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Massive parallel sequencing as a new diagnostic approach for phenylketonuria and tetrahydrobiopterin-deficiency in Thailand

Overview of attention for article published in BMC Medical Genetics, September 2017
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Title
Massive parallel sequencing as a new diagnostic approach for phenylketonuria and tetrahydrobiopterin-deficiency in Thailand
Published in
BMC Medical Genetics, September 2017
DOI 10.1186/s12881-017-0464-x
Pubmed ID
Authors

Pongsathorn Chaiyasap, Chupong Ittiwut, Chalurmpon Srichomthong, Apiruk Sangsin, Kanya Suphapeetiporn, Vorasuk Shotelersuk

Abstract

Hyperphenylalaninemia (HPA) can be classified into phenylketonuria (PKU) which is caused by mutations in the phenylalanine hydroxylase (PAH) gene, and BH4 deficiency caused by alterations in genes involved in tetrahydrobiopterin (BH4) biosynthesis pathway. Dietary restriction of phenylalanine is considered to be the main treatment of PKU to prevent irreversible intellectual disability. However, the same dietary intervention in BH4 deficiency patients is not as effective, as BH4 is also a cofactor in many neurotransmitter syntheses. We utilized next generation sequencing (NGS) technique to investigate four unrelated Thai patients with hyperphenylalaninemia. We successfully identified all eight mutant alleles in PKU or BH4-deficiency associated genes including three novel mutations, one in PAH and two in PTS, thus giving a definite diagnosis to these patients. Appropriate management can then be provided. This study identified three novel mutations in either the PAH or PTS gene and supported the use of NGS as an alternative molecular genetic approach for definite diagnosis of hyperphenylalaninemia, thus leading to proper management of these patients in Thailand.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 18%
Professor 3 14%
Student > Bachelor 3 14%
Other 2 9%
Researcher 2 9%
Other 3 14%
Unknown 5 23%
Readers by discipline Count As %
Medicine and Dentistry 5 23%
Agricultural and Biological Sciences 4 18%
Biochemistry, Genetics and Molecular Biology 3 14%
Nursing and Health Professions 2 9%
Psychology 1 5%
Other 0 0%
Unknown 7 32%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 17 September 2017.
All research outputs
#14,584,051
of 16,534,657 outputs
Outputs from BMC Medical Genetics
#769
of 999 outputs
Outputs of similar age
#236,986
of 277,496 outputs
Outputs of similar age from BMC Medical Genetics
#1
of 1 outputs
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So far Altmetric has tracked 999 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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