Back to Search Start Over

Interactive alkaptonuria database: investigating clinical data to improve patient care in a rare disease.

Authors :
Cicaloni V
Spiga O
Dimitri GM
Maiocchi R
Millucci L
Giustarini D
Bernardini G
Bernini A
Marzocchi B
Braconi D
Santucci A
Source :
FASEB journal : official publication of the Federation of American Societies for Experimental Biology [FASEB J] 2019 Nov; Vol. 33 (11), pp. 12696-12703. Date of Electronic Publication: 2019 Aug 28.
Publication Year :
2019

Abstract

Alkaptonuria (AKU) is an ultrarare autosomal recessive disorder (MIM 203500) that is caused byby a complex set of mutations in homogentisate 1,2-dioxygenasegene and consequent accumulation of homogentisic acid (HGA), causing a significant protein oxidation. A secondary form of amyloidosis was identified in AKU and related to high circulating serum amyloid A (SAA) levels, which are linked with inflammation and oxidative stress and might contribute to disease progression and patients' poor quality of life. Recently, we reported that inflammatory markers (SAA and chitotriosidase) and oxidative stress markers (protein thiolation index) might be disease activity markers in AKU. Thanks to an international network, we collected genotypic, phenotypic, and clinical data from more than 200 patients with AKU. These data are currently stored in our AKU database, named ApreciseKUre. In this work, we developed an algorithm able to make predictions about the oxidative status trend of each patient with AKU based on 55 predictors, namely circulating HGA, body mass index, total cholesterol, SAA, and chitotriosidase. Our general aim is to integrate the data of apparently heterogeneous patients with AKUAKU by using specific bioinformatics tools, in order to identify pivotal mechanisms involved in AKU for a preventive, predictive, and personalized medicine approach to AKU.-Cicaloni, V., Spiga, O., Dimitri, G. M., Maiocchi, R., Millucci, L., Giustarini, D., Bernardini, G., Bernini, A., Marzocchi, B., Braconi, D., Santucci, A. Interactive alkaptonuria database: investigating clinical data to improve patient care in a rare disease.

Details

Language :
English
ISSN :
1530-6860
Volume :
33
Issue :
11
Database :
MEDLINE
Journal :
FASEB journal : official publication of the Federation of American Societies for Experimental Biology
Publication Type :
Academic Journal
Accession number :
31462106
Full Text :
https://doi.org/10.1096/fj.201901529R