↓ Skip to main content

JIMD Reports, Volume 32

Overview of attention for book
Cover of 'JIMD Reports, Volume 32'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 537 Newborn Screening Programmes in Europe, Arguments and Efforts Regarding Harmonisation: Focus on Organic Acidurias
  3. Altmetric Badge
    Chapter 541 Whole Exome Sequencing Identifies the Genetic Basis of Late-Onset Leigh Syndrome in a Patient with MRI but Little Biochemical Evidence of a Mitochondrial Disorder
  4. Altmetric Badge
    Chapter 547 Hydroxysteroid 17-Beta Dehydrogenase Type 10 Disease in Siblings
  5. Altmetric Badge
    Chapter 553 Endurance Exercise Training in Young Adults with Barth Syndrome: A Pilot Study
  6. Altmetric Badge
    Chapter 556 Newborn Screening for Vitamin B6 Non-responsive Classical Homocystinuria: Systematical Evaluation of a Two-Tier Strategy
  7. Altmetric Badge
    Chapter 560 Establishing New Cut-Off Limits for Galactose 1-Phosphate-Uridyltransferase Deficiency for the Dutch Newborn Screening Programme
  8. Altmetric Badge
    Chapter 561 Management of an LCHADD Patient During Pregnancy and High Intensity Exercise
  9. Altmetric Badge
    Chapter 562 Rare Case of Hepatic Gaucheroma in a Child on Enzyme Replacement Therapy
  10. Altmetric Badge
    Chapter 564 Reliable Diagnosis of Carnitine Palmitoyltransferase Type IA Deficiency by Analysis of Plasma Acylcarnitine Profiles
  11. Altmetric Badge
    Chapter 566 Low Protein Formula: Consequences of Quantitative Effects of Pre-analytical Factors on Amino Acid Concentrations in Plasma of Healthy Infants
  12. Altmetric Badge
    Chapter 567 Relationships Between Childhood Experiences and Adulthood Outcomes in Women with PKU: A Qualitative Analysis
  13. Altmetric Badge
    Chapter 568 A Multiplatform Metabolomics Approach to Characterize Plasma Levels of Phenylalanine and Tyrosine in Phenylketonuria
  14. Altmetric Badge
    Chapter 570 Japanese Male Siblings with 2-Methyl-3-Hydroxybutyryl-CoA Dehydrogenase Deficiency (HSD10 Disease) Without Neurological Regression
  15. Altmetric Badge
    Chapter 571 The Effect of S-Adenosylmethionine on Self-Mutilation in a Patient with Lesch–Nyhan Disease
  16. Altmetric Badge
    Chapter 572 Four Years of Diagnostic Challenges with Tetrahydrobiopterin Deficiencies in Iranian Patients
Attention for Chapter 568: A Multiplatform Metabolomics Approach to Characterize Plasma Levels of Phenylalanine and Tyrosine in Phenylketonuria
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

twitter
3 X users

Readers on

mendeley
21 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
A Multiplatform Metabolomics Approach to Characterize Plasma Levels of Phenylalanine and Tyrosine in Phenylketonuria
Chapter number 568
Book title
JIMD Reports, Volume 32
Published in
JIMD Reports, June 2016
DOI 10.1007/8904_2016_568
Pubmed ID
Book ISBNs
978-3-66-254384-9, 978-3-66-254385-6
Authors

Blasco, H, Veyrat-Durebex, C, Bertrand, M, Patin, F, Labarthe, F, Henique, H, Emond, P, Andres, C R, Antar, C, Landon, C, Nadal-Desbarats, L, Maillot, F, H. Blasco, C. Veyrat-Durebex, M. Bertrand, F. Patin, F. Labarthe, H. Henique, P. Emond, C. R. Andres, C. Antar, C. Landon, L. Nadal-Desbarats, F. Maillot

Editors

Eva Morava, Matthias Baumgartner, Marc Patterson, Shamima Rahman, Johannes Zschocke, Verena Peters

Abstract

Different pathophysiological mechanisms have been described in phenylketonuria (PKU) but the indirect metabolic consequences of metabolic disorders caused by elevated Phe or low Tyr concentrations remain partially unknown. We used a multiplatform metabolomics approach to evaluate the metabolic signature associated with Phe and Tyr. We prospectively included 10 PKU adult patients and matched controls. We analysed the metabolome profile using GC-MS (urine), amino-acid analyzer (urine and plasma) and nuclear magnetic resonance spectroscopy (urine). We performed a multivariate analysis from the metabolome (after exclusion of Phe, Tyr and directly derived metabolites) to explain plasma Phe and Tyr concentrations, and the clinical status. Finally, we performed a univariate analysis of the most discriminant metabolites and we identified the associated metabolic pathways. We obtained a metabolic pattern from 118 metabolites and we built excellent multivariate models to explain Phe, Tyr concentrations and PKU diagnosis. Common metabolites of these models were identified: Gln, Arg, succinate and alpha aminobutyric acid. Univariate analysis showed an inverse correlation between Arg, alpha aminobutyric acid and Phe and a positive correlation between Arg, succinate, Gln and Tyr (p < 0.0003). Thus, we highlighted the following pathways: Arg and Pro, Ala, Asp and Glu metabolism. We obtain a specific metabolic signature related to Tyr and Phe concentrations. We confirmed the involvement of different pathophysiological mechanisms previously described in PKU such as protein synthesis, energetic metabolism and oxidative stress. The metabolomics approach is relevant to explore PKU pathogenesis.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 29%
Other 2 10%
Student > Bachelor 2 10%
Student > Doctoral Student 1 5%
Student > Master 1 5%
Other 2 10%
Unknown 7 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 24%
Chemistry 3 14%
Medicine and Dentistry 2 10%
Agricultural and Biological Sciences 1 5%
Environmental Science 1 5%
Other 2 10%
Unknown 7 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 March 2017.
All research outputs
#16,717,986
of 25,375,376 outputs
Outputs from JIMD Reports
#367
of 605 outputs
Outputs of similar age
#222,919
of 361,352 outputs
Outputs of similar age from JIMD Reports
#4
of 13 outputs
Altmetric has tracked 25,375,376 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 605 research outputs from this source. They receive a mean Attention Score of 3.0. This one is in the 32nd percentile – i.e., 32% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 361,352 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.