Springer Science and Business Media LLC

The lack of progress over the last decade in developing treatments for Alzheimer’s disease has called into question the quality of the cognitive assessments used while also shifting the emphasis from treatment to prophylaxis by studying the disorder at earlier stages, even prior to the development of cognitive symptoms. This has led various groups to seek cognitive tests which are more sensitive than those currently used and which can be meaningfully administered to individuals with mild or even no cognitive impairment. Although computerized tests have long been used in this field, they have made little inroads compared with non-automated tests. This review attempts to put in perspective the relative utilities of automated and non-automated tests of cognitive function in therapeutic trials of pathological aging and the dementias. Also by a review of the automation of cognitive tests over the last 150 years, it is hoped that the notion that such procedures are novel compared with pencil-and-paper testing will be dispelled. Furthermore, data will be presented to illustrate that older individuals and patients with dementia are neither stressed nor disadvantaged when tested with appropriately developed computerized methods. An important aspect of automated testing is that it can assess all aspects of task performance, including the speed of cognitive processes, and data are presented on the advantages this can confer in clinical trials. The ultimate objectives of the review are to encourage decision making in the field to move away from the automated/non-automated dichotomy and to develop criteria pertinent to each trial against which all available procedures are evaluated. If we are to make serious progress in this area, we must use the best tools available, and the evidence suggests that automated testing has earned the right to be judged against the same criteria as non-automated tests.

Alzheimer’s disease (AD) is a neurodegenerative disease that is clinically characterized by progressive cognitive decline. Mutations in amyloid-β precursor protein (APP), presenilin 1 (PSEN1), and presenilin 2 (PSEN2) are the pathogenic cause of autosomal dominant AD (ADAD). However, polymorphisms also exist within these genes. In order to distinguish polymorphisms from pathogenic mutations, the DIAN Expanded Registry has implemented an algorithm for determining ADAD pathogenicity using available information from multiple domains, including genetic, bioinformatic, clinical, imaging, and biofluid measures and in vitro analyses. We propose that PSEN1 M84V, PSEN1 A396T, PSEN2 R284G, and APP T719N are likely pathogenic mutations, whereas PSEN1 c.379_382delXXXXinsG and PSEN2 L238F have uncertain pathogenicity. In defining a subset of these variants as pathogenic, individuals from these families can now be enrolled in observational and clinical trials. This study outlines a critical approach for translating genetic data into meaningful clinical outcomes.

Chemokines, which are chemotactic inflammatory mediators involved in controlling the migration and residence of all immune cells, are closely associated with brain inflammation, recognized as one of the potential processes/mechanisms associated with cognitive impairment. We aim to determine the chemokines which are significantly altered in Alzheimer’s disease (AD) and mild cognitive impairment (MCI), as well as the respective effect sizes, by performing a meta-analysis of chemokines in cerebrospinal fluid (CSF) and blood (plasma or serum). We searched three databases (Pubmed, EMBASE and Cochrane library) for studies regarding chemokines. The three pairwise comparisons were as follows: AD vs HC, MCI vs healthy controls (HC), and AD vs MCI. The fold-change was calculated using the ratio of mean (RoM) chemokine concentration for every study. Subgroup analyses were performed for exploring the source of heterogeneity. Of 2338 records identified from the databases, 61 articles comprising a total of 3937 patients with AD, 1459 with MCI, and 4434 healthy controls were included. The following chemokines were strongly associated with AD compared with HC: blood CXCL10 (RoM, 1.92, p = 0.039), blood CXCL9 (RoM, 1.78, p < 0.001), blood CCL27 (RoM, 1.34, p < 0.001), blood CCL15 (RoM, 1.29, p = 0.003), as well as CSF CCL2 (RoM, 1.19, p < 0.001). In the comparison of AD with MCI, there was significance for blood CXCL9 (RoM, 2.29, p < 0.001), blood CX3CL1 (RoM, 0.77, p = 0.017), and blood CCL1 (RoM, 1.37, p < 0.001). Of the chemokines tested, blood CX3CL1 (RoM, 2.02, p < 0.001) and CSF CCL2 (RoM, 1.16, p = 0.004) were significant for the comparison of MCI with healthy controls. Chemokines CCL1, CCL2, CCL15, CCL27, CXCL9, CXCL10, and CX3CL1 might be most promising to serve as key molecular markers of cognitive impairment, although more cohort studies with larger populations are needed.

The Clock Drawing Test (CDT) and Rey–Osterrieth Complex Figure Test (RCFT) are widely used as a part of neuropsychological test batteries to assess cognitive function. Our objective was to confirm the prediction accuracies of the RCFT-copy and CDT for cognitive impairment (CI) using convolutional neural network algorithms as a screening tool. The CDT and RCFT-copy data were obtained from patients aged 60–80 years who had more than 6 years of education. In total, 747 CDT and 980 RCFT-copy figures were utilized. Convolutional neural network algorithms using TensorFlow (ver. 2.3.0) on the Colab cloud platform ( www.colab.research.google.com ) were used for preprocessing and modeling. We measured the prediction accuracy of each drawing test 10 times using this dataset with the following classes: normal cognition (NC) vs. mildly impaired cognition (MI), NC vs. severely impaired cognition (SI), and NC vs. CI (MI + SI). The accuracy of the CDT was better for differentiating MI (CDT, 78.04 ± 2.75; RCFT-copy, not being trained) and SI from NC (CDT, 91.45 ± 0.83; RCFT-copy, 90.27 ± 1.52); however, the RCFT-copy was better at predicting CI (CDT, 77.37 ± 1.77; RCFT, 83.52 ± 1.41). The accuracy for a 3-way classification (NC vs. MI vs. SI) was approximately 71% for both tests; no significant difference was found between them. The two drawing tests showed good performance for predicting severe impairment of cognition; however, a drawing test alone is not enough to predict overall CI. There are some limitations to our study: the sample size was small, all the participants did not perform both the CDT and RCFT-copy, and only the copy condition of the RCFT was used. Algorithms involving memory performance and longitudinal changes are worth future exploration. These results may contribute to improved home-based healthcare delivery.

Previous studies have shown that copy number variation (CNV) in the alpha (α)-amylase gene (AMY1A) is associated with body mass index, insulin resistance, and blood glucose levels, factors also shown to increase the risk of Alzheimer’s dementia (AD). We have previously demonstrated the presence of α-amylase in healthy neuronal dendritic spines and a reduction of the same in AD patients. In the current study, we investigate the relationship between AMY1A copy number and AD, memory performance, and brain α-amylase activity. The association between AMY1A copy number and development of AD was analyzed in 5422 individuals (mean age at baseline 57.5 ± 5.9, females 58.2%) from the Malmö diet and cancer study genotyped for AMY1A copy number, whereof 247 where diagnosed with AD during a mean follow-up of 20 years. Associations between AMY1A copy number and cognitive performance where analyzed in 791 individuals (mean age at baseline 54.7 ± 6.3, females 63%), who performed Montreal Cognitive Assessment (MoCA) test. Correlation analysis between α-amylase activity or α-amylase gene expression and AMY1A copy number in post-mortem hippocampal tissue from on demented controls (n = 8) and AD patients (n = 10) was also performed. Individuals with very high ( ≥10) AMY1A copy number had a significantly lower hazard ratio of AD (HR = 0.62, 95% CI 0.41–0.94) and performed significantly better on MoCA delayed word recall test, compared to the reference group with AMY1A copy number 6. A trend to lower hazard ratio of AD was also found among individuals with low AMY1A copy number (1–5) (HR = 0.74, 95% CI 0.53–1.02). A tendency towards a positive correlation between brain α-amylase activity and AMY1A copy number was found, and females showed higher brain α-amylase activity compared to males. Our study suggests that the degree of α-amylase activity in the brain is affected by AMY1A copy number and gender, in addition to AD pathology. The study further suggests that very high AMY1A copy number is associated with a decreased hazard ratio of AD and we speculate that this effect is mediated via a beneficial impact of AMY1A copy number on episodic memory performance.

An amendment to this paper has been published and can be accessed via the original article.

APOE4 is the strongest genetic risk factor for sporadic Alzheimer’s disease (AD), whereas APOE2 confers protection. However, effects of APOE on neurodegeneration in cognitively intact individuals, and how these associations evolve with cognitive decline, are unclear. Furthermore, few studies have evaluated whether effects of APOE on neurodegenerative changes are modified by other AD key risk factors including age and sex. Participants included older adults (57% women; 77 ± 7 years) from the Rancho Bernardo Study of Health Aging and the University of California San Diego Alzheimer’s Disease Research Center, including 192 cognitively normal (CN) individuals and 33 with mild cognitive impairment. Participants underwent diffusion MRI, and multicompartment restriction spectrum imaging (RSI) metrics were computed in white matter, gray matter, and subcortical regions of interest. Participants were classified as APOE4 carriers, APOE2 carriers, and APOE3 homozygotes. Analysis of covariance among CN (adjusting for age, sex, and scanner) assessed differences in brain microstructure by APOE, as well as interactions between APOE and sex. Analyses across all participants examined interactions between APOE4 and cognitive status. Linear regressions assessed APOE by age interactions. Among CN, APOE4 carriers showed lower entorhinal cortex neurite density than non-carriers, whereas APOE2 carriers showed lower cingulum neurite density than non-carriers. Differences in entorhinal microstructure by APOE4 and in entorhinal and cingulum microstructure by APOE2 were present for women only. Age correlated with lower entorhinal restricted isotropic diffusion among APOE4 non-carriers, whereas age correlated with lower putamen restricted isotropic diffusion among APOE4 carriers. Differences in microstructure between cognitively normal and impaired participants were stronger for APOE4-carriers in medial temporal regions, thalamus, and global gray matter, but stronger for non-carriers in caudate. The entorhinal cortex may be an early target of neurodegenerative changes associated with APOE4 in presymptomatic individuals, whereas APOE2 may support beneficial white matter and entorhinal microstructure, with potential sex differences that warrant further investigation. APOE modifies microstructural patterns associated with aging and cognitive impairment, which may advance the development of biomarkers to distinguish microstructural changes characteristic of normal brain aging, APOE-dependent pathways, and non-AD etiologies.