bluuebunny/crossref_metadata_2025 huggingface dataset:
How Naturalistic Driving Compares to Aβ‐related CSF and Plasma Biomarkers in the Detection of Amyloid PET Positivity: A Machine Learning Approach
Authors: Bayat Sayeh , Schindler Suzanne E. , Roe Catherine M , Babulal Ganesh M
Published: December 2022

Background

Identifying individuals with Alzheimer disease (AD) pathology a decade or more before the onset of dementia symptoms can be achieved with amyloid positron emission tomography (PET), cerebrospinal fluid (CSF) biomarkers, or blood biomarkers. This study compares driving behavior with CSF and blood biomarkers to identify amyloid deposition in AD, as defined by the “gold standard” PET‐amyloid.

Method

We used commercial‐in‐vehicle‐GPS dataloggers to study naturalistic driving behaviors among 101 cognitively normal older drivers (aged 65+). All participants had blood, CSF, and PET biomarker data. The cohort included 37 individuals with and 64 without PET‐amyloid positivity.

Driving variables included total number of trips, number of trips with a distance less than 1‐mile, trips in evening rush hour, trips with hard acceleration, speeding events, and average speed. Three Multi‐layer Perceptron (MLP) classifiers were trained with three sets of inputs: (1) driving variables, (2) driving variables and age, and (3) driving variables, age, and APOE ε4 status. Additionally, plasma Aβ42/Aβ40 < 0.1013, CSF Aβ42/Aβ40 < 0.0673, or Amyloid Probability Score (APS) (modeled score incorporating plasma Aβ42/40, age, and APOE ε4 status) > 15 were used to detect PET‐amyloid positivity. The driving models were trained on 80% of the data and all biomarkers were evaluated on the remaining 20% of the data. Specificity (Spe), sensitivity (Sen), F1‐score (F1), and area under the receiver operating curve (AUC) were compared across the three driving models and three fluid‐based biomarkers.

Result

For predicting PET‐amyloid positivity, CSF Aβ42/Aβ40 achieved the highest performance (Spe=0.96, Sen=0.98, F1=0.97) followed by the MLP model with driving variables, age, and APOE ε4 status (Spe=0.93, Sen=0.91, and F1=0.92), MLP model with driving variables and age (Spe=0.88, Sen=0.85, and F1=0.86), APS (Spe=0.82, Sen=0.84, and F1=0.81), plasma Aβ42/Aβ40 (Spe=0.79, Sen=0.80, and F1=0.76), and MLP model with driving variables (Spe=0.71, Sen=0.72, and F1=0.71). The AUC from driving variables was 0.800, and improved by adding age to 0.933, and age and APOE ε4 status to 0.977. Furthermore, AUC scores were 0.986, 0.911, and 0.873 for CSF Aβ42/Aβ40, APS, and plasma Aβ42/Aβ40, respectively.

Conclusion

Driving is a useful neurobehavioral marker in predicting PET‐amyloid positivity among cognitively normal older drivers.
Financial Mismanagement in Alzheimer’s Disease and Frontotemporal Dementia
Authors: Jackson Ashley J. , Ngo Sang , Manivannan Madhumitha , Young J. Clayton , Leggins Brandon , Cryns Noah G. , Tran Sheila T. , Grant Harli E. , Knudtson Marguerite V. , Chiong Winston
Published: December 2022

Background

Clinical experience in dementia indicates high risk for financial mismanagement, with grave consequences for patients and families. However, to date there has been little scientific study of real world financial errors in dementia or differential vulnerability in different syndromes.

Method

Caregivers for people with Alzheimer’s disease (n = 50), behavioral variant frontotemporal dementia (bvFTD, n = 58), and primary progressive aphasia (PPA, n = 39) reported whether care recipients had made financial mistakes within the last year; and if so, categorized these as resulting from: (a) being too trusting or gullible, (b) being wasteful or careless with money, or (c) trouble with memory. In a pre‐registered analysis (https://archive.org/details/osf-registrations-vupj7-v1), we examined two hypotheses regarding vulnerability in different syndromes. Hypothesis 1: Financial mistakes due to being too trusting or gullible and being wasteful or careless with money are more prevalent in bvFTD than in Alzheimer’s disease. Hypothesis 2: Financial mistakes due to trouble with memory are more prevalent in Alzheimer’s disease than in bvFTD.

Result

32% of Alzheimer’s disease caregivers, 51.7% of bvFTD caregivers, and 30.7% of PPA caregivers reported financial errors in the last year. Concordant with our Hypothesis 1, people with bvFTD were more likely than those with Alzheimer’s disease to make mistakes referable to being too trusting or gullible (OR 4.90, 95% CI 1.55‐19.2, p = 0.012) and to being wasteful or careless (OR 4.41, 95% CI 1.55‐14.7, p = 0.009) in analyses corrected for age, gender, and education. Contrary to Hypothesis 2, people with bvFTD and with Alzheimer’s disease were nearly equally likely to make financial mistakes due problems with memory (bvFTD OR 1.05, 95% CI 0.43‐2.59, p>0.9). In a planned exploratory analysis, no significant differences were found between Alzheimer’s disease and PPA.

Conclusion

Our positive findings for Hypothesis 1 are concordant with other studies demonstrating socioemotional impairment and insensitivity to adverse outcomes in bvFTD. Meanwhile, our negative finding for Hypothesis 2 may cohere with other work indicating comparable memory impairment in bvFTD and Alzheimer’s disease. More broadly, our findings indicate that caregiver reports can distinguish mechanisms underlying financial mismanagement across different syndromes.
Uncovering Diverse Mechanistic Spreading Pathways in Disease Progression of Alzheimer's Disease
Authors: Yu Zhentao , Dere Mustaf , Li Quefeng , Wu Guorong
Published: December 2022

Background

Although the root cause of Alzheimer's disease (AD) is largely elusive, the amyloid hypothesis has been widely used in the AD research framework, where amyloidosis induces (A biomarker) or facilitates the spread of pathologic tau (T biomarker) followed by immediate neurodegeneration ([N] biomarker) and progressive cognitive decline. As the massive heterogeneities manifested in the clinical symptoms, it is critical to understand the pathophysiological mechanism of how whole‐brain AT[N] biomarkers exert a synergistic effect on cognitive decline in the long period of disease progression.

Method

To answer this important scientific question, we employ a novel multivariate statistical inference approach to uncover the causal‐like effect of AT[N] biomarkers on cognitive decline as well as the underlying non‐modifiable risk factors through high‐dimensional neuroimaging phenotypes. Specifically, we first present a multivariate variable selection method to identify a set of brain regions where the AT[N] biomarkers exhibit strong correlations to the clinical outcomes, such as the composite scores regarding memory or executive function domains. Next, we apply mediation analysis to uncover all possible mechanistic spreading pathways of AT[N] biomarkers that lead to cognitive decline. On top of this, we further investigate the survival time for each identified (either direct or mediated) pathological pathway toward the onset of clinical symptoms, which allows us to manage the priority of risk factors more effectively in routine clinical practice.

Result

(1) There are several brain regions on which the amyloid burdens exert an indirect effect on cognitive decline, being mediated by the reduction of metabolism level at other topologically connected brain regions. (2) There is no overlap between memory‐specific and EF (executive function)‐specific pathways in terms of involved brain region. (3) Having two APOE ε4 alleles significantly increases the risk of developing AD in our survival model, where the odds ratio is 0.474 (p‐value: 0.01) regarding memory problem and 0.60 (p‐value: 0.002) for decline of executive functions.

Conclusion

We have identified a set of mechanistic pathways in the brain where AT[N] biomarkers from multiple regions exert synergistic effect to cognitive decline. The survival rates estimated on these pathways set the stage for the precision medicine in AD treatment.
Neurodegeneration blood markers in largely Hispanic and non‐Hispanic Black COVID‐19 patients: from acute hospitalization to long‐term PASC with/without brain fog
Authors: Nordvig Anna S , Purpura Lawrence , Xi Ke , Kevin Strobino , Noble James M , de Leon Mony J.
Published: December 2022

Background

Understanding the effect of COVID‐19 and Post‐Acute Sequelae of SARS CoV‐2 infection (PASC) on neurodegeneration using accessible blood biomarkers of neurofilament light (NfL) and phosphorylated tau 181 (p‐tau‐181) is of critical importance. Few studies to date have explored levels of neurodegenerative markers in COVID‐19 and PASC among race and ethnic minority populations.

Method

NfL and p‐tau181 blood levels were measured using highly sensitive Simoa technology across three cohorts: (1) 102 Hispanic and non‐Hispanic Black non‐intubated COVID‐19 inpatients (75 +/‐9yo) treated in NYC March to June 2020, 95 of whom had serial samples with a second sample average 17d later; (2) 96 contemporaneously sampled outpatient controls, pre‐vaccination era, without history of COVID‐19, matched for age, sex and race/ethnicity (72+/‐8yo) and (3) 119 PASC diverse outpatients examined at least three months after acute infection, including 55 with brain fog (47+/‐14yo) and 64 without (41+/‐15yo). Associations with clinically‐obtained inflammatory markers (C‐reactive protein [CRP], ferritin, interleukin‐6 [IL‐6], ESR, LDH) were explored. An external quality control allowed direct comparison of NfL and p‐tau‐181 across the groups.

Result

When controlling for age, NfL was significantly elevated in hospitalized COVID‐19 patients vs matched non‐COVID patients, but neither NfL nor p‐tau‐181 levels were significantly elevated in long‐term PASC outpatients with and without cognitive symptoms. NfL, but not p‐tau‐181, increased significantly between time points 1 and 2. At the second time‐point in the hospitalization, but not initially, NfL was significantly associated with CRP, ferritin, IL‐6; p‐tau‐181 was significantly associated with ferritin and IL‐6. There were no associations between NfL or p‐tau181 with either LDH or ESR.

Conclusion

Plasma NfL, but not p‐tau‐181, was elevated in hospitalized non‐intubated COVID‐19 patients in an aged cohort; after controlling for age, neither neurodegenerative marker was identifiable in PASC in middle aged adults. NfL increased significantly after prolonged hospitalization, and persistently elevated inflammatory markers correlated with NfL and p‐tau‐181 after a prolonged hospitalization period. The relationships between NfL, p‐tau‐181, and markers of systemic inflammation during acute COVID‐19 support other pathobiological models for neurodegenerative sequelae in older adults following COVID‐19 infection, but provide some reassurance for PASC brain fog sufferers.
The Proteasome Inhibitor Bortezomib Induces Neurogenesis and Toxicity in Rat Neural Stem Cells
Authors: Sohn Seung Yeon , Kim Hyun‐Jung
Published: December 2022

Background

Dysregulation of protein degradation is related with various diseases including Alzheimer’s disease. Bortezomib is the first drug to treat multiple myeloma, however, the major side effect is induction of peripheral neuropathy. This study was performed to explore the effects and mechanisms of proteasome inhibition in neural stem cells (NSCs).

Method

Cortical neural stem cells were obtained and cultured from embryonic day 14 rats. By immunocytochemistry (ICC), western blot analysis and real‐time PCR followed by reverse transcription PCR, the cell fate of neural stem cells were identified. Toxicity was determined by MTT assay and neurosphere size measurement. BCL2‐BAX protein ratio was detected by western blot to explore the cytotoxic mechanisms.

Result

Neurogenesis was significantly increased by bortezomib in proliferating NSCs when determine by ICC, western blot and PCR. However, such effect was not observed during NSC differentiation. In addition, Bortezomib induced toxicity in both proliferating NSCs and differentiated cells.

Conclusion

Bortezomib is toxic to NSCs and differentiated cells, however, it induced neurogenesis in NSCs.
Brain Structure and Allelic Associations in Alzheimer’s Disease
Authors: Moon Seok Woo , Kim Taeho
Published: December 2022

Background

This paper examines late‐onset dementia‐related cognitive impairment utilizing neuroimaging‐genetics biomarker associations.

Method

The participants, ages 65 to 85, included 266 normal controls (CN’s), 572 mild cognitive impairment (MCI’s), and 188 Alzheimer’s disease (AD) patients. Genotype dosage data for AD‐associated single nucleotide polymorphisms (SNPs) were extracted from the imputed ADNI genetics dosage data using sample‐major additive coding. 29 such SNPs were selected, representing a subset of independent SNPs reported to be highly associated with AD in a recent AD meta‐GWAS study by Jansen et al.

Result

The expected significant correlations between the SNPs and the neuroimaging phenotypes were confirmed using the top 29 genomic markers (GMs) and 200 neuroimaging markers (NIMs). Relative to CN, odds ratios and relative risks for AD and MCI were employed for prediction using multinominal linear modeling of diagnosis. In the CN and MCI cohorts, mainly cortical thickness measures were associated with GMs among thickness and the other measures, even though it was not in the AD cohort. Network patterns within the CN and AD groups were shown as separated 3 group metrics including thickness, volume, and pct (the proportion of White to Gray Matter), but not in the MCI cohort. Multinominal linear model of clinical diagnosis showed precisely the specific NIMs and GMs that were most impactful in discriminating between AD and CN and between MCI and CN.

Conclusion

Advanced analytics provide mechanisms for exploring the interrelations between morphometric biomarkers and genomic indicators. This facilitates clinical investigation of phenotypic associations and facilitates deep systematic understanding of AD pathogenesis.
Peripheral blood leukotriene B4 and E4 as biomarkers in Alzheimer’s disease
Authors: Xiong Lisa Y. , Yu Di , Liang Nuanyi , Shen Qing , Hegele Robert , Ramirez Joel , Goubran Maged , Rabin Jennifer S. , Lanctôt Krista L. , Black Sandra E. , Tartaglia Carmela , Lang Anthony E , Tan Brian , Symons Sean , Taha Ameer Y. , Swardfager Walter
Published: December 2022

Background

We showed recently that use of leukotriene receptor antagonists, typically used in asthma therapy, was associated with preserved executive function among people with Alzheimer’s disease (AD) dementia. The aim of this study was to determine if leukotriene B4 (LTB4) and E4 (LTE4) would be associated with longitudinal changes in cognitive performance and cerebrovascular disease markers in people with AD.

Method

Participants with clinical AD or mild cognitive impairment were identified from the Ontario Neurodegenerative Disease Research Initiative. LTB4 and LTE4 were extracted from fasting serum and quantified using ultra‐high performance liquid chromatography‐tandem mass spectrometry (UPLC‐MS/MS). Concentrations below the limit of detection were imputed using quantile regression imputation of left‐censored data. Cognition was assessed using composite scores for executive function (Trails Making Test B, Symbol Digit Modalities Test, Stroop switching task, and verbal fluency) and memory (Rey Auditory Verbal Learning Test and Brief Visuospatial Memory Test). White matter hyperintensities (WMH), lacunes, and perivascular spaces (PVS) were quantified using T2‐weighted structural magnetic resonance imaging (MRI). Longitudinal associations between baseline LTB4 or LTE4 and cognition and imaging markers at baseline and 1‐year‐follow‐up were assessed using mixed‐effects linear regression models, controlling for baseline demographic factors, medication use, and vascular comorbidities. Findings were corrected for multiple comparisons using a 5% false discovery rate.

Result

Among 158 participants (mean age = 69.22 years, 51% female, mean education = 14.61 years), higher baseline concentrations of LTB4 were not associated with performance in executive function or memory over time nor with changes in WMH, lacunes, or PVS over time. Higher baseline concentrations of LTE4 were associated with better performance in memory over time (β = 0.153 [95% CI = 0.026, 0.287]; however, this finding did not survive correction for multiple comparisons (adjusted p = 0.260; Table 1).

Conclusion

In a group of patients with AD, higher LTB4 and LTE4 in serum were not associated with changes in cognitive performance nor markers of cerebrovascular disease. These findings suggest very little potential for serum leukotrienes as biomarkers for cognitive decline of cerebrovascular disease progression in AD.
Music and Dance Therapy; The Effectiveness of Occupational Therapy Intervention in Preventing Depression amongst Persons living with Alzheimer in Lagos Nigeria
Authors: AKINYELURE FEYIKEMI MARY
Published: December 2022

Background

Globally an estimate of 50 million people were living with Alzheimer in 2017. This number is predicted to reach 82 million in 2030 and 152 million in 2050.

In older adults,Alzheimer and depression are associated with individual distress and with high societal cost of living especially in developing world.

In the same vein depression is the leading cause of disability worldwide among the older adults;it co‐occurs and interacts with Alzheimer in many complex ways.

In fact, depression has caused cognitive impairment, psychological and social dysfunctions which result to the increased in the risk of developing Alzheimer. Depression is very common in the early stages of Alzheimer and often lead to hospitalization.

In Nigeria,Alzheimer is associated with terrible stigma on the client and affiliate stigma among the care givers leading to rejection based on the psychosis features and perceived myths of witchcraft which make people believe out of the ordinary as either mad or possessed by evil spirits. Hence there is dire need to psycho educate people of the evidence based practices on best ways in taking care of people with Alzheimer challenges.

Method

Dora‐care Behavioral foundation an NGO i founded is passionate about elderly care and their well being. 17 people were identified during Alzheimer awareness program. Intervention involved 16 sessions of music and dance (listening to and singing along) at one week interval, cognitive functions (memory, attention, judgment, perception, and decision making ability) were evaluated using cognitive function instruments before and after the intervention.

Result

The result indicated that 12 out of 17 clients showed significant improvement in attention, judgment, decision making ability and perception. However, there was no significant improvement in memory.

Conclusion

Findings show that music and dance therapies has significant improvement in treating Alzheimer and enhance self care.
Associations between FDG metabolism and fMRI connectivity in the default mode network depend on Aβ status in MCI patients
Authors: Malotaux Vincent , Dricot Laurence , Quenon Lisa , Gérard Thomas , Ivanoiu Adrian , Lhommel Renaud , Hanseeuw Bernard J
Published: December 2022

Background

Brain function can be assessed using both resting‐state functional magnetic resonance imaging (rs‐fMRI) and Fluorodeoxyglucose (FDG) PET imaging. The associations between these biomarkers and their evolution with Alzheimer’s disease (AD) are unclear. We aimed to evaluate the associations between the default mode network (DMN) connectivity and glucose metabolism in mild cognitive impairment (MCI) patients with (Aβ+) and without (Aβ‐) AD pathology.

Method

Forty MCI patients (19 Aβ‐/21 Aβ+) performed between 2 to 4 rs‐fMRI acquisitions with an average follow‐up duration of 15 months. At baseline, DMN metabolism was estimated using [18F]‐FDG‐PET SUVr of the isthmus cingulate region‐of‐interest extracted from the Desikan‐Killiany atlas; and Aβ was measured using [18F]‐Flutemetamol‐PET. We used a Centiloid‐threshold>26 to define Aβ+. Multiple regressions were used to assess the FDG‐fMRI associations in the DMN, comparing the two subgroups using FDG‐Aβ interaction models. Table 1 provides demographics and follow‐up durations. All analyses were adjusted for age and sex.

Results

In the entire sample, DMN connectivity and metabolism were not significantly associated to each other. However, we observed an interaction between Aβ status and FDG metabolism (0.23, p=0.03) such that, in the high‐Aβ subgroup, lower FDG metabolism was signiticantly associated with lower DMN connectivity (Fig. 1). In the low‐Aβ subgroup, no associations were observed. We also observed an FDG‐Aβ interaction when predicting longitudinal changes in DMN (‐0.27, p=0.04) such that, in the high‐Aβ subgroup, lower FDG metabolism was associated with a subsequent increase in DMN connectivity over time (Fig. 2).

Conclusion

In high‐Aβ MCI patients, DMN connectivity is positively associated with FDG metabolism measured at baseline. However, the longitudinal association is negative with lower metabolism predicting increasing connectivity over time. Future research is needed to understand the mechanisms behind this inverse relationship. Hypothetically, a synchronous decrease in metabolism in several regions of the DMN could lead to an increase in the correlation between resting‐state activity measured in these regions.
Proteomic indicators of health relate to Alzheimer’s and neurodegenerative disease biomarkers
Authors: Dark Heather E , Peng Zhongsheng , Duggan Michael R , Daya Gulzar , Bilgel Murat , An Yang , Moghekar Abhay , Resnick Susan M. , Walker Keenan A
Published: December 2022

Background

Prior studies suggest that peripheral health and comorbid disease can influence Alzheimer’s disease (AD) pathology and neurodegenerative processes. However, no studies to date have comprehensively examined how measures of peripheral health and risk for non‐neurological disease relate to biomarkers commonly used in AD research. The present study examined the association between 16 protein‐based health indicators and plasma biomarkers of brain amyloid‐β (Aβ) accumulation, phosphorylated tau, neurodegeneration, and reactive astrogliosis.

Method

Plasma‐based biomarkers of AD pathology (Aβ42/40 ratio, pTau‐181), neurodegeneration (neurofilament light chain [NfL]), and reactive astrogliosis (glial fibrillary acidic protein [GFAP]) were measured in Baltimore Longitudinal Study of Aging participants using Quanterix SIMOA assays. Concurrently, the SomaScan proteomic platform was used to measure 7000 proteins, from which 16 proteomic signatures of health and disease risk were derived (i.e., SomaSignal Tests). A subset of participants also received PiB PET scans to assess cortical amyloid. We examined the relationship between health indicators and AD/neurodegeneration biomarkers using Pearson and Spearman correlations and linear regression analyses adjusted for age, sex, race, education, and APOEe4.

Result

The primary analysis included 720 participants (Table 1). Correlation analyses revealed several strong associations between measures of health/disease risk and plasma Aβ42/40 ratio, pTau‐181, NfL, and GFAP levels (Figure 1a). Notably, higher risk scores for heart failure, primary and secondary cardiovascular disease, and kidney disease were consistently positively associated with greater pTau‐181, NfL, and GFAP, and lower with Aβ42/40 ratio. Measures of body fat percentage, lean body mass, and visceral fat were associated with pTau‐181, NfL, and GFAP, whereas resting energy rate was only associated with NfL and GFAP. These relationships were maintained after adjusting for demographic factors and APOEe4 status (Figure 1b). Only heart failure and secondary cardiovascular disease risk scores were associated with elevated cortical amyloid (PiB+; Figure 2); these measures varied positively with cortical amyloid among participants who were PiB+, but not PiB‐ (Figure 3).

Conclusion

Indicators of peripheral health and disease risk demonstrate robust relationships with plasma AD, neurodegeneration, and reactive astrogliosis biomarkers. Peripheral health factors, particularly cardiovascular health, may play an important role in the pathophysiology of AD.
Effect of APOE4 on Plasma Phospho‐tau 217 and Neurofilament Light in the PSEN1 E280A Autosomal Dominant Alzheimer’s Disease Colombian Kindred
Authors: Pruzin Jeremy J. , Su Yi , Chen Yinghua , Chen Kewei , Lopez Hugo , Acosta‐Uribe Juliana , Alzate Diana , Aguillon David , Garcia Gloria , Craig‐Mueller Jennifer , Serrano Geidy E , Langbaum Jessica B. , Ríos‐Romenets Silvia , Quiroz Yakeel T. , Dage Jeffrey L. , Hansson Oskar , Blennow Kaj , Zetterberg Henrik , Kosik Kenneth S. , Lopera Francisco , Tariot Pierre N. , Reiman Eric M.
Published: December 2022

Background

The Colombian kindred affected by the autosomal dominant AD causative mutation PSEN1 E280A are an invaluable population in determining the utility of blood biomarkers (BB) and how additional risk factors may affect BB years to decades prior to symptom onset. Neurofilament light (NfL) (Quiroz et al., 2020) and phospho‐tau 217 (p‐tau217) (Palmqvist et al., 2020) diverge about 20 years prior to onset of clinical symptoms in carriers compared to non‐carriers. How APOE4 carriage may influence NfL and p‐tau217 in the kindred is unknown. We assessed cross‐sectional effects of APOE4 carriage on plasma NfL and p‐tau217 in the PSEN1 E280A kindred.

Method

We used a single molecule array immunoassay to quantify plasma NfL and a Meso Scale Discovery based plasma immunoassay to quantify p‐tau217. 1428 persons (age 18 to 75, mean 35.8, 23% APOE4 carriers, 54% PSEN1 E280A carriers) had available data for NfL analyses. A total of 612 persons (age 18 to 60, mean 35.9, 25% APOE4 carriers, 62% PSEN1 E280A carriers) had available data for p‐tau217 analyses. Age related trajectories were derived from cross‐sectional log‐transformed p‐tau217 and NfL concentrations modelled using a restricted cubic spline model. Model parameters were estimated using a Hamiltonian Markov chain Monte Carlo method in E280A mutation and APOE4 carriage defined groups. The primary comparison was made between APOE4 carrier and noncarriers within E280A carriers and noncarriers separately.

Result

In PSEN1 E280A mutation carriers, plasma NfL concentrations begin to differentiate those who were APOE4 carriers from non‐carriers at age 47.4 (figure 1). Plasma NfL concentrations did not differentiate APOE4 carriers versus non‐carriers in those without the PSEN1 E280A mutation though concentration of NfL trended higher in APOE4 carriers in the higher age range of the sample. Plasma p‐tau217 concentrations did not differentiate APOE4 carriers from non‐carriers in PSEN1 E280A mutation carriers or non‐carriers.

Conclusion

APOE4 carriage results in accelerated NfL plasma increases in PSEN1 E280A mutation carriers starting at about the age of symptom onset. The inability to detect APOE4‐related ptau217 and NfL differences in the other groups may be related to the younger age of participants and limitations in statistical power.
Predicting CSF neurogranin and neurofilament light chain protein levels with a neuropathology‐based APOE genetic risk score
Authors: Whitenack Vanessa M , Deming Yuetiva , Vasiljevic Eva , Van Hulle Carol A. , Jonaitis Erin M. , Kollmorgen Gwendlyn , Suridjan Ivonne , Asthana Sanjay , Carlsson Cynthia M. , Johnson Sterling C. , Zetterberg Henrik , Blennow Kaj , Engelman Corinne D. , Bendlin Barbara B. ,   Alzheimer's Disease Research Center, Madison WI
Published: December 2022

Background

Cerebrospinal fluid (CSF) levels of neurogranin, an index of synaptic degeneration, and neurofilament light chain (NfL), an index of neuroaxonal degradation, are both biomarkers of neurodegeneration in Alzheimer’s disease (AD). The presence of APOE is the strongest genetic risk factor for late onset AD and has also been associated with increased CSF neurogranin, a marker of neurodegeneration. To test the association between APOE and CSF biomarkers for neurodegeneration, we used a neuropathology‐based weighted risk score for APOE genotype (APOE‐npscore) and hypothesized that greater AD risk as indexed by the APOE‐npscore would be associated with higher CSF concentrations of neurogranin and NfL.

Method

We examined data collected from participants in the Wisconsin Registry for Alzheimer’s Prevention (n = 243) (avg age = 65) and Wisconsin Alzheimer’s Disease Research Center (n = 411) (avg age = 64) including participants with Dementia (n = 50) Impaired‐Other (n = 8), Mild Cognitive Impairment (MCI) (n = 55), and cognitively unimpaired (n = 545) participants. The CSF biomarkers were measured using the NeuroToolKit panel of robust prototype assays (Roche Diagnostics International Ltd, Rotkreuz, Switzerland). Using linear regression, we tested associations between the APOE‐npscore and CSF neurogranin and NfL concentrations, adjusting for age at lumbar puncture (LP) and sex. We also tested for interactions between age at LP or sex and the APOE‐npscore.

Results

The APOE‐npscore was significantly associated with CSF neurogranin concentration (β = 3.126, p < 0.01) but not significantly associated with CSF NfL concentration (β = 39.570, p > 0.05). Age at LP was significantly associated (p < 0.001) with CSF neurogranin and NfL concentrations. No significant interactions were found between the APOE‐np score and age at LP or sex in either test. APOE‐npscore, age at LP, and sex accounted for 7% of the variability of CSF neurogranin, and 27% of CSF NfL.

Conclusions

The current study lends additional support to the impact of APOE on neurodegeneration, and supports the utility of using the APOE‐npscore to index risk of AD. The effects of APOE were observed on markers of synaptic degeneration, which underscores the importance of synaptic dysfunction in AD.
Prevalence and Associations of Frailty in Preclinical Alzheimer’s Disease
Authors: Lee Kathryn , Huynh Andrew , Moe Thinza , Amadoru Sanka , Zisis Georgios , Raman Rema , Aisen Paul , Ernstrom Karin , Sperling Reisa A. , Masters Colin L. , Yates Paul A
Published: December 2022

Background

The prevalence of frailty in asymptomatic Alzheimer’s disease is not clear. In this cohort screened for a preclinical Alzheimer’s disease clinical trial, we aimed to compare the prevalence of frailty between participants with and without elevated amyloid as determined by PET and determine if frailty influences the relationship between amyloid and cognition.

Method

Analysis of pre‐randomization data from the Anti‐Amyloid Treatment in Asymptomatic Alzheimer’s (A4) Study, a clinical prevention trial of an anti‐amyloid monoclonal antibody in individuals who were cognitively normal with elevated amyloid burden, to determine a cumulative‐deficits Frailty Index (FI). Logistic regression was used to investigate the difference in the prevalence of frailty, defined as a FI greater than 0.25, according to amyloid status (Aβ+/‐), adjusted for age, gender and education. ANCOVA was used to examine the influence of frailty on the relationship between amyloid status and cognition (Preclinical Alzheimer Cognitive Composite [PACC] score), including an interaction term of frailty and amyloid, adjusted for age, gender and education.

Result

4,486 participants were included (mean age 71.3±4.7 years, 1323 participants Aβ+(29.5%), 59.4% female). Adjusting for age, sex and education, Aβ+ participants were 1.48 times more likely to be frail compared to Aβ− (p<0.001). Frail participants had a lower PACC score compared to non‐frail participants (p<0.001). Both frailty and amyloid status were associated with poorer cognition after adjusting for age, sex and education (p<0.001), but frailty did not influence the relationship between cognition and amyloid status.

Conclusion

There is strong evidence that elevated amyloid burden was associated with an increased risk of frailty and that frailty reduced cognitive performance compared to non‐frail participants in this cohort screened for a preclinical AD trial. These relationships, the potential underlying mechanisms, and whether this may be applicable to longitudinal outcomes, warrant further study.
Investigating the feasibility of creating a disease registry in Egypt: a case study of dementia
Authors: Heikal Shimaa Adel , Salama Mohamed , Barsoum Ghada
Published: December 2022

Background

Disease registries have emerged worldwide to help tackle the impact of chronic diseases by providing accurate data on several aspects of the disease care process. Age‐associated diseases, particularly dementia, are growing worldwide with several implications and increased economic burden, especially in lower‐income countries. In Egypt, there is a lack of accurate dementia prevalence and statistics data which hinders the establishment of appropriate disease management and care strategies. A national dementia registry would provide a massive valuable source of patient data that will significantly advance the disease management strategies and quality of patient care and impact health policy and decision‐making.

Method

This study investigates the feasibility of creating a disease registry for dementia in Egypt through interviewing relevant national and international experts to evaluate their perceptions, knowledge, and opinions, then provide recommendations for the most appropriate registry model to be developed in Egypt.

Result

Several core themes emerged from the analysis of experts’ interviews discussing many points that should direct the creation of any registry in Egypt. Learning from other successful registries, comparing their experiences, and applying them to the Egyptian culture imposes an excellent opportunity for the registry establishment. The findings clearly provided the proposed best practices to be followed while initiating a national registry in Egypt in terms of functionality, planning, comprehension, governance, ethics, and challenges to avoid. The initiating process should start with a leading institution that brings together the potential stakeholders and defines clear purpose and objectives of the registry to direct the planning and design. A primary phase should be the first step to test the functionality and effectiveness of the process then expansion of data and coverage can be a second step.

Conclusion

: Taken together, developing such a dataset is beneficial to the Egyptian healthcare system, which makes the investment worthwhile. Support and collaborative work from all stakeholders, along with suitable funding, are essential elements of the proper implementation of the project. Yet, it might seem to be an opportune time for initiating this kind of registry to address the needs and at the same time benefit from the strategic opportunities.
Prosocial Behavior in Caregivers to Older Adults with Chronic Conditions
Authors: Beadle Janelle
Published: December 2022

Background

In the United States, 1 in 9 adults 65 years of age and older have Alzheimer’s disease. Thus, there is an urgent need for caregivers to support individuals with Alzheimer’s disease, and other chronic diseases of aging. However, due to the challenging physical and emotional nature of caregiving, caregivers are at risk for experiencing chronic stress and burnout which can negatively impact the well‐being of both the care recipient and the caregiver. The purpose of the present study is to examine the degree to which currently serving in a caregiving role affects individuals’ capacity to empathize and exhibit prosocial behavior towards others.

Method

The study included 60 caregivers (Mage = 60.6) to older adults with chronic conditions, and 104 healthy comparison participants (Mage = 62.9). The groups were not significantly different in terms of age (p = .50) or gender (p = .6). Participants played an economic game in which they decided how much money they would like to allocate out of $10 to two different players. During the study, they read a series of notes from the other players which were designed to evoke either an empathetic or neutral state. (Notes were developed by the researcher prior to the study.) Monetary offers were compared between the empathy and neutral experimental conditions. Participants also completed a measure of trait empathy (the Interpersonal Reactivity Index).

Result

We found that the caregivers gave more money in the empathy condition than the non‐caregivers (p<.05), with no statistically significant group differences found in the neutral condition. Within the caregiver group, there was a positive correlation between offer amount in the empathy condition and trait emotional empathy (p<.05).

Conclusion

Despite the stressors involved in caregiving, we show that caregivers exhibited greater prosocial behavior than non‐caregivers towards strangers in an empathy‐eliciting context. This suggests that in specific contexts the stressors involved in caregiving may not reduce caregivers’ capacity to show prosocial behaviors towards others. Future research may investigate whether this finding extends to empathy and prosocial behavior towards care recipients.
A machine learning framework with uncertainty‐driven neuroimaging modality selection for data‐efficient prediction of Alzheimer’s Disease
Authors: Zheng Zhiyang , Su Yi , Chen Kewei , Weidman David , Wu Teresa , Lo ShihChung , Lure Fleming , Li Jing
Published: December 2022

Background

Early prediction of the AD risk for individuals with MCI has important clinical value. Machine Learning (ML) models integrating multi‐modality neuroimaging datasets have shown great promise. Existing approaches either require all the modalities or suffer from performance loss with fewer modalities. We proposed a data‐efficient ML framework, namely the Uncertainty‐driven Modality Selection (UMoS) framework, to sequentially add modalities for each patient on an as‐needed basis while at the same time ensuring high prediction accuracy.

Method

The dataset included 1319 T1‐MRI scans from MCI patients in ADNI and among these 612 additionally had amyloid‐PET. Regional volumetric and thickness measures were computed using FreeSurfer v7.1 from MRI and regional SUVR measures were computed using our in‐house pipeline from amyloid‐PET. MRI is used in the standard of care while amyloid‐PET has less accessibility and is more expensive. Thus, the goal of UMoS was to save a patient from needing PET if doing so did not hurt prediction accuracy. To achieve this, we first trained two elastic net logistic regression models to predict the risk of conversion to AD for MCI patients: one with MRI only; the other one additionally including amyloid‐PET. Uncertainty quantification (UQ) was performed to quantify the predictive uncertainty of the MRI model. Under the UMoS framework, each individual was first predicted using the MRI model. If the predictive uncertainty was high, the individual would be predicted using the MRI+PET model. The uncertainty threshold was selected by balancing the saving of PET in the patient cohort and the prediction accuracy.

Result

UMoS achieved 0.851 Area Under the Curve (AUC) with 46.2% patients predicted by the MRI‐only model and 53.8% by the MRI+PET model. If all patients were predicted by the MRI model, the AUC was 0.794. If all patients were predicted by the MRI +PET model, the AUC was 0.875.

Conclusion

We proposed an ML framework, UMoS, that used predictive uncertainty of the MRI model to drive the decision that if less‐accessible amyloid‐PET was needed for predicting MCI conversion to AD. This framework allows an individualized approach to make accurate prediction based on the data available and leverage additional data only when needed.
Predicting the pace of MCI progression to AD based on multi‐modality neuroimaging data by a novel hybrid ordinal learning algorithm
Authors: Wang Lujia , Su Yi , Zheng Zhiyang , Chen Kewei , Weidman David , Wu Teresa , Lo ShihChung , Lure Fleming , Li Jing
Published: December 2022

Background

Machine learning (ML) has shown great promise for integrating multi‐modality neuroimaging datasets to predict the risk of converting to AD for individuals with Mild Cognitive Impairment (MCI). Most existing work aims to classify MCI patients into converters versus non‐converters. The limitation is a lack of granularity in differentiating MCI patients who convert at different paces. Pace prediction has important clinical values by allowing for more personalized interventional strategies, better preparing patients and their caregivers, and facilitating patient selection in clinical trials. We proposed a novel Hybrid Ordinal Learning (HOL) algorithm for pace prediction of MCI conversion to AD.

Method

This study focused on the amyloid‐positive MCI patient cohort in ADNI for the pace prediction, which included 282 samples. The datasets included baseline T1‐MRI, amyloid‐PET, MMSE, CDR, age, gender, years of education, and APOE status. ROI‐based structural measures were computed from T1‐MRI using FreeSurfer v7.1 and regional SUVR measures were computed using our in‐house pipeline from amyloid‐PET. HOL was trained to predict the conversion to AD for each MCI patient into four ordinal classes representing four fast‐to‐slow paces of conversion, e.g., conversion in the first year, not in the first but in the second year, not in the first two years but by the fifth year, and not in the first five years, respectively. The novelty of HOL compared to existing ordinal classification algorithms was its capability of leveraging imperfectly‐labeled samples in the training set to build a robust learner.

Result

Under cross validation, HOL achieved 0.83 accuracy, balanced across the different paces, based on a combination of 314 features from MRI, PET, and clinical data, while the conventional ordinal SVM classifier achieved only 0.68 accuracy.

Conclusion

We demonstrated that a novel ML algorithm, HOC, could achieve a high accuracy in predicting the pace of conversion to AD for MCI patients. Future research is needed to validate the research finding with larger datasets.
Convergent and Discriminant Validity of NIH Toolbox Cognition Measures of Premorbid Intellectual Functioning in Older African American Adults With and Without Mild Cognitive Impairment
Authors: Halter Colt M , Moll Allison C. , Kero Katherine , Hanna Sophie , DiCerbo Loraine M. , Woodard John L. , Giordani Bruno , Kavcic Voyko
Published: December 2022

Background

Estimation of premorbid IQ (PMIQ) among older adults is crucial to characterize cognitive decline properly, particularly among older adults at risk for Alzheimer’s disease. Three scores from the NIH Toolbox‐Cognition Battery (NIHTB‐C) ostensibly may estimate premorbid functioning: Crystallized Cognition (CC) and its component subtests, Picture Vocabulary (PV) and Oral Reading Recognition (ORR). However, they have not yet been validated in a sample of older African American adults at risk for cognitive impairment. We investigated whether performance on the Crystallized NIHTB‐C measures was related to the WTAR, a gold standard word recognition test associated with PMIQ, in older African Americans with and without mild cognitive impairment (MCI). We also compared WTAR scores to the summary score from the NIHTB‐C Fluid Cognition (FC) battery, where no relationship was expected.

Methods

The WTAR and NIHTB‐C were administered to 36 cognitively normal and 18 MCI participants (diagnoses determined by consensus conference following NACC UDS guidelines) who were community‐dwelling, older African Americans aged 65–86 years. Data analysis used Bayesian bivariate correlations and hierarchical multiple regression to adjust for education effects.

Results

In the full sample, Bayesian bivariate correlations showed that WTAR performance was positively associated with performance on ORR (r = .86, BF10>100, 95%CI[.76, .92]), PV (r = .66, BF10>100, 95%CI[.47, .78]), and CC (r = .84, BF10>100, 95%CI[.72, .90]), and not associated with FC performance (r = .08, BF10 = 0.196, 95%CI[‐.19, .33]). This pattern held in analyses restricted to the cognitively normal (r = .84, BF10>100, 95%CI[.68, .91]; r = .58, BF10>100, 95%CI[.29, .75]; r = .81, BF10>100, 95%CI[.64, .90]; r = .12, BF10 = 0.22, 95%CI[‐.23, .37], respectively) and the MCI groups (r = .88, BF10>100, 95%CI[.64, .95]; r = .71, BF10 = 41.6, 95%CI[.31, .87]; r = .84, BF10>100, 95%CI[.55, .93]; r = ‐.33, BF10 = 0.70, 95%CI[‐.66, .15], respectively). Although education was positively related to the four measures (p<.05), hierarchical multiple regression revealed that education did not predict NIHTB‐C performance and did not improve model fit beyond WTAR performance alone.

Conclusion

WTAR scores are strongly positively associated with NIHTB‐C CC scores and unrelated to FC scores, suggesting appropriate convergent and discriminant validity. Our findings support our hypothesis that NIHTB‐C Crystalized Cognition scores represent reasonable, valid estimates of PMIQ in older African Americans with and without MCI.
A blood‐based diagnostic for Alzheimer’s disease using spectral microscopy of immuno‐enriched Aβ from frozen PBMCs
Authors: Tsutsui Shigeki , Templeton George W , Ota Tomoko , Black Stefanie AG , Stys Peter K
Published: December 2022

Background

In Alzheimer’s disease (AD), toxic Aβ peptides aggregate into higher molecular weight assemblies and accumulate not only in the extracellular space, but also in the walls of blood vessels in the brain, increasing their permeability, and promoting immune cell migration and activation. As immune cells contact these pathological brain materials, they may act as “sentinels” that are detectable once they return to the circulation. Previously, we have demonstrated that leukocytes, when stained with an amyloid sensitive probe, K114 (Tocris Bioscience), display distinct spectral changes in subjects with AD and mild cognitive impairment (MCI) (Black et al. 2022). Here we extend this work by introducing an enhanced method that combines the specificity of immunocapture of Aβ peptides together with spectral interrogation to reveal their amyloid character from easily obtainable frozen peripheral blood mononuclear cells (PBMCs).

Methods

30 frozen PBMC samples were obtained from the National Centralized Repository for Alzheimer’s Disease and Related Dementias (NCRAD) with 15 clinically‐ and histologically‐confirmed MCI/AD and 15 cognitively normal subjects based on the National Alzheimer’s Coordinating Center (NACC) database. To adapt our method to frozen samples, we used immunoprecipitation to purify target amyloid proteins by anti‐Aβ antibody (4G8)‐coated magnetic beads (Protein G SureBeads™, BioRad Laboratories), which were then labelled with K114, and imaged with a spectral confocal microscope.

Results

Comparing subjects with neuropathologically‐confirmed AD (n=6), Braak stage for neurofibrillary degeneration (B score) >5 and density of neocortical neuritic plaques (C score) >2 to cognitively normal controls (n=6), our technique detected highly significant differences between groups (P<0.005, Fig. 1). Correlation between our AD Score and B scores was R = 0.824, and with cognitive status was R = 0.735 (Fig. 2).

Conclusions

These observations indicate that our method is capable of detecting AD from circulating human PBMCs, potentially mirroring the “Aβ load” in the brain. Our technique could constitute a reliable and inexpensive biomarker for early AD and AD‐related MCI.