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

被引：8

作者：

Harms, Robbert L. ^{[1
]}

Ferrari, Alberto ^{[2
]}

Meier, Irene B. ^{[3
]}

Martinkova, Julie ^{[2
,4
,5
]}

Santus, Enrico ^{[2
]}

Marino, Nicola ^{[2
,6
]}

Cirillo, Davide ^{[2
,7
]}

Mellino, Simona ^{[2
]}

Solarz, Silvina Catuara ^{[2
]}

Tarnanas, Ioannis ^{[1
,8
]}

Szoeke, Cassandra ^{[2
,9
]}

Hort, Jakub ^{[4
,5
,10
]}

Valencia, Alfonso ^{[7
,11
]}

Ferretti, Maria Teresa ^{[2
]}

Seixas, Azizi ^{[12
]}

Chadha, Antonella Santuccione ^{[2
]}

机构：

[1] Altoida Inc, Houston, TX USA

[2] Womens Brain Project, Guntershausen, Switzerland

[3] Chione GmbH, CH-8122 Binz, Switzerland

[4] Charles Univ Prague, Fac Med 2, Dept Neurol, Memory Clin, Prague, Czech Republic

[5] Motol Univ Hosp, Prague, Czech Republic

[6] Univ Foggia, Dipartimento Sci Med & Chirurg, Foggia, Italy

[7] Barcelona Supercomp Ctr, Placa Eusebi Guell 1-3, Barcelona 08034, Spain

[8] Global Brain Hlth Inst, Dublin, Ireland

[9] Univ Melbourne, Fac Med Dent & Hlth Sci, Ctr Med Res, Melbourne, Vic, Australia

[10] St Annes Univ Hosp Brno, Int Clin Res Ctr, Brno, Czech Republic

[11] ICREA Inst Catalana Recerca & Estudis Avancats, Pg Lluis Co 23, Barcelona 08010, Spain

[12] Univ Miami, Miller Sch Med, Dept Psychiat & Behav Sci, Miami, FL 33136 USA

来源：

EPMA JOURNAL | 2022年 / 13卷 / 02期

关键词：

Alzheimer's disease; Digital biomarkers; Sex; Classifier; Predictive preventive personalized medicine (PPPM); ASSOCIATION WORKGROUPS; DIAGNOSTIC GUIDELINES; NATIONAL INSTITUTE; RECOMMENDATIONS; PREVENTION; DEMENTIA; MEMORY; CARE; MCI;

D O I：

10.1007/s13167-022-00284-3

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

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'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's, where men and women present with different symptoms and progression patterns that impact diagnosis. In this study, we explore sex differences in Altoida'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'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.

引用

页码：299 / 313

页数：15