Dragan Gamberger (Avtor), Nada Lavrač (Avtor)

Povzetek

The heterogeneity of Alzheimer’s disease contributes to the high failure rate of prior clinical trials. We analyzed 5-year longitudinal outcomes and biomarker data from 562 subjects with mild cognitive impairment (MCI) from two national studies (ADNI) using a novel multilayer clustering algorithm. The algorithm identified homogenous clusters of MCI subjects with markedly different prognostic cognitive trajectories. A cluster of 240 rapid decliners had 2-fold greater atrophy and progressed to dementia at almost 5 times the rate of a cluster of 184 slow decliners. A classifier for identifying rapid decliners in one study showed high sensitivity and specificity in the second study. Characterizing subgroups of at risk subjects, with diverse prognostic outcomes, may provide novel mechanistic insights and facilitate clinical trials of drugs to delay the onset of AD.

Ključne besede

Alzheimer's disease;rapid decliners;data clustering;mild cognitive impairment;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.01 - Izvirni znanstveni članek
Organizacija: UNG - Univerza v Novi Gorici
UDK: 577
COBISS: 4875771 Povezava se bo odprla v novem oknu
ISSN: 2045-2322
Št. ogledov: 3537
Št. prenosov: 343
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

URN: URN:SI:UNG
Vrsta dela (COBISS): Delo ni kategorizirano
Strani: str. 1-12
Zvezek: ǂVol. ǂ7
Čas izdaje: 2017
DOI: 10.1038/s41598-017-06624-y
ID: 10859184