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DOI 10.1002/jcla.21745

Медицинская библиотека · Journal of clinical laboratory analysis · 2014

Spectrum analysis of common inherited metabolic diseases in Chinese patients screened and diagnosed by tandem mass spectrometry.

Han Lianshu, Han Feng, Ye Jun, Qiu Wenjuan, Zhang Huiwen, Gao Xiaolan, Wang Yu, Ji Wenjun, Gu Xuefan

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Аннотация

BACKGROUND

Information concerning inherited metabolic diseases in China is scarce. We investigated the prevalence and age distributions of amino acid, organic acid, and fatty acid oxidation disorders in Chinese patients.

METHODS

Blood levels of amino acids and acylcarnitines (tandem mass spectrometry) were measured in 18,303 patients with suspected inherited metabolic diseases. Diagnosis was based on clinical features, blood levels of amino acids or acylcarnitines, urinary organic acid levels (gas chromatography-mass spectrometry), and (in some) gene mutation tests.

RESULTS

Inherited metabolic diseases were confirmed in 1,135 patients (739 males, 396 females). Median age was 12 months (1 day to 59 years). There were 28 diseases: 12 amino acid disorders (580 patients, 51.1%), with hyperphenylalaninemia (HPA) being the most common; nine organic acidemias (408 patients, 35.9%), with methylmalonic acidemia (MMA) as the most common; and seven fatty acid oxidation defects (147 patients, 13.0%), with multiple acyl-coenzyme A dehydrogenase deficiency (MADD) being the most common. Onset was mainly at 1-6 months for citrin deficiency, 0-6 months for MMA, and in newborns for ornithine transcarbamylase deficiency (OTCD). HPA was common in patients aged 1-3 years, and MADD was common in patients >18 years.

CONCLUSIONS

In China, HPA, citrin deficiency, MMA, and MADD are the most common inherited disorders, particularly in newborns/infants.

Для цитирования: Han Lianshu, Han Feng, Ye Jun, Qiu Wenjuan, Zhang Huiwen, Gao Xiaolan, Wang Yu, Ji Wenjun, Gu Xuefan. Spectrum analysis of common inherited metabolic diseases in Chinese patients screened and diagnosed by tandem mass spectrometry.. Journal of clinical laboratory analysis. 2014. DOI: 10.1002/jcla.21745.

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