P = 2.24 × 10−4, Pcorrected = 1.79 × 10−3) and U  were significantly associated with reduced risk of ADHD. In contrast, haplogroup HHV*  was significantly associated with increased risk of ADHD. Our results provide novel insight into the genetic basis of ADHD, implicating mitochondrial mechanisms in the pathophysiology of this relatively common psychiatric disorder.Although mitochondrial dysfunction has been implicated in the pathophysiology of attention deficit and hyperactivity disorder ADHD, the role of mitochondrial DNA (mtDNA) has not been extensively investigated. To determine whether mtDNA haplogroups influence risk of ADHD, we performed a case-control study comprising 2076 ADHD cases and 5078 healthy controls, all of whom were European decedents recruited from The Children’s Hospital of Philadelphia (CHOP). Associations between eight major European mtDNA Haplogroups and ADHD risk were assessed in three independent European cohorts. Meta-analysis of the three studies indicated that mtDNA haplogroups K (odds ratio = 0.69,  Genetic advances in ADHD revealed a polygenic genetic architecture with multiple common and rare genetic factors involved1. Recent genome-wide association studies (GWAS) have identified common variants at 12 loci that are significantly associated ADHD risk through analyzing 20,183 ADHD cases and 35,191 controls2. Rare copy number variations (CNVs) and single-nucleotide variants (SNVs) have also been reported in multiple ADHD studies9. However, most genetic studies of ADHD focused on nuclear DNA (nDNA), and detected susceptibility genes of ADHD so far only account for a small fraction of the genetic contribution to the disease. Mitochondrial DNA (mtDNA) therefore emerges as an appealing candidate for the heritability of ADHD.Attention-deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in children and adolescents, characterized by symptoms of hyperactivity, impulsivity, and inattention. It has been recognized as a highly heritable disorder with a twin-estimated heritability around 80%10. Human mitochondria possess a small circular genome, which sequentially accumulates genetic variants via maternal inheritance. Hence, human mitochondria genomes are classified into several mtDNA haplogroups according to accumulated mtDNA variants during ancient migrations of human populations11. Previous studies indicate that mtDNA haplogroups display diverse metabolic capacities, and play an important role in multiple diseases and traits, such as cancers, neurodegenerative diseases, and longevity16. Recently, cumulative evidence suggested that mitochondrial dysfunction might also lead to a disruption of normal neuronal plasticity and promote the development of psychiatric disorders17, implying a potential impact of mtDNA haplogroups in the risk of neuropsychiatric disorders, such as ADHD. However, to the best of our knowledge, the association between mtDNA haplogroups and ADHD has been only evaluated in a small Korean population of 150 cases and 322 controls18. Thus, the genetic relationship between mtDNA haplogroups and ADHD has not yet been studied in European populations.Mitochondria are best known for their pivotal role in energy production but are also involved in other cellular processes, such as amino-acid, lipid and steroid metabolism, and regulation of apoptosisIn this study, we investigated the mtDNA haplogroup distribution in three independent European cohorts of patients with ADHD and compared them with healthy control individuals, aiming to identify potential mtDNA haplogroups conferring risk to ADHD in European populations.This case-control study included three independent ADHD cohorts. Blood-derived DNA from participants from the three cohorts were genotyped at the Center for Applied Genomics (CAG), at The Children’s Hospital of Philadelphia (CHOP), using the Illumina HumanHap550 , HumanHap610 , and Infinium Global Screening (GSA) SNP arrays , respectively.19. Controls for the HH550 cohort were recruited by CAG through the CHOP Health Care Network including four primary care clinics and several group practices and outpatient practices that performed well-child visits. Healthy children aged 6–18 years old, with no serious underlying medical disorder, including but not limited to neurodevelopmental disorders, cancer, chromosomal abnormalities, and known metabolic or genetic disorders were included19.Cases genotyped of the HH550 chip were recruited from the pediatric and behavioral health clinics at CHOP, capturing the greater Philadelphia area and included children (age 6–18 y/o) diagnosed with ADHD following the K-SADS  interview. Exclusion criteria were prematurity (<36 weeks), intellectual disability, major medical and neurological disorders, pervasive developmental disorder, psychoses, and major mood disorders as described previouslyN = 50) and controls (N = 50), and yielded positive predictive values (PPVs) >96% for both cases and controls. All three groups were analyzed separately with their array and age/sex, race matched controls, and then meta-analyzed for the study as described in the results section.Individuals genotyped on the HH610 and GSA arrays were selected from the biorepository at the CAG, which collected over 100,000 unique samples recruited from CHOP from subjects linked to their electronic health records (EHRs). Cases and controls were selected based on diagnostic and medication information from EHRs. Inclusion criteria for ADHD cases included (1) ages above four years old; (2) two or more diagnosis of ICD9 codes for ADHD (314.1–314.9) in two separate in-person visits and more than two prescriptions of ADHD-related medications; or (3) three or more ICD9 codes for ADHD on separate calendar days. Exclusion criteria for ADHD cases were conditions related to brain anomalies or tumors, mental retardation, or psychiatric disorders. Controls were determined based on the following criteria (1) ages above four years old; (2) no diagnosis of ICD9 codes for ADHD or other psychiatric, neurological and related disorders; (3) no mention of the terms “ADHD”, “attention deficit”, “hyperkinesia”, “hyperkinesis”, “hyperkinetic”, or “hyperactivity”; (4) no ADHD related medication. The ADHD case and control selection method was further validated by manual chart review of 100 randomly selected cases .20. Given ambiguities in precise haplogroup assignment, evolutionary related haplogroups B, F, H, HV, P, R, and V were classified as the super-haplogroup HHV*; haplogroups O and X were classified as the super-haplogroup OX. The accuracy, sensitivity, and specificity of mtDNA haplogroup assignment were verified using the three sets of SNVs in 11240 mitochondrial reference genomes with known haplogroups, downloaded from GenBank. Eight haplogroups common in European populations, including HHV*, I, J, K, OX, T, U, and W, were analyzed in this study . The mtDNA haplogroup of each participant was determined by HaploGrep 221. Participants with European ancestry were selected by comparing with four reference European populations from 1000 Genome, including Utah Residents with Northern and Western European ancestry (CEU), Toscani in Italia (TSI), British in England and Scotland (GBR), and Iberian Population in Spain (IBS). PCA plots of the population structures are provided in Supplementary Fig. 22. Fixed effects P values were reported. Bonferroni correction was used for correction of multiple testing. A corrected P < 0.05 was considered statistically significant. The kinship between pairs of subjects was detected by identity by descent (IBD) analysis, and one of the related individuals with proportional IBD > 0.25 were excluded.The association between each haplogroup and ADHD risk was tested in R (version 3.5.1) using logistic regression analyses. Gender and the first ten principal components were included as covariates. Principal component analysis (PCA) was performed using EIGENSTRAT to infer genetic ancestry of samples and detect population substructures24. Association analyses indicated that haplogroup K was significantly less represented in patients with ADHD than healthy controls  production and energy generation32. It has also been reported to increase the risk of Alzheimer’s disease and lower the age onset of Huntington disease presentation32.Our study also revealed that the HHV* haplogroup, the most dominant haplogroup in European populations, is associated with increased risk of ADHD. In contrast to haplogroup K and U, haplogroup H was associated with higher ATP levels and oxidative phosphorylation OXPHOS capacitiesThis study has two limitations. First, the mtDNA haplogroups were deduced from genotyping arrays. It remains unclear which precise genetic variants are causal in ADHD. This limitation can be solved in future studies by sequencing the whole mtDNA genome in a large collection of ADHD cases and controls. Second, the three study cohorts were genotyped at the same location, and it is possible that unknown potential confounding factors might have influenced the results. Third, the results could be confounded by maternal ancestry, since human mtDNA is maternally inherited. However, this effect is not likely to be significant as it is much smaller for the homogeneous European population than for admixed populations.This study demonstrates that mtDNA haplogroups K and U confer protective effects against ADHD, while mtDNA haplogroup HHV* is associated with increased risk of ADHD, providing new insights into the genetic basis of ADHD. A better understanding of the role of mitochondria in the pathogenesis of ADHD might lead to new methods for the prevention and treatment of this common disease.Supplementary files


We considered three groups of young adult participants: ADHD patients without medication (ADHD), ADHD with medication (MADHD), and age/education-matched controls. Working memory training consisted of a daily practice of 20 blocks of Dual n-back task (approximately 30 min per day) for 20 days within one month. Participants of each group were randomly assigned into two subgroups, the first one with an adaptive mode of difficulty (adaptive training), while the second was blocked at the level 1 during the whole training phase . Alerting and orienting effects were not modified by working memory training. The dimensional analysis showed that after baseline training, the lesser the severity of the hyperactive-impulsive symptoms, the larger the improvement of reaction times on trials with high executive control/conflict demand , irrespective of the participants’ group. In the categorical analysis, we observed the improvement in such Conflict Effect after the adaptive training in adult ADHD patients irrespective of their medication, but not in controls. The ex-Gaussian analysis of RT and RT variability showed that the improvement in the Conflict Effect correlated with a decrease in the proportion of extreme slow responses. The Dual n-back task in the adaptive mode offers as a promising candidate for a cognitive remediation of adult ADHD patients without pharmaceutical medication.Patients affected by Attention-Deficit/Hyperactivity Disorder (ADHD) are characterized by impaired executive functioning and/or attention deficits. Our study aim is to determine whether the outcomes measured by the Attention Network Task (ANT), i.e., the reaction times (RTs) to specific target and cue conditions and alerting, orienting, and conflict (or executive control) effects are affected by cognitive training with a Dual  Attention-Deficit/Hyperactivity Disorder (ADHD) is a behavioral condition caused by a complex interplay between genetic and environmental risk factors affecting brain networks and leading to a broad range of impairments that interfere with functioning and development ,2,3,4,5.mu, sigma, and tau) derived from the ex-Gaussian distributional model of RTs [The Attention Network Task (ANT)  is a coml of RTs ,30,31,32l of RTs  concludemu did not document a significant slowing in adult ADHD and a significant correlation was reported between tau and the number of omission errors in a Go/NoGo task bringing evidence for attentional dysfunction [n-back task (NBT) were found to be a good predictor on math achievement [In contrast to increased mean RT, the distributional parameter function . Howeverfunction ,36. In cievement .N trials previously [n-back task (DNBT) is a version of the task eliciting divided attention because dual, one auditory and one visual, unrelated stimuli appear simultaneously and subjects are asked to monitor both stimuli independently [The NBT is a popular experimental paradigm for WM training , in whiceviously ,40. The endently . DNBT reendently ,43. The endently ,45 to teendently ,47 on a We recruited 114  young adults between 18 and 30 years old in the three groups of study, ADHD medicated with methylphenidate hydrochloride prescription  or to the ‘ADHD group without medication’ (ADHD) was decided by the psychiatrist in charge of the patients, on the exclusive basis of the patients’ therapeutic treatment. This assignment was ‘double-blind’, in the sense that the experimenters did not know which patient belonged to either ADHD group until the end of the protocol and the psychiatrist did not know which level of working memory training is assigned to a patient. Participants of the ADHD group with medication were required to stop medication 24 h prior to testing ,52,53. Abefore-training session of the ANT in the experimental laboratory . The second part was a WM training period lasting one month with the Dual n-back task at home. The third part was an after-training session of the ANT at the same laboratory as the pre-test.The experimental procedure of this study included 3 parts. The first part was a No Cue (NC), Center Cue , Double Cue , and Spatial Cue . The participants maintained their gaze on the black fixation cross during 400 ms, after the disappearance of the cue. Then, the participants were requested to identify a target  and determine its direction (left or right) as quickly as possible by pressing the corresponding button (left or right) of a computer mouse. The time taken to respond was recorded as reaction time (RT). Finally, the participants maintained their gaze on the black fixation cross during the remaining time till the end of the trial.This task was originally reproduced from the original ANT . Each trCongruent (CON), Incongruent , or Neutral . Errors  and no responses  were also recorded for each participant i, in order to calculate the accuracy rate. For each participant i we computed the accuracy rateNo Cue, Center Cue, Double Cue, Spatial Cue_below, Spatial Cue_above) × 3 target types  × 2 directions  defined 30 primary patterns of trials. After 1 practice block with 24 trials pseudorandomly selected , the participants performed 3 experimental blocks, each one including 96 trials, that means 288 trials overall for each session and for each participant. For data analysis, all trials with Spatial Cue_below and Spatial Cue_above were pooled together and all trials with targets oriented to the left or to right side were pooled together. Hence, the task included 12 final patterns, i.e.,  4 cue types  × 3 target types .The target arrow  was surrounded by flankers on both sides by 2 items, such that the target was located at the center of a line of 5 items. . FlankerAlerting Effect (AE) Orienting Effect (OE) Conflict Effect (CE) Alerting Effect and Orienting Effect scores, the more efficient the networks are. For Conflict Effect, the lower the score, the more efficient its network. Notice that the median RT for each one of the 12 final patterns is hereafter referred simply as the RT.The effectiveness of the attention networks can be estimated from the RTs measured for the cue and target conditions . The disn-back. Then, if participants were required to detect a match with the previous trial, the mode is referred to as 1-back, called also the baseline training. In the adaptive training, the difficulty n of the task was adjusted as a function of the performance. The whole task consisted of 20 blocks of 20 + n trials with the same level of difficulty. An increase by 1 in the level of difficulty in the next block was triggered by a performance of less than 3 mistakes in each modality. With levels of difficulty higher than 1, a decrease by 1 in the level was triggered by 5 or more errors accumulated in any modality. In other cases, the level remained unchanged. The total duration of the working memory task was approximately half an hour.The task consisted of two variants of the DNBT described in detail elsewhere ,21,41. Tbefore-training session, all participants performed one session of adaptive DNBT. Participants of each group were randomly assigned to either baseline or adaptive training mode for the one-month WM training period at home. It is very important to note that the random assignment to either group of training level was done in ‘blind’ mode to the experimenter, who knew only about the recruitment of controls vs. patients. This fact is very important for the comparison of MADHD and ADHD groups. This mode of assignment explains why the structure of ADHD and MADHD groups is not balanced with respect to the diagnosed subtype of ADHD , between sessions , and between WM training modes . We assume the null hypothesis of homoscedasticity in the data samples and test it with the studentized Breusch–Pagan test. The standard ANOVA can be used for factorial analysis if the value of the test statistics is not significant and partial omega squared  were computed with the mexgauss function package retimes [In case homoscedasticity is rejected, we apply robust versions of ANOVA, i.e., heteroscedastic one-way ANOVA for medians and two- and three-way ANOVAs with trimmed means at level 0.2 and effect size assessed by  retimes . In genescores function of the package outliers of the R statistical software throughout the study. The first step was aimed at excluding from the analysis the participants characterized by an outlying performance either before or after the WM training. For each participant i we computed the accuracy ratescores function with robust estimation of the differences between each value and median, divided by median absolute deviation (“mad”). According to the size of our samples the Z score of the outliers was bounded by the value We applied an unsupervised procedure aimed at excluding participants characterized by an outlier performance. In order to do so, we conducted a two steps procedure and we applied the  (n−1)/n . The outscores function based on the median absolute deviation. On average we observed 18.7/288, 17.6/288, and 17.8/288 outlier trials for each participant belonging to controls, MADHD and ADHD, respectively. After removal of all outlier trials for all participants, the median RT was computed for each primary trial pattern. Then, within each group and for each such primary trial pattern, the participant outliers were detected after applying the logarithmic transformation to the series of median RTs. Any participant with more than 1 outlier median RT in the group series of any primary trial pattern was checked out as an outlier participant. The outcome of this second procedure was the removal of additional 4 participants . At the end of both procedures for removal of outlier participants, the overall sample of the remaining 104 participants included 27,719 trials before training and 27,460 trials after training. The accuracy rates of all participants, irrespective of their groups and subgroups, were above 95%  did not complete the CAARS questionnaire. For the DSM-IV Inattentive Symptoms Subscale , the ADHD index of the patients diagnosed with a combined ADHD subtype , we controls , shows abaseline training (red lines) tended to be characterized by the same slopes. The intercepts after the baseline training were smaller, thus suggesting the training produced an increased speed in the reaction time, which was the same for light or severe values of the symptoms, measured by adaptive training tended to show lines becoming flat, thus suggesting a decrease in the reaction time, which tended to be independent of the severity of the symptoms. The only exception is illustrated by the correlations with the DSM-IV Hyperactive-Impulsive Symptoms Subscale, The dimensional analysis assumes that a measured variable depends on the severity  of the symptoms rated on a continuous scale. In the current study, this assumption was that the reaction times should be tested against the four scores derived from the analysis of the CAARS questionnaire  RTs of ADHD-C were shorter than the RTs of ADHD-I  and combined (ADHD-C) subtypes . For thiTarget × Cue) before and after training with baseline and adaptive levels. At first, we analyze the effect of factors group × session × level irrespective of any task patterns pooled together. The outcome of this robust ANOVA is a significant main effect of factor group . In both training modes we found a significant main effect for factor group  and a significant main effect for factor session .baseline training: −16.0, −18.6 ± 2.4 ms and adaptive training: −16.0, −20.4 ± 3.0 ms and session in each training protocol showed a similar result, but to a lesser degree of significance  the shorter the RT, the more neutral the target the shorter the RT  and with a stronger effect after adaptive training in medicated ADHD (baseline training).Non-medicated ADHD patients showed a significant difference in RTs after No Cue’), RTs were longer and in the presence of unambiguous comprehensive information , RTs were shorter. For sake of simplicity, we focus further analyses on these extreme cue conditions and skip the data obtained for ‘Center Cue’ and ‘Double Cue’  and of session . In addition, we observed significant two-way interactions group × training . This interaction effect was due to ADHD , which is the only group characterized by a very strong lack of significance of baseline training on RTs in No Cue . On the contrary, in the ADHD without medication only the adaptive level of training provoked a very large and significant effect .For each group of participants, we have eventually analyzed the effect of the training level during WMT with any significant regression and correlation between the variation of the ex-Gaussian parameters No Cue and Incongruent target conditions and the RTs were shorter after Spatial Cue and Congruent target conditions, in agreement with the well-established literature [The overall pattern of RTs to the combination of cues and targets in the Attention Network Test observed in this study showed that for any group of participants the RTs were longer after terature ,70,71,72terature ,78,79,80terature ,83,84,85It is worth noting some characteristics in the composition of our patients’ samples. Our final sample of medicated ADHD . In the literature, a study suggested that an ADHD subtype reporting effective fluctuations was characterized by slowed RTs to ANT [The MADHD group was characterized by the prevalence of ADHD-C/ADHD-I (28/10) compared to ADHD (16/12), and it is worth noting that our MADHD group was characterized by average values higher than ADHD for ASRS d ADHD-C ,95,96. Ws to ANT , somehows to ANT . Hence, s to ANT . We testbaseline or an adaptive level of training in WMT resulted in an even representation of ADHD subtypes in the baseline and adaptive subgroups. The same reasoning might hold for the dimensional analysis. However, we observed only a couple of differences between some CAARS scores of the subgroups assigned to baseline and adaptive prior to WMT. In the non-medicated ADHD group there was a difference very close to threshold  ,36,97,99orbities .baseline or adaptive mode in the Dual n-back task. In the case of non-medicated ADHD, the significant effect of WMT was observed only if the training was done in the most cognitive demanding version of the task, that is the adaptive Dual n-back task. The effect of WMT on RTs was already reported for healthy adults [Alerting Effect and Orienting Effect for all participant groups. The literature reports that Alerting Effect is improved by the stimulant medication in patients diagnosed as ADHD-C subtype, but not in ADHD-I subtype [Alerting Effect in ADHD-C vs. ADHD-I subgroups, but this difference was statistically significant only in MADHD. However, there was no significant difference between the two patients’ groups neither before nor after training. Differences between medicated and non-medicated ADHD patients in the Alerting Effect might depend on the kind of medication. In the case of dextroamphetamine, extracellular norepinephrine is much more increased than after dopamine [Alerting Effect reported elsewhere [For controls and MADHD, the outcome of the WMT during one month was significant shorter RTs to ANT with either y adults , but our subtype . In bothdopamine ,103. Dexdopamine . In our dopamine ,106,107 dopamine . Therefolsewhere .baseline mode of the Dual n-back task corresponds to the 1-back, i.e., when participants were required to detect a match with the immediately previous trial. This means that the baseline mode is characterized by a rather moderate attentional and cognitive load. Then, it is interesting to notice that WMT produced a little improvement, if any, in the conflict (or executive control) network of the ADHD group without medication. The outcome of the ex-Gaussian analysis was in the same direction, with a much stronger correlation of Conflict Effect after adaptive  subscales, with the notable exception of the ADHD group without medication after moxetine ,138 poin[BRIEF−A ,140. We n-back task training in the adaptive mode produced a significant improvement in such Conflict Effect of adult ADHD patients irrespective of their medication. The baseline mode was insufficient to produce measurable effects in the non-medicated ADHD patients, which may explain previous contradictory reports in the literature with respect to the usefulness of working memory training. Hence, the Dual n-back task in the adaptive mode offers as a promising candidate for a cognitive remediation of adult ADHD patients without pharmaceutical medication.The Attentional Network Task allows testing the plasticity of brain circuits in ADHD patients in a notable way. The present study demonstrates that working memory training for one month using the Dual


Effective treatments for various conditions such as obesity, cardiac heart diseases, or low back pain require not only personal on-site coaching sessions by health care experts but also a significant amount of home exercises. However, nonadherence to home exercises is still a serious problem as it leads to increased costs due to prolonged treatments.To improve adherence to home exercises, we propose, implement, and assess the novel coaching concept of hybrid ubiquitous coaching (HUC). In HUC, health care experts are complemented by a conversational agent (CA) that delivers psychoeducation and personalized motivational messages via a smartphone, as well as real-time exercise support, monitoring, and feedback in a hands-free augmented reality environment.We applied HUC to the field of physiotherapy and conducted 4 design-and-evaluate loops with an interdisciplinary team to assess how HUC is perceived by patients and physiotherapists and whether HUC leads to treatment adherence. A first version of HUC was evaluated by 35 physiotherapy patients in a lab setting to identify patients’ perceptions of HUC. In addition, 11 physiotherapists were interviewed about HUC and assessed whether the CA could help them build up a working alliance with their patients. A second version was then tested by 15 patients in a within-subject experiment to identify the ability of HUC to address adherence and to build a working alliance between the patient and the CA. Finally, a 4-week n-of-1 trial was conducted with 1 patient to show one experience with HUC in depth and thereby potentially reveal real-world benefits and challenges.Patients perceived HUC to be useful, easy to use, and enjoyable, preferred it to state-of-the-art approaches, and expressed their intentions to use it. Moreover, patients built a working alliance with the CA. Physiotherapists saw a relative advantage of HUC compared to current approaches but initially did not see the potential in terms of a working alliance, which changed after seeing the results of HUC in the field. Qualitative feedback from patients indicated that they enjoyed doing the exercise with an augmented reality–based CA and understood better how to do the exercise correctly with HUC. Moreover, physiotherapists highlighted that HUC would be helpful to use in the therapy process. The longitudinal field study resulted in an adherence rate of 92%  and a substantial increase in exercise accuracy during the 4 weeks.The overall positive assessments from both patients and health care experts suggest that HUC is a promising tool to be applied in various disorders with a relevant set of home exercises. Future research, however, must implement a variety of exercises and test HUC with patients suffering from different disorders. Musculoskeletal disorders (MSDs), such as rheumatoid arthritis, osteoarthritis, low back pain, neck pain, or gout, negatively impact the locomotor system and are influenced by various risk factors, such as a sedentary lifestyle, malnutrition, or obesity . IndividPhysiotherapy is an effective intervention for MSDs -10. HoweMoreover, adherence support is often limited to on-site physiotherapy sessions, leaving patients alone at home with standardized exercise instructions, which results in low adherence rates -36. TherTo this end, we propose hybrid ubiquitous coaching (HUC) to improve home exercise adherence for treatments that require not only personal on-site coaching sessions by health care experts but also a significant amount of home exercises. HUC relies primarily on a conversational agent (CA) that delivers relevant health literacy information about the importance and benefits of home exercises and personalized motivational exercise reminders via a smartphone. Moreover, the CA of HUC delivers real-time exercise support, monitoring, and feedback in a hands-free augmented reality (AR) environment. In HUC, health care experts introduce the CA as their trusted personal assistant that lives not only in the patient’s pocket/smartphone in the form of a text-based physiotherapy chatbot ,49,67, bHUC combines for the very first time (to the authors’ best knowledge) research on CAs, human-supported digital interventions, health psychology, and mobile and wearable technology–supported physical exercises. First, HUC employs a CA because they are able to build a working alliance with patients ,57,68, wBecause this research is unprecedented, the following research questions (RQs) were formulated to guide the design, implementation, and evaluation of HUC: (RQ1) How is HUC perceived by (a) patients and (b) health care experts?; and (RQ2) Does HUC lead to treatment adherence to home exercises?To answer these questions, we applied HUC exemplarily to the field of physiotherapy. During the last 3 years, 4 design-and-evaluate loops were conducted: two studies were carried out in the lab with 50 physiotherapy patients, 11 physiotherapists were interviewed, and finally, empirical data from 1 patient during a 4-week longitudinal field study were collected and assessed to reveal real-world benefits and challenges related to HUC.To address the challenge of nonadherence to home exercises in physiotherapy, we started the interdisciplinary development of HUC in collaboration with 2 physiotherapists. In a first step, a storybook was developed . In a seA conceptual overview of HUC is illustrated in First, a physiotherapist performs a physical assessment of the patient and, depending on the results, defines a tailored home exercise program. Next, the physiotherapist works together with the patient on the exercises from the program by focusing on the TADs . Then, tThe smartphone- and AR-based CAs allow for remote everyday coaching. The combination of the two CAs together results in a richer communication channel that enables more accurate and personalized information to be transmitted to the patient ,77. The HUC grants physiotherapists access to patients’ data about the TADs via a web-based dashboard. Based on that data, physiotherapists can tailor and optimize planned on-site and remote coaching sessions more efficiently. For example, if squats are performed incorrectly and the real-time feedback from the AR-based CA is not processed correctly by patients, pressure could be applied on the knees rather than on the muscles, which could cause knee injuries. If this happens, the physiotherapist would get an alert message from the CA to target the weakness directly in the next online or on-site coaching session.In the remainder of this paper, we describe 4 build-and-evaluate loops that we conducted to build and assess HUC according to our research questions. To address RQ1a and RQ2, we implemented a first version of HUC with a focus on the AR-based CA and tested it with 35 individuals with physiotherapy experience at a public fair in September 2018.HUC included an AR-based CA that appeared as a male cartoonlike superhero assistant of a human male physiotherapist and a female human-looking exercise model, demonstrating the exercise execution . A persoParticipants were recruited from a public fair using convenience sampling . They weParticipants who expressed an interest in HUC and provided their consent to participate in the study were invited to participate. HUC was then introduced, and usage of the AR glasses was demonstrated. Next, participants were asked to start the interaction with the AR-based CA and performed one exercise session. Afterward, participants were asked to fill out a feasibility questionnaire. Participants received no monetary compensation.HUC was assessed based on technology acceptance -85 and wTo address RQ1b and RQ2, we revised HUC based on the feedback from study 1 and assessed it with 11 physiotherapists between November 2018 and March 2019.HUC was revised as follows based on the qualitative results of study 1. The AR-based CA was scaled up to be human-sized and adapted in appearance to look like a physiotherapist . MoreovFinally, the HUC concept outlined in Physiotherapists treating patients with MSDs were recruited using chain sampling  until saFirst, we explained the HUC concept, the flowchart, and the sketches to each participating physiotherapist. Then, the physiotherapist performed the specific squat exercise session with the AR-based CA. Thereafter, a semistructured interview was conducted to gather feedback on the utility and feasibility of HUC. The interview was recorded and transcribed according to the rules of simple transcription . ThereafThe guiding questions of the semistructured interview are listed in To address RQ1a and RQ2, HUC was assessed by 15 patients seeking physiotherapy treatment in January and February 2019. To assess the relative advantage of HUC to commonly employed methods of exercise instruction, HUC was compared to paper-based and video-based exercise instruction.The revised HUC (version 2) as outlined in study 2 above was used for the assessment.Patients were recruited from a physiotherapy center of one of the collaborating physiotherapists. Inclusion criteria were age ≥18, participation in at least 3 physiotherapy sessions, no experience with the squat exercise, being in the physical condition to perform squat exercises, normal vision or wearing contact lenses, and normal hearing.A two-period crossover study design was used to assess the relative advantage of HUC compared to paper-based and video-based exercise instruction, two commonly used methods in physiotherapy. This study design also allowed us to account for learning effects . The stuThe exercise instructions were assessed with mental effort and frustration items from the task load index . MoreoveDue to the high burden nature of the study, with experimental technology that required support from the researchers, we conducted a 4-week n-of-1 trial to complement our findings from studies 1-3 and to answer RQ1a, RQ1b, and RQ2. The goal of this study was to complement the findings from the previous studies and to add external validity to the lab results by assessing the long-term adherence and feasibility of HUC in the everyday life of one patient. By assessing HUC with only one patient, this study was not designed to illustrate the breadth of possible use experiences but to show one experience in depth and thereby potentially reveal real-world benefits and challenges ,99.The objective of the third design loop was to adapt HUC for long-term use. For the field study assessment of HUC, there was no QR code provided, and no dedicated HUC was developed. Consistent with recent work ,100,101,First, depending on the patient’s familiarity with the AR-based app , tutorials became skippable, and explanations were shortened after the first week. Second, there was randomization of the coach’s speaking texts , animations , and interactions . Third, randomization of the coach’s texture  and the background music  changed. Lastly, the AR-based app showed the patient the number of sessions already completed as an early form of progress visualization, a well-established behavioral change technique (BCT 19) .A new physiotherapy patient who did not participate in one of the other studies was recruited from a physiotherapy center. The eligibility criteria were identical to those outlined in study 3. Additionally, 3 physiotherapists from the same center were recruited for a follow-up interview. One physiotherapist was the therapist treating the patient, the second therapist was involved in the evaluation in the course of the third study, and the third therapist was not involved in any of the previous studies.Before starting the study, the patient signed the informed consent. Then, at the beginning of the study, the patient received a study information sheet from the physiotherapist and agreed to practice a squat exercise 3 times per week. HUC was then demonstrated, and the patient received an introduction to the AR headset. Thereafter, the patient was coached by HUC in their everyday life as outlined in The results of the 4 studies are presented in the following sections. The depersonalized raw data and data analysis script are made available in Overall, 35  individuals with a mean age of 35 years (SD 11) and previous physiotherapy experience participated in the study. Most of them  had experience with the exercise. The results listed in The qualitative feedback on the positive aspects of HUC and suggestions for improvement are shown in the thematic maps . SuggestEleven physiotherapists with 3 to 30 years of experience  participated in the study. Five physiotherapists worked in a private practice, 4 in a hospital, and 2 in a rehabilitation clinic.The physiotherapists indicated in the interviews that patients could be better supported with the HUC and that physiotherapists would intend to use it for treatment sessions. The AR-based CA was perceived as an additional motivator due to its personal, interactive, and playful approach. The exercise guidance by the life-sized CA, including the real-time feedback , was also perceived as an improvement to the status quo. The smartphone-based CA was perceived as an advantage over current solutions, mainly due to its ability to remind patients to execute the exercise, but also by providing psychoeducational content that targets increasing patients’ health literacy. Physiotherapists were, however, skeptical of whether HUC could improve the quality of the treatment and adherence. The HUC was seen to have some potential to strengthen the working alliance between physiotherapists and their patients. Establishing therapeutic goals was seen as an advantage, since tracking enables patients to be continuously informed about the degree of goal achievement. The ability to instruct and provide feedback on the exercise technique was also identified as a factor that could potentially improve the shared understanding of treatment tasks. However, the majority of the physiotherapists expressed the belief that mutual trust, empathy, and, consequently, mutual goals and tasks were uniquely established during face-to-face encounters and that technological systems could not successfully act as assistants to foster a good working alliance. Lastly, physiotherapists suggested that continuously monitoring a patient could have a negative influence on mutual trust.This qualitative feedback is supported by the quantitative data from the online survey . The phyFifteen patients  with a mean age of 37 years (SD 9.93) participated in the study. Participants were generally very positive toward HUC, the video instruction, and, to some extent, the paper instructions . In totaThe qualitative feedback suggested that the three instruction methods provided different levels of richness of information. Eight patients described the paper exercises as boring and not enjoyable to follow. Even though patients found the paper instructions helpful to recall the exercise, they often had trouble interpreting the instructions correctly. Three patients found the video instructions authentic and found the exercise easy to understand. However, patients mentioned that they felt insecure about the correctness of exercise execution. Patients also found the exercises easier to understand while using HUC and appreciated the guidance, the reminder app, and the real-time feedback to understand when mistakes were made. Eight patients also perceived HUC as fun and enjoyable. Six patients particularly enjoyed performing the exercise together with a life-sized CA. One patient, however, found that the CA did not engage emotionally. A disadvantage of HUC perceived by 9 patients—thereby a frequently perceived disadvantage—was the bulkiness of the AR hardware used in this study.“looking a bit more human-like, not such a computer-figure”). Third, 2 patients suggested adding more detailed real-time feedback and reminders and elements of gamification . Overall, HUC was positively perceived.The patients suggested several improvements . First, Based on the behavioral data recorded by the HUC, a total of 3 exercise sessions per week were performed in 3 out of 4 weeks. This resulted in TAD rates of 92% in frequency, sets, and repetitions . During Overall, the patient described the experience with the HUC as very positive. The exercises guided by the AR-based CA were enjoyable and motivating. The patient liked the feeling of not being alone while performing the exercises and remarked that they preferred the HUC to a human personal trainer, as it was perceived as being “more relaxing.” Additionally, the patient pointed out usually having difficulties adhering to home exercises and consequently appreciating the variations of the WhatsApp-based motivational messages from the smartphone-based CA and feedback on the execution accuracy by the AR-based CA, both of which helped the patient with adherence. The patient expressed an interest in having a more dynamic intervention program that includes longer sessions and variations in the exercises. Finally, the patient wanted to continue working with the smartphone-based and AR-based CA beyond the period of this n-of-1 trial.Reflecting on the results of the study, all physiotherapists confirmed that HUC has the potential to improve adherence to home-based physiotherapy exercises. Referring to the progression of the exercise technique, the real-time feedback about the temporal and spatial accuracy was seen as a clear advantage. Two physiotherapists also liked the fact that the system ensured adherence to the prescribed number of sets and repetitions and described it as having a positive influence on patient motivation. As a treatment provider, the detailed monitoring information regarding the exercise technique was considered to be highly valuable. All physiotherapists highlighted that the therapy could be optimized and a patient’s problems could be addressed more individually during on-site therapy sessions. This could potentially also render the face-to-face encounters more efficient. In a future version of HUC, patients should be able to give feedback on their level of pain or well-being. Particularly, information about a patient’s pain level could enable more personalized digital coaching. Lastly, according to 2 therapists, it should be possible to calibrate the exercises more individually in terms of exercise technique by adding different variations of one exercise.The goal of this paper was to address the problem of nonadherence to home exercises by proposing HUC, a human- and CA-supported coaching approach that employs smartphone and AR technology. This paper is, to the best of our knowledge, the first to investigate the potential of HUC with patients and health care experts in two lab studies, interview studies, and a longitudinal n-of-1 trial in the field. HUC required collaborative and interdisciplinary effort from various stakeholders, including health care experts, patients, and experts in behavioral medicine, game design, AR, and human computer interaction. A strength of this work and HUC is, therefore, that its pragmatic and diverse investigation helps to broadcast the results to real-world scenarios and inform practitioners about effective digital designs for addressing the problem of treatment adherence. Moreover, the implemented home exercise  is not only relevant to physiotherapy patients but also an important component of other treatments, for example, of high-intensity interval trainings for patients who are overweight or patients with cardiovascular disease. In the following section, the results will be discussed along the research questions and design challenges. Limitations and future work will also be outlined.mental capacity, perceived enjoyment, and perceived usefulness between HUC and the paper-based instructions. This is still promising, however, for the following reasons. First, HUC was rated at least as good as video instructions, which is encouraging, since video instructions are associated with reduced symptoms in physiotherapy [Overall, patients stated that they enjoyed executing the exercise together with HUC, that they intended to use it, and that they would recommend the final HUC version to other patients. Compared to paper- and video-based instructions, HUC reached higher overall acceptance rates, required less mental capacity, was perceived as being easier to follow, and resulted in higher exercise accuracy ratings. However, significant differences were only found for the items otherapy . Second,otherapy , somethiotherapy  and is iotherapy ,49,57,59otherapy . Lastly,In summary and to answer RQ1a, we conclude that patients accepted and enjoyed HUC. Patients were also able to build a working alliance with the CA.HUC was also evaluated by physiotherapists to gather their feedback. Collecting behavioral data about various treatment adherence dimensions  was seen as a clear advantage of HUC. Physiotherapists also considered the real-time feedback to be an additional motivator due to its personal, interactive, and gamified approach, which reflects an improvement relative to the status quo. However, physiotherapists were initially (study 2) more skeptical about whether HUC could be conducive to building a strong working alliance between patients and physiotherapists. The importance of personal interaction between the physiotherapist and the patient was one reason for the negative assessment of attachment bond. Physiotherapists expressed that mutual trust, empathy, and, consequently, mutual goals and tasks were uniquely established during face-to-face encounters. Nevertheless, both the quantitative and qualitative patient feedback (study 3) underline the potential that a strong working alliance can be built with a CA. This result is consistent with prior work about working alliances and CAs . There iIn the follow-up interviews about the field study, all physiotherapists agreed that home exercises in physiotherapy could be optimized with HUC. They were convinced that various treatment adherence dimensions could be addressed more efficiently with HUC.In summary and to answer RQ1b, we conclude that HUC represents a clear relative advantage to current methods, as indicated by physiotherapists, in particular, with respect to its motivational features and real-time feedback.Results from study 3 and the 4-week n-of-1 trial were promising with respect to RQ2. Qualitative feedback from study 3 indicated that HUC addressed adherence challenges better than the paper- and video-based instruction methods. In particular, patients found the reminders (TAD1-2) useful, appreciated receiving guidance (TAD3) and real-time feedback on the spatial and temporal accuracy of the exercise execution (TAD4-5), and felt more comfortable about the exercise. Moreover, the results of the 4-week trial revealed a clear decrease in exercise execution errors (TAD4-5) and a high adherence rate of 92% in TAD1-3. Lastly, the patient reported being motivated and committed to doing the exercise doing the 4 weeks due to the variations in the messages and the feedback on exercise accuracy. Motivation and enjoyment are targeted by HUC and, according to prior work, associated with significantly increased rates of adherence ,29,30.In summary and to answer RQ2, we conclude that HUC did address the session completion rate (TAD1), set completion rate (TAD2), exercise repetition rate (TAD3), and temporal and spatial exercise accuracy (TAD5). Although this study does not prove beyond a doubt that the use of HUC led to better adherence, the rate was far higher than has typically been found in previous studies ,20 and wA first challenge during the design of HUC was the development of the CA’s personality in such a way that the patient perceives the CA coherently as the physiotherapist’s digital assistant via text messages on the smartphone and voice messages in the AR space. The first lab study and the NPS revealed that HUC, and the design in particular, still needed improvement. Accordingly, the first version of HUC was modified based on this feedback. In the second lab study, patients reported correspondently higher levels of satisfaction with HUC and acceptance of the design of the CA. Further, another challenge was the design of the AR interactions, which had to take into account the limited exercise space at patients’ homes, the limited field of view of the AR glasses, and anthropometric characteristics of patients. Any additional controller hardware also had to be omitted due to the requirement that physiotherapy exercises be hands-free. This challenge was partly met. Patients ranked HUC as their first-choice coaching method but still commented on the bulkiness of the hardware. Another major challenge was the design of variations in the smartphone-based and AR-based CA conversations to improve long-term adherence to physiotherapy in the last study. Variations in the design were implemented to make the exercises more diversified and to thereby increase adherence. The positive result for treatment adherence indicated that the last major design challenge was met.The current work has the following limitations. First and foremost, in the current HUC version, only one home exercise was implemented, and thus the findings, especially those related to the AR-based CA, cannot be generalized to a large extent. Implementations of HUC should be further developed to reach a level of implementation foreseen in its approach, as outlined in Second, objective adherence rates were based on lab studies and a 4-week study. Regular physical therapy treatment lasts approximately 9 weeks, while long-term treatment can last more than 9 months (36 sessions) . Thus, HThird, the current AR-based CA had a fixed coaching approach. A growing body of research reveals that certain personalities and therapeutic techniques  work better in specific contexts ,113. TheThis work provides evidence of the relevance and utility of HUC that aims to increase adherence to home exercises. It therefore contributes to the field of digital health by outlining how CAs hosted by mobile and wearable technologies can extend the reach and effectiveness of health care experts into the everyday lives of patients. HUC may be promising not only in the context of physiotherapy, as exemplarily elaborated in this work, but also for various other conditions, such as obesity or cardiovascular disease, as they also require intensive and longitudinal behavioral support in the everyday lives of patients.


HSPG2) encodes for perlecan, a large proteoglycan that plays an important role in cartilage formation, cell adhesion, and basement membrane stability. Mutations in HSPG2 have been associated with Schwartz-Jampel Syndrome (SJS) and Dyssegmental Dysplasia Silverman-Handmaker Type (DDSH), two disorders characterized by skeletal abnormalities. These data indicate a function for HSPG2 in cartilage development/maintenance. However, the mechanisms in which HSPG2 regulates cartilage development are not completely understood. Here, we explored the relationship between this gene and craniofacial development through morpholino-mediated knockdown of hspg2 using zebrafish.Heparan sulfate proteoglycan 2 . We surmised that defects in mandible development were a consequence of neural crest cell (NCC) dysfunction, as these multipotent progenitors produce the cartilage of the head. Early NCC development was normal in morphant animals as measured by distal-less homeobox 2a (dlx2a) and SRY-box transcription factor 10 (sox10) expression at 1 DPF. However, subsequent analysis at later stages of development (4 DPF) revealed a decrease in the number of Sox10 + and Collagen, type II, alpha 1a (Col2a1a)+ cells within the mandibular jaw joint region of morphants relative to random control injected embryos. Concurrently, morphants showed a decreased expression of nkx3.2, a marker of jaw joint formation, at 4 DPF.Knockdown of hspg2 in jaw joint formation and late stage NCC differentiation.Collectively, these data suggest a complex role for  HSPG2 gene causes Schwartz-Jampel Syndrome (SJS) and Dyssegmental Dysplasia Silverman-Handmaker Type (DDSH) [HSPG2 that vary from missense mutations to splice site mutations. These mutations are dispersed throughout the HSPG2 protein, with those located closer to the C -terminus being more readily tolerated [HSPG2 plays a role in regulating craniofacial development.Mutation of the e (DDSH) –3. SJS ie (DDSH) . Both die (DDSH) , 5. InteHSPG2 during chondrogenesis is not completely understood, but is likely related to the various domains within the HSPG2 protein and the vast array of interactions between HSPG2 and the extracellular matrix (ECM) to promote signal transduction and stability [HSPG2 encodes for perlecan, a large proteoglycan that consists of five domains, each of which have a unique function [The function of tability , 7. HSPGfunction . Four offunction . The N-tfunction –10. Thesfunction , 10, 11 function .HSPG2 expression leads to abnormal chondrocyte proliferation and disorganized columnar arrangement [As it relates to the chondrocyte phenotypes in SJS and DDSH, previous studies, both in vitro and in vivo, have established that disrupting angement , 14. Thiangement . During angement –18. Thesangement –21.The development of craniofacial bone is due to both endochondral and intramembranous ossification. In endochondral ossification, cells differentiate into chondrocytes and bones develop from a cartilaginous base. This form of ossification necessitates that chondrocytes are present in growth plates where they are arranged into zones of rest, proliferation, and hypertrophy , 22. Thehspg2 using the zebrafish model. Apart from general advantages like a high fecundity rate, extra-uterine development, and quick maturation, the zebrafish is an ideal organism to study craniofacial development. This is due to the relative simplicity of the cartilaginous structures of the head and face, all of which are readily visible with stains like Alcian blue [hspg2 in craniofacial development [hspg2 resulted in abnormal mandibular jaw joint formation and disrupted late- stage differentiation of CNCCs, with little to no effect on early stage CNCC development. Collectively, our results suggest that hspg2 is essential for joint formation in the developing zebrafish.To begin to test this hypothesis, we performed morpholino mediated knockdown of ian blue , 25. Moshspg2 mRNA is expressed ubiquitously throughout the head, eyes, and somites of the zebrafish. Additional immunohistochemistry staining revealed positive expression of perlecan in these regions from embryos at 2–3 h post fertilization (HPF) to 5 days post fertilization (DPF) [Hspg2 results in failure of the chondro-osseous junction of developing bones and craniofacial abnormalities [hspg2 gene would cause craniofacial abnormalities.It has previously been reported that on (DPF) , 27. Basmalities , we hypohspg2 translation blocking morpholino caused a 7% truncation in the zebrafish mandible when compared to the random control group. The observed truncation was subtle in morphants and did not appear to be the consequence of a malformed Meckel’s cartilage or defects in the development of the ceratohyal. However, upon higher magnification, hspg2 morphants demonstrated an abnormal mandibular jaw joint between the Meckel’s cartilage and palatoquadrate , a phenotype that was not present in the random control group  was first identified in the Drosophila melanogaster model (where it is known as bapx1) and is part of the NK family of homeobox genes [nkx3.2 causes abnormal jaw joint phenotypes (primarily fusion phenotypes) in amphibians and zebrafish [nkx3.2 expression as a marker of mandibular jaw joint development. In situ hybridization performed at 2 DPF  embryos at both the 18 somite  [sox10) at various stages of development where it maintains their survival, specification, and differentiation [sox10 expression as a valid marker for visualizing NCCs during early developmental stages [hspg2 morphants relative to control   and Primntiation . Previoul stages , 34. Resdlx2a) at the Prim-5 stage in random control and hspg2 morpholino injected embryos to determine if CNCC specification occurs normally upon knockdown of hspg2. This homeobox gene is expressed in CNCCs migrating to the pharyngeal arches [dlx2a in morphants relative to random control injected embryos. qPCR measurements performed at Prim-5 in both RC and MO groups validated the normal level of dlx2a expression in morphant animals  larvae. Chondrocytes across both random control and hspg2 morphant groups at 3 and 4 DPF had normal morphology and columnar arrangement. Chondrocytes to the left of the joint were more closely clustered together than those on the right and therefore, only cells from 3 rows to the left of the joint were easily discernable as opposed to 5 rows of identifiable cells on the right of the joint.Based on our results, which suggest that the early NCC lineage was not affected, we next hypothesized that + cells in the region of interest (3 rows of chondrocytes to the left of the joint and 5 rows of chondrocytes to the right of the joint)  transgenic reporter in the mandibular jaw joint region revealed similar chondrocyte morphology and arrangement as samples in the sox10 group. Cell counts  through its HS side chains, which in turn mediates the proliferation of chondrocytes [The mechanism by which perlecan mediates joint development is currently unknown. However, as discussed in the introduction, perlecan is a multi-domain protein with GAG side chains that interact with various growth factors like BMP, WNT, and FGF— all of which are essential for NCC development, chondrogenesis, and joint formation , 40. Defdrocytes . It shouhspg2 is associated with decreased numbers of Col2a1a+ cells at 4 DPF. These data suggest that hspg2 has a function regulating CNCC differentiation, a finding that is supported by the number of Sox10+ cells at an equivalent time point. Our studies are supported by previous analysis in mice (Hspg2−/−) that demonstrated abnormal arrangement and proliferation of chondrocytes in the appendicular skeleton [Sox9 in vitro [Sox9 is vital to chondrogenesis because it activates Col2a1 expression [HSPG2 in joint development because the HS side chains of perlecan are known to bind to collagen II [We further demonstrate that knockdown of skeleton , 37. It in vitro , 41. In pression . It is plagen II , suggesthspg2 was also associated with reduced expression of nkx3.2 at 4 DPF. These results, when understood in the context of the decrease of Col2a1a+ cells found at 4 DPF, appear to match previous results performed in mesenchymal cell culture where Nkx3.2 upregulates Col2a1 by directly binding to the promoter [Nkx3.2 appears to be directly proportional to a decrease in Col2a1+ cells and the differentiation of chondrocytes. It is not clear if hspg2 directly modulates nkx3.2 expression or if the decreased expression is simply the result of defects in the mandibular jaw joint, but studies performed in the chick have shown that Nkx3.2 and Sox9 cooperate to promote chondrogenic differentiation and serve as mediators of Sonic Hedgehog (Shh)-induced chondrogenesis [nkx3.2 and it would prove to be a novel discovery. Recently, it was shown that Nkx3.2 null animals are viable, making it possible to study this gene in relation to hspg2 without early lethality [Knockdown of promoter . In thisogenesis . This coethality .hspg2 in zebrafish as an alternative animal model to study the role of hspg2 during craniofacial development. Induced knockouts in the murine model have resulted in embryonic lethality from mass hemorrhaging in the pericardial cavity and severe chondrodysplasia, both occurrences which can be temporarily circumvented in the developing zebrafish [Hspg2 in chondrocytes [In this paper, we used morpholino-mediated knockdown of ebrafish . To circebrafish , the secebrafish , 46, anddrocytes .While the first two models are viable and can be used to examine adult skeletal phenotypes, the first is centered around exploring the loss of only one domain and the second is mimicking more subtle phenotypes associated with SJS. Our project seeks to understand the role of perlecan in craniofacial development using a null phenotype, a feat not easily done in a murine model. Zebrafish allow for this type of exploration because unlike mice, they are externally fertilized. This external fertilization enables the study of craniofacial development at early developmental stages, particularly with the use of transgenic fish to target specific cells , 49. Thehspg2 are warranted.Zebrafish are remarkably easy to manipulate genetically and have been used to great success in genetic studies. The zebrafish genome shares a high degree of genetic similarity with humans and thus provides a manner in which to understand gene function and mechanisms . 70% of hspg2 open reading frame is very large and difficult to perform mRNA restoration experiments with; this limited our ability to restore the morphant phenotype. In addition, we designed a splice inhibiting morpholino to the 3′ splice acceptor of exon 2, but the designed morpholino did not delete exon 3 as predicted, even at the highest concentration injected (2 nl of a 0.9 mM stock solution). We did, however, utilize a random control morpholino to account for the possibility of morpholino-induced cell death, an endeavor that proved to be rather successful in previous studies [hspg2.All work reported here has been completed by use of a single translation-blocking morpholino. While translation-blocking morpholinos are a simple and effective way in which to knockdown genes of interest, they have been associated with off target effects and non-specific cell death. We recognize that utilization of a single translation-blocking morpholino is a primary limitation to our approach. The  studies , 55. And studies , 37. In hspg2 in craniofacial development by examining the mandibular jaw joint region specifically. We understand that a germline mutant is required to substantiate our work, but our data is supported by previous studies, suggesting that what we observed is not a consequence of off-target effects. Nevertheless, future studies are required.Despite the limitations to our work, we demonstrate an additional function of hspg2 in the development of the mandibular jaw joint, a region of the craniofacial skeleton for which development has not been well elucidated. Furthermore, connections between hspg2 and nkx3.2 have yet to be drawn in literature. Additional data concerning late CNCC differentiation raises pertinent questions about the fate of certain cells within different areas of the developing face. Although future studies to more cohesively understand the role of hspg2 in craniofacial development are needed, these data lay significant groundwork for future experiments in this field and suggest that zebrafish are an acceptable model to study the function of hspg2 in craniofacial development.In summary, our results have created novel implications for the role of Tg(sox10:tagRFP), Tg(col2a1a:EGFP), or AB wildtype fish. Embryos were maintained in E3 embryo medium at 28 °C. All zebrafish were maintained at The University of Texas El Paso according to the Institutional Animal Care and Use Committee (IACUC) guidelines protocol 811,689–5. All adult fish were obtained from the University of Colorado, Anschutz Medical Campus or the Zebrafish International Resource Center (ZIRC). Adult and larval zebrafish were euthanized and anesthetized according to guidelines from the 2020 American Veterinary Medical Association (AVMA) which indicate 30 min at RT in 10 g/L buffered solution of MS222 in conjunction with a cold ice bath for adults. AVMA guidelines for embryos younger than 7 DPF were followed, which indicate 1–10% sodium hypochlorite solution following anesthesia. Detailed methods for anesthesia and euthanasia have been previously described [For all experiments, embryos were obtained by crossing adult escribed .hspg2 translation start site and sterically knockdown perlecan translation in the developing larvae. The second was a random control morpholino with the sequence 5′-AAAAAAAAAAAAAAAAAAAAAAAA-3′. This random control morpholino was used to assure that the translation blocking MO microinjections were not causing any form of extraneous cell death as previously described [Two antisense oligonucleotide morpholino sequences were designed in conjugation with Gene Tool LLC. The first was a translation blocking morpholino (MO) with the sequence 5′-TATCCTCGCCCCCATTTCTGCCAA-3′, created to bind to the escribed .The initial concentration gradient for the translation blocking morpholino was as follows: 0.10 mM (1.65 ng/embryo), 0.30 mM (4.95 ng/embryo), 0.50 mM (8.25 ng/embryo), and 0.70 mM (11.55 ng/embryo). A high mortality rate not attributed to lack of fertilization was found in larvae injected at higher concentrations (0.50 mM and 0.70 mM) when compared to wildtype group at 1 DPF. Morphant larvae at 0.30 mM exhibited growth delays when examined at 1 DPF (verified through somite counts), prohibiting accurate comparison between morphant and control group. Microinjections were then performed at 1.65 ng per embryo at a volume of 0.52 nL per embryo, a concentration and volume where there was minimal mortality and no growth delay. To ensure the final phenotype was not a consequence of global deformities at later stages, larvae were measured for length using Zeiss software and staged according to length at 3 and 4 DPF.For all experiments, the morphant experimental group is compared to either a random control group or wildtype non-injected. The randomized control morpholino has been shown through previous literature to have no associated phenotypes, indicating that it does not influence final results and therefore is the appropriate control group for comparison , 55, 57.hspg2 morphants and random control larvae) were dissected and viscerocranium was mounted on a glass slide with 100% glycerol. A Leica microscope was used to take high-resolution color images of each sample.Zebrafish larvae (aged 5 days post fertilization (DPF)) were fixed in 2% PFA in PBS, pH 7.5 for 1 h at room temperature (RT). Samples were washed for 10 min with 100 mM Tris pH 7.5/10 mM MgCl2, stained with Alcian blue stain  in 70% EtOH, Tris pH 7.5 , and 1 M MgCl2 ), and incubated overnight at RT. Samples were subsequently destained and rehydrated using an EtOH: Tris pH 7.5 gradient as previously described . Embryosdlx2a and nkx3.2 at 127 ng) at 70 °C and developed using anti-DIG Fab fragment (Sigma) antibodies with AP substrate (Sigma). All images were captured as previously described [ISH was performed as previously described , 58, 59.escribed , 58. Stadlx2a fwd CCTCACGCAAACACAGGTTA, dlx2a rev TGTTCATTCTCTGGCTGTGC, nkx3.2 fwd GCAGATTTAGCGGACGAGAC, nkx3.2 rev GCTTCAACCACCAGCGTTAT, sox10 fwd ACGCTACAGGTCAGAGTCAC, sox10 rev ATGTTGGCCATCACGTCATG, rpl13a fwd TCCCAGCTGCTCTCAAGATT, and rpl13a rev TTCTTGGAATAGCGCAGCTT. Data presented was derived by the 2ΔΔct relative fold change methodology as described [dlx2a, which was performed using a single pool of n = 10 larvae and was performed to validate in situ hybridization. For each biological replicate, the qPCR was performed in technical triplicates. A single gray dot on the graphs in Figs. qPCR was performed as previously described , 58 usinescribed , 58, 60.Tg(sox10:tagRFP) and Tg(col2a1a:EGFP)) were fixed at the stated time points using 4% paraformaldehyde. Fixed larvae were mounted in 0.6% low-melt agar in a glass bottom dish (Fisher). Imaging was performed on a Zeiss LSM 700 at 20X and 40X Oil magnification. Images were restricted to the larval craniofacial region. For each fish, a minimum of 20 to 30 z-stacks were collected. At 3 DPF, micron depth across the Tg(sox10:TagRFP) random control group ranged from 60 to 100 μm while micron depth ranged from 57 to 84 μm in morphants. Micron depth across the 4 DPF Tg(sox10:TagRFP) random control group ranged from 63 to 100 μm and from 66 to 93 μm in the morphant group. At 4 DPF Tg(col2a1a:EGFP) random control group micron depth ranged from 63 to 99 μm and from 72 to 90 μm in the morphant group.Transgenic larvae (The number of cells per z-stack (20–30 stacks/fish) at both jaw joints were manually counted using the ImageJ cell counter, which marks each individual cell and keeps track of total cell numbers. Region of interest around the jaw joints were selected to be 3 rows of chondrocytes on the left side of the joint and 5 rows on the right. This region was selected because these cells were consistently visible across z-stacks. Statistical significance was obtained by using a Student t-test with random control and morphant data .


Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition ADHD criteria, revised NEO Personality Inventory, Imp, Vent, and PRS, we identified three ADHD subtypes. These are an impulsive–neurotic type, an adventurous–hyperactive type with a stronger genetic component, and an anxious–inattentive type. Our study thus suggests the importance of adventurousness and the differential consideration of impulsivity in ADHD. The genetic risk is distributed differently between these subtypes, which underlines the importance of clinically motivated subtyping. Impulsivity subtyping might give insights into the organization of comorbid disorders in ADHD and different genetic background.While impulsivity is a basic feature of attention-deficit/hyperactivity disorder (ADHD), no study explored the effect of different components of the Impulsiveness (Imp) and Venturesomeness (Vent) scale (IV7) on psychiatric comorbidities and an ADHD polygenic risk score (PRS). We used the IV7 self-report scale in an adult ADHD sample of 903 patients, 70% suffering from additional comorbid disorders, and in a subsample of 435 genotyped patients. Venturesomeness, unlike immediate Impulsivity, is not specific to ADHD. We consequently analyzed the influence of Imp and Vent also in the context of a PRS on psychiatric comorbidities of ADHD. Vent shows a distinctly different distribution of comorbidities, e.g., less anxiety and depression. PRS showed no effect on different ADHD comorbidities, but correlated with childhood hyperactivity. In a complementary analysis using principal component analysis with  Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder that manifests in early childhood and continues into adulthood. Adult ADHD is characterized by a complex pattern of comorbidities, e.g., anxiety, depression, or substance abuse disorders , and shoDuring the developmental trajectory of ADHD, patients often contract comorbid disorders . In a st2 receptors in rats bred for high impulsivity , where patients with higher functional impairment have lower self-directedness independent of psychiatric comorbidity and ADHD subtype .But how does the genetic risk of ADHD relate to different aspects of impulsivity? So far, there is no study comparing impulsivity  and general personality traits  and relating them to psychiatric comorbidities and PRSs in an adult ADHD sample where stable personality traits can be assumed (as compared to children and adolescents). Both ADHD and impulsivity have been shown to have a high heritability , which wThe objectives of the present study are to test whether venturesomeness and impulsivity according to the IV7 scale do indeed differ between ADHD cases and controls and to further characterize how psychiatric comorbidities cluster along different impulsivity axes in our ADHD sample. As complementary, bottom-up analysis, we want to look how a principal component analysis (PCA) divides the personality traits and ADHD symptoms of our ADHD patient sample and how this relates to comorbid disorders. Finally, we were especially interested in understanding how the analysis above relates to an ADHD PRS in a genotyped subset of our sample.Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV): onset before the age of 7 years via retrospective diagnosis, lifelong persistence, and current diagnosis. Age at recruitment was between 18 and 65 years. Withdrawal of patients with SUD was treated in an inpatient setting. Patients with autism spectrum disorder, psychotic disorders, intelligence below IQ < 80, or any ADHD-like symptom better accounted for by other mental illness were excluded. Healthy controls were screened for the absence of psychiatric disorders. The Ethics Committee of the University of Würzburg approved the study, and written informed consent was obtained from all patients after procedures, and the aims of the study had been fully explained. In the present study, we discuss two ADHD samples: first, the complete sample  and second a subgroup .Patients were suffering from an adult ADHD according to the diagnostic criteria of DSM-IV inattentiveness criteria and on nine hyperactivity/impulsivity criteria based on a clinical interview. The diagnosis was based on a one-time clinical interview, which retrospectively assessed childhood symptoms. Additional information was used if available: school reports (which are done routinely for the first 2 years in German schools), information from partners, relatives or friends.Patients of the Department of Psychiatry and Psychotherapy, University of Würzburg, referred for diagnostic assessment and treatment of ADHD, were screened with the structured clinical interviews of Axis I [severe combined immunodeficiency (SCID I)] and Axis II (SCID II) disorders by trained raters. ADHD symptoms were scored as being present or not on nine DSM-IV, defined by onset before the age of 7 years and current diagnosis.Inclusion criteria were confirmed adult ADHD according to the diagnostic criteria of Traits were assessed by self-rating scales. The participants filled in the revised NEO Personality Inventory (NEO-PI-R) and the IV7 . The NEOGenotype data were generated using the PsychChip array (15048346 B) with HumanCore, Human Exome, and custom content. Normalized intensity values were obtained using Illumina's. GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4. Individuals with a call rate >95% were included in the final sample.n = 435 participants with available GWAS data using PRSice2 software (http://www.prsice.info/). We used the mega GWAS summary statistics of the Demontis et al. . After clumping, PRSice runs a logistic regression to find the best p threshold based on the explained variance (Nagelkerke's pseudo-r2 correlation). Full variance explained, R2 =.023, regression coefficient = 5656.22, threshold = 0.494, p = 0.000322.PRSs were computed for each of the s et al.  study ass et al. . PRS calp-value thresholding), multiplying the natural log of the odds ratio of each variant by the allele number of each variant. We controlled for population stratification by including four principal components as covariates for population stratification, regressed them out of the PRS, and used the residual for calculation of linear regression models.Linear regression models were used to estimate associations between PRSs and six phenotypes  in the Würzburg ADHD sample. PRS were then estimated by the software tool PRSice for each target sample using all available SNPS of the meta-analysis, which were available in our sample  were compared using general linear models; age and sex were included as covariates; impulsivity, venturesomeness, and empathy were the dependent variables. For a correlation in the number of symptoms according to DSM-IV criteria with IV7 subscales, we used a Spearman correlation.Statistical analysis was done with SPSS 25 . Frequena priori assumptions, e.g., different algorithm, different rotation criteria, and the choice of the number of components to be rotated , with the correlation between impulsivity and childhood hyperactivity showing the highest correlation . Venturesomeness was strongly correlated with childhood hyperactivity and inattention , but not adulthood. Empathy correlated with adulthood symptoms  but not childhood symptoms.We looked at the relationship between impulsivity, venturesomeness, and empathy with inattention and hyperactivity in both adulthood and childhood with a Spearman correlation. Impulsivity was significantly correlated with hyperactivity and inattention in adulthood and childhood  with our healthy controls: only impulsiveness , but not venturesomeness  and empathy , was different between ADHD cases and controls.In an independent p < 0.001], followed by extraversion  and neuroticism . Therefore, impulsiveness gives good testing characteristics; neuroticism or extraversion performs poorly . When in = 435) with PRS and the larger sample without PRS (n = 903). All other covariates were the same between the four models.We calculated three linear regression models with impulsiveness (Imp), venturesomeness (Vent), empathy (Emp) with and without PRS, see Patients with alcohol and hallucinogen abuse or dependency showed higher impulsiveness scores. No other diagnostic entities or the PRS were significant for the dependent variable impulsiveness. Patients with anxiety disorder diagnosis showed significantly lower venturesomeness scores. Patients with cannabis abuse or dependency showed higher venturesomeness scores. No other diagnostic entity was significant for the dependent variable venturesomeness.Patients suffering from stimulant abuse or dependency disorder showed higher scores on empathy in the smaller sample with PRS covariate, but not in the complete sample, pointing to a false-positive effect see .* age or scale * sex was significant (p > 0.24).As all regression models found strong effects for a decline of venturesomeness and impulsiveness with age and lower score for females, we looked in additional analyses whether there are significant interactions between IV7 scales and age or sex. No interaction term in scale We combined the dimensional scales of the PRS , NEO-PI-R, the IV7, and the ADHD inattentive and hyperactivity scale in a PCA to gain further insight how adult ADHD can be differentiated into different  components . Three cp = 0.047, df = 11,421, β = 0.11, T = 1.997) and negatively by SUD cocaine , while component 2 was negatively associated with depression in our regression model , thus predicting resilience against depression. In the larger sample, component 1 showed in addition a significant association with depression . Component 2 was significantly associated with hallucinogen use  and negatively associated with age . Component 2 therefore goes together with being younger, non-depressed, risk-taking in the form of hallucinogen use, and with high impulsiveness and venturesomeness. Interestingly, there is no direct correlation with neuroticism  representing therefore a predominantly female, inattentive dimension of ADHD with less genetic load. Interestingly, in the larger sample, the link to affective and anxiety disorder was much stronger. Here, component 3 was associated with anxiety  and depressive disorder . Thus, in the larger sample, component 3 seems to be associated with the anxious dimension of ADHD comorbidity.Component 3 was associated with sex , and only childhood hyperactivity showed a significant correlation with ADHD PRS (p = 0.005).To better understand the relation of the PRS to ADHD symptoms in our samples, we correlated the number of fulfilled diagnostic criteria according to Our study provided evidence that impulsivity and venturesomeness give rise to a very specific pattern of psychiatric comorbid disorders in ADHD and that not all ADHD patients are per definition “thrill-seeking.” Indeed, in a subgroup of our patients, venturesomeness seems to be even decreased as it is negatively correlated with anxiety disorders, and our sample had a high number of ADHD patients suffering from anxiety disorders. This is in line with studies of adult ADHD patients showing higher harm avoidance as personality trait or higher prevalence of anxiety disorders , 37. PatImpulsivity has been conceptualized as a core ADHD symptom, but different aspects of impulsivity might cluster differently on comorbid disorders in ADHD , e.g., mPrevious studies rarely used impulsivity subtypes for getting insights into substructures of comorbid disorders: In a recent study with 209 participants (72 ADHD patients), the authors studied how components of the UPPS  differentiate between controls and cases and psychiatric comorbidities . Lack ofReceiver Operating Characteristic Curve for Personality Traits in Differentiating ADHD. Faraone et al. , which depart from normally distributed quantitative PRS model, e.g., Crohn disease. In psychiatric diseases, however, the contribution of several small-scale effects might lead to low predictive power in smaller samples as ours . While PIs has been a matter of debate whether childhood ADHD represents on a genetic level the same as adulthood ADHD. In previous studies, the genetic correlation between ADHD in childhood and adulthood has been estimated to be about 80% , 42. IntDSM-IV was not correlated, but between ADHD symptoms in childhood and venturesomeness. Finally, the more fine-grained items of the self-report questionnaire capture a different aspect of impulsivity than the broader criteria of DSM-IV hyperactivity in ADHD in clinical situations.While our sample had the advantages of thorough clinical assessment, we nevertheless want to point out some general limitations. One might argue that looking at impulsivity in a disease entity that is defined and operationalized by impulsivity is tautological. This is reflected by the high correlation between symptoms and impulsivity. Interestingly, the correlation in adulthood between venturesomeness and the number of ADHD symptoms after While regression models of the dependent variables venturesomeness and impulsivity give interesting insights, we looked for a PCA as a complementary data-driven method. This has the obvious advantage that the upcoming components are not correlated  and therefore are easier to interpret. The results of our PCA show that component 2 with high venturesomeness is different from the basic (=mean) ADHD component 1 and the more anxiety- and inattentiveness-related component 3. This is reminiscent of a recent debate based mainly on child and adolescent data whether the hyperactivity subtype with its higher comorbidity with conduct disorder can be regarded a separate entity –46. ThisOur PCA bears an interesting resemblance to the subtyping of combined (component 1), inattentive (component 3), and impulsive/hyperactive (component 2) subtyping and its relation to psychiatric comorbidity. However, the strong correlation of neuroticism that can be interpreted as emotional regulation ability and Impulsiveness in distinction from venturesomeness  points to the neglected issue of including emotional dysregulation as a core ADHD trait. As PCA is a purely data-driven method that leads to independent components, one might argue that it gives a better estimate of the range of possible subtypes. Therefore, we do not interpret these components as natural kinds, but they point to dimensions mirror subtypes and point strongly to the influence of venturesomeness in subtyping. While the current therapeutic and diagnostic procedures have the advantage of standardization and operationalization, they do not reflect the wide phenotypic range of ADHD in adults. As our PCA components are only “virtual” measures, they cannot solve this problem, but the usage of the IV7 might add useful additional information about subtypes.While the regression analysis did not give significant results for PRS in relation to clinical phenotype, the PCA indicates a certain genetic influence for component 2. As this component is more abundant in young, adventurous male patients with cannabis dependence, the clinical phenotype may be closer to the core symptoms of childhood ADHD, where the sex ratio is skewed toward males, and the hyperactive component is more pronounced. As the mega-analysis GWASs include both childhood and adult cases, this might lead to a higher genetic background in component 2. However, Demontis et al.  found a 2/D3 receptor binding found binding in people with high venturesomeness but no effect of impulsiveness   . The UPPiveness) . Therefoiveness) . A receniveness) . Our PCAWhile our PCA analysis gives subtypes that can easily be aligned to clinical categories, subtyping has received general criticism as subtypes do not seem to be stable across time . This suFirst, we showed that venturesomeness, unlike immediate Impulsivity, is not specific to ADHD. Therefore, a differentiated consideration of impulsivity in ADHD is needed. We consequently analyzed the influence of Imp and Vent also in the context of a PRS on psychiatric comorbidities of ADHD. Vent shows a distinctly different distribution of comorbidities, e.g., less anxiety and depression, more cannabis dependence. PRSs showed no effect on different ADHD comorbidities but was significantly correlated with childhood hyperactivity. In a complementary bottom-up analysis using PCA with particular emphasis on NEO-PI-R, Imp, Vent, and PRS, we identified three ADHD subtypes that had similarities and differences to conventional subtypes. These are an impulsive, neurotic type; an adventurous, less depressive, hyperactive, predominantly male type with a stronger genetic component; and a more female, inattentive type. Our study thus suggests the importance of adventurousness and the differential consideration of impulsivity in ADHD. The genetic risk seems to be distributed differently between these subtypes, which underlines the sense of clinically motivated subtyping. From a clinical point of view, this suggests that the IV7 questionnaire is a relatively easy-to-administer questionnaire that can predict affective and substance abuse–related comorbidities. As SUD, hyperactivity, amd higher genetic loading with an ADHD PRS, as opposed to higher anxiety, seem to lie on the other side of a venturesomeness continuum, clinical studies should look at the usefulness of venturesomeness in making a treatment decision and applying different therapeutic strategies, maybe even on a psychopharmacological level. On a genetic level, our data-driven component analysis suggests that adult ADSHD subtypes show distinct genetic loading of ADHD PRS. Adult ADHD is not a homogenous entity. Impulsivity subtyping might give insights into the axis on which comorbid disorders cluster. These subtypes might show a different genetic background. Future studies might use this information for therapeutic and diagnostic predictions.oliver.grimm@kgu.de.The data analyzed in this study is subject to the following licenses/restrictions: Pseudonymized data can only be shared if patients give their consent. Requests to access these datasets should be directed to Oliver Grimm, The studies involving human participants were reviewed and approved by Ethik-Kommission der Universität Würzburg Institut für Pharmakologie und Toxikologie Versbacher Str. 9 97078 Würzburg, Germany. The patients/participants provided their written informed consent to participate in this study.OG analyzed the data and wrote the manuscript. TK calculated PRSs. HW curated data, especially genetics data and supervised biomaterial. SK-S, CJ, K-PL, and AR collected data and biomaterial and recruited patients. All authors contributed to the manuscript.AR received personal fees from MEDICE Arzneimittel Pütter GmbH & Co. KG, Shire PLC, Neuraxpharm Arzneimittel GmbH, Janssen-Cilag GmbH, Takeda (former Shire) and Servier Deutschland GmbH at present or during 36 months prior to publication. OG received personal fees from MEDICE Arzneimittel Pütter GmbH & Co. KG. SK-S received personal fees from MEDICE Arzneimittel Pütter GmbH & Co. KG and Takeda (former Shire) at present or during 36 months prior to publication. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.