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18.09.2017 | Original Article | Ausgabe 1/2018

Journal of Inherited Metabolic Disease 1/2018

Diagnostic approach to neurotransmitter monoamine disorders: experience from clinical, biochemical, and genetic profiles

Journal of Inherited Metabolic Disease > Ausgabe 1/2018
Alice Kuster, Jean-Baptiste Arnoux, Magalie Barth, Delphine Lamireau, Nada Houcinat, Cyril Goizet, Bérénice Doray, Stéphanie Gobin, Manuel Schiff, Aline Cano, Daniel Amsallem, Christine Barnerias, Boris Chaumette, Marion Plaze, Abdelhamid Slama, Christine Ioos, Isabelle Desguerre, Anne-Sophie Lebre, Pascale de Lonlay, Laurence Christa, Individual contributors who contributed to this work
Wichtige Hinweise
Responsible Editor: Georg Hoffmann

Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1007/​s10545-017-0079-6) contains supplementary material, which is available to authorized users.
Alice Kuster and Jean-Baptiste Arnoux: contributed equally to the manuscript.


Background and aim

To improve the diagnostic work-up of patients with diverse neurological diseases, we have elaborated specific clinical and CSF neurotransmitter patterns.


Neurotransmitter determinations in CSF from 1200 patients revealed abnormal values in 228 (19%) cases. In 54/228 (24%) patients, a final diagnosis was identified.


We have reported primary (30/54, 56%) and secondary (24/54, 44%) monoamine neurotransmitter disorders. For primary deficiencies, the most frequently mutated gene was DDC (n = 9), and the others included PAH with neuropsychiatric features (n = 4), PTS (n = 5), QDPR (n = 3), SR (n = 1), and TH (n = 1). We have also identified mutations in SLC6A3, FOXG1 (n = 1 of each), MTHFR (n = 3), FOLR1, and MTHFD (n = 1 of each), for dopamine transporter, neuronal development, and folate metabolism disorders, respectively. For secondary deficiencies, we have identified POLG (n = 3), ACSF3 (n = 1), NFU1, and SDHD (n = 1 of each), playing a role in mitochondrial function. Other mutated genes included: ADAR, RNASEH2B, RNASET2, SLC7A2-IT1 A/B lncRNA, and EXOSC3 involved in nuclear and cytoplasmic metabolism; RanBP2 and CASK implicated in post-traductional and scaffolding modifications; SLC6A19 regulating amino acid transport; MTM1, KCNQ2 (n = 2), and ATP1A3 playing a role in nerve cell electrophysiological state. Chromosome abnormalities, del(8)(p23)/dup(12) (p23) (n = 1), del(6)(q21) (n = 1), dup(17)(p13.3) (n = 1), and non-genetic etiologies (n = 3) were also identified.


We have classified the final 54 diagnoses in 11 distinctive biochemical profiles and described them through 20 clinical features. To identify the specific molecular cause of abnormal NT profiles, (targeted) genomics might be used, to improve diagnosis and allow early treatment of complex and rare neurological genetic diseases.

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Supplementary Fig. 3 Biochemical algorithm for patients with hyperphenylalaninemia. Hyperphenylalaninemia characterizes the following primary NTDs: PAH with neuropsychiatric features, BH4 synthesis or recycling deficiencies. *HVA, HIAA, BIO, NEO, and MTHF were normal, abnormal, or unavailable CSF parameters were not mandatory for diagnostic purpose, because measurement of pterins in urines and DHPR enzyme activity in red blood cells was sufficient to diagnose PTPS and QDPR deficiencies. However, CSF NT analysis was performed for the follow up of NT levels under treatment (PPTX 59.8 kb)
Supplementary Table 1 Genetics, biochemical analysis, and medication of the 54 patients with a diagnosis of primary or secondary NTDs. Biochemical values for HVA, HIAA BIO, NEO, and MTHF in CSF were expressed in (nM) and pterins in urines (ur) in (μmol/mmol creatinine). Reference values were the adjacent values to the interquartile space (P25–P75) (Ormazabal et al 2005). DHPR enzyme activity in red blood cells was expressed as nmol/min/mg hemoglobin; nd: not determined; na: not available; RV: reference value. Case reports published by: 1 Mazzuca, 2015, 2 (Barth et al 2012), 3 (Arnoux et al 2013), 4 (Le Guen et al 2011), 5 (Burda et al 2015), 6 (Nizon et al 2014), 7(Cartault et al 2012), 8 (Alexandre et al 2016) (XLSX 26 kb)
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