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

Scientific paper - Original scientific paper

• Author: Matej Mihelčić
• Author: Goran Šimić
• Author: Mirjana Babić Leko
• Author: Nada Lavrač
• Author: Sašo Džeroski
• Author: Tomislav Šmuc
• Author's institution: University of Zagreb; School of Medicine
• Scientific / art field, discipline and subdiscipline: BIOMEDICINE AND HEALTHCARE; Basic Medical Sciences

Abstract (english)

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.

• Keywords (english): Algorithms; Alzheimer Disease/pathology; Cognition Disorders/pathology; Humans
• Language: english
• Publication type: Scientific paper - Original scientific paper
• Publication status: Published
• Peer review: Peer review
• Publication version: Published version
• Journal title: PLoS One
• Numbering: vol. 12, no. 10, e0187364
• p-ISSN: 1932-6203
• DOI: https://doi.org/10.1371/journal.pone.0187364
• URN:NBN: urn:nbn:hr:105:643165
• Publication: 2017-10-31
• Document URL: https://doi.org/10.1371/journal.pone.0187364
• Type of resource: Text
• Access conditions: Open access
• Created on: 2024-04-09 05:47:54