P4-046: A EUROPEAN MEDICAL INFORMATION FRAMEWORK FOR ALZHEIMER'S DISEASE (EMIF-AD)

Background: physiological differences between males and females could contribute to the development of Alzheimer's Disease (AD). Here, we examined metabolic pathways that may lead to precision medicine initiatives. Methods: We explored whether sex modifies the association of 540 plasma metabolites with AD endophenotypes including diagnosis, cerebrospinal fluid (CSF) biomarkers, brain imaging, and cognition using regression analyses for 695 participants (377 females), followed by sex-specific pathway overrepresentation analyses, APOE ε4 stratification and assessment of metabolites’ discriminatory performance in AD. Results: In females with AD, vanillylmandelate (tyrosine pathway) was increased and tryptophan betaine (tryptophan pathway) was decreased. The inclusion of these two metabolites (area under curve (AUC) = 0.83, standard error (SE) = 0.029) to a baseline model (covariates + CSF biomarkers, AUC = 0.92, SE = 0.019) resulted in a significantly higher AUC of 0.96 (SE = 0.012). Kynurenate was decreased in males with AD (AUC = 0.679, SE = 0.046). Conclusions: metabolic sex-specific differences were reported, covering neurotransmission and inflammation pathways with AD endophenotypes. Two metabolites, in pathways related to dopamine and serotonin, were associated to females, paving the way to personalised treatment.

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Primary fatty amides in plasma associated with brain amyloid burden, hippocampal volume, and memory in the European Medical Information Framework for Alzheimer's Disease biomarker discovery cohort

Alzheimer s & Dementia ◽

10.1016/j.jalz.2019.03.004 ◽

2019 ◽

Vol 15 (6) ◽

pp. 817-827 ◽

Cited By ~ 16

Author(s):

Min Kim ◽

Stuart Snowden ◽

Tommi Suvitaival ◽

Ashfaq Ali ◽

David J. Merkler ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Medical Information ◽

Biomarker Discovery ◽

Hippocampal Volume ◽

Amyloid Burden ◽

Discovery Cohort ◽

Disease Biomarker ◽

Fatty Amides ◽

Information Framework

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FTS-01-01: A european medical information framework for Alzheimer's disease (EMIF-AD)

Alzheimer s & Dementia ◽

10.1016/j.jalz.2015.07.022 ◽

2015 ◽

Vol 11 (7S_Part_3) ◽

pp. P120-P121 ◽

Cited By ~ 1

Author(s):

Pieter Jelle Visser ◽

Johannes Streffer

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Medical Information ◽

Information Framework

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Serving a Forgotten Population

The International Journal of Information, Diversity, & Inclusion (IJIDI) ◽

10.33137/ijidi.v4i1.32414 ◽

2019 ◽

Vol 4 (1) ◽

Author(s):

Mary Beth Riedner ◽

Tysha Shay ◽

Kayla Kuni

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Social Isolation ◽

Social Impact ◽

Medical Information ◽

Mission Statements ◽

National Library ◽

Communication Techniques ◽

The Social

The stigma attached to a diagnosis of Alzheimer’s Disease or a related dementia is enormous, and those living with dementia often speak of the negative, and almost immediate, social impact of the disease. According to Alzheimer’s Disease International, there were approximately 50 million people worldwide living with dementia in 2017 and this number could reach 131.5 million by 2050 (n.d.). The social isolation that affects many people living with dementia is best combatted by knowledge and understanding. There are many ways that libraries can put their mission statements into action with regard to this devastating disease. People living with dementia are coming into libraries every day. Library staff need training to recognize those who may be affected and to develop effective communication techniques to meet their special needs. In addition to purchasing books and other materials about the disease and how to cope with it, libraries can help those living with dementia and their caregivers find medical information available from underused sources such as Medline Plus from the National Library of Medicine. Libraries are uniquely suited to host educational events and community discussions. Outside organizations such as the Alzheimer’s Association can provide informational sessions held in the library. There are also several model projects developed by libraries across the country that demonstrate how libraries can provide direct programming and services to those living with dementia. Libraries can play a significant role in reducing social isolation among those living with dementia and improving the quality of their lives.

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A metabolite-based machine learning approach to diagnose Alzheimer’s-type dementia in blood: Results from the European Medical Information Framework for Alzheimer’s Disease biomarker discovery cohort

10.1101/19007146 ◽

2019 ◽

Author(s):

Daniel Stamate ◽

Min Kim ◽

Petroula Proitsi ◽

Sarah Westwood ◽

Alison Baird ◽

...

Keyword(s):

Machine Learning ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Medical Information ◽

Biomarker Discovery ◽

Gradient Boosting ◽

Plasma Metabolites ◽

Csf Biomarkers ◽

Extreme Gradient Boosting ◽

And Gender

AbstractINTRODUCTIONMachine learning (ML) may harbor the potential to capture the metabolic complexity in Alzheimer’s Disease (AD). Here we set out to test the performance of metabolites in blood to categorise AD when compared to CSF biomarkers.METHODSThis study analysed samples from 242 cognitively normal (CN) people and 115 with AD-type dementia utilizing plasma metabolites (n=883). Deep Learning (DL), Extreme Gradient Boosting (XGBoost) and Random Forest (RF) were used to differentiate AD from CN. These models were internally validated using Nested Cross Validation (NCV).RESULTSOn the test data, DL produced the AUC of 0.85 (0.80-0.89), XGBoost produced 0.88 (0.86-0.89) and RF produced 0.85 (0.83-0.87). By comparison, CSF measures of amyloid, p-tau and t-tau (together with age and gender) produced with XGBoost the AUC values of 0.78, 0.83 and 0.87, respectively.DISCUSSIONThis study showed that plasma metabolites have the potential to match the AUC of well-established AD CSF biomarkers in a relatively small cohort. Further studies in independent cohorts are needed to validate whether this specific panel of blood metabolites can separate AD from controls, and how specific it is for AD as compared with other neurodegenerative disorders

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Leverage Real-world Longitudinal Data in Large Clinical Research Networks for Alzheimer's Disease and Related Dementia (ADRD)

10.1101/2020.08.03.20167619 ◽

2020 ◽

Author(s):

Rui Duan ◽

Zhaoyi Chen ◽

Jiayi Tong ◽

Chongliang Luo ◽

Tianchen Lyu ◽

...

Keyword(s):

Risk Factors ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Longitudinal Data ◽

Clinical Research ◽

Distributed Algorithms ◽

Real World ◽

Medical Information ◽

Patient Privacy ◽

Research Networks

With vast amounts of patients' medical information, electronic health records (EHRs) are becoming one of the most important data sources in biomedical and health care research. Effectively integrating data from multiple clinical sites can help provide more generalized real-world evidence that is clinically meaningful. To analyze the clinical data from multiple sites, distributed algorithms are developed to protect patient privacy without sharing individual-level medical information. In this paper, we applied the One-shot Distributed Algorithm for Cox proportional hazard model (ODAC) to the longitudinal data from the OneFlorida Clinical Research Consortium to demonstrate the feasibility of implementing the distributed algorithms in large research networks. We studied the associations between the clinical risk factors and Alzheimer's disease and related dementia (ADRD) onsets to advance clinical research on our understanding of the complex risk factors of ADRD and ultimately improve the care of ADRD patients.

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The Media's influence on the validity of medical information regarding Alzheimer's Disease

Journal of Student Research ◽

10.47611/jsrhs.v10i2.1524 ◽

2021 ◽

Vol 10 (2) ◽

Author(s):

Samhita Korukonda ◽

Hiranmayi Pantula

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Medical Information ◽

The Internet ◽

Common Source ◽

Web Browsers ◽

Patient Awareness ◽

The Us ◽

The Usa ◽

The Media

This article aims to statistically analyze misinformation regarding dementia and Alzheimer’s disease (AD) on the internet and discuss common trends amongst falsities. The internet is the most common source of medical information and is largely used by the general public to seek information about a condition/treatment. Dementia is one of the most searched conditions across online platforms. AD is the most common cause of dementia in the US and accounts for 75% of dementia cases. As the prevalence of AD increases, more patients turn to the media to seek information about its implications and treatments. With the increasingly important role that media plays in the field of medicine, families need to be aware of potential sources of misinformation. This paper analyzes one hundred total sources, then categorizes each source into one of three groups (with varying degrees of falsities): misleading, partially misleading, and reliable. The sources were collected using the keywords “Alzheimer’s disease” and included 50 videos from YouTube and 25 recommended sources from Google and Firefox respectively (Google and Firefox are some of the most used web browsers in the USA). Subsequently, a misinformed source was thematically classified based on the type of misinformation found. To verify results, all sources were reviewed by a senior geropsychiatric consultant from London, who specializes in dementia care/treatment. [Further elaborated in ‘methods’ section] The results indicate that there is systematic misinformation on the internet. It highlights the importance of patient awareness towards this issue. On this basis, it should be recommended that provider’s offices alert their patients of this problem.

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TMEM106B and CPOX are genetic determinants of cerebrospinal fluid Alzheimer’s disease biomarker levels

10.1101/2020.05.31.125633 ◽

2020 ◽

Author(s):

Shengjun Hong ◽

Valerija Dobricic ◽

Isabelle Bos ◽

Stephanie J. B. Vos ◽

Dmitry Prokopenko ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cerebrospinal Fluid ◽

Medical Information ◽

Genome Wide Association Study ◽

Biomarker Discovery ◽

Csf Biomarkers ◽

Sequence Of Events ◽

Genome Wide ◽

Csf Levels

AbstractBackgroundNeurofilament light (NF-L), chitinase-3-like protein 1 (YKL-40), and neurogranin (Ng) are utilized as biomarkers for Alzheimer’s disease (AD), to monitor axonal damage, astroglial activation, and synaptic degeneration, respectively. Here we performed genome-wide association study (GWAS) analyses using all three biomarkers as outcome.MethodsDNA and cerebrospinal fluid (CSF) samples originated from the European Medical Information Framework AD Multimodal Biomarker Discovery (EMIF-AD MBD) study. Overlapping genotype/phenotype data were available for n=671 (NF-L), 677 (YKL-40), and 672 (Ng) individuals. GWAS analyses applied linear regression models adjusting for relevant covariates.FindingsWe identify novel genome-wide significant associations with markers in TMEM106B and CSF levels of NF-L. Additional novel signals were observed with DNA variants in CPOX and CSF levels of YKL-40. Lastly, we confirmed previous work suggesting that YKL-40 levels are regulated by cis protein quantitative trait loci (pQTL) in CHI3L1.InterpretationOur study provides important new insights into the genetic architecture underlying inter-individual variation in all three tested AD-related CSF biomarkers. In particular, our data shed light on the sequence of events regarding the initiation and progression of neuropathological processes relevant in AD.

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