Sharing data in the global alzheimer's association interactive network

Comparison of genetic and health risk factors for mild cognitive impairment and Alzheimer's disease between Hispanic and non-Hispanic white participants

INTRODUCTION

The influence of apolipoprotein E (APOE) genotype on mild cognitive impairment (MCI) and Alzheimer's disease (AD) is well studied in the non-Hispanic white (NHW) population but not in the Hispanic population. Additionally, health risk factors such as hypertension, stroke, and depression may also differ between the two populations.

METHODS

We combined three data sets (National Alzheimer's Coordinating Center [NACC], Alzheimer's Disease Neuroimaging Initiative [ADNI], Health and Aging Brain Study: Health Disparities [HABS-HD]) and compared risk factors for MCI and AD between Hispanic and NHW participants, with a total of 24,268 participants (11.1% Hispanic).

RESULTS

APOEε4 was associated with fewer all-cause MCI cases in Hispanic participants (Hispanic odds ratio [OR]: 1.114; NHW OR: 1.453), and APOEε2 (Hispanic OR: 1.224; NHW OR: 0.592) and depression (Hispanic OR: 2.817; NHW OR: 1.847) were associated with more AD cases in Hispanic participants.

DISCUSSION

APOEε2 may not be protective for AD in Hispanic participants and Hispanic participants with depression may face a higher risk for AD.

HIGHLIGHTS

GAAIN allows for discovery of data sets to use in secondary analyses. APOEε2 was not protective for AD in Hispanic participants. APOEε4 was associated with fewer MCI cases in Hispanic participants. Depression was associated with more AD cases in Hispanic participants.

A large public dataset of annotated clinical MRIs and metadata of patients with acute stroke

To extract meaningful and reproducible models of brain function from stroke images, for both clinical and research proposes, is a daunting task severely hindered by the great variability of lesion frequency and patterns. Large datasets are therefore imperative, as well as fully automated image post-processing tools to analyze them. The development of such tools, particularly with artificial intelligence, is highly dependent on the availability of large datasets to model training and testing. We present a public dataset of 2,888 multimodal clinical MRIs of patients with acute and early subacute stroke, with manual lesion segmentation, and metadata. The dataset provides high quality, large scale, human-supervised knowledge to feed artificial intelligence models and enable further development of tools to automate several tasks that currently rely on human labor, such as lesion segmentation, labeling, calculation of disease-relevant scores, and lesion-based studies relating function to frequency lesion maps.

The pursuit of approaches to federate data to accelerate Alzheimer's disease and related dementia research: GAAIN, DPUK, and ADDI

There is common consensus that data sharing accelerates science. Data sharing enhances the utility of data and promotes the creation and competition of scientific ideas. Within the Alzheimer's disease and related dementias (ADRD) community, data types and modalities are spread across many organizations, geographies, and governance structures. The ADRD community is not alone in facing these challenges, however, the problem is even more difficult because of the need to share complex biomarker data from centers around the world. Heavy-handed data sharing mandates have, to date, been met with limited success and often outright resistance. Interest in making data Findable, Accessible, Interoperable, and Reusable (FAIR) has often resulted in centralized platforms. However, when data governance and sovereignty structures do not allow the movement of data, other methods, such as federation, must be pursued. Implementation of fully federated data approaches are not without their challenges. The user experience may become more complicated, and federated analysis of unstructured data types remains challenging. Advancement in federated data sharing should be accompanied by improvement in federated learning methodologies so that federated data sharing becomes functionally equivalent to direct access to record level data. In this article, we discuss federated data sharing approaches implemented by three data platforms in the ADRD field: Dementia's Platform UK (DPUK) in 2014, the Global Alzheimer's Association Interactive Network (GAAIN) in 2012, and the Alzheimer's Disease Data Initiative (ADDI) in 2020. We conclude by addressing open questions that the research community needs to solve together.

Italian, European, and international neuroinformatics efforts: An overview

Neuroinformatics is a research field that focusses on software tools capable of identifying, analysing, modelling, organising and sharing multiscale neuroscience data. Neuroinformatics has exploded in the last two decades with the emergence of the Big Data phenomenon, characterised by the so-called 3Vs (volume, velocity and variety), which provided neuroscientists with an improved ability to acquire and process data faster and more cheaply thanks to technical improvements in clinical, genomic and radiological technologies. This situation has led to a 'data deluge', as neuroscientists can routinely collect more study data in a few days than they could in a year just a decade ago. To address this phenomenon, several neuroimaging-focussed neuroinformatics platforms have emerged, funded by national or transnational agencies, with the following goals: (i) development of tools for archiving and organising analytical data (XNAT, REDCap and LabKey); (ii) development of data-driven models evolving from reductionist approaches to multidimensional models (RIN, IVN, HBD, EuroPOND, E-DADS and GAAIN BRAIN); and (iii) development of e-infrastructures to provide sufficient computational power and storage resources (neuGRID, HBP-EBRAINS, LONI and CONP). Although the scenario is still fragmented, there are technological and economical attempts at both national and international levels to introduce high standards for open and Findable, Accessible, Interoperable and Reusable (FAIR) neuroscience worldwide.

Developing a Dementia Platform Databank Using Multiple Existing Cohorts

This study was conducted as a pilot project to evaluate the feasibility of building an integrate dementia platform converging preexisting dementia cohorts from several variable levels. The following four cohorts were used to develop this pilot platform: 1) Clinical Research Center for Dementia of South Korea (CREDOS), 2) Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer's disease (K-BASE), 3) Environmental Pollution-induced Neurological Effects (EPINEF) study, and 4) a prospective registry in Dementia Platform Korea project (DPKR). A total of 29916 patients were included in the platform with 348 integrated variables. Among participants, 13.9%, 31.5%, and 44.2% of patients had normal cognition, mild cognitive impairment, and dementia, respectively. The mean age was 72.4 years. Females accounted for 65.7% of all patients. Those with college or higher education and those without problems in reading or writing accounted for 12.3% and 46.8%, respectively. Marital status, cohabitation, family history of Parkinson's disease, smoking and drinking status, physical activity, sleep status, and nutrition status had rates of missing information of 50% or more. Although individual cohorts were of the same domain and of high quality, we found there were several barriers to integrating individual cohorts, including variability in study variables and measurements. Although many researchers are trying to combine pre-existing cohorts, the process of integrating past data has not been easy. Therefore, it is necessary to establish a protocol with considerations for data integration at the cohort establishment stage.

The Association between the Usage of Non-Steroidal Anti-Inflammatory Drugs and Cognitive Status: Analysis of Longitudinal and Cross-Sectional Studies from the Global Alzheimer's Association Interactive Network and Transcriptomic Data

The degenerative cognitive and physical decline of Alzheimer patients, coupled with the extensive psychological and economic tolls imposed on family members that serve as caretakers, necessitate the discovery of effective cures and preventative measures for age-related cognitive depreciation. In the journey of Alzheimer’s disease treatment discovery, several cross-sectional and longitudinal studies have delineated a noticeable association between the use of nonsteroidal anti-inflammatory drugs (NSAIDs), a class of low-cost drugs with minimal side effects, and the alleviation of age-related memory impairment. In this study, four datasets (two cross-sectional and two longitudinal studies) derived from the Global Alzheimer’s Association Interactive Network (GAAIN) were analyzed. The significant association between the usage of NSAIDs and better cognitive status was observed. The results agree with the findings of previous studies that the use of NSAIDs may be beneficial in the early stages of Alzheimer’s disease. Transcriptomic data show that ibuprofen treatment results in upregulation of several genes involved in arachidonic acid metabolism including PPARγ, Cyp4a12b, Cyp2c66, and Cyp2c37 in the hippocampus. The increase in conversion of arachidonic acid into anti-inflammatory 16C and 18C dicarboxylic acids as well as epoxyeicosatrienoic acids may play a role in reducing the risk of Alzheimer’s disease development.

The power of knowledge about dementia in Latin America across health professionals working on aging

INTRODUCTION

Expert knowledge is critical to fight dementia in inequitable regions like Latin American and Caribbean countries (LACs). However, the opinions of aging experts on public policies' accessibility and transmission, stigma, diagnostic manuals, data-sharing platforms, and use of behavioral insights (BIs) are not well known.

METHODS

We investigated opinions among health professionals working on aging in LACs (N = 3365) with regression models including expertise-related information (public policies, BI), individual differences (work, age, academic degree), and location.

RESULTS

Experts specified low public policy knowledge (X2  = 41.27, P < .001), high levels of stigma (X2  = 2636.37, P < .001), almost absent BI knowledge (X2  = 56.58, P < .001), and needs for regional diagnostic manuals (X2  = 2893.63, df = 3, P < .001) and data-sharing platforms (X2 = 1267.5, df = 3, P < .001). Lack of dementia knowledge was modulated by different factors. An implemented BI-based treatment for a proposed prevention program improved perception across experts.

DISCUSSION

Our findings help to prioritize future potential actions of governmental agencies and non-governmental organizations (NGOs) to improve LACs' dementia knowledge.

Utilisation of hospital information systems for medical research in Saudi Arabia: A mixed-method exploration of the views of healthcare and IT professionals involved in hospital database management systems

BACKGROUND

Although in recent times the Saudi government has paid much attention to the adaptation of hospital information systems (HIS) and electronic medical records (EMR), the importance of utilising HIS to enhance medical research has been neglected.

OBJECTIVE

We aimed to (i) investigate the current state of medical research in Saudi Arabia, (ii) identify possible issues that hinder improvement of medical research and (iii) identify possible solutions to enhance the role of HIS in medical research in Saudi Arabia.

METHOD

We used a questionnaire and structured interview approach. Questionnaires were distributed to Saudi healthcare professionals. One hundred responses to our questionnaire were captured by the online Google Form designed specifically for our survey. Structured interviews with two IT professionals were conducted regarding technical aspects of their hospital data management systems.

RESULTS

Six themes contributing to the inefficacy of HIS in medical research in Saudi Arabia emerged from the data: incorrect datasets, difficult data collection and storage, poor data analytics, a lack of system interoperability across different HIS for universal access and negative perception of the usefulness of HIS for medical research.

CONCLUSION AND IMPLICATIONS

Our findings suggest (i) cloud-based HIS would support efficient, reliable and integrated data collection and storage across all hospitals in Saudi Arabia; (ii) EMR data sources should be seamlessly linked to avoid incomplete, fragmented or erroneous EMR in Saudi Arabia; and (iii) collaboration between all hospitals in Saudi Arabia to adopt a uniform standard to support interoperability and improve data exchange and integration is necessary.

Patient data discovery platforms as enablers of biomedical and translational research: A systematic review

BACKGROUND

The global shift from paper health records to electronic ones has led to an impressive growth of biomedical digital data along the past two decades. Exploring and extracting knowledge from these data has the potential to enhance translational research and lead to positive outcomes for the population's health and healthcare.

OBECTIVE

The aim of this study was to conduct a systematic review to identify software platforms that enable discovery, secondary use and interoperability of biomedical data. Additionally, we aim evaluating the identified solutions in terms of clinical interest and main healthcare-related outcomes.

METHODS

A systematic search of the scientific literature published and indexed in Pubmed between January 2014 and September 2018 was performed. Inclusion criteria were as follows: relevance for the topic of biomedical data discovery, English language, and free full text. To increase the recall, we developed a semi-automatic and incremental methodology to retrieve articles that cite one or more of the previous set.

RESULTS

A total number of 500 candidate papers were retrieved through this methodology. Of these, 85 were eligible for abstract assessment. Finally, 37 studies qualified for a full-text review, and 20 provided enough information for the study objectives.

CONCLUSIONS

This study revealed that biomedical discovery platforms are both a current necessity and a significantly innovative agent in the area of healthcare. The outcomes that were identified, in terms of scientific publications, clinical studies and research collaborations stand as evidence.

Age-Related Increase of Insulin-Degrading Enzyme Is Inversely Correlated with Cognitive Function in APPswe/PS1dE9 Mice

Background

Insulin-degrading enzyme (IDE) is an important regulator for Aβ clearance and diabetes. Although it is indispensable in removing plaques related to onset Alzheimer’s disease (AD) and in degrading insulin related to diabetes, there have been few studies on the dynamic level of IDE in different stages of AD.

Material/Methods

The present study explored the level IDE protein in different stages of APPswe/PS1dE9 mice and their correlations with cognitive decline. The 4-month-old, 10-month-old, and 18-month-old mice were used as the different age stages of mice. Cognitive function was evaluated using the Morris water maze test. We also observed the level of Aβ plaques in brain regions of different stages.

Results

The data revealed that the expression of IDE was dramatically higher than in age-matched wild mice at the age of 10 months and 18 months. In terms of distribution, Aβ plaques were deposited mostly in the cortex and hippocampus, especially in 10-month-old and 18-month-old APPswe/PS1dE9 mice. The cognitive function of 4-month-old APPswe/PS1dE9 mice was not significantly differ in spatial learning. However, the cognitive function, both spatial learning and spatial memory, was dramatically lower in 10-month-old and 18-month-old groups.

Conclusions

There was a positive correlation between the expression of IDE and spatial memory in 10-month-old and 18-month-old APPswe/PS1dE9 mice. The study of this protein may provide reference values for the further study of IDE in Alzheimer’s disease.

Apolipoprotein E Genotype and Sex Risk Factors for Alzheimer Disease: A Meta-analysis

Importance

It is unclear whether female carriers of the apolipoprotein E (APOE) ε4 allele are at greater risk of developing Alzheimer disease (AD) than men, and the sex-dependent association of mild cognitive impairment (MCI) and APOE has not been established.

Objective

To determine how sex and APOE genotype affect the risks for developing MCI and AD.

Data Sources

Twenty-seven independent research studies in the Global Alzheimer's Association Interactive Network with data on nearly 58 000 participants.

Study Selection

Non-Hispanic white individuals with clinical diagnostic and APOE genotype data.

Data Extraction and Synthesis

Homogeneous data sets were pooled in case-control analyses, and logistic regression models were used to compute risks.

Main Outcomes and Measures

Age-adjusted odds ratios (ORs) and 95% confidence intervals for developing MCI and AD were calculated for men and women across APOE genotypes.

Results

Participants were men and women between ages 55 and 85 years. Across data sets most participants were white, and for many participants, racial/ethnic information was either not collected or not known. Men (OR, 3.09; 95% CI, 2.79-3.42) and women (OR, 3.31; CI, 3.03-3.61) with the APOE ε3/ε4 genotype from ages 55 to 85 years did not show a difference in AD risk; however, women had an increased risk compared with men between the ages of 65 and 75 years (women, OR, 4.37; 95% CI, 3.82-5.00; men, OR, 3.14; 95% CI, 2.68-3.67; P = .002). Men with APOE ε3/ε4 had an increased risk of AD compared with men with APOE ε3/ε3. The APOE ε2/ε3 genotype conferred a protective effect on women (OR, 0.51; 95% CI, 0.43-0.61) decreasing their risk of AD more (P value = .01) than men (OR, 0.71; 95% CI, 0.60-0.85). There was no difference between men with APOE ε3/ε4 (OR, 1.55; 95% CI, 1.36-1.76) and women (OR, 1.60; 95% CI, 1.43-1.81) in their risk of developing MCI between the ages of 55 and 85 years, but women had an increased risk between 55 and 70 years (women, OR, 1.43; 95% CI, 1.19-1.73; men, OR, 1.07; 95% CI, 0.87-1.30; P = .05). There were no significant differences between men and women in their risks for converting from MCI to AD between the ages of 55 and 85 years. Individuals with APOE ε4/ε4 showed increased risks vs individuals with ε3/ε4, but no significant differences between men and women with ε4/ε4 were seen.

Conclusions and Relevance

Contrary to long-standing views, men and women with the APOE ε3/ε4 genotype have nearly the same odds of developing AD from age 55 to 85 years, but women have an increased risk at younger ages.

The Cloud Gets Personal

Cloud computing, at its most fundamental level, is a technology that allows computing to occur as an on-demand utility. Personalized medicine is revolutionizing the field of medicine, and aims to provide individualized treatment for patients, based on their genetic material and medical history, through comparisons to genetic material from thousands of other patients. Better patient outcomes are expected in a personalized medicine domain as compared to more generic generalized options. In this paper the authors explore the use of cloud computing in the area of personalized medicine examining unique benefits and opportunities. They also recognize and discuss the presence of some inherent risks. Using the cloud for personalized medicine can expedite collaborations and data collection across different clinicians, researchers and other stakeholders involved in the fight against diseases. This paper examines key elements associated with using cloud computing in the specialized area of personalized medicine.

The Global Alzheimer's Association Interactive Network

INTRODUCTION

The Global Alzheimer's Association Interactive Network (GAAIN) is consolidating the efforts of independent Alzheimer's disease data repositories around the world with the goals of revealing more insights into the causes of Alzheimer's disease, improving treatments, and designing preventative measures that delay the onset of physical symptoms.

METHODS

We developed a system for federating these repositories that is reliant on the tenets that (1) its participants require incentives to join, (2) joining the network is not disruptive to existing repository systems, and (3) the data ownership rights of its members are protected.

RESULTS

We are currently in various phases of recruitment with over 55 data repositories in North America, Europe, Asia, and Australia and can presently query >250,000 subjects using GAAIN's search interfaces.

DISCUSSION

GAAIN's data sharing philosophy, which guided our architectural choices, is conducive to motivating membership in a voluntary data sharing network.

The Alzheimer's Disease Neuroimaging Initiative informatics core: A decade in review

The Informatics Core of the Alzheimer's Disease Neuroimaging Initiative has coordinated data integration and dissemination for a continually growing and complex data set in which both data contributors and recipients span institutions, scientific disciplines, and geographic boundaries. This article provides an update on the accomplishments and future plans.