Evidence map›Paper›PMID 31462106›Full record

ArticleFASEB journal : official publication of the Federation of American Societies for Experimental Biology2019

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

Vittoria Cicaloni, Ottavia Spiga, Giovanna Maria Dimitri, Rebecca Maiocchi, Lia Millucci, Daniela Giustarini, Giulia Bernardini, Andrea Bernini, Barbara Marzocchi, Daniela Braconi and 1 more

Open access · greenAbstract read
In one paragraph

Article in FASEB journal : official publication of the Federation of American Societies for Experimental Biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.3field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. Review
  3. Alkaptonuria.Nature reviews. Disease primers · 2024
    Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 2 countries.

Vittoria CicaloniDepartment of Biotechnology, Chemistry, and Pharmacy, University of Siena, Siena, Italy.
Ottavia SpigaDepartment of Biotechnology, Chemistry, and Pharmacy, University of Siena, Siena, Italy.
Giovanna Maria DimitriDepartment of Computer Science, University of Cambridge, Cambridge, United Kingdom.
Rebecca MaiocchiDepartment of Biotechnology, Chemistry, and Pharmacy, University of Siena, Siena, Italy.
Lia MillucciDepartment of Biotechnology, Chemistry, and Pharmacy, University of Siena, Siena, Italy.
Daniela GiustariniDepartment of Biotechnology, Chemistry, and Pharmacy, University of Siena, Siena, Italy.
Giulia BernardiniDepartment of Biotechnology, Chemistry, and Pharmacy, University of Siena, Siena, Italy.
Andrea BerniniDepartment of Biotechnology, Chemistry, and Pharmacy, University of Siena, Siena, Italy.
Barbara MarzocchiDepartment of Biotechnology, Chemistry, and Pharmacy, University of Siena, Siena, Italy.
Daniela BraconiDepartment of Biotechnology, Chemistry, and Pharmacy, University of Siena, Siena, Italy.
Annalisa SantucciDepartment of Biotechnology, Chemistry, and Pharmacy, University of Siena, Siena, Italy.
University of Siena · ITToscana Life Sciences · ITUniversity of Cambridge · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AlkaptonuriaComputational BiologyDatabases, GeneticPrecision MedicineRare DiseasesFemaleHumansMalebiomarkersmachine learningprecision medicine

Identifiers

PMID31462106
PMCPMC6902683
OpenAlexW2970042411

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.