Digital biomarkers and sex impacts in Alzheimer's disease management - potential utility for innovative 3P medicine approach

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00159816%3A_____%2F22%3A00077653" target="_blank" >RIV/00159816:_____/22:00077653 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00064203:_____/22:10444545 RIV/00216208:11130/22:10444545

Výsledek na webu

<a href="https://link.springer.com/article/10.1007/s13167-022-00284-3" target="_blank" >https://link.springer.com/article/10.1007/s13167-022-00284-3</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s13167-022-00284-3" target="_blank" >10.1007/s13167-022-00284-3</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Digital biomarkers and sex impacts in Alzheimer's disease management - potential utility for innovative 3P medicine approach

Popis výsledku v původním jazyce

Digital biomarkers are defined as objective, quantifiable physiological and behavioral data that are collected and measured by means of digital devices. Their use has revolutionized clinical research by enabling high-frequency, longitudinal, and sensitive measurements. In the field of neurodegenerative diseases, an example of a digital biomarker-based technology is instrumental activities of daily living (iADL) digital medical application, a predictive biomarker of conversion from mild cognitive impairment (MCI) due to Alzheimer&apos;s disease (AD) to dementia due to AD in individuals aged 55+. Digital biomarkers show promise to transform clinical practice. Nevertheless, their use may be affected by variables such as demographics, genetics, and phenotype. Among these factors, sex is particularly important in Alzheimer&apos;s, where men and women present with different symptoms and progression patterns that impact diagnosis. In this study, we explore sex differences in Altoida&apos;s digital medical application in a sample of 568 subjects consisting of a clinical dataset (MCI and dementia due to AD) and a healthy population. We found that a biological sex-classifier, built on digital biomarker features captured using Altoida&apos;s application, achieved a 75% ROC-AUC (receiver operating characteristic - area under curve) performance in predicting biological sex in healthy individuals, indicating significant differences in neurocognitive performance signatures between males and females. The performance dropped when we applied this classifier to more advanced stages on the AD continuum, including MCI and dementia, suggesting that sex differences might be disease-stage dependent. Our results indicate that neurocognitive performance signatures built on data from digital biomarker features are different between men and women. These results stress the need to integrate traditional approaches to dementia research with digital biomarker technologies and personalized medicine perspectives to achieve more precise predictive diagnostics, targeted prevention, and customized treatment of cognitive decline.

Název v anglickém jazyce

Digital biomarkers and sex impacts in Alzheimer's disease management - potential utility for innovative 3P medicine approach

Popis výsledku anglicky

Digital biomarkers are defined as objective, quantifiable physiological and behavioral data that are collected and measured by means of digital devices. Their use has revolutionized clinical research by enabling high-frequency, longitudinal, and sensitive measurements. In the field of neurodegenerative diseases, an example of a digital biomarker-based technology is instrumental activities of daily living (iADL) digital medical application, a predictive biomarker of conversion from mild cognitive impairment (MCI) due to Alzheimer&apos;s disease (AD) to dementia due to AD in individuals aged 55+. Digital biomarkers show promise to transform clinical practice. Nevertheless, their use may be affected by variables such as demographics, genetics, and phenotype. Among these factors, sex is particularly important in Alzheimer&apos;s, where men and women present with different symptoms and progression patterns that impact diagnosis. In this study, we explore sex differences in Altoida&apos;s digital medical application in a sample of 568 subjects consisting of a clinical dataset (MCI and dementia due to AD) and a healthy population. We found that a biological sex-classifier, built on digital biomarker features captured using Altoida&apos;s application, achieved a 75% ROC-AUC (receiver operating characteristic - area under curve) performance in predicting biological sex in healthy individuals, indicating significant differences in neurocognitive performance signatures between males and females. The performance dropped when we applied this classifier to more advanced stages on the AD continuum, including MCI and dementia, suggesting that sex differences might be disease-stage dependent. Our results indicate that neurocognitive performance signatures built on data from digital biomarker features are different between men and women. These results stress the need to integrate traditional approaches to dementia research with digital biomarker technologies and personalized medicine perspectives to achieve more precise predictive diagnostics, targeted prevention, and customized treatment of cognitive decline.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30218 - General and internal medicine

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

EPMA JOURNAL

ISSN

1878-5077

e-ISSN

1878-5085

Svazek periodika

13

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

15

Strana od-do

299-313

Kód UT WoS článku

000806659500001

EID výsledku v databázi Scopus

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