Effect of disease-associated SLC9A9 mutations on protein–protein interaction networks: implications for molecular mechanisms for ADHD and autism

  • Yanli Zhang-James
  • Marc Vaudel
  • Olav Mjaavatten
  • Frode S. Berven
  • Jan Haavik
  • Stephen V. FaraoneEmail author
Original Article


Na+/H+ Exchanger 9 (NHE9) is an endosomal membrane protein encoded by the Solute Carrier 9A, member 9 gene (SLC9A9). SLC9A9 has been implicated in attention deficit hyperactivity disorder (ADHD), autism spectrum disorders (ASDs), epilepsy, multiple sclerosis and cancers. To better understand the function of NHE9 and the effects of disease-associated variants on protein–protein interactions, we conducted a quantitative analysis of the NHE9 interactome using co-immunoprecipitation and isobaric labeling-based quantitative mass spectrometry. We identified 100 proteins that interact with NHE9. These proteins were enriched in known functional pathways for NHE9: the endocytosis, protein ubiquitination and phagosome pathways, as well as some novel pathways including oxidative stress, mitochondrial dysfunction, mTOR signaling, cell death and RNA processing pathways. An ADHD-associated mutation (A409P) significantly altered NHE9’s interactions with a subset of proteins involved in caveolae-mediated endocytosis and MAP2K2-mediated downstream signaling. An ASD nonsense mutation in SLC9A9, R423X, produced no-detectable amount of NHE9, suggesting the overall loss of NHE9 functional networks. In addition, seven of the NHE9 interactors are products of known autism candidate genes (Simons Foundation Autism Research Initiative, SFARI Gene) and 90% of the NHE9 interactome overlap with SFARI protein interaction network PIN (p < 0.0001), supporting the role of NHE9 interactome in ASDs molecular mechanisms. Our results provide a detailed understanding of the functions of protein NHE9 and its disrupted interactions, possibly underlying ADHD and ASDs. Furthermore, our methodological framework proved useful for functional characterization of disease-associated genetic variants and suggestion of druggable targets.


ASDs ADHD SLC9A9/NHE9 Protein–protein interaction Network Mass spectrometry Endocytosis Drug targets 



We thank Dr. Hanno Steen for helpful advice on proteomics and comments on the manuscript. This work was supported by Stiftelsen Kristian Gerhard Jebsen (SKGJ-MED-002 to Haavik), NIH Grant 5R01MH066877 (Stephen V Faraone, PI) and a NARSAD Young Investigator Award to Yanli Zhang-James. Dr. Faraone is supported by the K. G. Jebsen Centre for Research on Neuropsychiatric Disorders, University of Bergen, Bergen, Norway, the European Union’s Seventh Framework Programme for research, technological development and demonstration under Grant Agreement No 602805, the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 667302 and NIMH Grant 5R01MH101519.

Compliance with ethical standards

Conflict of interest

Yanli Zhang-James, Frode S. Berven, Olav Mjaavatten, Marc Vaudel and Hanno Steen declare no conflict of interest. During the past three years, Jan Haavik has received speaker fees from Lilly, Novartis, Shire, Medice, HB Pharma and Janssen-Cilag. In the past year, Dr. Faraone received income, travel expenses and/or research support from and/or has been on an Advisory Board for Pfizer, Ironshore, Shire, Akili Interactive Labs, CogCubed, Alcobra, VAYA Pharma, Neurovance, Impax, NeuroLifeSciences and research support from the National Institutes of Health (NIH). With his institution, he has US patent US20130217707 A1 for the use of sodium-hydrogen exchange inhibitors in the treatment of ADHD. In previous years, he received consulting fees or was on Advisory Boards or participated in continuing medical education programs sponsored by: Shire, Alcobra, Otsuka, McNeil, Janssen, Novartis, Pfizer and Eli Lilly. Dr. Faraone receives royalties from books published by Guilford Press: Straight Talk about Your Child’s Mental Health, Oxford University Press: Schizophrenia: The Facts and Elsevier, ADHD: Non-Pharmacologic Treatments.

Supplementary material

12402_2018_281_MOESM1_ESM.pdf (244 kb)
Supplementary Figure 1 A TMT experimental design showing Co-IP samples and TMT labeling. A total of four MS samples were conducted in our study by combining equal amount of Co-IP samples that were labeled with randomly assigned TMT labels. For MS sample labeled as “WT,” a total of 6 samples were combined including three replicates of WT co-IP samples and their corresponding negative control samples (CT). The corresponding TMT ratios that were used in analysis and shown in Figure B were labeled following the order of “MS sample name,” “numerator sample name” and “denominator sample names.” Therefore, three ratios were obtained from the 6-plex MS sample “WT”: “wt_wt1ct1,” “wt_wt2ct2” and “wt_wt3ct3.” Three other MS samples (named mut1, mut2, mut3) each was generated by combining a set of three parallel-processed Co-IP samples, the WT, AP and their corresponding CT samples. The ratios of WT versus CT and AP versus CT were obtained from each set. Therefore, a total of 6 TMT ratios were obtained from these three MS samples, and they were labeled in Figure B following the same naming convention. BTMT raw ratios (Left) were log-transformed (Middle) and normalized (Right). (PDF 244 kb)
12402_2018_281_MOESM2_ESM.pdf (117 kb)
Supplementary Figure 2 Distribution of percentage of protein coverage, the numbers of PSMs and peptides identified for each protein were plotted against the normalized mean WT versus CT ratios (Top row) and the Z test negative log p values (Bottom row) to show that these factors do not influence the Z test-based PPI filtering. (PDF 117 kb)
12402_2018_281_MOESM3_ESM.pdf (1.1 mb)
Supplementary Figure 3 Known interactions form a single connected network for WT (A) and AP (B) proteins. The degree of each node is proportional to size. Significantly changed proteins (Z test p < 0.05) by A409P mutation are colored, with green indicating decreased interactions and red indicating increased interactions. The color intensity is proportional to the averaged AP versus WT ratios (log2 ratios), i.e., the log2 fold change of binding to NHE9 due to the mutation. Proteins that did not show significant changes are white. Notice the loss of MAP2K2 and a big hub node, VIM in the AP network, as well as a number of increased interactions such as FLOT1. (PDF 1177 kb)
12402_2018_281_MOESM4_ESM.pdf (2.1 mb)
Supplementary Figure 4 Transferrin (TF) and cholera toxin beta subunit (CTB) endocytosis in N2a cells. A Representative images of TF and CTB staining (green) at 30 min are shown. TF uniformly labels almost all cells; however, CTB labeling in N2a cells is more heterogeneous. DAPI nuclei stain is blue. B, C show representative 10 × images of TF (B) and CTB (C) labeling for different groups at different time points. (PDF 2127 kb)
12402_2018_281_MOESM5_ESM.docx (22 kb)
Supplementary file 1 (DOCX 21 kb)
12402_2018_281_MOESM6_ESM.xlsx (291 kb)
Supplementary file 2 (XLSX 290 kb)
12402_2018_281_MOESM7_ESM.xls (43 kb)
Supplementary file 3 (XLS 43 kb)


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Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Departments of PsychiatrySUNY Upstate Medical UniversitySyracuseUSA
  2. 2.Department of Clinical ScienceUniversity of BergenBergenNorway
  3. 3.Department of BiomedicineUniversity of BergenBergenNorway
  4. 4.K.G. Jebsen Centre for Research on Neuropsychiatric DisordersUniversity of BergenBergenNorway
  5. 5.Division of PsychiatryHaukeland University HospitalBergenNorway
  6. 6.Neuroscience and PhysiologySUNY Upstate Medical UniversitySyracuseUSA

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