. Interviews and cognitive assessment occurred every six months and included self‐reported education (≤high school, some college, and ≥college graduate (reference)) and Spanish and English Neuropsychological Assessment Scales (SENAS). SENAS encompasses the domains of verbal episodic memory, semantic memory, and executive function. Mixed models with random intercepts estimated possible differences in the association between education and late‐life cognition adjusting for time (years since baseline), baseline age, race/ethnicity, and practice effects. Practice effects were accounted for by using an indicator variable for the first visit. Interactions terms allowed for possible gender differences in the association of education with baseline cognitive scores (i.e. education*male) and cognitive change (i.e., education*male*time).

Result

The 669 participants were on average 92.8 years of age, 63% were women, 34% were college graduates, and 69% were racial/ethnic minorities (Table 1 and Table 2). Lower levels of education were associated with worse performance on baseline cognitive assessment but not performance over time. Women with ≤high school or some college averaged worse baseline cognition in each domain than women who had completed college (Table 3). There was no significant gender by education interaction for verbal episodic memory (p‐value=0.22) or semantic memory (p‐value=0.26), but the disadvantage in executive function associated with lower education was significantly attenuated in men (some college*male β=0.32, 95% CI=0.08, 0.56; p‐value=0.01). There were no differences across genders in the association between education and any of the domain specific cognitive scores over time.

Conclusion

The association between education and late‐life cognitive function appears to be similar across genders with the exception of college completion having a larger effect on baseline executive function scores for women than for men. We will continue to explore these differences as additional visits occur in this ongoing cohort of ethnically diverse oldest‐old individuals.
Association of cerebrospinal fluid and plasma biomarkers with longitudinal tau accumulation
Authors: Moscoso Alexis , Karikari Thomas K. , Grothe Michel J. , Ashton Nicholas J. , Zetterberg Henrik , Blennow Kaj , Schöll Michael
Published: December 2021

Background

Due to its tight relation with neurodegeneration and cognitive decline, tau pathology is increasingly recognized as an attractive therapeutic target in Alzheimer’s disease. To be more efficient, clinical trials testing anti‐tau drugs need to target subjects at risk for longitudinal tau accumulation. So far, only elevated signal in an amyloid‐β (Aβ) PET scan has been consistently identified as predictor of future tau burden. Here, we studied whether more accessible cerebrospinal fluid (CSF) and plasma biomarkers were associated with PET‐measured longitudinal tau accumulation.

Method

We included two partially overlapping cohorts of participants from the Alzheimer’s Disease Neuroimaging Initiative that underwent baseline and follow‐up [18F]flortaucipir (FTP) scans, as well as baseline Aβ PET scans. In cohort 1 (93 cognitively unimpaired (CU) and 70 impaired (CI)), all participants had available CSF biomarkers (Aβ1‐42, p‐tau181, and p‐tau181/Aβ1‐42 ratio) at baseline; in cohort 2 (37 CU and 37 CI), participants had a plasma p‐tau181 measurement within 2 years prior to the baseline FTP scan. Annual standardized uptake value ratio (SUVR) change on FTP scans was estimated at the voxel level and in a previously defined meta‐region of interest (ROI) using linear mixed effects models. In cohort 1, correlations of CSF markers with FTP SUVR annual change were determined using Pearson correlation coefficients, separately for CU and CI. In cohort 2, we instead used clinical diagnosis‐adjusted partial correlations in the combined cohort (CU+CI) due to lower sample size.

Result

Among CU individuals in cohort 1, all CSF biomarkers showed moderately strong correlations with FTP SUVR change; CSF p‐tau181/Aβ1‐42 ratio showed the strongest association with FTP SUVR change, slightly outperforming Aβ PET (Fig. 1). Similarly, CSF p‐tau181/Aβ1‐42 ratio was the strongest correlate of FTP SUVR change in CI subjects (Fig. 2). In cohort 2, plasma p‐tau181 was moderately correlated with FTP SUVR change, though not stronger than Aβ PET (Fig. 3).

Conclusion

CSF biomarkers might be as effective as Aβ PET for the prediction of longitudinal tau accumulation. Plasma p‐tau181, though not as strongly correlated as Aβ PET, might represent a cost‐effective solution for the prediction of tau accumulation. These findings may have implications for clinical trials with anti‐tau drugs.
Large‐scale cross‐sectional and longitudinal validation of a digital speech‐based measure of cognition
Authors: Stegmann Gabriela M , Hahn Shira , Liss Julie , Berisha Visar , Mueller Kimberly D
Published: December 2021

Background

Cognitive decline is associated with deficits in attention to tasks and attention to relevant details. We developed a metric, semantic relevance (SemR), which is algorithmically extracted from speech and measures overlap between a picture’s content and the words used to describe the picture. In this study, we validate it in a sample that was not used when developing it. We automatically extract SemR from transcripts of Cookie Theft (BDAE) and evaluate its cross‐sectional and longitudinal clinical validity using four groups: Normal Cognition (NC), Early MCI (EMCI), MCI, and Dementia (D).

Method

Dementia Bank and Wisconsin Registry for Alzheimer’s Prevention (WRAP) were combined, and participants (average age 63.7) included: NC (N = 918; 647 F), EMCI (n = 180; 110 F), MCI (n = 26, 9 F), and D (n = 195, 126 F). Participants provided Cookie Theft descriptions and Mini‐Mental State Exam (MMSE) assessments on an average of 2.1 occasions/participant, assessed on average 2.4 years apart (total n=2,717). SemR was algorithmically computed from each picture description transcript. Transcripts were also hand‐coded for “content information units” as a ground‐truth comparison with automated SemR. Cross‐sectionally, we used a mixed‐effects model to calculate relationships between SemR and ground truth, and between SemR and MMSE. We estimated within‐speaker SemR longitudinal trajectories using growth curve models (GCM) for each group.

Result

(Figure 1) Automatic and hand‐coded SemR were strongly correlated (r = .85, p<.05). (Figure 2) SemR was significantly related to MMSE (b = .002, p<.05), such that decrease in MMSE resulted in decrease in SemR. (Figure 3) Longitudinal GCMs showed that SemR declined with age for all groups. The decline was slowest for NCs, steepened for the EMCI and MCI groups, and then slowed again for D, who had the lowest scores. Figure 3 displays SemR trajectories and confidence bands for age ranges with the most data for each group. SemR has a standard error of measurement (SEM) of .05.

Conclusion

SemR is reliable, shows convergent validity with MMSE, and correlates strongly with manual hand‐counts. SemR declines with age and severity of cognitive impairment, with the speed of decline differing by level of impairment.
Associations between remote cognitive testing on an individual’s own digital device and amyloid burden on neuroimaging in clinically normal older adults: Results from Boston Remote Assessment for Neurocognitive Health (BRANCH)
Authors: Papp Kate V. , Rentz Dorene M. , Buckley Rachel F. , Schneider Olivia R , Hsieh Stephanie , Soberanes Daniel , Properzi Michael J , Schultz Aaron P. , Johnson Keith A. , Sperling Reisa A. , Amariglio Rebecca E.
Published: December 2021

Background

Digital cognitive testing completed on an individual’s own device, independently, and remotely is a highly appealing solution to sensitively capture early memory changes in preclinical AD. However, few digital assessments have been designed specifically for a preclinical AD population and validated against paper‐and‐pencil measures and relevant AD biomarkers. Here, we describe initial validation steps for the Boston Remote Assessment of Neurocognitive Health (BRANCH), web‐based cognitive testing targeting cognitive domains with AD susceptibility (e.g., cross‐modal associative memory, semantically facilitated learning and recall, and pattern separation) and using task stimuli relevant to everyday life. To determine the validity of BRANCH, we explored correlations between remote BRANCH to in‐clinic paper and pencil measures and PET amyloid burden.

Method

A link to BRANCH was either texted or emailed to 128 clinically normal (CN) older adults participating in the Harvard Aging Brain Study. Participants completed the 4 BRANCH measures (modified Face Name Test, groceries test, categories test, signs test) over a mean 19 minutes. 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 11CPittsburg Compound‐B to estimate global amyloid burden. A composite of accuracy across BRANCH tasks was computed.

Result

Participants had a mean age of 74.38(Range 51‐89), were 82% Caucasian, and 60.7% female. They completed BRANCH on smartphones (26%), tablets (18%), laptops (26%), and desktops(29%). Only 2.59% of participants reported difficulty completing BRANCH on a post‐test survey. Lower BRANCH composite performance was associated with worse performance on in‐person paper and pencil measures (Figure 1; PACC; r=0.637, p<0.001). Lower BRANCH performance was associated with greater amyloid burden (r=‐0.275, p=0.003).

Conclusion

A digital memory assessment with ecologically‐valid tasks and stimuli is feasible for CN older adults to complete independently on their own devices. The relatively strong correlation observed between BRANCH and PACC suggests that BRANCH captures valid information about cognitive performance despite being collected remotely on an individual’s own device. The significant association between BRANCH and amyloid burden suggests that these remotely captured tasks may be promising tools to detect and track AD‐specific cognitive decrements on a larger scale.
CS6253 ABCA1 agonist in cynomolgus monkeys increases APOA‐I subspecies PREβ‐HDL and lowers Aβ42 and Aβ40 in cerebrospinal fluid
Authors: Johansson Jan O
Published: December 2021

Background

Then main genetic late‐onset Alzheimer’s disease (AD) risk factor, apolipoprotein E (APOE) ε4 genotype is characterized by the apoE4 protein having impaired interaction with astrocyte’s ATP‐binding cassette transporter A1 (ABCA1) resulting in; (1) poor cholesterol efflux (Bielicki 2016) to apoE and reduced lipid transport to cells in brain, (2) build‐up of residual cholesterol in lipid rafts, impeding astrocyte function (Rawat 2019), and (3) increased neuron cell death (Voskuhl 2018). ApoE as opposed to most other apolipoproteins does not cross the blood brain barrier (BBB). It has been suggested that the apoA‐I subspecies preβ‐HDL effectively crosses the BBB where it can compensate for ApoE4’s impaired interaction with ABCA1. We hypothesized that the ABCA1 agonist CS6253 would generate preβ‐HDL in plasma and decrease AD risk factors in brain including Aβ42.

Method

In vitro: CS6253 was incubated with human plasma (Figure, A‐B) and generation of preβ‐HDL assessed by 2D electrophoreses using a.b. to apoA‐I and CS6253 generating EC50 values. In vivo: Cynomolgus monkeys (cynos) have 93% homology with human apoE, lipid and amyloid metabolism similar to humans making them representative models for humans. In cynos; (1) CS6253 single dose 25 mg/kg iv was administered (n=2) and plasma collected for preβ‐HDL analysis by ELISA (Daichii a.b.) (Figure, C); (2) CS6253 multiple dose 0 (control), 75, 150 and 225 mg/kg iv (n=2/sex/group) 5 times was administered over 10 days and plasma collected serially for preβ‐HDL analysis (Figure, D). CSF and plasma were collected before treatment and 6 hours after the 5th/last dosing and Aβ42 and 40 analyzed by SIMOA.

Result

CS6253 increased preβ‐HDL in vitro in human plasma and in vivo in cynos, see Figure. In cynos CS6253 decreased Aβ42 and Aβ40 concentration in CSF following dose‐response pattern.

Conclusion

The CS6253 ABCA1 agonist transiently increases plasma preβ‐HDL and reduces CSF concentrations of Aβ42 and Aβ40. The Aβ reduction is consistent with apoE targeted replacement mice models studies where CS6253 reduced Aβ42, prevented AD brain pathology and improved cognition. Studies in human APOE ε4 carriers with and without AD are needed to corroborate these findings and to investigate the therapeutic potential of CS6253 or similar compounds.
Effects of COVID‐19 on cognition of older African Americans
Authors: Kavcic Voyko , Podlesek Anja , DiCerbo Loraine M , Hanna Sophie , Shair Sarah , Giordani Bruno
Published: December 2021

Background

The Covid‐19 pandemic, with its diverse effects (e.g., on quality of life, health and illness, physical and psychological well‐being, social and economic life), has also been suggested to effect cognitive functioning. To better understand the possible effect of the COVID‐19 pandemic, we examined cognitive functioning of older African Americans.

Method

Study included 164 community‐dwelling older African Americans (mean age= 75.6, range=64‐94) recruited from the Wayne State Institute of Gerontology Healthier Black Elders Center and general Detroit area. Responses were gathered over the phone between 7/28/2020 to 1/14/2021. Change in cognitive functioning was evaluated with the newly developed Cognitive Change Questionnaire (CCQ) in which participants self‐evaluated their cognition related to daily activities (e.g., memorizing, paying attention, task switching) on a 5‐point scale (1–Much easier, 3–No difference, to 5–Much harder), comparing it to the pre‐pandemic time. In addition, all participants received the TICSm phone‐based cognitive screen. Responses to COVID‐19 were measured on these scales: positive emotions (e.g., gratitude, happiness), negative emotion (e.g., anger, fear), unmet needs (e.g., food, medical care), and personal issues (e.g., economic problems, reduced privacy).

Result

Findings showed that 106 (65%) participants did not report any COVID‐19 related cognitive changes, 7 (4%) indicated improved cognitive functioning, and 50 (31%) indicated that their cognitive functioning was worse as compared to pre‐COVID‐19 times. Average CCQ scale score (range 8‐40) was 26.86. CCQ scale showed good psychometric properties (Cronbach alpha=.84). Significant correlations were obtained between CCQ and TICSm subscales: r=–.16 (p=.05) with total score, r=–.19 (p=.01) with immediate recall, and r=–.24 (p=.002) with delayed recall. Stepwise regression analysis showed that COVID‐19 related responses explained 24% of variability on CCQ: participants reported greater cognitive decline if they expressed greater level of negative emotions (21% explained variance) and higher anxiety (3% explained variance).

Conclusion

These results demonstrate that a sizeable percentage of older community‐dwelling African Americans do self‐report cognitive decline following COVID‐19, associated with increased presence of negative emotions and anxiety. The possibility of altered cognitive function should be considered not only for quality‐of‐care issues, but also when recruiting for research trials during and after the pandemic.
Assessment of AD‐related plasma biomarkers in diverse ancestral populations
Authors: Griswold Anthony J. , Rajabli Farid , Garcia‐Serje Catherine , Hamilton‐Nelson Kara L. , Adams Larry D. , Tejada Sergio , Mena Pedro Ramon , Starks Takiyah D. , Whitehead Patrice L. , Silva‐Vergara Concepcion , Cuccaro Michael L. , Martinez Izri , Illanes‐Manrique Maryenela , Cornejo‐Olivas Mario R. , Laux Renee A. , Caywood Laura J. , Reitz Christiane , Beecham Gary W. , Byrd Goldie S. , Feliciano‐Astacio Briseida E. , Scott William K. , Haines Jonathan L. , Vance Jeffery M. , Pericak‐Vance Margaret A.
Published: December 2021

Background

Plasma proteins as biomarkers for the differential diagnosis of AD from other similar neurodegenerative disorders, as well as the identification of preclinical AD, has recently been well supported across several large AD cohorts. However, these are composed primarily of individuals of non‐Hispanic European ancestry. Few studies have been performed in African‐American or Hispanic/Latinx AD populations to determine if plasma biomarkers are also useful in these populations. Given the differences in AD risk loci found across ancestries, the application of these biomarkers in diverse populations is not assured. Therefore, the aim of this study is to explore the utility of plasma biomarkers in AD, MCI and at‐risk family members from diverse ancestral backgrounds.

Method

As part of ongoing initiatives to understand AD in individuals of diverse ancestry, we are measuring the plasma level of biomarkers in a cohort of more than 3,000 individuals. This includes: 999 African Americans (248 AD cases, 591 controls, 160 MCI), 581 Puerto Ricans (223 AD cases, 208 controls, 150 MCI), 1052 Puerto Ricans in families (411 AD cases, 413 controls, 228 MCI), 98 Cubans (23 AD cases, 39 controls, 36 MCI), and 117 Peruvians (33 AD cases, 75 controls, 9 MCI). We will also have data on autopsy confirmed European AD cases (37) and a cohort of Amish individuals (∼400 AD cases, ∼200 MCI, and ∼500 controls). Plasma proteins tested are Aβ42, Aβ40, total Tau, and p‐Tau181 using Simoa chemistry assays (Quanterix HD‐X). All measurements are performed in duplicate and data analysis performed using HD‐X Analyzer Software v1.6.

Result

Measurement and analysis of biomarkers in this diverse dataset is currently underway and will be completed in a few months. These results will allow a direct comparison of biomarker analysis related to AD diagnosis between European, African, and Amerindian ancestries. Moreover, a family‐based design for over 1000 Puerto Rican individuals will be the first to identify potential heritable trends in biomarker levels.

Conclusion

This study is critical to being to understand how plasma biomarkers for AD may vary across diverse ancestries and whether previous findings will be generalizable and useful for all individuals, regardless of ancestry.
Acoustic features of voice as a measure of cognitive load during performance of serial subtraction in a remote data collection context
Authors: Cormack Francesca K , Barnett Jennifer H , Taptiklis Nick
Published: December 2021

Background

Cognitive load is the mental demand a task imposes for a specific person. Performance declines when demand exceed capacity; therefore, increase of mental effort may precede measurable cognitive decline. Physiological indices of load (e.g. heart rate, skin conductance etc.) are sensitive to task demand (e.g. subtracting three vs seven), show increased cognitive load with ageing, and in MCI compared to healthy ageing. Voice features have promise as non‐invasive and scalable indicators of mental effort. Here, we aim to classify serial subtraction at high and low cognitive load using voice recordings captured using an automated remote data collection system.

Method

Participants (aged 17‐86) completed serial subtraction via the Neurovocalix web‐app on their own devices. From a pool of 5,742 participants, 100 were randomly selected for manual review. Seven participants were excluded for audio or performance issues. Responses were transcribed and the start and end of each subtraction attempt marked, producing 3,254 attempts for analysis. Low‐level acoustic features were extracted and aggregated over each attempt, then normalized within participant. Random Forest classifiers were trained and evaluated using Leave‐One‐Subject‐Out‐Cross‐Validation (LOSOCV) to predict high vs low load. LOSOCV repeatedly splits the dataset by subject, with one participant at a time used for testing, and the remainder used for training the model. This produces model predictions for each participant and attempt.

Result

Average cross‐validation accuracy was 0.81 (95% CI 0.78 to 0.84), with an average area under the curve (AUC) of 0.87 (95% CI 0.85 to 0.89). We tested predictions for specific numbers which appeared in both subtraction by seven and by three. Accuracy was 0.78, suggesting that predictions were not driven by specific numeric responses. We observed a significant negative correlation between behavioural performance on the task (response rate), and utterance load probability metric for utterances (ρ=‐0.32, p<0.001), suggesting that participants who were more fluent in serial subtraction exhibited lower cognitive load.

Conclusion

Acoustic features of voice can distinguish between utterances generated under conditions of high and low cognitive load during serial subtraction, adding a novel, independent and sensitive outcome measure to a cognitive task with established utility in the context of neurodegeneration.
Modeling brain‐predicted age from functional connectivity in early‐stage and preclinical Alzheimer disease
Authors: Millar Peter R , Luckett Patrick H , Benzinger Tammie L.S. , Fagan Anne M. , Morris John C. , Ances Beau M.
Published: December 2021

Background

The “brain‐predicted age” approach summarizes complex age relationships with neuroimaging features by quantifying apparent brain age compared to normative trajectories. Advanced brain‐predicted age has been observed in many studies of symptomatic Alzheimer disease (AD), but the effects of preclinical AD have not been investigated. Prior studies have typically modeled brain aging with structural MRI, but other modalities, including resting‐state functional connectivity (FC), are underexplored. Here we modeled FC‐predicted brain age and tested its relationships with preclinical and symptomatic AD.

Method

We calculated FC correlation matrices between 300 regions of interest in 493 cognitively normal (clinical dementia rating [CDR]=0), amyloid‐negative (CSF pTau/Aβ42 ratio and/or amyloid PET Centiloid) control participants (18‐91 years old). We trained a Gaussian process regression model to predict age from these FC features using 10‐fold cross‐validation. We applied the trained model to a separate set of 153 amyloid‐negative, 143 preclinical AD (CDR=0, amyloid‐positive), and 183 symptomatic AD participants (CDR>0). Finally, we tested group differences in FC‐predicted brain age between the AD samples and continuous relationships with biomarkers of amyloid (CSF Aβ42, amyloid PET Centiloid), tau (CSF pTau‐181, tau PET [AV‐1451]), and neurodegeneration (CSF NfL, hippocampal volume), controlling for true age as a covariate.

Result

The FC‐based model accurately predicted age in the training set (R2
=.72, mean absolute error=8.14, Figure 1). FC‐predicted brain age was 2.43 years older in symptomatic AD compared to cognitively normal controls (p<.001, Cohen’s d=0.38, Figure 2A), but was 1.90 years younger in preclinical AD compared to amyloid‐negative controls (p=.011, Cohen’s d=‐0.29, Figure 2B). Greater FC‐predicted brain age was associated with smaller hippocampal volume (p=.009, Figure 3F), but also with lower CSF pTau‐181 (p=.012, Figure 3C). Relationships between FC‐predicted age and other AD biomarkers were not significant (p’s>.20, Figure 3).

Conclusion

Elevated FC‐predicted brain age may reflect advanced brain aging in FC networks during symptomatic AD. This finding is consistent with previous models based on structural MRI. Reduced FC‐predicted brain age in amyloid‐positive participants may reflect compensation during early preclinical stages, but this interpretation requires further investigation. FC‐predicted brain age may be a sensitive biomarker in future models of healthy aging and symptomatic AD.
CSF metabolites associated with CSF NeuroToolKit biomarkers
Authors: Dong Ruocheng , Lu Qiongshi , Suridjan Ivonne , Kollmorgen Gwendlyn , Blennow Kaj , Zetterberg Henrik , Carlsson Cynthia M. , Asthana Sanjay , Johnson Sterling C. , Engelman Corinne D.
Published: December 2021

Background

Metabolomics technology has emerged as a tool to study small molecules influenced by age, sex, genetics, lifestyle, and disease processes. Correlating metabolites in cerebrospinal fluid (CSF) with established and developing Alzheimer’s disease (AD) CSF biomarkers may elucidate additional changes that are associated with early AD pathology and enhance our knowledge of the disease.

Method

The relative abundance of untargeted metabolites was assessed via Metabolon’s UHPLC/MS platform in 161 non‐Hispanic white, cognitively unimpaired individuals from the Wisconsin Registry for Alzheimer’s Prevention (WRAP). A metabolome‐wide association study (MWAS) was conducted between 269 known CSF metabolites and CSF biomarkers, which were measured with the exploratory Roche NeuroToolKit assays, a panel of automated robust prototype immunoassays (Roche Diagnostics International Ltd): phosphorylated tau (P‐tau), total tau (T‐tau), amyloid β (Aβ42), Aβ42/40, neurofilament light protein (NFL), neurogranin, chitinase‐3‐like protein 1 (YKL‐40), S100b, glial fibrillary acidic protein (GFAP), interleukin‐6 (IL‐6), soluble triggering receptor expressed on myeloid cells 2 (sTREM2), and α‐synuclein. Linear mixed‐effects regression analyses were performed with random intercepts for individual and family adjusting for age, gender, body mass index, and years of education. The metabolome‐wide significance was determined by a false discovery rate (FDR)‐corrected p<0.05. The significant metabolites from WRAP were subsequently tested in 154 non‐Hispanic white, cognitively unimpaired individuals from the Wisconsin Alzheimer’s Disease Research Center (ADRC). Using single nucleotide polymorphisms (SNP) associated with the top metabolites, we applied linear mixed‐effects models to perform mediation analyses.

Result

The MWAS results for each NeuroToolKit biomarker from WRAP are shown in Figure 1. Metabolites were significantly associated with all biomarkers except Ab42/40 and IL‐6. Top metabolites that were associated with multiple NeuroToolKit CSF biomarkers are shown in Table 1. Significant mediation effects of stearoyl sphingomyelin(d18:1/18:0)(SM(d18:1/18:0)) were detected for P‐tau and sTREM2 (Figure 2).

Conclusion

This study provides evidence that CSF metabolites are associated with AD‐related pathology through most AD CSF biomarkers and may be influenced by upstream genetic variation. The significant results for Aβ42 and Aβ40, but nonsignificant results for Aβ42/40 indicate that the metabolites associated with Aβ42 and Aβ40 may influence production of amyloid in general versus clearance of the pathological form, Aβ42.
Association of anticholinergic medication and AD biomarkers among cognitively normal late middle‐age adults: Results from the Wisconsin Registry for Alzheimer's Prevention (WRAP)
Authors: Du Lianlian , Koscik Rebecca L , Chin Nathaniel A , Bratzke Lisa C , Cody Karly Alex , Erickson Claire M , Betthauser Tobey J , Jonaitis Erin M , Hermann Bruce P , Vasiljevic Eva , Deming Yuetiva , Mueller Kimberly D , Engelman Corinne D , Chappell Richard J , Johnson Sterling C
Published: December 2021

Background

Studies of anticholinergic (AC) medications (drugs that block acetylcholine neurotransmitter action) have shown associations between the AC medications use, cognitive impairment, and increased dementia risk. Associations between AC medication and AD biomarkers among cognitively normal late middle‐aged adults are unclear. This study examined associations between AC use, cognition, physical health, and amyloid PET measures.

Methods

Wisconsin Registry for Alzheimer’s Prevention (WRAP) participants with >=3 cognitive composite scores, free of dementia at baseline cognition (n=1262) were included in analyses of cognitive and general health measures; PET amyloid measures were examined in a subset with Pittsburgh Compound B PET imaging (PiB; n=299). Participants were classified as either taking or not taking at least one AC medication at baseline (AC+, n=437; AC‐, n=825; Table 1). Cross‐sectional analysis of baseline associations examined AC+/AC‐ differences in AD‐related cognitive composites (e.g., memory, PACC) and health markers (e.g., depression, comorbidities). Linear mixed‐effects models (LME) examined whether AC modified age‐related cognitive trajectories in APOE ε4 carriers or non‐carriers and PiB positive or negative group. Sensitivity analyses repeated models only in the high AC+ (AC score > 1) group (n=191) relative to the AC‐ group. The statistical threshold for significance was set at P < .05.

Results

Mean(sd) age for AC+ and AC‐ participants was 55.4(6.4) and 53.7(6.6). The AC+ group was significantly higher than the AC‐ group on depression scores, BMI, total medications, total comorbidities, and cardiovascular problems (Table 2). The AC groups did not differ on amyloid PET measures (Table 3). At baseline cognition, the AC+ group (n=437) showed lower executive function and PACC3 scores (Figure 1). Longitudinal analyses indicated that AC+ predicted a steeper decline slope in executive function and PACC3 with effects exacerbated in individuals with AD risk factors (Fig. 2‐3, respectively). The slopes of AC + group differed significantly after age 65.

Conclusion

AC medication use was associated with faster cognitive decline, particularly among APOE4 carriers and those with PET‐based evidence of amyloid plaques, suggesting AC use may exacerbate AD‐related cognitive decline in the preclinical time frame. The results have implications for AC usage in older adults with AD risk or biomarker positivity.