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. 2021 Sep 4;144(8):2443-2456.
doi: 10.1093/brain/awab123.

Aromatic l-amino acid decarboxylase deficiency: a patient-derived neuronal model for precision therapies

Giada Rossignoli  1   2 , Karolin Krämer  1 , Eleonora Lugarà  3 , Haya Alrashidi  4 , Simon Pope  5 , Carmen De La Fuente Barrigon  4 , Katy Barwick  1 , Giovanni Bisello  2 , Joanne Ng  1   6 , John Counsell  1 , Gabriele Lignani  3 , Simon J R Heales  5   7 , Mariarita Bertoldi  2 , Serena Barral  1 , Manju A Kurian  1   8
Affiliations

Aromatic l-amino acid decarboxylase deficiency: a patient-derived neuronal model for precision therapies

Giada Rossignoli et al. Brain. .

Abstract

Aromatic l-amino acid decarboxylase (AADC) deficiency is a complex inherited neurological disorder of monoamine synthesis which results in dopamine and serotonin deficiency. The majority of affected individuals have variable, though often severe cognitive and motor delay, with a complex movement disorder and high risk of premature mortality. For most, standard pharmacological treatment provides only limited clinical benefit. Promising gene therapy approaches are emerging, though may not be either suitable or easily accessible for all patients. To characterize the underlying disease pathophysiology and guide precision therapies, we generated a patient-derived midbrain dopaminergic neuronal model of AADC deficiency from induced pluripotent stem cells. The neuronal model recapitulates key disease features, including absent AADC enzyme activity and dysregulated dopamine metabolism. We observed developmental defects affecting synaptic maturation and neuronal electrical properties, which were improved by lentiviral gene therapy. Bioinformatic and biochemical analyses on recombinant AADC predicted that the activity of one variant could be improved by l-3,4-dihydroxyphenylalanine (l-DOPA) administration; this hypothesis was corroborated in the patient-derived neuronal model, where l-DOPA treatment leads to amelioration of dopamine metabolites. Our study has shown that patient-derived disease modelling provides further insight into the neurodevelopmental sequelae of AADC deficiency, as well as a robust platform to investigate and develop personalized therapeutic approaches.

Keywords: aromatic l-amino acid decarboxylase deficiency; dopaminergic neurons; induced pluripotent stem cells; neurodevelopment; personalized medicine.

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Figures

Figure 1
Figure 1
Patient-derived neurons show loss of AADC enzymatic activity and dysregulated dopamine synthesis. (A) AADC activity assay relative to total protein (n = 19, 9, and 6 for the control subject, Patient 1 and Patient 2, respectively). (B) HPLC detection of extracellular dopamine, HVA, DOPAC and 3-OMD in control, Patient 1 and Patient 2-derived neuronal cultures. Values are relative to total protein (n = 6, 3, 3; n = 3, 3, 3; n = 5, 3, 3; n = 4, 3, 3, respectively). (C) Immunoblot analysis for AADC protein in control, Patient 1 and Patient 2-derived neurons at Day 65 of differentiation. Quantification relative to loading control (GAPDH) (n = 6, 5, 7, respectively). (D) Representative images for AADC and TH immunofluorescence in derived neurons. Scale bar = 100 µm. Data are presented as mean ± SEM. *P < 0.05; **P < 0.01; ***P < 0.001, one-way ANOVA followed by Tukey’s multiple comparisons test.
Figure 2
Figure 2
Patient-derived neurons show defects in developmental maturation. (A) Representative immunofluorescence images for NeuN and TH in control and patient-derived neurons. Arrows indicate double positive cells. Scale bar = 100 µm. Insets show higher magnification of NeuN-positive dopaminergic neurons. (B) Quantification of NeuN-positive, TH-positive and NeuN-negative, and TH/NeuN double-positive cells in derived neuronal cultures (n = 3 for all). (C) Representative immunoblot for synaptophysin and loading control (β-ACT) and quantification of relative synaptophysin abundance in total neuronal cell lysates (n = 5 for all). (D) Representative immunofluorescence for synaptophysin and TH in derived neurons. Scale bar = 100 µm. Insets show higher magnification of synaptophysin-positive dopaminergic neurons. Data are presented as mean ± SEM. *P < 0.05; **P < 0.01; ***P < 0.001, one-way ANOVA followed by Tukey’s multiple comparisons test.
Figure 3
Figure 3
Bulk RNA sequencing analysis shows an abnormal gene expression profile in AADC deficiency patients. (A) Heat map showing hierarchical clustering of protein-coding DEGs in AADC deficiency patients compared to control (n = 3). (B) GO terms enrichment for biological process of underexpressed (blue) protein-coding and overexpressed (red) protein-coding DEGs. The top five categories are shown. (C and D) ClueGO analysis of GO terms enrichment of (C) under- and (D) over-expressed protein-coding DEGs, showing network graph and pie chart for cellular component (CC), and pie chart for molecular function (MF). Network graph nodes represent GO terms (the most significant are named) and edges indicate shared genes between GO terms. Functional groups of GO terms are indicated by the same colour. Pie charts show the percentages of each functional group representation, named with the most significant term. GO functional groups exhibiting higher statistically significant differences using Benjamini-Hochberg P-value correction (FDR < 0.05) are shown.
Figure 4
Figure 4
Bulk RNA-Seq analysis reveals differences in gene expression profiles between Patient 1 and 2-derived neurons. (A) Heat map showing hierarchical clustering of protein-coding DEGs in Patient 2, compared to Patient 1 (n = 3). (B) GO terms enrichment for biological process of underexpressed (blue) protein-coding and overexpressed (red) protein-coding DEGs. The top five categories are shown. (C and D) ClueGO analysis of GO terms enrichment of (C) under- and (D) over-expressed protein-coding DEGs, showing network graph and pie chart for cellular component (CC), and pie chart for molecular function (MF). Network graph nodes represent GO terms (the most significant are named) and edges indicate shared genes between GO terms. Functional groups of GO terms are indicated by the same colour. Pie charts show the percentages of each functional group representation, named with the most significant term. GO functional groups exhibiting higher statistically significant differences using Benjamini-Hochberg P-value correction (FDR < 0.05) are shown.
Figure 5
Figure 5
Patient-derived neurons show altered neuronal electrophysiological properties and defects in primary neurite branching. (A) Representative traces of action potentials (APs) elicited by injecting a 40 pA current in patients and control lines. (B) Input/output plot showing number of action potentials triggered by incremental current steps. (C) Active (current threshold and max current sustained) and passive (capacitance) properties of neurons in control, Patient 1 and Patient 2 neurons (n = 39, 34, 26, n = 35, 34, 25, and n = 41, 38, 32, respectively, from four biological replicates). (D) Percentage of neurons that sustain >100pA current injection. (E) Representative images for dopaminergic neurons branching (scale bar = 10 µm) and quantification of average primary neurite branching in control, Patient 1 and Patient 2 mDA neurons (n = 11, 7, 11, respectively). (F) Representative traces showing spontaneous excitatory postsynaptic currents (sEPSCs) at −70 mV and quantification of neurons with sEPSC, sEPSC amplitude and inter-time intervals in control, Patient 1 and Patient 2 neurons (n = 5 for all, n = 27, 28, 28, and n = 24, 28, 18, respectively, from four biological replicates). Data are presented as mean ± SEM. *P < 0.05; **P < 0.01; ***P < 0.001, one-way ANOVA followed by Tukey’s multiple comparisons test and chi-square test in D.
Figure 6
Figure 6
Gene therapy significantly improves maturation defects in patient-derived neurons. (A) Representative immunofluorescence for NeuN and TH of patient-derived neurons transduced with a lentiviral construct expressing only GFP (LV GFP) or human DDC and GFP (LV DDC-GFP). Scale bar = 100 µm. (B) Quantification of NeuN-positive, TH-positive and NeuN-negative, and TH/NeuN double-positive cells in patient-derived neuronal cultures transduced with LV GFP and LV DDC-GFP (n = 3 each). (C) Representative immunoblot for synaptophysin and loading control (GAPDH), and quantification of relative synaptophysin abundance from total cell lysates extracted from LV GFP and LV DDC-GFP transduced neurons. Results are normalized to the corresponding LV GFP for each patient (n = 4, 4, 5, 5, respectively). (D) Representative immunofluorescence for synaptophysin and TH in patient-derived neurons transduced with LV GFP or LV DDC-GFP. Scale bar =100 µm. (E) Representative images for dopaminergic neurons branching (scale bar = 10 µm) and quantification of average primary neurite branches in patient-derived neurons transduced with LV GFP or LV DDC-GFP (n = 15, 18, 13, 18, respectively). Data are presented as mean ± SEM. *P < 0.05; **P < 0.01; ***P < 0.001, two-tailed Student’s t-test.
Figure 7
Figure 7
l-DOPA treatment increases dopamine metabolite production in Patient 2-derived neuronal cultures, with no evidence of cellular toxicity. (A) Localization of Cys100 in AADC protein structure. The structure corresponds to Sus scrofa holoenzyme (PDB code: 1JS3), solved in complex with PLP and carbidopa, and rendered using PyMol™ software. AADC is shown as a schematic, with the two monomers composing the native rearrangement of the enzyme (wheat and marine blue, respectively). PLP and carbidopa are represented as green and yellow sticks, respectively. The side chain of Cys100 is represented as a pink stick. Side chains of Ile101 and Phe103 are represented as orange sticks. (B) HPLC detection of extracellular HVA after 80 µM l-DOPA treatment of neuronal cultures for 24 h. Values are relative to total protein (n = 3, 3, 5, 5, 4, 4, respectively). (C) Dead-cell protease release assay after treatment. Results are normalized to the corresponding non-treated condition (n = 3 for all). Data are presented as mean ± SEM. *P < 0.05; **P < 0.01; ***P < 0.001, one-way ANOVA followed by Tukey’s multiple comparisons test.
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