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Pregled bibliografske jedinice broj: 906129

Using redescription mining to relate clinical and biological characteristics of cognitively impaired and Alzheimer's disease patients


(Alzheimer’s Disease Neuroimaging Initiative) Mihelčić, Matej; Šimić, Goran; Babić Leko, Mirjana; Lavrač, Nada; Džeroski, Sašo; Šmuc, Tomislav
Using redescription mining to relate clinical and biological characteristics of cognitively impaired and Alzheimer's disease patients // PLoS One, 12 (2017), 10; 1-35 doi:10.1371/journal.pone.0187364 (međunarodna recenzija, članak, znanstveni)


Naslov
Using redescription mining to relate clinical and biological characteristics of cognitively impaired and Alzheimer's disease patients

Autori
Mihelčić, Matej ; Šimić, Goran ; Babić Leko, Mirjana ; Lavrač, Nada ; Džeroski, Sašo ; Šmuc, Tomislav

Kolaboracija
Alzheimer’s Disease Neuroimaging Initiative

Izvornik
PLoS One (1932-6203) 12 (2017), 10; 1-35

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Biological and clinical indicators ; cognitive impairment ; predictive clustering trees ; redescription mining ; unsupervised learning

Sažetak
Based on a set of subjects and a collection of attributes obtained from the Alzheimer's Disease Neuroimaging Initiative database, we used redescription mining to find interpretable rules revealing associations between those determinants that provide insights about the Alzheimer's disease (AD). We extended the CLUS-RM redescription mining algorithm to a constraint-based redescription mining (CBRM) setting, which enables several modes of targeted exploration of specific, user-constrained associations. Redescription mining enabled finding specific constructs of clinical and biological attributes that describe many groups of subjects of different size, homogeneity and levels of cognitive impairment. We confirmed some previously known findings. However, in some instances, as with the attributes: testosterone, ciliary neurotrophic factor, brain natriuretic peptide, Fas ligand, the imaging attribute Spatial Pattern of Abnormalities for Recognition of Early AD, as well as the levels of leptin and angiopoietin-2 in plasma, we corroborated previously debatable findings or provided additional information about these variables and their association with AD pathogenesis. Moreover, applying redescription mining on ADNI data resulted with the discovery of one largely unknown attribute: the Pregnancy-Associated Protein-A (PAPP-A), which we found highly associated with cognitive impairment in AD. Statistically significant correlations (p ≤ 0.01) were found between PAPP-A and clinical tests: Alzheimer's Disease Assessment Scale, Clinical Dementia Rating Sum of Boxes, Mini Mental State Examination, etc. The high importance of this finding lies in the fact that PAPP-A is a metalloproteinase, known to cleave insulin-like growth factor binding proteins. Since it also shares similar substrates with A Disintegrin and the Metalloproteinase family of enzymes that act as α-secretase to physiologically cleave amyloid precursor protein (APP) in the non-amyloidogenic pathway, it could be directly involved in the metabolism of APP very early during the disease course. Therefore, further studies should investigate the role of PAPP-A in the development of AD more thoroughly.

Izvorni jezik
Engleski

Znanstvena područja
Temeljne medicinske znanosti, Kliničke medicinske znanosti, Kognitivna znanost (prirodne, tehničke, biomedicina i zdravstvo, društvene i humanističke znanosti)



POVEZANOST RADA


Projekt / tema
HRZZ-IP-2014-09-9730 - Hiperfosforilacija, agregacija i transsinaptički prijenos tau proteina u Alzheimerovoj bolesti: analiza likvora i ispitivanje potencijalnih neuroprotektivnih spojeva

Ustanove
Institut "Ruđer Bošković", Zagreb,
Medicinski fakultet, Zagreb

Časopis indeksira:


  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE


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