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Abstract Interdisciplinary approaches are needed to understand the relationship between genetic factors and brain structure and function. Here we describe a database that includes genetic data on apolipoprotein E (APOE) and phosphatidylinositol binding clathrin assembly protein (PICALM) genes, both of which are known to increase the risk of late-onset Alzheimer's disease, paired with psychometric (memory, intelligence, mood, personality, stress coping strategies), basic demographic and health data on a cohort of 192 healthy middle-aged (50–63) individuals. Part of the database (~79 participants) also includes blood tests (blood counts, lipid profile, HSV virus) and functional neuroimaging data (EEG/fMRI) recorded with a resting-state protocol (eyes open and eyes closed) and two cognitive tasks (multi-source interference task, MSIT; and Sternberg's memory task). The data were validated and showed overall good quality. This open-science dataset is well suited not only for research relating to susceptibility to Alzheimer's disease but also for more general questions on brain aging or can be used as part of meta-analytical multi-disciplinary projects.

Background: A number of late‐onset Alzheimer's disease (AD) risk genes have been discovered, among which the most studied but not fully explored is the apolipoprotein E gene (APOE). PICALM (coding Phosphatidylinositol Binding Clathrin Assembly Protein) is another well‐recognized risk‐gene, shown to interact with the APOE gene in conferring AD risk. MicroRNAs (miRNAs) are post‐transcriptional regulators of mRNAs, some of which are known to be involved in AD pathology. The purpose of this study was to investigate in middle‐aged, healthy participants the association between AD risk‐genes (APOE and PICALM) and circulating miRNAs that were previously identified as altered in AD patients. Method: Blood samples were collected from 76 healthy individuals (36 F, 36 M; age: 56.38±3.16), assigned to three groups: A+P+ (APOE/PICALM risk), A+P‐ (APOE risk, PICALM neutral alleles) and N group (APOE/PICALM neutral alleles). RT‐qPCR was used to compare the levels of 11 microRNA identified by us in previous studies as candidate early AD biomarkers in blood plasma (hsa‐miR‐29b‐3p, hsa‐miR‐34a‐5p, hsa‐miR‐125b, hsa‐miR‐146a, hsa‐miR‐135a, hsa‐miR‐30b‐5p, hsa‐miR‐142‐3p, hsa‐miR‐200a‐3p, hsa‐miR‐483‐5p, hsa‐miR‐486‐5p, hsa‐miR‐502‐3p) [1, 2]. We followed standard procedures of blood assays. Result: Single gene risk (APOE) carriers had lower levels of miR‐29b‐3p than non‐carriers and double risk carriers (F(2,73) = 12.75, p < 0.001 with Welch homogeneity correction; post‐hoc with Tukey correction: p < 0.01 for A+P‐ versus N, p < 0.001 for A+P‐ versus A+P+). No other changes in miRNA panels were discovered. Conclusion: Downregulation of miR‐29b‐3p in blood was detected repeatedly before in patients with AD, in 4 independent studies [1]. Here we show the same effect in a subpopulation of middle‐age, healthy individuals with APOE related genetic risk for AD. Further research is needed to understand the interaction reversing this effect in PICALM risk carriers. Longitudinal follow‐up may validate this blood‐based miRNA not only as an easy‐to‐access diagnostic biomarker, but also as a risk‐assessment biomarker for AD prevention. Funding: This work was funded by the Polish National Science Centre (NCN) grant no. 2018/31/N/HS6/03551, 2016/20/W/NZ4/00354 and 2018/29/B/NZ7/02757. [1], [2] https://doi.org/10.1016/j.arr.2018.10.008; 10.18632/oncotarget.15109. [ABSTRACT FROM AUTHOR]

Background: The APOE (allele ε4) and PICALM (SNPs rs541458: allele T; and rs3851179: allele G) genes were recognized as risk factors for late‐onset Alzheimer's disease (AD). However, effects of these risk genes on the cognitive functions of healthy individuals are still not determined and their possible interactions have never been studied. We investigated the preclinical influence of both genes on brain cognitive functions in a healthy middle‐aged population. Method: Seventy three healthy adults (50‐63 y/o) completed computer tasks measuring attention, cognitive control and memory. MSIT task included an easy‐control condition and an attentionally demanding condition with combined cognitive conflicts. Sternberg's task included an easy condition (there is a need to memorize 4 letters strings) and a hard‐one (with 8 letters strings). APOE (rs429358/rs7412) and PICALM (rs3851179 and rs541458) alleles were determined using a traditional Sanger sequencing protocol. The data was divided according to the genetic tests results (control group: absence of ε4 and less‐risky PICALM alleles; the double risk group: ε4‐carriers, and homozygous carriers of high‐risk PICALM alleles; single risk group: ε4‐carriers and less‐risky PICALM alleles). ANOVA was used to determine the effects of genetic variants on task performance (reaction time (RT) and accuracy for easy/hard MSIT and Sternberg conditions). Result: Results revealed that while the groups did not differ in accuracy or RTs for easy conditions, they did differ significantly on hard conditions (p<0.05). The single‐risk group showed longer RTs than the control group in both tasks. The effect was preserved when performing the analysis of covariance (ANCOVA) with the age as a covariate. Conclusion: AD risk genes, APOE and PICALM, can affect cognitive abilities even in healthy individuals. APOE‐ε4‐carriers needed longer time to process difficult stimuli but surprisingly an addition of PICALM risk alleles seemed to reverse this tendency. Further studies are needed to unambiguously determine the effects of the PICALM and its interactions with other risk genes (including APOE) in modulating the cognitive abilities of still healthy individuals. [Supported by National Science Centre, Poland, no. 2018/31/N/HS6/03551.] [ABSTRACT FROM AUTHOR]

Background: One of the best‐known genes associated with late‐onset Alzheimer's disease (AD) is the apolipoprotein E (APOE). It is thought that the ε4 allele of this gene increases the risk of developing AD. The aim of this study was to investigate the preclinical influence of APOE‐ε4 on brain cognitive functions in a healthy population. Method: 200 (F:108, M: 92) healthy middle‐aged (50‐64 years old; M=55) right‐handed adults completed a series of psychometric questionnaires: RAVEN (Raven's Progressive Matrices, classical version), BDI (Beck Depression Inventory), Mini‐COPE (Mini‐COPE Questionnaire) and CVLT (California Verbal Learning Test). We also collected information about demography, family history of AD and health. APOE alleles were determined by sequencing their chosen variants (APOE SNPs rs429358/rs7412) using a traditional Sanger sequencing protocol. The group was divided according to the results of the genetic test for ε4‐non carriers (150) and ε4‐carriers (50). Result: Both groups were equivalent in age, gender, and years of completed education. There were no differences in intelligence (RAVEN scores), depressive symptoms (BDI) nor memory test results (CVLT). More ε4‐carriers had a family (parents) history of AD (Welch's t‐test, t(75.21)=‐2.11, p<0.05). In the Mini‐COPE questionnaire ε4‐carriers group also scored less points on two (out of 3) scales rating problem‐focused (adaptation) strategies: Planning (2. scale) (trend: Welch's t‐test t(77.45)=1.84, p=0.07) and Using Instrumental Support (8. scale) (Welch's t‐test t(77.40)=2.07, p<0.05). Despite overall comparable memory performance, there was also a tendency for ε4‐carriers to be statistically better at recalling words from List A (5) (Welch's t‐test, t(112.72)=‐2.14, p<0.05) in the CVLT test. Conclusion: These preliminary results indicate that even in a healthy middle‐aged population APOE genotype could influence cognitive abilities and alter stress‐coping strategies. Further research is needed to determine if better memory recall is present also in younger ε4‐carriers or whether it is a (transient) benefit of mnemonics techniques developed later in life to cope with a slowly starting memory decline. Supported by Polish National Science Centre (NCN) grant no. 2018/31/N/HS6/03551. [ABSTRACT FROM AUTHOR]

Interdisciplinary approaches are needed to understand the relationship between genetic factors and brain structure and function. Here we describe a database that includes genetic data on apolipoprotein E (APOE) and phosphatidylinositol binding clathrin assembly protein (PICALM) genes, both of which are known to increase the risk of late-onset Alzheimer's disease, paired with psychometric (memory, intelligence, mood, personality, stress coping strategies), basic demographic and health data on a cohort of 192 healthy middle-aged (50-63) individuals. Part of the database (~79 participants) also includes blood tests (blood counts, lipid profile, HSV virus) and functional neuroimaging data (EEG/fMRI) recorded with a resting-state protocol (eyes open and eyes closed) and two cognitive tasks (multi-source interference task, MSIT; and Sternberg's memory task). The data were validated and showed overall good quality. This open-science dataset is well suited not only for research relating to susceptibility to Alzheimer's disease but also for more general questions on brain aging or can be used as part of meta-analytical multi-disciplinary projects., (© 2024. The Author(s).)

The ability to identify and resolve conflicts between standard, well-trained behaviors and behaviors required by the current context is an essential feature of cognitive control. To date, no consensus has been reached on the brain mechanisms involved in exerting such control: while some studies identified diverse patterns of activity across different conflicts, other studies reported common resources across conflict tasks or even across simple tasks devoid of the conflict component. The latter reports attributed the entire activity observed in the presence of conflict to longer time spent on the task (i.e., to the so-called time-on-task effects). Here, we used an extended Multi-Source Interference Task (MSIT) which combines Simon and flanker types of interference to determine shared and conflict-specific mechanisms of conflict resolution in fMRI and their separability from the time-on-task effects. Large portions of the activity in the dorsal attention network and decreases of activity in the default mode network were shared across the tasks and scaled in parallel with increasing reaction times. Importantly, the activity in the sensory and sensorimotor cortices, as well as in the posterior medial frontal cortex (pMFC) - a key region implicated in conflict processing - could not be exhaustively explained by the time-on-task effects., (© 2024 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

APOE‑ε4 genotype (apolipoprotein E, epsilon 4) is the strongest genetic risk factor for Alzheimer's disease (AD). Despite years of research, it is still not known how it contributes to dementia development. APOE has been implicated in many AD pathology mechanisms, like Aβ clearance, brain metabolism, changes within microglia and other glial functions and inflammatory processes. In fact, immunological/inflammatory processes are recently discussed as an important factor in Alzheimer's development and granulocyte profiles changes are reported in patients. However, the exact link between the immune system and risk‑genes is unknown. In particular, it is not known whether and how they interact throughout the lifetime, before the disease onset. The aim of the study was to investigate the relationship between granulocyte count and the APOE/PICALM genes in healthy individuals with an increased genetic risk of AD. An exploratory analysis regarding other blood cells was also conducted. Blood samples were collected from 77 healthy middle‑aged (50-63 years old) participants, who were also asked to complete a health and life‑style questionnaires. Groups with different AD risk‑genes were compared. Differences in granulocyte profiles were found in healthy carriers of AD risk‑genes who had slightly elevated eosinophil levels as compared to non-risk carriers. An exploratory analysis showed some alteration in mean corpuscular hemoglobin content and concentration (MCH/MCHC) levels between risk‑carriers subgroups and non-risk carriers. No other differences in blood count or lipoprotein profile were found between healthy APOE/PICALM risk‑carriers and non-risk carriers. Longitudinal studies will reveal if and how those changes contribute to the development of AD pathology.

Background: One of the goals of neuropsychology is to understand the brain mechanisms underlying aspects of attention and cognitive control. Several tasks have been developed as a part of this body of research, however their results are not always consistent. A reliable comparison of the data and a synthesis of study conclusions has been precluded by multiple methodological differences. Here, we describe a publicly available, high-density electroencephalography (EEG) dataset obtained from 42 healthy young adults while they performed 3 cognitive tasks: (i) an extended multi-source interference task; (ii) a 3-stimuli oddball task; (iii) a control, simple reaction task; and (iv) a resting-state protocol. Demographic and psychometric information are included within the dataset., Dataset Validation: First, data validation confirmed acceptable quality of the obtained EEG signals. Typical event-related potential (ERP) waveforms were obtained, as expected for attention and cognitive control tasks (i.e., N200, P300, N450). Behavioral results showed the expected progression of reaction times and error rates, which confirmed the effectiveness of the applied paradigms., Conclusions: This dataset is well suited for neuropsychological research regarding common and distinct mechanisms involved in different cognitive tasks. Using this dataset, researchers can compare a wide range of classical EEG/ERP features across tasks for any selected subset of electrodes. At the same time, 128-channel EEG recording allows for source localization and detailed connectivity studies. Neurophysiological measures can be correlated with additional psychometric data obtained from the same participants. This dataset can also be used to develop and verify novel analytical and classification approaches that can advance the field of deep/machine learning algorithms, recognition of single-trial ERP responses to different task conditions, and detection of EEG/ERP features for use in brain-computer interface applications., (© The Author(s) 2022. Published by Oxford University Press GigaScience.)