Alterations in proliferation of neuronal stem cells in Attention-Deficit/Hyperactivity Disorder and Wnt modulation by methylphenidate

Alterations in proliferation of neuronal stem cells in Attention-Deficit/Hyperactivity Disorder and Wnt modulation by methylphenidate | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Alterations in proliferation of neuronal stem cells in Attention-Deficit/Hyperactivity Disorder and Wnt modulation by methylphenidate Edna Grünblatt, Cristine Marie Yde Ohki, Natalie Monet Walter, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3956813/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Jul, 2025 Read the published version in Journal of Neural Transmission → Version 1 posted You are reading this latest preprint version Abstract As the most common neurodevelopmental and mental disorders around the world, attention-deficit/hyperactivity disorder (ADHD) affects mostly children and adolescents. Both genetic (polygenicity) and environmental variables interplay in the etiology of this disorder. The Wnt signaling pathway, which regulates proliferation and differentiation during neurodevelopment, has been implicated in ADHD. Clinically, ADHD individuals may exhibit delays in structural and functional brain development. Available evidence has proposed that methylphenidate (MPH) treatment can potentially improve these delays. However, the molecular and cellular mechanisms underlying ADHD and the therapeutic targets of MPH are still not completely elucidated. In a pilot investigation, the proliferation of neural stem cells (NSCs) derived from induced pluripotent stem cells (iPSCs) was significantly lowered in ADHD male patients. Yet, we did not observe any variations in growth rates during the iPSC stage. To extend the earlier results, we increased the sample size to include females and explored if MPH may improve NSC proliferation in ADHD and clarified the role of the Wnt pathway. To do so, iPSC and NSC proliferation of five ADHD patients and five controls was assessed. The results corroborated our previous findings on decreased proliferation in ADHD NSCs. Conversely, ADHD NSC proliferation slightly increased following MPH treatment at 10 nM, which also showed modulatory effects in the Wnt signaling in this group. Interestingly, no increases in proliferation were seen when DKK1 blocked Wnt signaling before MPH treatment. These findings suggest MPH regulates the canonical Wnt pathway and may partially explain ADHD neurodevelopmental abnormalities and MPH-specific benefits. Biological sciences/Neuroscience Biological sciences/Stem cells Biological sciences/Cell biology Biological sciences/Genetics Biological sciences/Molecular biology ADHD Alzheimer’s disease Anxiety Autism spectrum disorder β-catenin Bipolar disorder GSK3β iPSC LRP6 Major depressive disorder Methylphenidate Neural stem cells Obsessive-compulsive disorder Polygenic risk score proliferation protein expression real time impedance cell analysis reporter assays RTCA Wnt signaling WST-1 xCELLigence Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Methylphenidate (MPH) is a psychostimulant that is commonly employed as a pharmacological treatment strategy in attention-deficit/hyperactivity disorder (ADHD), a multifactorial neurodevelopmental disorder that is often characterized by delays in brain maturation of up to 4 years when compared to controls 1 . Structural delays include decreased cortical thickness 2 , 3 as a result of common reductions in gray and white matter in brain regions highly implicated in ADHD-related cognitive functions, such as attention 4 , 5 and inhibition of motor response 6 , 7 . Some examples of these areas are the basal ganglia 8 , 9 and the prefrontal cortex of ADHD patients 10 . MPH may potentially normalize gray and white matter volumes in individuals with ADHD compared to unmedicated patients 11 . Not limited to structural ameliorations, it may also improve functional maturational delays in the brain networks of ADHD patients 11 . Among other molecular mechanisms, MPH is a psychostimulant that blocks dopamine and norepinephrine transporters (DAT and NET, respectively) 12 – 14 . MPH shows one of the largest effect sizes among medications used in children and adolescent psychiatry 15 , 16 and has been found to be largely beneficial in reducing hyperactivity and impulsivity in patients with ADHD 17 . The primary therapeutic mechanism of action of MPH is said to be DAT inhibition; nevertheless, the precise molecular mechanisms behind MPH remain unclear. For instance, MPH has a paradoxical impact in that it improves attention in ADHD patients, while decreasing hyperactivity and impulsivity, which seems counterintuitive given its psychostimulant properties 18 , 19 . Moreover, an in vivo study has demonstrated that MPH-induced behavioral benefits persisted in DAT-knockout mice 20 , suggesting that MPH may have additional modes of action which are not dependent on DAT inhibition 14 . One of the mechanisms that was previously linked to ADHD is the Wnt signaling pathway 21 , 22 . In a review paper, MacDonald et al. described in a detailed manner that the Wnt cascade is triggered when transmembrane receptors LRP5/6 (LDL receptor-related protein 5/6) and Frizzled (FZD) get activated by extracellular Wnt ligands, such as Wnt3a, Wnt5a, and Wnt7a. Among others, the Dickkopf-related protein 1 (DKK1) acts upstream in this cascade as a well-known Wnt-antagonist since it can internalize LRP5/6 receptors through Kremen-mediated endocytosis 23 or compete with extracellular Wnt ligands for binding to LRP6 24 . More specifically, in the absence of these Wnt-agonists or the presence of antagonists, GSK3 \(\:{\beta\:}\) , one of the key components of the so-called “destruction complex”, phosphorylates \(\:{\beta\:}\) -catenin and leads to its subsequent degradation. On the other hand, when phosphorylated at the Serine-9 position (S9), GSK3 \(\:{\beta\:}\) becomes inactive and is no longer able to phosphorylate \(\:{\beta\:}\) -catenin for further proteasomal degradation. When Wnt ligands are available in the extracellular milieu and activate the LRP5/6 and FZD receptors, the cascade is turned on, which leads to the inhibition of the destruction complex and to the accumulation and posterior translocation of β-catenin into the nucleus, where it will activate the transcription of Wnt target genes with the aid of the TCF/LEF (T cell factor/lymphoid enhancer factor) family of transcription factors 25 . These Wnt target genes might be, in a context-dependent manner, highly associated with essential cellular processes during neurodevelopment, such as proliferation, cell fate specification, and differentiation, that might be differentially modulated in distinct cell types 26 . The use of induced pluripotent stem cells (iPSCs) as models for studies of ADHD and other neuropsychiatric disorders allows the preservation of the genetic background from the somatic cells of origin, and subsequently, the study of patient-specific cellular and molecular phenotypes in functional living neural cells 27 . Our group’s preliminary data have demonstrated that male ADHD neural stem cells (NSCs) grow at a considerably slower rate than controls, whereas no differences between the two groups were found at the early developmental stage of iPSCs 28 . Moreover, we demonstrated in our recently published paper that ADHD NSCs have higher basal Wnt activity than controls in terms of protein expression and functional assessment 29 . One of the goals of the current study was to assess the growth of a greater number of cell lines, including both sexes. Moreover, we investigated whether treatment with varying doses of MPH can effectively reverse any differences in ADHD NSC proliferation through a Wnt-dependent mechanism. Material and Methods Recruitment of participants ADHD patients (aged 6 − 18 years old) who clinically respond to MPH treatment, with no comorbidities and matching healthy controls were recruited by the Department of Child and Adolescent Psychiatry and Psychotherapy (KJPP) of the University of Zurich (UZH), as described in Yde Ohki et al. 28 . Previous publications 30 – 32 and a recently published paper 29 provide further information regarding the inclusion and exclusion criteria. Supplementary Table 1 provides a list of the individual subjects included in the current study together with their demographic and clinical characteristics. After recruitment, salivary DNA samples from patients and controls were submitted to genotyping, as reported in previous publications 30 – 32 . Individual Polygenic Risk Scores (PRS) were calculated as a quantitative indicator of genetic predisposition to ADHD 33 and other neuropsychiatric disorders (Alzheimer’s disease (AD) 34 , Autism Spectrum Disorder (ASD) 35 , bipolar disorder (BD) 36 , major depressive disorder (MDD) 37 , obsessive-compulsive disorder (OCD) 38 ), using a clumping / thresholding method for p = 0.05 in Plink, as previously described 29 . PRS for anxiety (ANX) was also calculated based on the summary statistics provided by the corresponding authors (Prof. Dr. Thalia C. Eley and Gerome Breen) from Purves et al., 2020 39 . Pathway-PRS for ADHD 40 was calculated specifically for the Wnt pathway (Molecular Signatures Database version v2023.2.Hs; source code: hsa04310) using PRSet. PRS for baldness 29 was calculated and analyzed as negative PRS control 29 . As part of the recruitment process, ADHD patients and controls were evaluated according to Child Behavior Checklist (CBCL) from parents 41 and Conners-3-Rating Scales 42 from patients, teachers and parents. Controls were required to have lower Conners’ T-values (< 60) in hyperactivity/impulsivity and inattention whereas ADHD patients should score at least 65 in every symptomatology scale in at least one of the Conners’ questionnaires 30 – 32 . This project was approved by the Cantonal Ethics Committee (BASEC-Nr.-2016-00101 & BASEC-Nr.-201700825) and followed the latest version of the Declaration of Helsinki, as previously reported 28 , 30 – 32 , 43 . The consent form for the study was signed by all participants and/or their parents. Generation and culture of iPSCs and NSCs IPSCs from plucked hair-derived keratinocytes or peripheral mononuclear blood cells (PBMCs) from ADHD patients and healthy controls were generated and submitted to quality control (QC) as reported in previous publications 30 – 32 . These cell lines underwent extensive QC that included verification of genomic integrity using Single Nucleotide Polymorphism (SNP) arrays, mycoplasma testing, Sendai virus detection, Copy Number Variation (CNV) analysis, embryoid body formation, and assessment of gene and protein expression of pluripotency markers 30 – 32 . The culture of NSCs and their QC in terms of gene and protein expression analysis through RT-PCR and immunocytochemistry, respectively, were performed as described in our previously published papers 28 , 29 . The NSCs utilized in this paper were positive for classical NSC markers ( i.e. , SOX2, TUJ1, NESTIN and PAX6) 28 , 29 . Details about NSC culture and treatment can be found in the next sections. xCELLigence and WST-1 assays for iPSC and NSC proliferation at basal levels Human iPSCs and NSCs that have successfully undergone QC were submitted to the real-time impedance cell analysis, xCELLigence, and the colorimetric assay WST-1, as described in Yde Ohki et al. 28 . Briefly, on day 0, 25000 iPSCs in Essential 8 Flex (Gibco ™ ) were seeded per well in an E96 Plate (OLS ® BIO) or in regular 96-well plates (Sarstedt) for xCELLigence and WST-1, respectively. These plates were respectively coated with Vitronectin (Gibco ™ ) at 15 µg/mL and 5 µg/mL. Similarly, 15000 NSCs were seeded onto E96-well plates (Agilent) or in regular 96-well plates (Sarstedt) coated with Matrigel (Corning® Matrigel® hESC-Qualified Matrix) diluted 1:100 in DMEM/F12 (Gibco ™ ) in Neural Expansion Media (NEM; PSC Neural Induction Medium, Gibco™) for xCELLigence and WST-1 assays, respectively. We determined the growth rates from xCELLigence by fitting cell index (CI) curves into Malthusian growth models using R Statistical Software v. 4.1.2. 28 . In xCELLigence, the first measurement occurs in the first experimental minute to detect the impedance in the wells containing only media. For baseline experiments, xCELLigence CI was measured for 2 hours every 10 minutes, followed by measurements every hour throughout a 24-sweep cycle. Next, the xCELLigence Real-Time Cell Analysis (RTCA) station recorded measurements every hour throughout two 48-hour sweep cycles. This schedule allowed us to refresh the media during sweep intervals. The experiment finished after 120 h. The slope of the impedance curves from 24 h post-seeding until their maximum CI were determined. For WST-1, the same number of cells were seeded onto wells of 96 well plates, and WST-1 tetrazolium salt (Sigma) was added to the wells at the timepoints of 24 h, 42 h, 48 h, 66 h, 72 h, 90 h, 96 h, and 114 h post-seeding. Absorbance measurements at 440 nm took place 4 h later using the Mithras2 LB 943 Multimode Reader (Berthold Technologies) and adopting a reference wavelength of 630 nm, as previously reported 28 . Absorbance curves were log2-transformed for linearization, and growth rates were calculated as the slopes after fitting the curve from 24 h to the maximum absorbance in linear regression models 28 . Regarding data analysis, data from xCELLigence wells per replicate were cleaned using the Interquartile Range (IQR) method, whereas WST-1 wells per timepoint per replicate were cleaned using a z-score method, consistent with our previous publication 28 . Replicates were averaged per cell line and represented as dots in each graph. Each investigated group included four males and one female (including 2 iPSC clones per person) (see Supplementary Table 1). The average of two technical replicate trials for each cell line was used for all analyses. For iPSCs, WST-1 assays involved conducting a minimum of two technical replicates per cell line and then determining the average. MPH treatment of NSCs for subsequent evaluation of proliferation For both xCELLigence and WST-1, the cells were chronically treated with MPH hydrochloride (Lipomed AG, MPH-1043-HC) every 24 h at 10 nM and 100 nM throughout 5 experimental days. WST-1 experiments and analysis in MPH-treated NSCs were performed as described above. Slopes from the xCELLigence and WST-1 growth curves were calculated as reported in the previous section and in Yde Ohki et al. 28 . As in baseline experiments, CI values were assessed for 2 hours every 10 minutes followed by 24-hour measurements every hour. Next, four sweep cycles of 24 hours each were performed to ensure that treatments were performed every day. In the present study, the slope of impedance curves in xCELLigence from the moment that MPH (or vehicle) was added for the first time to the cultures (24 h and 24.5 h post-seeding for experiments with MPH and DKK1, respectively) until its maximum CI were calculated as growth rates. On days 1 and 3, the NSCs were completely refreshed with NEM and MPH. On days 2 and 4 after seeding, we only added MPH or vehicle (water) to the wells. Figure 2 A depicts the experimental design of these assays. DKK1 treatment of NSCs with and without MPH for xCELLigence assays DKK1 treatment before MPH was performed using the xCELLigence assay to investigate the hypothesis that the Wnt signaling system modulates MPH proliferation (Fig. 3 A). To do so, a stock solution of DKK1 was prepared at 10000 ng/mL in water containing BSA 1%, which was freshly diluted in NEM to prepare an intermediate solution at 600 ng/mL. On days 1 and 3 post-seeding, the media from the wells were completely replaced with fresh NEM plus DKK1, whereas DKK1 was only added to the wells on days 2 and 4 (final concentration of 60 ng/mL). This concentration was able to fully block the Wnt activity when these NSCs were submitted to functional Wnt reporter assays 29 . The plate was returned to the xCELLigence station, and the measurements were restarted for a duration of 30 minutes, in which CIs were measured every 5 minutes. Subsequently, the wells were treated with MPH, resulting in a final concentration of 10 nM. Water was considered as vehicle for untreated wells. Growth rates were determined using the same methodology as the aforementioned experiments, but solely with MPH. Wnt reporter assay in NSCs after acute MPH treatment Wnt reporter assays were conducted in both ADHD and control NSCs, following the transfection-based methodology outlined in Yde Ohki et al., 2023 43 . In this protocol, NSCs were co-transfected with the plasmid of interest containing a Wnt luciferase reporter gene under the control of a TCF/LEF responsive element (pGL4.49[luc2P/TCF-LEF RE/Hygro] Vector, from Promega) and a normalization vector containing NanoLuc luciferase gene under the control of a TK (thymidine-kinase) promoter (pNL1.1.TK[Nluc/TK] Vector, Promega). After previous overnight treatment with the Wnt-agonist Wnt3a, EC50 values were determined for each cell line in two technical replicates 43 . According to the previous results 29 , NSCs were treated individually with the respective Wnt3a’s EC25 in triplicates. Subsequently, they were returned into a cell culture incubator set at a temperature of 37°C and 5% CO 2 . After 10 minutes, MPH 10 nM was added to the wells. The condition named as “Vehicle” represents treatment with individual EC25 concentrations of Wnt3a, only. In this context, water was used as vehicle for MPH treatment. Next, the cells were incubated overnight at 37°C and 5% CO 2 . On the following day, luminescence assays and subsequent data analysis from Relative Luminescence Units (RLU) were performed as previously reported 43 . Experiments with MPH were also conducted in two technical replicates for each cell line. Western Blot of Wnt-related proteins following chronic MPH treatment Western Blot analyses were conducted after administrating MPH for seven consecutive days to investigate the potential effects of chronic MPH on the expression of key Wnt-proteins, which may be associated with proliferation outcomes. When one well from a 6-well plate (Sarstedt) containing NSCs reached 100% confluence, they were harvested and subsequently seeded at a 1:3 to 1:6 dilution ratio into new 6 wells coated with Geltrex (Gibco™) diluted in DMEM/F12 (Gibco™) in a ratio of 1:100 and incubated for 1 hour at 37°C. Throughout this 7-day period, cells were cultured at 37°C and 5% CO 2 , and daily treated with water as vehicle or MPH at 10 nM or 100 nM. More specifically, the wells were completely refreshed with fresh media, which consisted of NEM with MPH on days 1, 3, 5 and 7 post-seeding, while MPH was only added to the wells on days 2, 4 and 6 post-seeding. On day 8 post-seeding, NSCs were harvested using StemPro® Accutase® (Gibco™), and after centrifugation at 300 x g for 4 minutes, proteins were extracted using 1% of Halt™ Protease & Phosphatase Single-Use Inhibitor Cocktail (Thermo Fisher Scientific™) in RIPA Buffer (Thermo Fisher Scientific™). Colorimetric detection quantitation of total protein concentration was measured for each cell line in triplicates according to the Microplate procedure using the Pierce™ BCA Protein Assay Kit (Thermo Fisher Scientific™). Every protein sample (5 µg) was incubated in Bolt™ LDS Sample Buffer 1X (Thermo Fisher Scientific™) and Bolt™ Sample Reducing Agent 1X (Thermo Fisher Scientific™) for 10 minutes at 70°C. Bolt™ 4–12% Bis-Tris Plus Gels and the XCell SureLock Mini-Cell Electrophoresis System (Thermo Fisher Scientific™) were used, and the gel was run at constant 200 V for 40 minutes. The transfer of gels onto iBlot® nitrocellulose membranes (Thermo Fisher Scientific™) was performed for 7 minutes at 20 V using the iBlot® Gel Transfer Device (Thermo Fisher Scientific™). The Pierce™ Fast Western Blot Kit, ECL Substrate (Thermo Fisher Scientific™) was used to stain the membrane for proteins involved in the Wnt/β-catenin pathway such as LRP6, active β-catenin, and total and phosphorylated GSK3β. Details about the primary and secondary antibodies used in this protocol may be found in Supplementary Table 2. Membranes were incubated in primary antibodies diluted in antibody buffer for 20 hours at 4°C. On the next day, an incubation with secondary antibodies diluted 1:10000 in antibody buffer was performed. The membrane was imaged by the Molecular Image® ChemiDoc™ XRS + using the Chemi Hi Resolution set for 30s, 45s, 60s and 75s and the protein ladder (PageRuler Prestained Protein Ladder; 10–180 kDa) was detected by the colorimetric application. All images were analyzed in ImageLab 6.0, and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used as a housekeeping protein. As an additional normalization factor, a protein sample belonging to the cell line MR010 c3 was used as an internal control. For each condition, two protein samples per cell line were analyzed in two independent experiments. Data and statistical analysis According to the iPSC-based tool developed by Brunner et al. 44 and considering an effect size (Cohen’s d ) equal to 1.0 (based on a study using iPSCs in similar readouts and research questions 45 ) and a moderate intercluster correlation of 0.15, the sufficient statistical power of 0.8 would have been achieved for the main outcome given by the investigation of the MPH effects in NSCs (which includes at least 52 observations per cell line) by adopting 8 or 10 cell lines per group. Therefore, to ensure a statistical power equivalent or higher than 0.8, N = 10 cell lines per group was chosen. In all experiments, 5 individuals per group (2 iPSC clones each) were analyzed. Band intensities from Western Blots were analyzed with ImageLab 6.0, while absorbance and luminescence data were measured using the MikroWin 2010 software (version 5.18). All statistical tests were performed in R (version 4.4.1) and the integrated development environment RStudio (version 2023.6.1.524). The graphs (except for the correlation matrix) were generated with GraphPad Prism software (GraphPad Software Inc; San Diego, CA, USA; version 10.3.0). To account for the nested data structure, we performed linear mixed-effects modeling with fixed effects and a nested random intercept (1 | Cell/Replicate), using the lmer function from the ‘lme4’ package in R. Satterthwaite-approximated degrees of freedom were used to generate p-values. Model assumptions were tested using a simulation-based approach implemented in the ‘DHARMa’ package. In cases where deviations from the assumptions were detected, robust models (the rlmer function from the ‘robustlmm’ package) were used. Posthoc comparisons with Tukey’s correction were applied if a main effect or interaction was statistically significant (or if there was a trend toward significance), using the ‘emmeans’ package to explore pairwise differences between levels of the fixed effects. Statistics from the posthoc tests are listed in Supplementary Table 3. To compare baseline versus water conditions in ADHD and control groups (Supplementary Fig. 2), Mann-Whitney tests were applied instead of nested models, as only one clone per donor was considered in both groups. Spearman’s correlations were computed as a correlation matrix among different clinical, genetic and cellular variables of interest, as previously described 29 . Both the uncorrected and Bonferroni-corrected matrices were presented. Given that genetic and epigenetic differences introduced by cell culture are expected between clones derived from the same subject and therefore, from the same genetic background 46 , 47 , the data points in the bar graphs illustratively represent each clone separately. The graphs depict model-adjusted means ± standard error of the mean (SEM). Dots in all bar charts represent the average of at least two independent replicates per cell line. Overall, a p-value lower than 0.05 (graphically depicted by asterisks) was considered significant, whereas p-values between 0.05 and 0.075 (graphically depicted by hashtags) were considered trends toward statistical significance. Code Availability R code used for calculation of growth rates of xCELLigence, the generation of the correlation matrices, and all statistical analyses in this study can be provided upon request. Results ADHD NSCs proliferate at a slower rate than controls Both of our proliferation methods showed that growth rates of iPSCs did not significantly differ between ADHD and control groups (Figs. 1 A and 1 B; for xCELLigence: standard lmer , estimate (Est.) = 0.001, standard error (SE) = 0.003, t (15.81) = 0.50, p = 0.627; for WST-1: standard lmer , Est. = 0.005, SE = 0.007, t (4.26) = 0.81, p = 0.463). Individual growth rates for iPSCs in xCELLigence and WST-1 assays are provided in Supplementary Figs. 1A and 1B, respectively. Yet, ADHD NSCs exhibited a significantly lower rate of proliferation in both xCELLigence (Fig. 1 C; standard lmer , Est. = -0.007, SE = 0.003, t (8.00) = -2.74, * p = 0.025) and WST-1 methods (Fig. 1 D; standard lmer , Est. = -0.007, SE = 0.003, t (16.15) = -2.72, * p = 0.015). Since we previously observed that proliferation results from vehicle-treated NSCs (water) were not statistically different from baseline results when 4 ADHD and 4 control lines were analyzed (Supplementary Fig. 2), the findings presented on Figs. 1 C and 1 D, Fig. 5 and Supplementary Figs. 3A, 4A and 6 represent vehicle-treated NSCs. MPH treatment at a low concentration slightly increases proliferation in ADHD NSCs In the next step, NSCs were treated with MPH on a daily basis in order to examine any potential rescue effects of this drug on their proliferation (Fig. 2 A). A significant effect of diagnosis was found in both xCELLigence (standard lmer , Est. = 0.37, SE = 0.13, t (15.49) = 2.93, * p = 0.010) and WST-1 (standard lmer , Est. = 0.30, SE = 0.11, t (19.74) = 2.84, * p = 0.010). Diagnosis-wise posthoc tests were applied to data generated from both methods to verify differences between ADHD and control groups for each MPH dose. After treatment in xCELLigence, the notable differences observed at basal level continued and MPH did not raise the growth rates of the ADHD group to the control levels, which was evidenced by the pairwise comparisons between groups (* p = 0.012 for ADHD versus Control at Vehicle, * p = 0.043 for ADHD versus Control at MPH 10 nM and # p = 0.055 for ADHD versus Control at MPH 100 nM) (Fig. 2 B, Supplementary Table 3). However, in terms of percentage change, there were indications of increased rates of proliferation, specifically when ADHD NSCs were subjected to a concentration of 10 nM of MPH in the xCELLigence system. When applied to ADHD cell lines, this led to an approximate 18% (statistically non-significant) increase in growth rates beyond their baseline rates, whereas the dose of 100 nM resulted in a lower change in proliferation in this group corresponding to ca. 8.6% (Fig. 2 B). The proliferation of the control group increased by only 3% after treatment with MPH at 10 nM in comparison to its vehicle (Fig. 2 B). In contrast, MPH 100 nM slightly decreased proliferation by 4.8% in the control group when compared to its vehicle (Fig. 2 B). Similarly, statistically significant differences between groups were observed for each MPH concentration in WST-1 (standard lmer , * p = 0.020 for ADHD versus Control at Vehicle, * p = 0.029 for ADHD versus Control at MPH 10 nM and * p = 0.046 for ADHD versus Control at MPH 100 nM) (Fig. 2 C, Supplementary Table 3). In terms of percentage change, MPH-treated ADHD NSCs at 10 nM showed a 5.7% increase in comparison to ADHD vehicle, although in a statistically non-significant manner. The dose of 100 nM increased proliferation of ADHD NSCs by only 4.7% in comparison to its vehicle, while moderately reducing growth rates from control NSCs relative to control vehicle, resulting in a statistically non-significant decrease of 2.2% (Fig. 2 C). Supplementary Figs. 3A-C and 4A-C show individual growth rates before and after MPH treatment. Blocking the Wnt pathway with DKK1 prevents proliferative effects of MPH treatment in ADHD NSCs Given previous studies demonstrating the ability of MPH to regulate the canonical Wnt pathway 21 , 48 , we postulated that DKK1, an upstream Wnt inhibitor, could be effective in reducing the increase in ADHD NSC proliferation induced by a concentration of 10 nM MPH. In order to determine whether there are any associations between MPH, Wnt, and proliferation, growth rates were measured using xCELLigence for five days after MPH treatment. However, 30 minutes prior to MPH treatment, DKK1 at 60 ng/mL was used to inhibit Wnt signaling. Figure 3 A illustrates the experimental design for four treatment cycles of DKK1 and/or MPH treatment. The effect of diagnosis was found to be significant (standard lmer , Est = 0.36, SE = 0.17, t (13.52) = 2.17, * p = 0.049). Diagnosis-wise post hoc tests revealed trends towards significance between Control and ADHD at the basal level ( # p = 0.051) and after double treatment with DKK1 and MPH ( # p = 0.073). However, no significant differences were seen between groups when NSCs were treated with MPH ( p = 0.124) or DKK1 alone ( p = 0.110) (Fig. 3 B, Supplementary Table 3). While MPH increased ADHD growth rates, DKK1 treatment did not enhance these rates and instead reduced them in the control group. Notably, the proliferative effects of MPH on ADHD NSCs ceased when the Wnt signaling pathway was blocked, compared to the growth rates observed when the NSCs were solely treated with MPH (Fig. 3 B, Supplementary Table 3). Protein expression and functional findings indicate upregulation of Wnt activity by MPH 10 nM in ADHD NSCs To investigate whether chronic MPH treatment was able to induce changes in the expression of specific proteins that compose the Wnt/β–catenin pathway, we performed Western Blot experiments after 7 daily MPH treatments at 10 nM and 100 nM (Figs. 4 A and 4 B). Expression of total LRP6 (Fig. 4 C), active β–catenin (Fig. 4 D) and inactive GSK3β (Fig. 4 E) was measured for all conditions. Inactive GSK3β levels were calculated as the ratio between S9-phosphorylated and total GSK3β. For all three proteins, no statistically significant effects or trends were observed for any variable in this study (diagnosis, MPH concentrations, or their interaction) based on the standard lmer model involving expression of total LRP6 and the robust lmer model involving active β–catenin (Fig. 4 D) and inactive GSK3β (Fig. 4 E). However, we noticed non-significant increased levels of active β-catenin (increase of 85% versus control) at the basal state (vehicle) in ADHD compared to control. Consequently, we compared the basal levels of this protein between ADHD and control NSCs. As opposed to LRP6 and inactive GSK3β (Supplementary Figs. 5A and 5C), we observed a tendency toward increased levels of active β-catenin in ADHD NSCs, even though this difference was not statistically significant (Supplementary Fig. 5B; standard lmer , # p = 0.068). Using functional Wnt reporter assays 43 , Wnt activity in ADHD NSCs was assessed after acute treatment with MPH at 10 nM. In order to assess the impact of MPH at a concentration of 10 nM compared to the baseline state, both the control and ADHD groups are subjected to a baseline level of 25% Wnt activity. As a result, their vehicle conditions are not being compared. In our recently published paper, we have shown that ADHD cell lines had overactive Wnt activity in comparison to controls, which was indicated by Western Blot and Wnt reporter results 29 . Thus, the goal of this experiment was to solely identify any modulatory effects of MPH. In our findings, ADHD NSCs demonstrated a significant increase in Wnt activity following MPH treatment at 10 nM compared to the vehicle (Fig. 4 F; standard lmer , Est. = -8.36, SE = 3.06, t (18.00) = -2.73, * p = 0.014). Conversely, MPH 10 nM did not enhance Wnt activity in the control group (Fig. 4 G; standard lmer , Est. = -1.41, SE = 1.55, t (14.00) = -0.91, p = 0.378). Multiple associations between genetic, cellular and clinical parameters were found in the present study. As anticipated, due to the same pattern of results provided by xCELLigence and WST-1 assays, growth rates derived from these methods correlated significantly and positively with one another (Fig. 5 A). Slower proliferation was shown to be significantly associated with people who scored higher clinically on Conners' Rating Scales for hyperactivity, impulsivity, and inattention, as well as with externalizing or total scores from CBCL (Fig. 5 A). Consistent with previous large population study findings 49 , there was a significant positive correlation between ADHD-PRS and CBCL’s externalizing and total scores, as well as between ADHD-PRS and Conners’ scores for hyperactivity and impulsivity. Furthermore, there was a negative correlation between NSC growth rates (measured by both xCELLigence and WST-1) and individual ADHD-PRS ( p = 0.025 and p = 0.097, respectively) (Fig. 5 A, Supplementary Table 4). Overall, we identified negative associations between growth rates and genetic susceptibility to other neuropsychiatric illnesses, such as ASD, BD, and MDD. Genetic liability to ADHD also correlated positively to ASD- and AD-PRS in a statistically significant manner, while no correlation was observed for ADHD versus MDD, OCD, ANX, or BD (Fig. 5 A). The Wnt-specific PRS exhibited a substantial negative correlation with ADHD-related behavioral scores, such as Conners’ hyperactivity/impulsivity and inattention and CBCL inattention, as shown in Fig. 5 A. The correlation between Wnt-PRS and ADHD-PRS was negative, with a nominal significance of p = 0.058 (Supplementary Table 4). In contrast, baldness-related PRS expectedly did not correlate with ADHD symptomatology or any cellular variables, as also previously described 29 (Fig. 5 A). Upon thorough examination of the interconnections among the three Wnt elements analyzed in this study, it is evident that a positive correlation exists, albeit not statistically significant, between the expression of active β-catenin and total LRP6. This implies the potential existence of a positive feedback loop mechanism (Fig. 5 A). While our correlation analyses are exploratory in nature, the large number of comparisons (171) increases the risk of Type I errors. Therefore, we present the correlation matrices both uncorrected (Fig. 5 A) and after Bonferroni correction (Fig. 5 B). Additionally, Supplementary Table 4 reports both uncorrected and corrected p-values. Only six pairs survived the corrections: (1) Conners Inattention (Conners In) scores versus Hyperactivity/Impulsivity scores (Conners H-I); (2) Conners In versus total problems scores from the CBCL (CBCL T); (3) Conners H-I versus CBCL T; (4) CBCL T versus externalizing problems scores from the CBCL (CBCL Ext); (5) CBCL T versus ADHD-PRS; and (6) CBCL Ext versus ADHD-PRS (Fig. 5 B). To further explore the results by eliminating the issue of pseudoreplication due to the representation of two clones from one individual in the matrix, we averaged the in vitro results from both clones per individual and recalculated the correlations with N = 10 (Supplementary Fig. 6, Supplementary Table 5). Although ADHD-PRS no longer correlated with AD-PRS in a statistically significant manner ( p = 0.120) (Supplementary Table 5), we observed that similar patterns of correlations were preserved when compared to Fig. 5 A. These include: 1) growth rates obtained from xCELLigence and WST-1 assays, 2) different clinical scores of ADHD symptomatology overall, 3) clinical scores versus ADHD-PRS, 4) ADHD-PRS versus ASD-PRS, 5) Wnt-PRS versus Conners’ scores for inattention, 6) PRS of distinct neuropsychiatric disorders versus ADHD-related cellular findings and clinical scores, and 7) NSC growth rates versus clinical scores (Supplementary Fig. 6A, Supplementary Table 5). However, only the correlation between CBCL scores for inattention versus CBCL total scores survived the conservative Bonferroni correction in this analysis (Supplementary Fig. 6B, Supplementary Table 5). All in all, despite the exploratory nature of these analyses, the results may inspire novel hypotheses to be tested in the future. Discussion This study expands on our previous research on iPSC-derived cell line growth rates from ADHD patients and controls by employing a larger sample size and female participants. It demonstrates that variations in cell proliferation primarily occur during the later stages of NSCs rather than iPSCs 28 . These results align with the view that ADHD is a disorder of brain development, and gene expression profiles can change both temporally and spatially during this period 50 , 51 , which could lead to phenotypes that are specific to certain cell types. In ADHD patients, reduced cortical thickness is a frequent finding that has been associated with its etiology 52 . Accordingly, the impaired cell proliferation in ADHD NSCs found in this paper may be related to clinical brain maturational delays. In vivo evidence has shown that hippocampal cells from thyroid hormone-responsive protein-overexpressing (THRSP-OE) mice, considered animal models for ADHD, also proliferate less than controls 53 . Furthermore, the result from an in vitro study conducted in a more complex model is also in line with our findings: the authors showed reduced thickness at the cortical plate and ventricular zone of iPSC-derived brain organoids in one male ADHD patient 54 . In humans, despite distinct opinions about the potential of postnatal NSC proliferation and neurogenesis, there is increasing evidence that proliferative adult NSCs may still be found in the mammalian brain, populating the subventricular zone and being able to undergo neurogenesis/astrogenesis and transiently persist in the cortex after injury contexts 55 . The presence of cortical NSCs and neural progenitor cells (NPCs) has also been reported and discussed in more detail by Ohira in 2018 56 . Based on that, our hypothesis is that postnatal proliferation of NSCs might be affected in ADHD, in a non-embryonic stage, and modulated by MPH. Consistent with our Wnt-related discoveries regarding protein expression 29 , we have confirmed that the presence of genetic susceptibility to ADHD should be considered as an important factor when studying the proliferation of NSCs. Albeit being exploratory in nature, our data indicate a negative correlation between growth rates in NSCs and ADHD-PRS. A recent study has demonstrated that individuals with high polygenic load for this disorder exhibited reduced intracranial variance and cortical surface area 57 . Our findings also indicate a positive correlation between ADHD-PRS and ADHD-related behavioral traits, as also shown in our previous study 29 , as well as a negative association between those clinical features and the proliferation of NSCs. Multiple evidence in the clinical context revealed a robust correlation between a higher genetic susceptibility to ADHD and distinct clinical traits, such as impulsivity 58 – 60 . Previous research has indicated that cortical thickness in specific regions associated with important cognitive functions, such as the right anterior attention network, could potentially serve as a predictor for ADHD symptoms 61 . Similarly, Castellanos et al. showed that there was a substantial correlation between lower cerebral volumes ( e.g. , from cerebellum, frontal and temporal gray matter, and caudate) and the severity of ADHD symptoms 62 . Similarly, the same pattern of correlation was observed when PRS for ASD and MDD were analyzed against growth rates of NSCs. This correlation can be attributed to the significant genetic overlap and the high occurrence of comorbidities among these disorders 63 . Consistently, as expected, individuals who are genetically more prone to develop ADHD showed higher clinical and behavioral scores, which was also observed for ASD- and MDD-PRS in a significant manner. We did observe tendencies of positive association between high predisposition to ANX and high hyperactivity/impulsivity scores. However, contrary to our expectations, associations between ANX-PRS and other parameters were not as insightful, given the high prevalence of comorbidities between ANX and ADHD 64 . Interestingly, the strong genetic association between the genetic predisposition to AD, a neurodegenerative disorder, and ADHD constitutes one of the evidences that these two conditions are strongly related in terms of cellular and clinical outcomes 65 , 66 , as previously discussed 29 . Additionally, a growing body of evidence has previously linked downregulation of Wnt activity to cognitive dysfunctions in AD 67 , 68 , which is in agreement with the significant negative correlation between inactive GSK3β levels and AD-PRS found in the present study. Notably, there was a tendency for increased Wnt-PRS to correlate with increased NSC proliferation. This discovery corroborates our prior hypothesis that genetic variations within this cascade may be responsible for its functional regulation while conferring protection and promoting favorable neurodevelopment 29 . This is also in concordance with the tendencies of negative correlations between Wnt-PRS and ADHD-PRS in this study, which might indicate the close relationship between this pathway and ADHD, as stated in our initial hypothesis 21 . Conversely, the absence of important correlations between ADHD-related clinical scores, cellular variables, and genetic predisposition to baldness, a non-psychiatric disorder, increases our confidence in the specificity of our results. After Bonferroni corrections, only six correlation pairs involving PRS and ADHD-related clinical scores of CBCL and Conners were preserved. Among these, when clone data were averaged, only the correlation between CBCL T versus CBCL Ext remained significant after correction. Altogether, this shows the strong correlation among distinct facets of ADHD symptomatology and between these symptoms and genetic predisposition to the disorder. This reflects the high consistency in the recruitment process of our ADHD patients and controls and aligns with previous studies reporting that ADHD-PRS correlates with symptom severity 69 , 70 . Concerning cellular variables, a negative correlation between the levels of active β-catenin and the proliferation results obtained from NSCs evaluated using xCELLigence showed a trend towards significance (Supplementary Table 4). While in vivo evidence has shown that stabilized β-catenin leads to the expansion of pools of NPCs 71 , the literature attributes the maintenance of general NSC homeostasis to the activation of the Wnt/β-catenin pathway, which includes other processes such as cell fate specification and differentiation 72 . We also observed on our data contrasting tendencies in the correlations between internalizing scores from CBCL and xCELLigence or WST-1 results. Disparities in outcomes obtained from the two approaches can be attributed to technical inconsistencies between them, as elaborated in our preliminary publication 28 . While both methods provided similar results, WST-1 tests indirectly evaluate proliferation at a single timepoint, whereas xCELLigence provides cell indexes from single wells over time 28 . This could potentially result in xCELLigence measurements being more representative of the rates at which NSCs proliferate. Regarding treatment, we found that the differences in NSC proliferation between the ADHD and control groups were not entirely corrected by the administration of MPH, as hypothesized. It is possible that the drug's four-day administration, as opposed to the months or years that patients typically take their prescription, is the reason for its limited ability to significantly stimulate the cell proliferation of our ADHD NSCs. Nevertheless, our findings suggest that the ADHD group is experiencing a distinct proliferative improvement, as seen in clinical observations 1 . The results of the current study contradict previous findings from our research group, which showed that MPH promoted the process of neuronal differentiation at the expense of cell proliferation in murine NSCs 73 . However, considering variations in cell profile that are peculiar to each species is essential. A subsequent investigation demonstrated that the administration of MPH resulted in decreased proliferation and increased differentiation of rat PC12 and human SH-SY5Y neuroblastoma cells, attributed to the activation of Wnt signaling 48 . While the Wnt pathway is generally believed to be conserved among different species 74 , discrepancies between past and present findings may be due to variations in the Wnt signaling between human and rat cells. These differences could include the expression of Wnt-related genes 75 , and the inherent variability in Wnt dynamics across different cell types 26 . Our recent work has revealed that ADHD NSCs have higher levels of Wnt activity compared to those without the condition 29 . This was primarily observed through expression analysis of the same proteins investigated in our current study, and was further confirmed using Wnt reporter assays 29 . Here, the levels of active β-catenin showed a tendency to increase following the continuous administration of MPH at a concentration of 10 nM in ADHD NSCs. However, this increase was not statistically significant. Given the absence of statistical significance, it is important to take these data cautiously and seek more clarity on the implicated mechanisms. Nevertheless, these preliminary results might represent a starting point for deeper investigation into the enhancement of Wnt activity by chronic MPH treatment at lower doses. If confirmed, this evidence would be in agreement with in vivo findings, which have previously shown that a 28-day MPH treatment at lower doses (1 mg/kg) increased β-catenin levels in mice, concomitantly leading to higher proliferation of hippocampal cells 76 . However, a 10-fold higher dose led to reduced expression levels of the same protein during the same period of time and favored neuronal differentiation 76 . Functional experiments revealed that only ADHD NSCs showed elevated Wnt activity following an acute treatment with a low dose of MPH (10 nM). In ADHD cells, a non-significant increase in active β-catenin levels following the administration of 10 nM of MPH and a minor reduction at 100 nM throughout 7 days were observed in this study. This might suggest that MPH-related benefits might persist over long-term treatment, even though more studies are required to confirm it. Indeed, 10 nM falls within the physiological range observed in humans after 2 hours of administration, which corresponds to the pharmacodynamic point when MPH reaches its peak concentration in blood plasma 77 . Given β-catenin's capacity to stimulate cell division of human NSCs 72 , it is plausible that the heightened Wnt activity following treatment with MPH 10 nM plays a crucial role in slightly augmenting proliferation of ADHD NSCs. Consequently, this discovery might hold potential clinical significance. DKK1-induced Wnt inhibition prior to MPH treatment in ADHD NSCs resulted in the loss of detectable MPH effects, indicating that MPH-induced increases in proliferation of ADHD NSCs are dependent on the Wnt signaling pathway. However, additional research is necessary to accurately ascertain the specific mechanism by which MPH affects the Wnt cascade, due to the intricate intracellular interactions between Wnt and other proliferation-regulating pathways, such as Notch, fibroblast growth factors (FGF), and brain-derived neurotrophic factors (BDNF) 78 – 80 . In summary, based on the observation that increased levels of active β-catenin tended to correlate with diminished proliferation of NSCs as measured by xCELLigence, we hypothesized that the elevated basal Wnt activity observed in ADHD NSCs in our recently published study 29 may serve as a compensatory mechanism to enhance their growth rates. However, this is likely due to the interplay between the Wnt pathway and other signaling pathways. Thus, compensatory efforts might potentially be improved by administering a chronic dose of MPH at 10 nM, since this treatment results in a small increase in the proliferation of NSCs in ADHD patients. We acknowledge that some of the techniques presented in this paper might have limitations. For instance, Western Blot experiments might be a large source of variability. For being a qualitative assessment of protein expression, normalization and subsequent reproducibility might be challenging in Western Blots, unlike more sensitive methods such as automated assays or ELISA. Moreover, this methodology only depicts the exact frame of protein extraction after chronic treatment with MPH and not the functionality of Wnt signaling, even though we investigated three different proteins at distinct points of the cascade. Additionally, the relatively short period of MPH treatment in proliferation experiments may explain the absence of complete recovery in growth rates of ADHD NSCs by MPH. Although this context may not accurately reflect the treatment received by patients, it does indicate the ideal duration for an in vitro treatment to yield more dependable outcomes. The sample size can significantly influence the observed results in this research and account for the presence of merely tendencies in certain experiments 81 , 82 . While the generation of iPSC lines is a cost- and time-consuming process, increasing the sample size of both patients and controls would be optimal to determine whether these trends grow more pronounced and statistically significant. Moreover, doing an in-depth investigation into the effects of MPH is crucial for gaining a more precise understanding of the specific mechanisms of this drug. This research is currently underway in our laboratory. This work presents the Wnt pathway as a novel target of MPH and links it to the proliferative phenotype in ADHD using patient-specific cell lines. Although the results are tentative, it is the first publication to do so. Nevertheless, our findings open doors to further studies aiming to investigate novel MPH targets, the involvement of Wnt and other pathways in ADHD, and ADHD-related phenotypes. Since the Wnt signaling modulates not only cell proliferation but also maturation and differentiation processes, future research in the field of ADHD disease modeling should focus on examining potential differences in neuronal or glial differentiation and functionality between individuals with and without ADHD. This will help in gaining a more comprehensive understanding of the precise role played by the canonical Wnt signaling pathway in these circumstances. Declarations Conflict of Interest Some of the authors would like to declare potential conflicts of interest. E.G. received research grant support from MEDICE Arzneimittel Pütter GmbH & Co. KG. S.W. has received royalties in the last 5 years from Thieme, Hogrefe, Kohlhammer, Springer, Beltz. In 2023, she received honorary speakers from Takeda. Her work was supported in the last years by the Swiss National Science Foundation (SNF), diff. EU FP7s, HSM Hochspezialisierte Medizin of the Kanton Zurich, Switzerland, Bfarm Germany, ZInEP, Hartmann Müller Stiftung, Olga Mayenfisch, Gertrud Thalmann, Vontobel, Unicentia, Erika Schwarz, Heuberg Fonds, National Government of Health (BAG), Gesundheitsförderung Schweiz and Horizon Europe. Outside professional activities and interests are declared under the link of the University of Zurich www.uzh.ch/prof/ssl-dir/interessenbindungen/client/web/ . Author contributions C.M.Y.O. performed experiments, conducted data analysis and drafted the manuscript. N.W. reviewed the manuscript. A.B. and M.R. performed experiments, conducted data analysis and reviewed the manuscript. L.S. conducted PRS calculations, supported data analysis and reviewed the manuscript. S.W. conceptualized the project and reviewed the manuscript. E.G. conceptualized the project, assisted in results interpretation and reviewed the manuscript. Acknowledgments We would like to thank the individuals recruited in this study, as well as their families, for their valuable participation. Moreover, we acknowledge MEDICE Arzneimittel Pütter GmbH & Co. KG, the Waterloo Foundation for funding part of this project (reference number 2462/4548), Ms. Kristin Koppelmaa for her technical support during xCELLigence and WST-1 experiments, Dr. Per Hoffmann and Dr. Stefan Herms for genotyping iPSCs during QC stages, Prof. Ditte Demontis for providing the newest ADHD GWAS summary statistics, Prof. Dr. Thalia C. Eley and Prof. Dr. Gerome Breen for providing the ANX GWAS summary statistics, and Dr. Anna Maria Werling and Dr. Christian Döring for recruiting patients and controls to this study. References Nakao T, Radua J, Rubia K, Mataix-Cols D. 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Polygenic Risk and the Course of Attention-Deficit/Hyperactivity Disorder From Childhood to Young Adulthood: Findings From a Nationally Representative Cohort. Journal of the American Academy of Child and Adolescent Psychiatry 2021; 60: 1147–1156. Saraçaydın G, Ruisch IH, van Rooij D, Sprooten E, Franke B, Buitelaar JK et al. Shared genetic etiology between ADHD, task-related behavioral measures and brain activation during response inhibition in a youth ADHD case-control study. Eur Arch Psychiatry Clin Neurosci 2024; 274: 45–58. Chenn A, Walsh CA. Regulation of cerebral cortical size by control of cell cycle exit in neural precursors. Science 2002; 297: 365–369. Gao J, Liao Y, Qiu M, Shen W. Wnt/beta-Catenin Signaling in Neural Stem Cell Homeostasis and Neurological Diseases. Neuroscientist 2021; 27: 58–72. Bartl J, Mori T, Riederer P, Ozawa H, Grünblatt E. Methylphenidate enhances neural stem cell differentiation. J Mol Psychiatry 2013; 1: 5. Croce JC, McClay DR. Evolution of the Wnt pathways. Methods in molecular biology (Clifton, N.J.) 2008; 469: 3–18. Gonzalez-Fernandez C, Arevalo-Martin A, Paniagua-Torija B, Ferrer I, Rodriguez FJ, Garcia-Ovejero D. Wnts Are Expressed in the Ependymal Region of the Adult Spinal Cord. Molecular neurobiology 2017; 54: 6342–6355. Oakes HV, DeVee CE, Farmer B, Allen SA, Hall AN, Ensley T et al. Neurogenesis within the hippocampus after chronic methylphenidate exposure. J Neural Transm (Vienna) 2019; 126: 201–209. W Wargin, K Patrick, C Kilts, C T Gualtieri, K Ellington, R A Mueller et al. Pharmacokinetics of methylphenidate in man, rat and monkey. Journal of Pharmacology and Experimental Therapeutics 1983; 226: 382. Lee S, Remark LH, Josephson AM, Leclerc K, Lopez EM, Kirby DJ et al. Notch-Wnt signal crosstalk regulates proliferation and differentiation of osteoprogenitor cells during intramembranous bone healing. NPJ Regenerative medicine 2021; 6: 29. Yang J-W, Ma W, Luo T, Wang D-Y, Lu J-J, Li X-T et al. BDNF promotes human neural stem cell growth via GSK-3β-mediated crosstalk with the wnt/β-catenin signaling pathway. Growth factors (Chur, Switzerland) 2016; 34: 19–32. Tang D, He Y, Li W, Li H. Wnt/β-catenin interacts with the FGF pathway to promote proliferation and regenerative cell proliferation in the zebrafish lateral line neuromast. Experimental & molecular medicine 2019; 51: 1–16. Dutan Polit L, Eidhof I, McNeill RV, Warre-Cornish KM, Yde Ohki CM, Walter NM et al. Recommendations, guidelines, and best practice for the use of human induced pluripotent stem cells for neuropharmacological studies of neuropsychiatric disorders. Neuroscience Applied 2023; 2: 101125. Beekhuis-Hoekstra SD, Watanabe K, Werme J, Leeuw CA de, Paliukhovich I, Li KW et al. Systematic assessment of variability in the proteome of iPSC derivatives. Stem Cell Res 2021; 56: 102512. Additional Declarations Yes Some of the authors would like to declare potential conflicts of interest. E.G. received research grant support from MEDICE Arzneimittel Pütter GmbH & Co. KG. S.W. has received royalties in the last 5 years from Thieme, Hogrefe, Kohlhammer, Springer, Beltz. In 2023, she received honorary speakers from Takeda. Her work was supported in the last years by the Swiss National Science Foundation (SNF), diff. EU FP7s, HSM Hochspezialisierte Medizin of the Kanton Zurich, Switzerland, Bfarm Germany, ZInEP, Hartmann Müller Stiftung, Olga Mayenfisch, Gertrud Thalmann, Vontobel, Unicentia, Erika Schwarz, Heuberg Fonds, National Government of Health (BAG), Gesundheitsförderung Schweiz and Horizon Europe. Outside professional activities and interests are declared under the link of the University of Zurich www.uzh.ch/prof/ssl-dir/interessenbindungen/client/web/ . Supplementary Files YdeOhkiSupplementaryRebuttal202Dec24.pdf Supplementary Information SupplementaryTable4Rebuttal2.pdf Supplementary Table 4 SupplementaryTable5Rebuttal2.pdf Supplementary Table 5 Cite Share Download PDF Status: Published Journal Publication published 27 Jul, 2025 Read the published version in Journal of Neural Transmission → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3956813","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":414825604,"identity":"f9af5138-6e04-4c14-90b8-fdd14e502fe6","order_by":0,"name":"Edna Grünblatt","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0001-8505-7265","institution":"University of Zurich","correspondingAuthor":true,"prefix":"","firstName":"Edna","middleName":"","lastName":"Grünblatt","suffix":""},{"id":414825605,"identity":"14209dc3-d39b-43b8-a82b-78a7d876f7fc","order_by":1,"name":"Cristine Marie Yde Ohki","email":"","orcid":"","institution":"Psychiatric University Hospital Zurich, University of Zurich","correspondingAuthor":false,"prefix":"","firstName":"Cristine","middleName":"Marie Yde","lastName":"Ohki","suffix":""},{"id":414825606,"identity":"d3bcc609-668b-4629-bcbd-f74327a84394","order_by":2,"name":"Natalie Monet Walter","email":"","orcid":"","institution":"Psychiatric University Hospital Zurich, University of Zurich (UZH)","correspondingAuthor":false,"prefix":"","firstName":"Natalie","middleName":"Monet","lastName":"Walter","suffix":""},{"id":414825607,"identity":"43bb8b7a-ce12-4856-9de0-e293585849cb","order_by":3,"name":"Lukasz Smigielski","email":"","orcid":"","institution":"University Hospital of Psychiatry / Unversity of Zurich","correspondingAuthor":false,"prefix":"","firstName":"Lukasz","middleName":"","lastName":"Smigielski","suffix":""},{"id":414825608,"identity":"ec3ff5e7-c0fc-4df3-b8a8-5cb22a94536e","order_by":4,"name":"Audrey Bender","email":"","orcid":"","institution":"Psychiatric University Hospital Zurich, University of Zurich (UZH)","correspondingAuthor":false,"prefix":"","firstName":"Audrey","middleName":"","lastName":"Bender","suffix":""},{"id":414825609,"identity":"4643b6c0-c688-4d3a-9ccd-7cfd0f8ba7f0","order_by":5,"name":"Michelle Rickli","email":"","orcid":"","institution":"Psychiatric University Hospital Zurich, University of Zurich (UZH)","correspondingAuthor":false,"prefix":"","firstName":"Michelle","middleName":"","lastName":"Rickli","suffix":""},{"id":414825610,"identity":"f272227d-7e1c-4735-9da3-599ca5b2546d","order_by":6,"name":"Susanne Walitza","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Susanne","middleName":"","lastName":"Walitza","suffix":""}],"badges":[],"createdAt":"2024-02-14 19:10:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3956813/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3956813/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00702-025-02988-y","type":"published","date":"2025-07-28T00:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":76284551,"identity":"1e59f1c9-a1ed-46dc-9324-83351f7c589a","added_by":"auto","created_at":"2025-02-14 10:57:42","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":75270,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProliferation analysis in ADHD and control cell lines.\u003c/strong\u003eBoth in xCELLigence (A) and WST-1 assays (B), no statistically significant (n.s.) differences were observed between ADHD and control iPSCs. N=at least 2 technical replicates were analyzed for each cell line (5 individuals per group, 2 clones each). In NSCs, lower growth rates in ADHD are seen for both xCELLigence (C) and WST-1 (D). For xCELLigence, Est. = -0.007, SE = 0.003, \u003cem\u003et\u003c/em\u003e(8.00) = -2.74, *\u003cem\u003ep\u003c/em\u003e = 0.025. For WST-1, Est. = -0.007, SE = 0.003, \u003cem\u003et\u003c/em\u003e(16.15) = -2.72, *\u003cem\u003ep\u003c/em\u003e = 0.015.\u003cem\u003e \u003c/em\u003eIn xCELLigence, the average of 4 vehicle experiments was calculated per cell line. N=5 Control (2 clones each) and 5 ADHD patients (2 clones each) were analyzed in 2 technical replicates. Each dot represents the averaged raw data obtained from independent experiments per cell line. Mean ± SEM (model-adjusted, standard \u003cem\u003elmer\u003c/em\u003e) is depicted in the graphs.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3956813/v1/5766ca3154d766f549fec3c1.png"},{"id":76284556,"identity":"0c206a31-f108-4f8c-8986-d7c7fb8ec50b","added_by":"auto","created_at":"2025-02-14 10:57:42","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":139996,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferences in growth rates between ADHD and control NSCs with and without MPH treatment. \u003c/strong\u003eA) Experimental design of xCELLigence and WST-1 with daily MPH treatments. The red tubes represent the addition of WST-1 at each timepoint (figure created with Biorender.com). Absorbance measurements took place 4 hours later.\u003cstrong\u003e \u003c/strong\u003eThe bar graphs represent growth rates obtained by xCELLigence (B) or WST-1 assays (C) after 4-day MPH treatment.\u003cstrong\u003e \u003c/strong\u003eStatistically significant \u003cem\u003eposthoc \u003c/em\u003ecomparisons are depicted by asterisks, whereas hashtags represent trends toward significance (for xCELLigence: standard \u003cem\u003elmer\u003c/em\u003e, *\u003cem\u003ep\u003c/em\u003e = 0.012 for ADHD \u003cem\u003eversus\u003c/em\u003e Control at Vehicle, *\u003cem\u003ep\u003c/em\u003e = 0.043 for ADHD \u003cem\u003eversus\u003c/em\u003e Control at MPH 10 nM and \u003csup\u003e#\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e = 0.055 for ADHD \u003cem\u003eversus\u003c/em\u003e Control at MPH 100 nM; for WST-1: standard \u003cem\u003elmer\u003c/em\u003e, *\u003cem\u003ep\u003c/em\u003e = 0.020 for ADHD \u003cem\u003eversus\u003c/em\u003e Control at Vehicle, *\u003cem\u003ep\u003c/em\u003e = 0.029 for ADHD \u003cem\u003eversus\u003c/em\u003e Control at MPH 10 nM and *\u003cem\u003ep\u003c/em\u003e = 0.046 for ADHD \u003cem\u003eversus\u003c/em\u003e Control at MPH 100 nM). Four vehicle experiments were considered and averaged per cell line. Mean ± SEM (model-adjusted, standard \u003cem\u003elmer\u003c/em\u003e) is depicted in the graphs. N=5 Control individuals (2 clones each) and 5 ADHD patients (2 clones each) were analyzed in 2 technical replicates. Each dot represents the averaged raw data from 2 independent experiments per cell line.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3956813/v1/db0ec2b329b9405ad04c81b2.png"},{"id":76284554,"identity":"17f639eb-8414-4915-b011-13ffbacda4b9","added_by":"auto","created_at":"2025-02-14 10:57:42","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":218938,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNSC proliferation after blockage of Wnt activity using DKK1 60 ng/mL\u003c/strong\u003e. A) Timeline representing the design of xCELLigence experiments, in which proliferation of NSCs was tested throughout 5 days of four-day treatment with DKK1 and/or MPH. Water was used as MPH’s vehicle when only DKK1 was added to the wells. Figure created with Biorender.com. B) Growth rates of NSCs after daily treatment with DKK1 and/or MPH. Hashtags represent trends of differential responses between ADHD and control groups (standard \u003cem\u003elmer,\u003c/em\u003e \u003csup\u003e#\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e = 0.051 at Vehicle and \u003csup\u003e#\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e = 0.073 at MPH 100 nM). For vehicle conditions in xCELLigence, the average of 4 vehicle experiments was calculated per cell line. All the other conditions were normalized by Control Vehicle. Mean ± SEM (model-adjusted, standard \u003cem\u003elmer\u003c/em\u003e) is depicted in the graph. N=5 Control individuals (2 clones each) and 5 ADHD patients (2 clones each) were analyzed in 2 technical replicates. Each dot represents the averaged raw data from 2 independent experiments per cell line.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-3956813/v1/9290b92908b601d5848b7d65.png"},{"id":76285950,"identity":"39b4201a-0392-45ba-a008-b8a4d85b5b5c","added_by":"auto","created_at":"2025-02-14 11:13:42","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":344605,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAnalysis of MPH influence on Wnt signaling of NSCs from ADHD patients and controls. \u003c/strong\u003eA) Timeline of Western Blot experiments. Figure created with Biorender.com. B) Representative bands from one control NSC line (K011 c10) and one ADHD NSC (MR010 c18) for all analyzed Wnt-proteins\u003cstrong\u003e \u003c/strong\u003eafter chronic treatment with MPH 10 nM and 100 nM. GAPDH is shown as reference. Total levels of LRP6 (C), active β-catenin (D) and inactive GSK3β (E) were quantified before and after 7-day MPH treatment. No significant effects or trends were observed. Group-specific Wnt activity in ADHD (F) and control NSCs (G), using the reporter assay, was measured after acute treatment with MPH at 10 nM. For ADHD NSCs: standard \u003cem\u003elmer\u003c/em\u003e, Est. = -8.36, SE = 3.06, \u003cem\u003et\u003c/em\u003e(18.00) = -2.73, *\u003cem\u003ep \u003c/em\u003e= 0.014; for control NSCs: standard \u003cem\u003elmer\u003c/em\u003e, Est. = -1.41, SE = 1.55, \u003cem\u003et\u003c/em\u003e(14.00) = -0.91, \u003cem\u003ep = \u003c/em\u003e0.378). In (F) and (G), bar charts show levels of Wnt activity after the treatment with MPH, normalized by their respective vehicles representing 25% of Wnt activity. Mean ± SEM (model-adjusted, standard \u003cem\u003elmer\u003c/em\u003e for LRP6 and Wnt reporter findings;\u003cem\u003e \u003c/em\u003erobust\u003cem\u003e lmer \u003c/em\u003efor active\u003cem\u003e \u003c/em\u003eβ-catenin and inactive GSK3β) is depicted in the graph. N=5 Control individuals (2 clones each) and 5 ADHD patients (2 clones each) were analyzed in 2 technical replicates. Each dot represents the averaged raw data from 2 independent experiments per cell line.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-3956813/v1/8821081720a0a526c6d4a5bb.png"},{"id":76284560,"identity":"3a1dc59f-2600-4c1c-b6a6-75db6fe33ae1","added_by":"auto","created_at":"2025-02-14 10:57:43","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":86101,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelations between ADHD-related behavioral scores, Wnt-PRS, PRS for ADHD and other disorders and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ein vitro\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e findings. \u003c/strong\u003eA) Uncorrected pairwise Spearman’s correlations are shown in the plot. Colors code the strength and direction of each correlation whereas asterisks indicate statistically significant correlations without any correction (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). B) After the Bonferroni correction for 171 unique pair combinations (0.05/171), 6 pairs survived the correction (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05): Conners In \u003cem\u003eversus\u003c/em\u003e Conners H-I, Conners In \u003cem\u003eversus \u003c/em\u003eCBCL T, Conners H-I \u003cem\u003eversus \u003c/em\u003eCBCL T, CBCL T \u003cem\u003eversus \u003c/em\u003eCBCL Ext, CBCL T \u003cem\u003eversus \u003c/em\u003eADHD-PRS, CBCL Ext \u003cem\u003eversus\u003c/em\u003e ADHD-PRS. The red color in these comparisons indicates positive correlations while the numbers represent their respective correlation coefficients. Abbreviations: GR NSCs – xCELL: Growth rates of NSCs from xCELLigence assays; GR NSCs – WST: Growth rates of NSCs from WST-1 assays; Conners In = Inattention scores from Conners’ Rating Scales; Conners H-I: Hyperactivity/Impulsivity scores from Conners’ Rating Scales; CBCL T = Total Scores from CBCL; CBCL Int = Internalizing scores from CBCL; CBCL Ext = Externalizing scores from CBCL; Active βcat = Protein expression of active β-catenin after a 7-day cell culture; Inactive GSK3β = Protein expression of inactive GSK3β after a 7-day cell culture; LRP6 = Protein expression of LRP6 after a 7-day cell culture; ADHD-PRS = Polygenic Risk Scores for Attention-Deficit Hyperactivity Disorder; Path-Wnt-PRS = Pathway-PRS specific to Wnt signaling; ASD-PRS = Polygenic Risk Scores for Autism Spectrum Disorder; BD-PRS = Polygenic Risk Scores for Bipolar Disorder; AD-PRS = Polygenic Risk Scores for Alzheimer’s Disease; MDD-PRS = Polygenic Risk Scores for Major Depressive Disorder; OCD-PRS = Polygenic Risk Scores for Obsessive-Compulsive Disorder; ANX-PRS = Polygenic Risk Scores for Anxiety Disorder. Genetic variables were also present in a previous publication\u003csup\u003e29\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-3956813/v1/9b1ea5c0ce3ec71314b1d8f2.png"},{"id":87840267,"identity":"28ea3848-8158-40a1-bb63-fd267d83075b","added_by":"auto","created_at":"2025-07-29 14:05:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1800822,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3956813/v1/c2507172-c8f8-4760-a5ec-fa1fd877d784.pdf"},{"id":76285227,"identity":"43f502fc-d698-47b1-8e86-02a356f0d695","added_by":"auto","created_at":"2025-02-14 11:05:42","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":828394,"visible":true,"origin":"","legend":"Supplementary Information","description":"","filename":"YdeOhkiSupplementaryRebuttal202Dec24.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3956813/v1/8c80567e661f3a2bc93a7b32.pdf"},{"id":76284552,"identity":"95239b87-7d5c-412b-b775-1538cc983346","added_by":"auto","created_at":"2025-02-14 10:57:42","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":473181,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 4\u003c/p\u003e","description":"","filename":"SupplementaryTable4Rebuttal2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3956813/v1/d5a19f881a03502c736e96db.pdf"},{"id":76285230,"identity":"db478197-a6ed-43ed-9b86-a78ee43510c9","added_by":"auto","created_at":"2025-02-14 11:05:42","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":471584,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 5\u003c/p\u003e","description":"","filename":"SupplementaryTable5Rebuttal2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3956813/v1/7c3d973ad3fdd904d36ed8d1.pdf"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e\nSome of the authors would like to declare potential conflicts of interest. E.G. received research grant support from MEDICE Arzneimittel Pütter GmbH \u0026 Co. KG. S.W. has received royalties in the last 5 years from Thieme, Hogrefe, Kohlhammer, Springer, Beltz. In 2023, she received honorary speakers from Takeda. Her work was supported in the last years by the Swiss National Science Foundation (SNF), diff. EU FP7s, HSM Hochspezialisierte Medizin of the Kanton Zurich, Switzerland, Bfarm Germany, ZInEP, Hartmann Müller Stiftung, Olga Mayenfisch, Gertrud Thalmann, Vontobel, Unicentia, Erika Schwarz, Heuberg Fonds, National Government of Health (BAG), Gesundheitsförderung Schweiz and Horizon Europe. Outside professional activities and interests are declared under the link of the University of Zurich www.uzh.ch/prof/ssl-dir/interessenbindungen/client/web/.","formattedTitle":"Alterations in proliferation of neuronal stem cells in Attention-Deficit/Hyperactivity Disorder and Wnt modulation by methylphenidate","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMethylphenidate (MPH) is a psychostimulant that is commonly employed as a pharmacological treatment strategy in attention-deficit/hyperactivity disorder (ADHD), a multifactorial neurodevelopmental disorder that is often characterized by delays in brain maturation of up to 4 years when compared to controls\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Structural delays include decreased cortical thickness\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e as a result of common reductions in gray and white matter in brain regions highly implicated in ADHD-related cognitive functions, such as attention\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e and inhibition of motor response\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Some examples of these areas are the basal ganglia\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e and the prefrontal cortex of ADHD patients\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMPH may potentially normalize gray and white matter volumes in individuals with ADHD compared to unmedicated patients\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Not limited to structural ameliorations, it may also improve functional maturational delays in the brain networks of ADHD patients\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Among other molecular mechanisms, MPH is a psychostimulant that blocks dopamine and norepinephrine transporters (DAT and NET, respectively)\u003csup\u003e\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. MPH shows one of the largest effect sizes among medications used in children and adolescent psychiatry\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e and has been found to be largely beneficial in reducing hyperactivity and impulsivity in patients with ADHD\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe primary therapeutic mechanism of action of MPH is said to be DAT inhibition; nevertheless, the precise molecular mechanisms behind MPH remain unclear. For instance, MPH has a paradoxical impact in that it improves attention in ADHD patients, while decreasing hyperactivity and impulsivity, which seems counterintuitive given its psychostimulant properties\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Moreover, an \u003cem\u003ein vivo\u003c/em\u003e study has demonstrated that MPH-induced behavioral benefits persisted in DAT-knockout mice\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, suggesting that MPH may have additional modes of action which are not dependent on DAT inhibition\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOne of the mechanisms that was previously linked to ADHD is the Wnt signaling pathway\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. In a review paper, MacDonald et al. described in a detailed manner that the Wnt cascade is triggered when transmembrane receptors LRP5/6 (LDL receptor-related protein 5/6) and Frizzled (FZD) get activated by extracellular Wnt ligands, such as Wnt3a, Wnt5a, and Wnt7a. Among others, the Dickkopf-related protein 1 (DKK1) acts upstream in this cascade as a well-known Wnt-antagonist since it can internalize LRP5/6 receptors through Kremen-mediated endocytosis\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e or compete with extracellular Wnt ligands for binding to LRP6\u003csup\u003e24\u003c/sup\u003e. More specifically, in the absence of these Wnt-agonists or the presence of antagonists, GSK3\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}\\)\u003c/span\u003e\u003c/span\u003e, one of the key components of the so-called \u0026ldquo;destruction complex\u0026rdquo;, phosphorylates \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}\\)\u003c/span\u003e\u003c/span\u003e-catenin and leads to its subsequent degradation. On the other hand, when phosphorylated at the Serine-9 position (S9), GSK3\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}\\)\u003c/span\u003e\u003c/span\u003e becomes inactive and is no longer able to phosphorylate \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}\\)\u003c/span\u003e\u003c/span\u003e-catenin for further proteasomal degradation. When Wnt ligands are available in the extracellular milieu and activate the LRP5/6 and FZD receptors, the cascade is turned on, which leads to the inhibition of the destruction complex and to the accumulation and posterior translocation of β-catenin into the nucleus, where it will activate the transcription of Wnt target genes with the aid of the TCF/LEF (T cell factor/lymphoid enhancer factor) family of transcription factors\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. These Wnt target genes might be, in a context-dependent manner, highly associated with essential cellular processes during neurodevelopment, such as proliferation, cell fate specification, and differentiation, that might be differentially modulated in distinct cell types\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe use of induced pluripotent stem cells (iPSCs) as models for studies of ADHD and other neuropsychiatric disorders allows the preservation of the genetic background from the somatic cells of origin, and subsequently, the study of patient-specific cellular and molecular phenotypes in functional living neural cells\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Our group\u0026rsquo;s preliminary data have demonstrated that male ADHD neural stem cells (NSCs) grow at a considerably slower rate than controls, whereas no differences between the two groups were found at the early developmental stage of iPSCs\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Moreover, we demonstrated in our recently published paper that ADHD NSCs have higher basal Wnt activity than controls in terms of protein expression and functional assessment\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. One of the goals of the current study was to assess the growth of a greater number of cell lines, including both sexes. Moreover, we investigated whether treatment with varying doses of MPH can effectively reverse any differences in ADHD NSC proliferation through a Wnt-dependent mechanism.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eRecruitment of participants\u003c/h2\u003e \u003cp\u003eADHD patients (aged 6\u0026thinsp;\u0026minus;\u0026thinsp;18 years old) who clinically respond to MPH treatment, with no comorbidities and matching healthy controls were recruited by the Department of Child and Adolescent Psychiatry and Psychotherapy (KJPP) of the University of Zurich (UZH), as described in Yde Ohki et al.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Previous publications\u003csup\u003e\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e and a recently published paper\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e provide further information regarding the inclusion and exclusion criteria. Supplementary Table\u0026nbsp;1 provides a list of the individual subjects included in the current study together with their demographic and clinical characteristics.\u003c/p\u003e \u003cp\u003eAfter recruitment, salivary DNA samples from patients and controls were submitted to genotyping, as reported in previous publications\u003csup\u003e\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Individual Polygenic Risk Scores (PRS) were calculated as a quantitative indicator of genetic predisposition to ADHD\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e and other neuropsychiatric disorders (Alzheimer\u0026rsquo;s disease (AD)\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e, Autism Spectrum Disorder (ASD)\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, bipolar disorder (BD)\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, major depressive disorder (MDD)\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, obsessive-compulsive disorder (OCD)\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e), using a clumping / thresholding method for \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05 in Plink, as previously described\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. PRS for anxiety (ANX) was also calculated based on the summary statistics provided by the corresponding authors (Prof. Dr. Thalia C. Eley and Gerome Breen) from Purves et al., 2020\u003csup\u003e39\u003c/sup\u003e. Pathway-PRS for ADHD\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e was calculated specifically for the Wnt pathway (Molecular Signatures Database version v2023.2.Hs; source code: hsa04310) using PRSet. PRS for baldness\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e was calculated and analyzed as negative PRS control\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAs part of the recruitment process, ADHD patients and controls were evaluated according to Child Behavior Checklist (CBCL) from parents\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e and Conners-3-Rating Scales\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e from patients, teachers and parents. Controls were required to have lower Conners\u0026rsquo; T-values (\u0026lt;\u0026thinsp;60) in hyperactivity/impulsivity and inattention whereas ADHD patients should score at least 65 in every symptomatology scale in at least one of the Conners\u0026rsquo; questionnaires\u003csup\u003e\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis project was approved by the Cantonal Ethics Committee (BASEC-Nr.-2016-00101 \u0026amp; BASEC-Nr.-201700825) and followed the latest version of the Declaration of Helsinki, as previously reported\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. The consent form for the study was signed by all participants and/or their parents.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGeneration and culture of iPSCs and NSCs\u003c/h3\u003e\n\u003cp\u003eIPSCs from plucked hair-derived keratinocytes or peripheral mononuclear blood cells (PBMCs) from ADHD patients and healthy controls were generated and submitted to quality control (QC) as reported in previous publications\u003csup\u003e\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. These cell lines underwent extensive QC that included verification of genomic integrity using Single Nucleotide Polymorphism (SNP) arrays, mycoplasma testing, Sendai virus detection, Copy Number Variation (CNV) analysis, embryoid body formation, and assessment of gene and protein expression of pluripotency markers\u003csup\u003e\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. The culture of NSCs and their QC in terms of gene and protein expression analysis through RT-PCR and immunocytochemistry, respectively, were performed as described in our previously published papers\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. The NSCs utilized in this paper were positive for classical NSC markers (\u003cem\u003ei.e.\u003c/em\u003e, SOX2, TUJ1, NESTIN and PAX6)\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Details about NSC culture and treatment can be found in the next sections.\u003c/p\u003e\n\u003ch3\u003exCELLigence and WST-1 assays for iPSC and NSC proliferation at basal levels\u003c/h3\u003e\n\u003cp\u003eHuman iPSCs and NSCs that have successfully undergone QC were submitted to the real-time impedance cell analysis, xCELLigence, and the colorimetric assay WST-1, as described in Yde Ohki et al.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBriefly, on day 0, 25000 iPSCs in Essential 8 Flex (Gibco\u003csup\u003e\u0026trade;\u003c/sup\u003e) were seeded per well in an E96 Plate (OLS\u003csup\u003e\u0026reg;\u003c/sup\u003e BIO) or in regular 96-well plates (Sarstedt) for xCELLigence and WST-1, respectively. These plates were respectively coated with Vitronectin (Gibco\u003csup\u003e\u0026trade;\u003c/sup\u003e) at 15 \u0026micro;g/mL and 5 \u0026micro;g/mL. Similarly, 15000 NSCs were seeded onto E96-well plates (Agilent) or in regular 96-well plates (Sarstedt) coated with Matrigel (Corning\u0026reg; Matrigel\u0026reg; hESC-Qualified Matrix) diluted 1:100 in DMEM/F12 (Gibco\u003csup\u003e\u0026trade;\u003c/sup\u003e) in Neural Expansion Media (NEM; PSC Neural Induction Medium, Gibco\u0026trade;) for xCELLigence and WST-1 assays, respectively. We determined the growth rates from xCELLigence by fitting cell index (CI) curves into Malthusian growth models using R Statistical Software v. 4.1.2.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn xCELLigence, the first measurement occurs in the first experimental minute to detect the impedance in the wells containing only media. For baseline experiments, xCELLigence CI was measured for 2 hours every 10 minutes, followed by measurements every hour throughout a 24-sweep cycle. Next, the xCELLigence Real-Time Cell Analysis (RTCA) station recorded measurements every hour throughout two 48-hour sweep cycles. This schedule allowed us to refresh the media during sweep intervals. The experiment finished after 120 h. The slope of the impedance curves from 24 h post-seeding until their maximum CI were determined. For WST-1, the same number of cells were seeded onto wells of 96 well plates, and WST-1 tetrazolium salt (Sigma) was added to the wells at the timepoints of 24 h, 42 h, 48 h, 66 h, 72 h, 90 h, 96 h, and 114 h post-seeding. Absorbance measurements at 440 nm took place 4 h later using the Mithras2 LB 943 Multimode Reader (Berthold Technologies) and adopting a reference wavelength of 630 nm, as previously reported\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Absorbance curves were log2-transformed for linearization, and growth rates were calculated as the slopes after fitting the curve from 24 h to the maximum absorbance in linear regression models\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRegarding data analysis, data from xCELLigence wells per replicate were cleaned using the Interquartile Range (IQR) method, whereas WST-1 wells per timepoint per replicate were cleaned using a z-score method, consistent with our previous publication\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Replicates were averaged per cell line and represented as dots in each graph.\u003c/p\u003e \u003cp\u003eEach investigated group included four males and one female (including 2 iPSC clones per person) (see Supplementary Table\u0026nbsp;1). The average of two technical replicate trials for each cell line was used for all analyses. For iPSCs, WST-1 assays involved conducting a minimum of two technical replicates per cell line and then determining the average.\u003c/p\u003e\n\u003ch3\u003eMPH treatment of NSCs for subsequent evaluation of proliferation\u003c/h3\u003e\n\u003cp\u003eFor both xCELLigence and WST-1, the cells were chronically treated with MPH hydrochloride (Lipomed AG, MPH-1043-HC) every 24 h at 10 nM and 100 nM throughout 5 experimental days. WST-1 experiments and analysis in MPH-treated NSCs were performed as described above. Slopes from the xCELLigence and WST-1 growth curves were calculated as reported in the previous section and in Yde Ohki et al.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. As in baseline experiments, CI values were assessed for 2 hours every 10 minutes followed by 24-hour measurements every hour. Next, four sweep cycles of 24 hours each were performed to ensure that treatments were performed every day.\u003c/p\u003e \u003cp\u003eIn the present study, the slope of impedance curves in xCELLigence from the moment that MPH (or vehicle) was added for the first time to the cultures (24 h and 24.5 h post-seeding for experiments with MPH and DKK1, respectively) until its maximum CI were calculated as growth rates.\u003c/p\u003e \u003cp\u003eOn days 1 and 3, the NSCs were completely refreshed with NEM and MPH. On days 2 and 4 after seeding, we only added MPH or vehicle (water) to the wells. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eA depicts the experimental design of these assays.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eDKK1 treatment of NSCs with and without MPH for xCELLigence assays\u003c/h3\u003e\n\u003cp\u003eDKK1 treatment before MPH was performed using the xCELLigence assay to investigate the hypothesis that the Wnt signaling system modulates MPH proliferation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). To do so, a stock solution of DKK1 was prepared at 10000 ng/mL in water containing BSA 1%, which was freshly diluted in NEM to prepare an intermediate solution at 600 ng/mL. On days 1 and 3 post-seeding, the media from the wells were completely replaced with fresh NEM plus DKK1, whereas DKK1 was only added to the wells on days 2 and 4 (final concentration of 60 ng/mL). This concentration was able to fully block the Wnt activity when these NSCs were submitted to functional Wnt reporter assays\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe plate was returned to the xCELLigence station, and the measurements were restarted for a duration of 30 minutes, in which CIs were measured every 5 minutes. Subsequently, the wells were treated with MPH, resulting in a final concentration of 10 nM. Water was considered as vehicle for untreated wells. Growth rates were determined using the same methodology as the aforementioned experiments, but solely with MPH.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eWnt reporter assay in NSCs after acute MPH treatment\u003c/h2\u003e \u003cp\u003eWnt reporter assays were conducted in both ADHD and control NSCs, following the transfection-based methodology outlined in Yde Ohki et al., 2023\u003csup\u003e43\u003c/sup\u003e. In this protocol, NSCs were co-transfected with the plasmid of interest containing a Wnt luciferase reporter gene under the control of a TCF/LEF responsive element (pGL4.49[luc2P/TCF-LEF RE/Hygro] Vector, from Promega) and a normalization vector containing NanoLuc luciferase gene under the control of a TK (thymidine-kinase) promoter (pNL1.1.TK[Nluc/TK] Vector, Promega).\u003c/p\u003e \u003cp\u003eAfter previous overnight treatment with the Wnt-agonist Wnt3a, EC50 values were determined for each cell line in two technical replicates\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. According to the previous results\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, NSCs were treated individually with the respective Wnt3a\u0026rsquo;s EC25 in triplicates. Subsequently, they were returned into a cell culture incubator set at a temperature of 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003eAfter 10 minutes, MPH 10 nM was added to the wells. The condition named as \u0026ldquo;Vehicle\u0026rdquo; represents treatment with individual EC25 concentrations of Wnt3a, only. In this context, water was used as vehicle for MPH treatment.\u003c/p\u003e \u003cp\u003eNext, the cells were incubated overnight at 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e. On the following day, luminescence assays and subsequent data analysis from Relative Luminescence Units (RLU) were performed as previously reported\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Experiments with MPH were also conducted in two technical replicates for each cell line.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eWestern Blot of Wnt-related proteins following chronic MPH treatment\u003c/h3\u003e\n\u003cp\u003eWestern Blot analyses were conducted after administrating MPH for seven consecutive days to investigate the potential effects of chronic MPH on the expression of key Wnt-proteins, which may be associated with proliferation outcomes.\u003c/p\u003e \u003cp\u003eWhen one well from a 6-well plate (Sarstedt) containing NSCs reached 100% confluence, they were harvested and subsequently seeded at a 1:3 to 1:6 dilution ratio into new 6 wells coated with Geltrex (Gibco\u0026trade;) diluted in DMEM/F12 (Gibco\u0026trade;) in a ratio of 1:100 and incubated for 1 hour at 37\u0026deg;C. Throughout this 7-day period, cells were cultured at 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e, and daily treated with water as vehicle or MPH at 10 nM or 100 nM. More specifically, the wells were completely refreshed with fresh media, which consisted of NEM with MPH on days 1, 3, 5 and 7 post-seeding, while MPH was only added to the wells on days 2, 4 and 6 post-seeding. On day 8 post-seeding, NSCs were harvested using StemPro\u0026reg; Accutase\u0026reg; (Gibco\u0026trade;), and after centrifugation at 300 x g for 4 minutes, proteins were extracted using 1% of Halt\u0026trade; Protease \u0026amp; Phosphatase Single-Use Inhibitor Cocktail (Thermo Fisher Scientific\u0026trade;) in RIPA Buffer (Thermo Fisher Scientific\u0026trade;).\u003c/p\u003e \u003cp\u003eColorimetric detection quantitation of total protein concentration was measured for each cell line in triplicates according to the Microplate procedure using the Pierce\u0026trade; BCA Protein Assay Kit (Thermo Fisher Scientific\u0026trade;).\u003c/p\u003e \u003cp\u003eEvery protein sample (5 \u0026micro;g) was incubated in Bolt\u0026trade; LDS Sample Buffer 1X (Thermo Fisher Scientific\u0026trade;) and Bolt\u0026trade; Sample Reducing Agent 1X (Thermo Fisher Scientific\u0026trade;) for 10 minutes at 70\u0026deg;C. Bolt\u0026trade; 4\u0026ndash;12% Bis-Tris Plus Gels and the XCell SureLock Mini-Cell Electrophoresis System (Thermo Fisher Scientific\u0026trade;) were used, and the gel was run at constant 200 V for 40 minutes. The transfer of gels onto iBlot\u0026reg; nitrocellulose membranes (Thermo Fisher Scientific\u0026trade;) was performed for 7 minutes at 20 V using the iBlot\u0026reg; Gel Transfer Device (Thermo Fisher Scientific\u0026trade;).\u003c/p\u003e \u003cp\u003eThe Pierce\u0026trade; Fast Western Blot Kit, ECL Substrate (Thermo Fisher Scientific\u0026trade;) was used to stain the membrane for proteins involved in the Wnt/β-catenin pathway such as LRP6, active β-catenin, and total and phosphorylated GSK3β. Details about the primary and secondary antibodies used in this protocol may be found in Supplementary Table\u0026nbsp;2. Membranes were incubated in primary antibodies diluted in antibody buffer for 20 hours at 4\u0026deg;C. On the next day, an incubation with secondary antibodies diluted 1:10000 in antibody buffer was performed. The membrane was imaged by the Molecular Image\u0026reg; ChemiDoc\u0026trade; XRS\u0026thinsp;+\u0026thinsp;using the Chemi Hi Resolution set for 30s, 45s, 60s and 75s and the protein ladder (PageRuler Prestained Protein Ladder; 10\u0026ndash;180 kDa) was detected by the colorimetric application. All images were analyzed in ImageLab 6.0, and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used as a housekeeping protein. As an additional normalization factor, a protein sample belonging to the cell line MR010 c3 was used as an internal control. For each condition, two protein samples per cell line were analyzed in two independent experiments.\u003c/p\u003e\n\u003ch3\u003eData and statistical analysis\u003c/h3\u003e\n\u003cp\u003eAccording to the iPSC-based tool developed by Brunner et al.\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e and considering an effect size (Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e) equal to 1.0 (based on a study using iPSCs in similar readouts and research questions\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e) and a moderate intercluster correlation of 0.15, the sufficient statistical power of 0.8 would have been achieved for the main outcome given by the investigation of the MPH effects in NSCs (which includes at least 52 observations per cell line) by adopting 8 or 10 cell lines per group. Therefore, to ensure a statistical power equivalent or higher than 0.8, N\u0026thinsp;=\u0026thinsp;10 cell lines per group was chosen. In all experiments, 5 individuals per group (2 iPSC clones each) were analyzed. Band intensities from Western Blots were analyzed with ImageLab 6.0, while absorbance and luminescence data were measured using the MikroWin 2010 software (version 5.18). All statistical tests were performed in R (version 4.4.1) and the integrated development environment RStudio (version 2023.6.1.524). The graphs (except for the correlation matrix) were generated with GraphPad Prism software (GraphPad Software Inc; San Diego, CA, USA; version 10.3.0).\u003c/p\u003e \u003cp\u003eTo account for the nested data structure, we performed linear mixed-effects modeling with fixed effects and a nested random intercept (1 | Cell/Replicate), using the \u003cem\u003elmer\u003c/em\u003e function from the \u0026lsquo;lme4\u0026rsquo; package in R. Satterthwaite-approximated degrees of freedom were used to generate p-values. Model assumptions were tested using a simulation-based approach implemented in the \u0026lsquo;DHARMa\u0026rsquo; package. In cases where deviations from the assumptions were detected, robust models (the \u003cem\u003erlmer\u003c/em\u003e function from the \u0026lsquo;robustlmm\u0026rsquo; package) were used. \u003cem\u003ePosthoc\u003c/em\u003e comparisons with Tukey\u0026rsquo;s correction were applied if a main effect or interaction was statistically significant (or if there was a trend toward significance), using the \u0026lsquo;emmeans\u0026rsquo; package to explore pairwise differences between levels of the fixed effects. Statistics from the \u003cem\u003eposthoc\u003c/em\u003e tests are listed in Supplementary Table\u0026nbsp;3. To compare baseline \u003cem\u003eversus\u003c/em\u003e water conditions in ADHD and control groups (Supplementary Fig.\u0026nbsp;2), Mann-Whitney tests were applied instead of nested models, as only one clone per donor was considered in both groups.\u003c/p\u003e \u003cp\u003eSpearman\u0026rsquo;s correlations were computed as a correlation matrix among different clinical, genetic and cellular variables of interest, as previously described\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Both the uncorrected and Bonferroni-corrected matrices were presented.\u003c/p\u003e \u003cp\u003eGiven that genetic and epigenetic differences introduced by cell culture are expected between clones derived from the same subject and therefore, from the same genetic background\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e, the data points in the bar graphs illustratively represent each clone separately.\u003c/p\u003e \u003cp\u003eThe graphs depict model-adjusted means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error of the mean (SEM). Dots in all bar charts represent the average of at least two independent replicates per cell line. Overall, a p-value lower than 0.05 (graphically depicted by asterisks) was considered significant, whereas p-values between 0.05 and 0.075 (graphically depicted by hashtags) were considered trends toward statistical significance.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCode Availability\u003c/h2\u003e \u003cp\u003eR code used for calculation of growth rates of xCELLigence, the generation of the correlation matrices, and all statistical analyses in this study can be provided upon request.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eADHD NSCs proliferate at a slower rate than controls\u003c/p\u003e \u003cp\u003eBoth of our proliferation methods showed that growth rates of iPSCs did not significantly differ between ADHD and control groups (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003eB; for xCELLigence: standard \u003cem\u003elmer\u003c/em\u003e, estimate (Est.)\u0026thinsp;=\u0026thinsp;0.001, standard error (SE)\u0026thinsp;=\u0026thinsp;0.003, \u003cem\u003et\u003c/em\u003e(15.81)\u0026thinsp;=\u0026thinsp;0.50, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.627; for WST-1: standard \u003cem\u003elmer\u003c/em\u003e, Est. = 0.005, SE\u0026thinsp;=\u0026thinsp;0.007, \u003cem\u003et\u003c/em\u003e(4.26)\u0026thinsp;=\u0026thinsp;0.81, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.463). Individual growth rates for iPSCs in xCELLigence and WST-1 assays are provided in Supplementary Figs.\u0026nbsp;1A and 1B, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eYet, ADHD NSCs exhibited a significantly lower rate of proliferation in both xCELLigence (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003eC; standard \u003cem\u003elmer\u003c/em\u003e, Est. = -0.007, SE\u0026thinsp;=\u0026thinsp;0.003, \u003cem\u003et\u003c/em\u003e(8.00) = -2.74, *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.025) and WST-1 methods (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003eD; standard \u003cem\u003elmer\u003c/em\u003e, Est. = -0.007, SE\u0026thinsp;=\u0026thinsp;0.003, \u003cem\u003et\u003c/em\u003e(16.15) = -2.72, *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015).\u003c/p\u003e \u003cp\u003eSince we previously observed that proliferation results from vehicle-treated NSCs (water) were not statistically different from baseline results when 4 ADHD and 4 control lines were analyzed (Supplementary Fig.\u0026nbsp;2), the findings presented on Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003eC and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003eD, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Supplementary Figs.\u0026nbsp;3A, 4A and 6 represent vehicle-treated NSCs.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMPH treatment at a low concentration slightly increases proliferation in ADHD NSCs\u003c/p\u003e \u003cp\u003eIn the next step, NSCs were treated with MPH on a daily basis in order to examine any potential rescue effects of this drug on their proliferation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). A significant effect of diagnosis was found in both xCELLigence (standard \u003cem\u003elmer\u003c/em\u003e, Est. = 0.37, SE\u0026thinsp;=\u0026thinsp;0.13, \u003cem\u003et\u003c/em\u003e(15.49)\u0026thinsp;=\u0026thinsp;2.93, *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.010) and WST-1 (standard \u003cem\u003elmer\u003c/em\u003e, Est. = 0.30, SE\u0026thinsp;=\u0026thinsp;0.11, \u003cem\u003et\u003c/em\u003e(19.74)\u0026thinsp;=\u0026thinsp;2.84, *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.010). Diagnosis-wise \u003cem\u003eposthoc\u003c/em\u003e tests were applied to data generated from both methods to verify differences between ADHD and control groups for each MPH dose. After treatment in xCELLigence, the notable differences observed at basal level continued and MPH did not raise the growth rates of the ADHD group to the control levels, which was evidenced by the pairwise comparisons between groups (*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.012 for ADHD \u003cem\u003eversus\u003c/em\u003e Control at Vehicle, *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.043 for ADHD \u003cem\u003eversus\u003c/em\u003e Control at MPH 10 nM and \u003csup\u003e#\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.055 for ADHD \u003cem\u003eversus\u003c/em\u003e Control at MPH 100 nM) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, Supplementary Table\u0026nbsp;3).\u003c/p\u003e \u003cp\u003eHowever, in terms of percentage change, there were indications of increased rates of proliferation, specifically when ADHD NSCs were subjected to a concentration of 10 nM of MPH in the xCELLigence system. When applied to ADHD cell lines, this led to an approximate 18% (statistically non-significant) increase in growth rates beyond their baseline rates, whereas the dose of 100 nM resulted in a lower change in proliferation in this group corresponding to ca. 8.6% (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). The proliferation of the control group increased by only 3% after treatment with MPH at 10 nM in comparison to its vehicle (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). In contrast, MPH 100 nM slightly decreased proliferation by 4.8% in the control group when compared to its vehicle (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eSimilarly, statistically significant differences between groups were observed for each MPH concentration in WST-1 (standard \u003cem\u003elmer\u003c/em\u003e, *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.020 for ADHD \u003cem\u003eversus\u003c/em\u003e Control at Vehicle, *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.029 for ADHD \u003cem\u003eversus\u003c/em\u003e Control at MPH 10 nM and *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.046 for ADHD \u003cem\u003eversus\u003c/em\u003e Control at MPH 100 nM) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eC, Supplementary Table\u0026nbsp;3). In terms of percentage change, MPH-treated ADHD NSCs at 10 nM showed a 5.7% increase in comparison to ADHD vehicle, although in a statistically non-significant manner. The dose of 100 nM increased proliferation of ADHD NSCs by only 4.7% in comparison to its vehicle, while moderately reducing growth rates from control NSCs relative to control vehicle, resulting in a statistically non-significant decrease of 2.2% (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Supplementary Figs.\u0026nbsp;3A-C and 4A-C show individual growth rates before and after MPH treatment.\u003c/p\u003e \u003cp\u003eBlocking the Wnt pathway with DKK1 prevents proliferative effects of MPH treatment in ADHD NSCs\u003c/p\u003e \u003cp\u003eGiven previous studies demonstrating the ability of MPH to regulate the canonical Wnt pathway\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e, we postulated that DKK1, an upstream Wnt inhibitor, could be effective in reducing the increase in ADHD NSC proliferation induced by a concentration of 10 nM MPH. In order to determine whether there are any associations between MPH, Wnt, and proliferation, growth rates were measured using xCELLigence for five days after MPH treatment. However, 30 minutes prior to MPH treatment, DKK1 at 60 ng/mL was used to inhibit Wnt signaling. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eA illustrates the experimental design for four treatment cycles of DKK1 and/or MPH treatment.\u003c/p\u003e \u003cp\u003eThe effect of diagnosis was found to be significant (standard \u003cem\u003elmer\u003c/em\u003e, Est\u0026thinsp;=\u0026thinsp;0.36, SE\u0026thinsp;=\u0026thinsp;0.17, \u003cem\u003et\u003c/em\u003e(13.52)\u0026thinsp;=\u0026thinsp;2.17, *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.049). Diagnosis-wise \u003cem\u003epost hoc\u003c/em\u003e tests revealed trends towards significance between Control and ADHD at the basal level (\u003csup\u003e#\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.051) and after double treatment with DKK1 and MPH (\u003csup\u003e#\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.073). However, no significant differences were seen between groups when NSCs were treated with MPH (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.124) or DKK1 alone (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.110) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, Supplementary Table\u0026nbsp;3).\u003c/p\u003e \u003cp\u003eWhile MPH increased ADHD growth rates, DKK1 treatment did not enhance these rates and instead reduced them in the control group. Notably, the proliferative effects of MPH on ADHD NSCs ceased when the Wnt signaling pathway was blocked, compared to the growth rates observed when the NSCs were solely treated with MPH (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, Supplementary Table\u0026nbsp;3).\u003c/p\u003e \u003cp\u003eProtein expression and functional findings indicate upregulation of Wnt activity by MPH 10 nM in ADHD NSCs\u003c/p\u003e \u003cp\u003eTo investigate whether chronic MPH treatment was able to induce changes in the expression of specific proteins that compose the Wnt/β\u0026ndash;catenin pathway, we performed Western Blot experiments after 7 daily MPH treatments at 10 nM and 100 nM (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Expression of total LRP6 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eC), active β\u0026ndash;catenin (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eD) and inactive GSK3β (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eE) was measured for all conditions. Inactive GSK3β levels were calculated as the ratio between S9-phosphorylated and total GSK3β. For all three proteins, no statistically significant effects or trends were observed for any variable in this study (diagnosis, MPH concentrations, or their interaction) based on the standard \u003cem\u003elmer\u003c/em\u003e model involving expression of total LRP6 and the robust \u003cem\u003elmer\u003c/em\u003e model involving active β\u0026ndash;catenin (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eD) and inactive GSK3β (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eHowever, we noticed non-significant increased levels of active β-catenin (increase of 85% \u003cem\u003eversus\u003c/em\u003e control) at the basal state (vehicle) in ADHD compared to control. Consequently, we compared the basal levels of this protein between ADHD and control NSCs. As opposed to LRP6 and inactive GSK3β (Supplementary Figs.\u0026nbsp;5A and 5C), we observed a tendency toward increased levels of active β-catenin in ADHD NSCs, even though this difference was not statistically significant (Supplementary Fig.\u0026nbsp;5B; standard \u003cem\u003elmer\u003c/em\u003e, \u003csup\u003e#\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.068).\u003c/p\u003e \u003cp\u003eUsing functional Wnt reporter assays\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, Wnt activity in ADHD NSCs was assessed after acute treatment with MPH at 10 nM. In order to assess the impact of MPH at a concentration of 10 nM compared to the baseline state, both the control and ADHD groups are subjected to a baseline level of 25% Wnt activity. As a result, their vehicle conditions are not being compared. In our recently published paper, we have shown that ADHD cell lines had overactive Wnt activity in comparison to controls, which was indicated by Western Blot and Wnt reporter results\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Thus, the goal of this experiment was to solely identify any modulatory effects of MPH. In our findings, ADHD NSCs demonstrated a significant increase in Wnt activity following MPH treatment at 10 nM compared to the vehicle (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eF; standard \u003cem\u003elmer\u003c/em\u003e, Est. = -8.36, SE\u0026thinsp;=\u0026thinsp;3.06, \u003cem\u003et\u003c/em\u003e(18.00) = -2.73, *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.014). Conversely, MPH 10 nM did not enhance Wnt activity in the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eG; standard \u003cem\u003elmer\u003c/em\u003e, Est. = -1.41, SE\u0026thinsp;=\u0026thinsp;1.55, \u003cem\u003et\u003c/em\u003e(14.00) = -0.91, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.378).\u003c/p\u003e \u003cp\u003eMultiple associations between genetic, cellular and clinical parameters were found in the present study.\u003c/p\u003e \u003cp\u003eAs anticipated, due to the same pattern of results provided by xCELLigence and WST-1 assays, growth rates derived from these methods correlated significantly and positively with one another (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Slower proliferation was shown to be significantly associated with people who scored higher clinically on Conners' Rating Scales for hyperactivity, impulsivity, and inattention, as well as with externalizing or total scores from CBCL (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eConsistent with previous large population study findings\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e, there was a significant positive correlation between ADHD-PRS and CBCL\u0026rsquo;s externalizing and total scores, as well as between ADHD-PRS and Conners\u0026rsquo; scores for hyperactivity and impulsivity. Furthermore, there was a negative correlation between NSC growth rates (measured by both xCELLigence and WST-1) and individual ADHD-PRS (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.025 and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.097, respectively) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, Supplementary Table\u0026nbsp;4). Overall, we identified negative associations between growth rates and genetic susceptibility to other neuropsychiatric illnesses, such as ASD, BD, and MDD.\u003c/p\u003e \u003cp\u003eGenetic liability to ADHD also correlated positively to ASD- and AD-PRS in a statistically significant manner, while no correlation was observed for ADHD \u003cem\u003eversus\u003c/em\u003e MDD, OCD, ANX, or BD (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). The Wnt-specific PRS exhibited a substantial negative correlation with ADHD-related behavioral scores, such as Conners\u0026rsquo; hyperactivity/impulsivity and inattention and CBCL inattention, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA. The correlation between Wnt-PRS and ADHD-PRS was negative, with a nominal significance of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.058 (Supplementary Table\u0026nbsp;4). In contrast, baldness-related PRS expectedly did not correlate with ADHD symptomatology or any cellular variables, as also previously described\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eUpon thorough examination of the interconnections among the three Wnt elements analyzed in this study, it is evident that a positive correlation exists, albeit not statistically significant, between the expression of active β-catenin and total LRP6. This implies the potential existence of a positive feedback loop mechanism (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eWhile our correlation analyses are exploratory in nature, the large number of comparisons (171) increases the risk of Type I errors. Therefore, we present the correlation matrices both uncorrected (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA) and after Bonferroni correction (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Additionally, Supplementary Table\u0026nbsp;4 reports both uncorrected and corrected p-values. Only six pairs survived the corrections: (1) Conners Inattention (Conners In) scores versus Hyperactivity/Impulsivity scores (Conners H-I); (2) Conners In versus total problems scores from the CBCL (CBCL T); (3) Conners H-I versus CBCL T; (4) CBCL T versus externalizing problems scores from the CBCL (CBCL Ext); (5) CBCL T versus ADHD-PRS; and (6) CBCL Ext versus ADHD-PRS (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eTo further explore the results by eliminating the issue of pseudoreplication due to the representation of two clones from one individual in the matrix, we averaged the \u003cem\u003ein vitro\u003c/em\u003e results from both clones per individual and recalculated the correlations with N\u0026thinsp;=\u0026thinsp;10 (Supplementary Fig.\u0026nbsp;6, Supplementary Table\u0026nbsp;5). Although ADHD-PRS no longer correlated with AD-PRS in a statistically significant manner (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.120) (Supplementary Table\u0026nbsp;5), we observed that similar patterns of correlations were preserved when compared to Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA. These include: 1) growth rates obtained from xCELLigence and WST-1 assays, 2) different clinical scores of ADHD symptomatology overall, 3) clinical scores \u003cem\u003eversus\u003c/em\u003e ADHD-PRS, 4) ADHD-PRS \u003cem\u003eversus\u003c/em\u003e ASD-PRS, 5) Wnt-PRS \u003cem\u003eversus\u003c/em\u003e Conners\u0026rsquo; scores for inattention, 6) PRS of distinct neuropsychiatric disorders \u003cem\u003eversus\u003c/em\u003e ADHD-related cellular findings and clinical scores, and 7) NSC growth rates \u003cem\u003eversus\u003c/em\u003e clinical scores (Supplementary Fig.\u0026nbsp;6A, Supplementary Table\u0026nbsp;5). However, only the correlation between CBCL scores for inattention \u003cem\u003eversus\u003c/em\u003e CBCL total scores survived the conservative Bonferroni correction in this analysis (Supplementary Fig.\u0026nbsp;6B, Supplementary Table\u0026nbsp;5).\u003c/p\u003e \u003cp\u003eAll in all, despite the exploratory nature of these analyses, the results may inspire novel hypotheses to be tested in the future.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e This study expands on our previous research on iPSC-derived cell line growth rates from ADHD patients and controls by employing a larger sample size and female participants. It demonstrates that variations in cell proliferation primarily occur during the later stages of NSCs rather than iPSCs\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. These results align with the view that ADHD is a disorder of brain development, and gene expression profiles can change both temporally and spatially during this period\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e, which could lead to phenotypes that are specific to certain cell types.\u003c/p\u003e \u003cp\u003eIn ADHD patients, reduced cortical thickness is a frequent finding that has been associated with its etiology\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Accordingly, the impaired cell proliferation in ADHD NSCs found in this paper may be related to clinical brain maturational delays. \u003cem\u003eIn vivo\u003c/em\u003e evidence has shown that hippocampal cells from thyroid hormone-responsive protein-overexpressing (THRSP-OE) mice, considered animal models for ADHD, also proliferate less than controls\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. Furthermore, the result from an \u003cem\u003ein vitro\u003c/em\u003e study conducted in a more complex model is also in line with our findings: the authors showed reduced thickness at the cortical plate and ventricular zone of iPSC-derived brain organoids in one male ADHD patient\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. In humans, despite distinct opinions about the potential of postnatal NSC proliferation and neurogenesis, there is increasing evidence that proliferative adult NSCs may still be found in the mammalian brain, populating the subventricular zone and being able to undergo neurogenesis/astrogenesis and transiently persist in the cortex after injury contexts\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. The presence of cortical NSCs and neural progenitor cells (NPCs) has also been reported and discussed in more detail by Ohira in 2018\u003csup\u003e56\u003c/sup\u003e. Based on that, our hypothesis is that postnatal proliferation of NSCs might be affected in ADHD, in a non-embryonic stage, and modulated by MPH.\u003c/p\u003e \u003cp\u003eConsistent with our Wnt-related discoveries regarding protein expression\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, we have confirmed that the presence of genetic susceptibility to ADHD should be considered as an important factor when studying the proliferation of NSCs. Albeit being exploratory in nature, our data indicate a negative correlation between growth rates in NSCs and ADHD-PRS. A recent study has demonstrated that individuals with high polygenic load for this disorder exhibited reduced intracranial variance and cortical surface area\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. Our findings also indicate a positive correlation between ADHD-PRS and ADHD-related behavioral traits, as also shown in our previous study\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, as well as a negative association between those clinical features and the proliferation of NSCs. Multiple evidence in the clinical context revealed a robust correlation between a higher genetic susceptibility to ADHD and distinct clinical traits, such as impulsivity\u003csup\u003e\u003cspan additionalcitationids=\"CR59\" citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. Previous research has indicated that cortical thickness in specific regions associated with important cognitive functions, such as the right anterior attention network, could potentially serve as a predictor for ADHD symptoms\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. Similarly, Castellanos et al. showed that there was a substantial correlation between lower cerebral volumes (\u003cem\u003ee.g.\u003c/em\u003e, from cerebellum, frontal and temporal gray matter, and caudate) and the severity of ADHD symptoms\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSimilarly, the same pattern of correlation was observed when PRS for ASD and MDD were analyzed against growth rates of NSCs. This correlation can be attributed to the significant genetic overlap and the high occurrence of comorbidities among these disorders\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. Consistently, as expected, individuals who are genetically more prone to develop ADHD showed higher clinical and behavioral scores, which was also observed for ASD- and MDD-PRS in a significant manner. We did observe tendencies of positive association between high predisposition to ANX and high hyperactivity/impulsivity scores. However, contrary to our expectations, associations between ANX-PRS and other parameters were not as insightful, given the high prevalence of comorbidities between ANX and ADHD\u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eInterestingly, the strong genetic association between the genetic predisposition to AD, a neurodegenerative disorder, and ADHD constitutes one of the evidences that these two conditions are strongly related in terms of cellular and clinical outcomes\u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e,\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e, as previously discussed\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Additionally, a growing body of evidence has previously linked downregulation of Wnt activity to cognitive dysfunctions in AD\u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e,\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e, which is in agreement with the significant negative correlation between inactive GSK3β levels and AD-PRS found in the present study.\u003c/p\u003e \u003cp\u003eNotably, there was a tendency for increased Wnt-PRS to correlate with increased NSC proliferation. This discovery corroborates our prior hypothesis that genetic variations within this cascade may be responsible for its functional regulation while conferring protection and promoting favorable neurodevelopment\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. This is also in concordance with the tendencies of negative correlations between Wnt-PRS and ADHD-PRS in this study, which might indicate the close relationship between this pathway and ADHD, as stated in our initial hypothesis\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Conversely, the absence of important correlations between ADHD-related clinical scores, cellular variables, and genetic predisposition to baldness, a non-psychiatric disorder, increases our confidence in the specificity of our results.\u003c/p\u003e \u003cp\u003eAfter Bonferroni corrections, only six correlation pairs involving PRS and ADHD-related clinical scores of CBCL and Conners were preserved. Among these, when clone data were averaged, only the correlation between CBCL T \u003cem\u003eversus\u003c/em\u003e CBCL Ext remained significant after correction. Altogether, this shows the strong correlation among distinct facets of ADHD symptomatology and between these symptoms and genetic predisposition to the disorder. This reflects the high consistency in the recruitment process of our ADHD patients and controls and aligns with previous studies reporting that ADHD-PRS correlates with symptom severity\u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e,\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eConcerning cellular variables, a negative correlation between the levels of active β-catenin and the proliferation results obtained from NSCs evaluated using xCELLigence showed a trend towards significance (Supplementary Table\u0026nbsp;4). While \u003cem\u003ein vivo\u003c/em\u003e evidence has shown that stabilized β-catenin leads to the expansion of pools of NPCs\u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e, the literature attributes the maintenance of general NSC homeostasis to the activation of the Wnt/β-catenin pathway, which includes other processes such as cell fate specification and differentiation\u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWe also observed on our data contrasting tendencies in the correlations between internalizing scores from CBCL and xCELLigence or WST-1 results. Disparities in outcomes obtained from the two approaches can be attributed to technical inconsistencies between them, as elaborated in our preliminary publication\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. While both methods provided similar results, WST-1 tests indirectly evaluate proliferation at a single timepoint, whereas xCELLigence provides cell indexes from single wells over time\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. This could potentially result in xCELLigence measurements being more representative of the rates at which NSCs proliferate.\u003c/p\u003e \u003cp\u003eRegarding treatment, we found that the differences in NSC proliferation between the ADHD and control groups were not entirely corrected by the administration of MPH, as hypothesized. It is possible that the drug's four-day administration, as opposed to the months or years that patients typically take their prescription, is the reason for its limited ability to significantly stimulate the cell proliferation of our ADHD NSCs. Nevertheless, our findings suggest that the ADHD group is experiencing a distinct proliferative improvement, as seen in clinical observations\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe results of the current study contradict previous findings from our research group, which showed that MPH promoted the process of neuronal differentiation at the expense of cell proliferation in murine NSCs\u003csup\u003e\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e. However, considering variations in cell profile that are peculiar to each species is essential. A subsequent investigation demonstrated that the administration of MPH resulted in decreased proliferation and increased differentiation of rat PC12 and human SH-SY5Y neuroblastoma cells, attributed to the activation of Wnt signaling\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. While the Wnt pathway is generally believed to be conserved among different species\u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e, discrepancies between past and present findings may be due to variations in the Wnt signaling between human and rat cells. These differences could include the expression of Wnt-related genes\u003csup\u003e\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e, and the inherent variability in Wnt dynamics across different cell types\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur recent work has revealed that ADHD NSCs have higher levels of Wnt activity compared to those without the condition\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. This was primarily observed through expression analysis of the same proteins investigated in our current study, and was further confirmed using Wnt reporter assays\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Here, the levels of active β-catenin showed a tendency to increase following the continuous administration of MPH at a concentration of 10 nM in ADHD NSCs. However, this increase was not statistically significant. Given the absence of statistical significance, it is important to take these data cautiously and seek more clarity on the implicated mechanisms. Nevertheless, these preliminary results might represent a starting point for deeper investigation into the enhancement of Wnt activity by chronic MPH treatment at lower doses. If confirmed, this evidence would be in agreement with \u003cem\u003ein vivo\u003c/em\u003e findings, which have previously shown that a 28-day MPH treatment at lower doses (1 mg/kg) increased β-catenin levels in mice, concomitantly leading to higher proliferation of hippocampal cells\u003csup\u003e\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u003c/sup\u003e. However, a 10-fold higher dose led to reduced expression levels of the same protein during the same period of time and favored neuronal differentiation\u003csup\u003e\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFunctional experiments revealed that only ADHD NSCs showed elevated Wnt activity following an acute treatment with a low dose of MPH (10 nM). In ADHD cells, a non-significant increase in active β-catenin levels following the administration of 10 nM of MPH and a minor reduction at 100 nM throughout 7 days were observed in this study. This might suggest that MPH-related benefits might persist over long-term treatment, even though more studies are required to confirm it. Indeed, 10 nM falls within the physiological range observed in humans after 2 hours of administration, which corresponds to the pharmacodynamic point when MPH reaches its peak concentration in blood plasma\u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e. Given β-catenin's capacity to stimulate cell division of human NSCs\u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e, it is plausible that the heightened Wnt activity following treatment with MPH 10 nM plays a crucial role in slightly augmenting proliferation of ADHD NSCs. Consequently, this discovery might hold potential clinical significance.\u003c/p\u003e \u003cp\u003eDKK1-induced Wnt inhibition prior to MPH treatment in ADHD NSCs resulted in the loss of detectable MPH effects, indicating that MPH-induced increases in proliferation of ADHD NSCs are dependent on the Wnt signaling pathway. However, additional research is necessary to accurately ascertain the specific mechanism by which MPH affects the Wnt cascade, due to the intricate intracellular interactions between Wnt and other proliferation-regulating pathways, such as Notch, fibroblast growth factors (FGF), and brain-derived neurotrophic factors (BDNF)\u003csup\u003e\u003cspan additionalcitationids=\"CR79\" citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn summary, based on the observation that increased levels of active β-catenin tended to correlate with diminished proliferation of NSCs as measured by xCELLigence, we hypothesized that the elevated basal Wnt activity observed in ADHD NSCs in our recently published study\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e may serve as a compensatory mechanism to enhance their growth rates. However, this is likely due to the interplay between the Wnt pathway and other signaling pathways. Thus, compensatory efforts might potentially be improved by administering a chronic dose of MPH at 10 nM, since this treatment results in a small increase in the proliferation of NSCs in ADHD patients.\u003c/p\u003e \u003cp\u003eWe acknowledge that some of the techniques presented in this paper might have limitations. For instance, Western Blot experiments might be a large source of variability. For being a qualitative assessment of protein expression, normalization and subsequent reproducibility might be challenging in Western Blots, unlike more sensitive methods such as automated assays or ELISA. Moreover, this methodology only depicts the exact frame of protein extraction after chronic treatment with MPH and not the functionality of Wnt signaling, even though we investigated three different proteins at distinct points of the cascade.\u003c/p\u003e \u003cp\u003eAdditionally, the relatively short period of MPH treatment in proliferation experiments may explain the absence of complete recovery in growth rates of ADHD NSCs by MPH. Although this context may not accurately reflect the treatment received by patients, it does indicate the ideal duration for an \u003cem\u003ein vitro\u003c/em\u003e treatment to yield more dependable outcomes.\u003c/p\u003e \u003cp\u003eThe sample size can significantly influence the observed results in this research and account for the presence of merely tendencies in certain experiments\u003csup\u003e\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e,\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e\u003c/sup\u003e. While the generation of iPSC lines is a cost- and time-consuming process, increasing the sample size of both patients and controls would be optimal to determine whether these trends grow more pronounced and statistically significant. Moreover, doing an in-depth investigation into the effects of MPH is crucial for gaining a more precise understanding of the specific mechanisms of this drug. This research is currently underway in our laboratory. This work presents the Wnt pathway as a novel target of MPH and links it to the proliferative phenotype in ADHD using patient-specific cell lines. Although the results are tentative, it is the first publication to do so.\u003c/p\u003e \u003cp\u003eNevertheless, our findings open doors to further studies aiming to investigate novel MPH targets, the involvement of Wnt and other pathways in ADHD, and ADHD-related phenotypes. Since the Wnt signaling modulates not only cell proliferation but also maturation and differentiation processes, future research in the field of ADHD disease modeling should focus on examining potential differences in neuronal or glial differentiation and functionality between individuals with and without ADHD. This will help in gaining a more comprehensive understanding of the precise role played by the canonical Wnt signaling pathway in these circumstances.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConflict of Interest\u003c/h2\u003e\n\u003cp\u003eSome of the authors would like to declare potential conflicts of interest. E.G. received research grant support from MEDICE Arzneimittel P\u0026uuml;tter GmbH \u0026amp; Co. KG. S.W. has received royalties in the last 5 years from Thieme, Hogrefe, Kohlhammer, Springer, Beltz. In 2023, she received honorary speakers from Takeda. Her work was supported in the last years by the Swiss National Science Foundation (SNF), diff. EU FP7s, HSM Hochspezialisierte Medizin of the Kanton Zurich, Switzerland, Bfarm Germany, ZInEP, Hartmann M\u0026uuml;ller Stiftung, Olga Mayenfisch, Gertrud Thalmann, Vontobel, Unicentia, Erika Schwarz, Heuberg Fonds, National Government of Health (BAG), Gesundheitsf\u0026ouml;rderung Schweiz and Horizon Europe. Outside professional activities and interests are declared under the link of the University of Zurich \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.uzh.ch/prof/ssl-dir/interessenbindungen/client/web/\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\n\u003ch2\u003eAuthor contributions\u003c/h2\u003e\n\u003cp\u003eC.M.Y.O. performed experiments, conducted data analysis and drafted the manuscript. N.W. reviewed the manuscript. A.B. and M.R. performed experiments, conducted data analysis and reviewed the manuscript. L.S. conducted PRS calculations, supported data analysis and reviewed the manuscript. S.W. conceptualized the project and reviewed the manuscript. E.G. conceptualized the project, assisted in results interpretation and reviewed the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgments\u003c/h2\u003e\n\u003cp\u003eWe would like to thank the individuals recruited in this study, as well as their families, for their valuable participation. Moreover, we acknowledge MEDICE Arzneimittel P\u0026uuml;tter GmbH \u0026amp; Co. KG, the Waterloo Foundation for funding part of this project (reference number 2462/4548), Ms. Kristin Koppelmaa for her technical support during xCELLigence and WST-1 experiments, Dr. Per Hoffmann and Dr. Stefan Herms for genotyping iPSCs during QC stages, Prof. Ditte Demontis for providing the newest ADHD GWAS summary statistics, Prof. Dr. Thalia C. Eley and Prof. Dr. Gerome Breen for providing the ANX GWAS summary statistics, and Dr. Anna Maria Werling and Dr. Christian D\u0026ouml;ring for recruiting patients and controls to this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNakao T, Radua J, Rubia K, Mataix-Cols D. Gray matter volume abnormalities in ADHD: voxel-based meta-analysis exploring the effects of age and stimulant medication. Am J Psychiatry 2011; 168: 1154\u0026ndash;1163.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoogman M, Bralten J, Hibar DP, Mennes M, Zwiers MP, Schweren LSJ \u003cem\u003eet al.\u003c/em\u003e Subcortical brain volume differences in participants with attention deficit hyperactivity disorder in children and adults: a cross-sectional mega-analysis. The lancet. 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Stem Cell Res 2021; 56: 102512.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"ADHD, Alzheimer’s disease, Anxiety, Autism spectrum disorder, β-catenin, Bipolar disorder, GSK3β, iPSC, LRP6, Major depressive disorder, Methylphenidate, Neural stem cells, Obsessive-compulsive disorder, Polygenic risk score, proliferation, protein expression, real time impedance cell analysis, reporter assays, RTCA, Wnt signaling, WST-1, xCELLigence","lastPublishedDoi":"10.21203/rs.3.rs-3956813/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3956813/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAs the most common neurodevelopmental and mental disorders around the world, attention-deficit/hyperactivity disorder (ADHD) affects mostly children and adolescents. Both genetic (polygenicity) and environmental variables interplay in the etiology of this disorder. The Wnt signaling pathway, which regulates proliferation and differentiation during neurodevelopment, has been implicated in ADHD. Clinically, ADHD individuals may exhibit delays in structural and functional brain development. Available evidence has proposed that methylphenidate (MPH) treatment can potentially improve these delays. However, the molecular and cellular mechanisms underlying ADHD and the therapeutic targets of MPH are still not completely elucidated. In a pilot investigation, the proliferation of neural stem cells (NSCs) derived from induced pluripotent stem cells (iPSCs) was significantly lowered in ADHD male patients. Yet, we did not observe any variations in growth rates during the iPSC stage. To extend the earlier results, we increased the sample size to include females and explored if MPH may improve NSC proliferation in ADHD and clarified the role of the Wnt pathway. To do so, iPSC and NSC proliferation of five ADHD patients and five controls was assessed. The results corroborated our previous findings on decreased proliferation in ADHD NSCs. Conversely, ADHD NSC proliferation slightly increased following MPH treatment at 10 nM, which also showed modulatory effects in the Wnt signaling in this group. Interestingly, no increases in proliferation were seen when DKK1 blocked Wnt signaling before MPH treatment. These findings suggest MPH regulates the canonical Wnt pathway and may partially explain ADHD neurodevelopmental abnormalities and MPH-specific benefits.\u003c/p\u003e","manuscriptTitle":"Alterations in proliferation of neuronal stem cells in Attention-Deficit/Hyperactivity Disorder and Wnt modulation by methylphenidate","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-14 10:57:37","doi":"10.21203/rs.3.rs-3956813/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dd7c26ef-9855-46dc-b69d-798af09b0377","owner":[],"postedDate":"February 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":44234654,"name":"Biological sciences/Neuroscience"},{"id":44234655,"name":"Biological sciences/Stem cells"},{"id":44234656,"name":"Biological sciences/Cell biology"},{"id":44234657,"name":"Biological sciences/Genetics"},{"id":44234658,"name":"Biological sciences/Molecular biology"}],"tags":[],"updatedAt":"2025-07-29T14:05:22+00:00","versionOfRecord":{"articleIdentity":"rs-3956813","link":"https://doi.org/10.1007/s00702-025-02988-y","journal":{"identity":"journal-of-neural-transmission","isVorOnly":true,"title":"Journal of Neural Transmission"},"publishedOn":"2025-07-28 00:00:00","publishedOnDateReadable":"July 28th, 2025"},"versionCreatedAt":"2025-02-14 10:57:37","video":"","vorDoi":"10.1007/s00702-025-02988-y","vorDoiUrl":"https://doi.org/10.1007/s00702-025-02988-y","workflowStages":[]},"version":"v1","identity":"rs-3956813","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3956813","identity":"rs-3956813","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}