Attention-deficit/hyperactivity disorder (ADHD) is among the most common mental disorders in children and adolescents, and it is a strong risk factor for several adverse psychosocial outcomes over the lifespan. There are large between-country and within-country variations in diagnosis and medication rates. Due to ethical and practical considerations, a few studies have examined the effects of receiving a diagnosis, and there is a lack of research on effects of medication on long-term outcomes.Our project has four aims organised in four work packages: (WP1) To examine the prognosis of ADHD (with and without medication) compared with patients with other psychiatric diagnoses, patients in contact with public sector child and adolescent psychiatric outpatient clinics (without diagnosis) and the general population; (WP2) Examine within-country variation in ADHD diagnoses and medication rates by clinics’ catchment area; and(WP3) Identify causal effects of being diagnosed with ADHD and (WP4) ADHD medication on long-term outcomes.Our project links several nationwide Norwegian registries. The patient sample is all persons aged 5–18 years that were in contact with public sector child and adolescent psychiatric outpatient clinics in 2009–2011. Our comparative analysis of prognosis will be based on survival analysis and mixed-effects models. Our analysis of variation will apply mixed-effects models and generalised linear models. We have two identification strategies for the effect of being diagnosed with ADHD and of receiving medication on long-term outcomes. Both strategies rely on using preference-based instrumental variables, which in our project are based on provider preferences for ADHD diagnosis and medication.The project is approved by the Regional Ethics Committee, Norway (REC number 2017/2150/REC south-east D). All papers will be published in open-access journals and results will be presented in national and international conferences.ISRCTN11573246 and ISRCTN11891971. This study will use reliable and complete national registry data to study real-world effects of attention-deficit/hyperactivity disorder (ADHD) diagnosis and medication on long-term psychosocial outcomes highly relevant for patients, families and society at large.We use observed variations in rates of ADHD diagnoses and medication between public sector child and adolescent psychiatric outpatient clinics for causal modelling, enabling empirical investigation of research questions which cannot be addressed in conventional randomised controlled trials for ethical and practical reasons.In Norway, ADHD in children and adolescents is almost exclusively diagnosed in public sector specialist services, which is covered by our registry data, ensuring representative data for the Norwegian general population.The observed variation in ADHD diagnosis and medication within Norway reflects most of the variation observed between countries, relevant to the external validity of the study.Whereas the strength of registry data as used in this study is related to data completeness and reliability, the weakness relates to validity and in some cases also data availability.Attention-deficit/hyperactivity disorder (ADHD) is among the most common mental disorders in children and adolescents,22–24Clinical treatment guidelines recommend a multimodal approach that combine psychosocial and pharmacological treatment options.In the case of pharmacological treatment, on the other hand, several clinical trials have provided evidence of psychostimulants’ safety and efficacy in reducing ADHD symptoms in the short term.29Journal of the American Academy of Child & Adolescent Psychiatry.34While short-term effects of medication are established ,A promising source of long-term effect estimates to contribute to this debate is nationwide register studies.28 29 34 37 45Over recent decades, there have been substantial increases in clinical diagnosis and pharmacological treatment of ADHD in many countries,3A retrospective study based on population-level databases from 13 countries and 154.5 million individuals showed that prevalence of ADHD medication use in children aged 3–18 years varied between 0.27% and 6.69% across included countries.61Even within Norway, a country with a modest inequality and a universal healthcare system, there are substantial regional differences in diagnosis and medication.67Internationally, the variation in ADHD diagnosis and medication rates have caused a debate with two opposing perspectives. On the one hand, there is a restrictive perspective characterised by concerns about potential overdiagnosis of ADHD, leading to medicalisation of normal behaviour,43This debate may be reflected in clinical practice, where patients referred to specialist healthcare with suspicion of ADHD present with various degrees and compositions of symptoms . CliniciThe controversy on ADHD diagnosis and ADHD medication mostly relates to the middle area of the symptom distribution in In light of increasing ADHD diagnosis and medication rates in most Western countries, it is important to improve our knowledge on the effect of diagnosis among patients around the clinical threshold for diagnosis, as well as the effects of medication on long-term outcomes among patients. This is an important issue to address as it can inform the debate on underdiagnosis and overdiagnosis and medication. A pressing issue is whether patients with ambiguous ADHD symptoms benefit or not from being diagnosed. As pointed out by Owens,The key issue in identifying an effect of receiving a diagnosis is that diagnoses cannot be randomised to patients. Hence, we must either rely on epidemiological designs that precludes causal inference unless all potential confounding is statistically controlled, or we need to find sources of plausibly exogenous variation that can be used as a natural experiment. We believe the geographical variation in diagnosis and medication can be used as a natural experiment to identify causal effects of diagnosis and medication on long-term outcomes. There are several plausible explanations for geographical variation in diagnosis and medication rates on both the supply and demand side, including resources, capacity and patient mix. Nevertheless, a portion of the variation may be due to variation in clinician’s diagnosis and medication practice among public sector child and adolescent psychiatric outpatient clinics, commonly referred to as provider preference,86The current research project aims to contribute to the existing knowledge on ADHD diagnosis and ADHD medication in several ways. Our project will employ Norwegian registry data to explore four main aims with corresponding work packages (WP):WP1: The epidemiology of ADHD prognosis. The main aim of this WP is to describe the general long-term prognosis of ADHD compared with the general population. This is in response to the typical parental concern: ‘My child is diagnosed with ADHD, how will he/she do in life?’ By long term, we here mean years rather than months, including the important transition from childhood and adolescence to early adult life. We will examine the prognosis of patients diagnosed with ADHD in child and adolescent psychiatry (with and without medication). These will be compared with patients in child and adolescent psychiatry who received other diagnoses, or who received no diagnosis. We will also compare to the general population without contact with child and adolescent psychiatry. Measures of prognosis include registry data records of emergency care visits/injuries, comorbidity, contact with child welfare services, contact with adult psychiatric health services, education, employment and income, welfare dependency, crime, self-harm, suicide and mortality.WP2: The ADHD variation controversy. This WP has two aims: first, we will describe the geographical variation in ADHD diagnosis and medication in Norway. We will describe this variation at the level of the catchment areas for child and adolescent psychiatric outpatient clinics in Norway. We will describe the variation in ADHD diagnosis as proportion of children and adolescents referred to these clinics and as proportion of children and adolescents in the catchment area, and also in ADHD medication as proportion of diagnosed patients. Second, we aim to explain this variation by three strategies:We will explore to what extent this variation in clinical practice can be attributed to catchment area characteristics. Data on catchment areas will also be included in WP3 and WP4 as potential confounding variables.Further, we will explore to what extent it can be attributed to the variation in observed ADHD symptoms as observed in a nationwide health study of the general population.Finally, we will survey clinicians working at the about 90 child and adolescent psychiatric outpatient clinics in Norway, exploring the variation in their attitudes and opinions towards ADHD diagnosis and medication. Specifically, we will explore if these attitudes and opinions vary on a continuum from restrictive to liberal. We will also explore if this variation in attitudes and opinions correlate at the aggregated level of the clinics with observed rates of ADHD diagnosis and medication (according to the registry data), and with the variation in ADHD symptoms  in the ADHD population compared with the general population. The aim is to provide general data on the prognosis of the ADHD population, employing all available outcomes. We will use survival analysis93 95This second WP will employ conventional statistics including scatter plots and regression models. Most analyses will be performed on data aggregated to geographical regions (counties or finer) and  to the about 90 child and adolescent psychiatric outpatient clinic catchment areas. To account for patient clustering and repeated observations over time, we will use standard generalised linear models with cluster-robust SEs and mixed-effects models.93 96To identify the effect of ADHD diagnosis (WP3) and ADHD medication (WP4) on long-term outcomes, we will use child and adolescent psychiatric outpatient clinics’ catchment area variation in diagnosis and medication as IVs. IV is a common identification strategy in health services researchIt is plausible that a provider’s preference for diagnosing ADHD affects whether or not an individual is diagnosed with ADHD, while it is not associated with the outcomes of interest  net of certain controls. We will use provider preference for ADHD diagnosis to identify the effect of diagnosis on long-term outcomes. Similarly, provider preference for ADHD medication likely affects whether or not a patient receives medication, while it is not associated with our outcomes of interest, net of certain controls. Provider preference for ADHD medication will be used to identify the effect of ADHD medication on long-term outcomes. Provider preferences for medication have become a well-established IV in epidemiology,104To our knowledge, provider-level preference for diagnosisAlthough rates of diagnosis and medication follow each other closely, preliminary evidence on the county level indicates that they do not correlate perfectly, as shown in Preference-based instruments may lead to biased inferences if the identifying assumptions are not met.as-if randomly assigned to ADHD medication or no ADHD medication at a national level.We expect that the instrument meets the exclusion restriction in several respects. We expect provider preference for diagnosis and medication only to affect long-term outcomes through diagnosis and treatment decisions. Although patients in Norway are free to choose outpatient clinics, which opens the door to self-selection bias in principle, in practice, the vast majority of patients use the nearest child and adolescent psychiatric outpatient clinic for convenience and because child and adolescent psychiatric outpatient clinics are expected to deliver equal services of equal quality.Next, we will control for the characteristics of the catchment area and the patient mix of each provider that may partially explain variation in diagnosis and prescription practices. We have relied on existing research and expert knowledge in our assessment of relevant control variables and included variables in our data accordingly.et al.115Our assessment of causal effects relies on IV triangulated with other methods based on other assumptions.Our data comprises one sample of patients and one sample of controls from the general population. The patient sample includes all persons between 5 and 18 years of age that had any contact (for any reason) with child and adolescent psychiatric outpatient clinics between 2009 and 2011 . Children younger than 5 years are not included as few children are diagnosed with ADHD before age 5.As the project will examine outcomes that occur at different points over a life course , we will receive data for 2009–2019 in 2020 and for 2020–2021 in 2022. We have estimated that the patient sample with an equally sized control sample from the general population  will be approximately 200 000. All analyses are registry based. We combine data from a total of nine national registries, presented in The registry data set will be supplemented with a municipality data set based on publicly available aggregated administrative data. The municipalities will be grouped by child and adolescent psychiatric outpatient clinic catchment areas. The municipality data set serves two purposes: (1) examine associations between environmental factors and geographical variation in ADHD diagnosis and prescription patterns and (2) account for population mix at child and adolescent psychiatric outpatient clinics in analyses. The municipality data set will include covariates for socioeconomic conditions , crime, income inequality, living conditions, health service utilisation and health service economic variables.Patients and public were not involved in the development of WPs or study design.This project examines (1) the prognosis of ADHD, (2) within-country variation in ADHD diagnosis and medication rates by clinics’ catchment area, (3) causal effects of being diagnosed with ADHD on long-term outcomes and (4) causal effects of ADHD medication on long-term outcomes. The project relies on Norwegian nationwide register data and employs several methodological approaches, including survival analysis, mixed-effects models and IVs.As outlined in the introduction, the debate concerning the long-term consequences of variation in diagnosis and medication of ADHD is far from settled. RCTs on ADHD may not adequately address the controversy on long-term effects of ADHD diagnosis or medication, as randomisation of these exposures on a large scale with long follow-up is infeasible. Causal inference from conventional epidemiological designs is also generally implausible, due to unobserved confounding. By combining rich nationwide register data with an IVs design, we are able to circumvent the shortcomings of both RCTs and conventional epidemiological designs on these topics. Our approach aims to fill this knowledge gap by analysing effects of diagnosis and medication for children and adolescents on long-term outcomes.In this sense, this project has merit to provide empirical evidence that neither RCTs nor conventional epidemiological designs can address. First, there is to our knowledge no trial randomising children to ADHD diagnosis. Our approach aims to fill this knowledge gap by instrument variable analysis for children at the margin of an ADHD diagnosis. Second, most clinical trials of medication in ADHD to date has been conducted on children that clearly meet diagnostic criteria, whereas the variation and controversy is regarding children on the margin of receiving medication.This project is the first detailed examination of within-country variation in ADHD diagnosis and ADHD medication by child and adolescent outpatient psychiatric clinics’ catchment areas, including possible associations with socioeconomic and demographic covariates. The project will be the first application of provider preference for ADHD diagnosis as an IV. The project will also be the first application of IVs to assess the effects of ADHD diagnosis and ADHD medication on several psychosocial outcomes.The project is subject to the following limitations: Register data are limited to precollected data in registers, which also determine data selection and data quality.92 117The Norwegian Prescription Database (NorPD) will combine data from the different registries and replace the personal identification number with a project-specific number (pseudonymisation) before distributing data to the research group to protect the privacy of participants. NorPD will keep the linkage key between the personal identification number and the project-specific number. Data will be stored and analysed on a secure server at Haukeland University Hospital that only the PI and other preapproved researchers will have access to. To ensure the quality and reproducibility of our data management and statistical analyses, we will (1) cross-check each step in the data cleaning and preparation process and (2) document each step from the raw data to the final data sets and statistical analyses in version-controlled syntax and log-files. Missing data will be assessed, and we will consider strategies for multiple imputation.The project is approved by the Regional Committee for Medical and Health Research Ethics, Norway: REC South East, Committee D (REC number 2017/2150/REC south-east D). Due to the large number of participants, it is not feasible to obtain consent from all participants. The study has been evaluated by REC to be ‘of considerable importance to society’ and to ‘protect the integrity and welfare of the participants’. Based on the fulfilment of these criteria, the project has been exempted from the requirement of collecting informed consent from participants. The REC approval is given under the precondition that the project is conducted as described in the project application, protocol, communication and the administrative provisions in the Norwegian Health Research Act (‘Helseforskningsloven’) and appurtenant regulations.The data used in this project may not be made publicly available due to the sensitive nature of the data. Current approvals and regulations do not allow sharing these data. Due to general data protection regulations, restrictions in the ethics approval and restrictions by the registry owners, data may not be shared. We may share statistical code.The publication strategy distinguishes between six types of publications planned from this project:Preparatory publications: This includes the present protocol paper, trial registrations, systematic literature reviews on subject matter issues regarding ADHD119WP1: The epidemiology of ADHD prognosis. We will utilise all data to describe common trajectories in ADHD. Multiple comparison groups will be employed including other patients referred to child and adolescent psychiatry who got other diagnoses or no diagnosis, and also the general population. Outcomes are according to data as described in WP2: The variation in ADHD diagnosis and treatment. We will describe in detail the geographical variation in ADHD diagnosis and medication, and also explore if characteristics of the catchment areas may explain some of the observed variation in clinical practice. We will publish results from the survey among clinicians at the public sector child and adolescent psychiatric outpatient clinics in Norway, exploring if their opinions and attitudes to ADHD diagnosis and treatment vary from restrictive to liberal, and if this variation corresponds with the observed geographical variation in rates of ADHD diagnosis and medication. Further, we will publish results from the health survey, exploring if there is an association between rates of ADHD symptoms and ADHD diagnosis and medication.WP3: Long-term effects of receiving an ADHD diagnosis for children on the margin of the diagnostic threshold. Publications on the effect of ADHD diagnosis among those referred to child and adolescent psychiatry on outcomes as described above. Outcomes according to data in WP4: Long-term effects of ADHD medication. Publications on the effect of ADHD medication among those diagnosed with ADHD on outcomes as described above. Outcomes according to data in Exploratory publications on hypotheses and topics beyond those here described. These may be subject to additional approvals from the ethics committee and the owners of the registries, eventually also an update of the Data Protection Impact Assessment.We will follow International Committee of Medical Journal Editors Vancouver recommendations for authorship when publishing the papers. Most of our team members have significant experience in writing and publishing scientific papers, and we believe our multidisciplinary team’s experience will serve as the main expertise in writing the planned articles. We aim to publish with open access. Substantial amendments to our protocol will be reported to relevant parties through relevant channels.


The aim of this study is to identify the association between Attention Deficit Hyperactivity Disorder (ADHD) proneness and aggressive propensity in adolescents.A quantitative, large‐scale, cross‐sectional study was performed from April to May 2016 in Korea. The survey questionnaire included overall health behaviors, as well as scales for assessing ADHD proneness  and aggressive behavior  in adolescents. Area under the receiver operator characteristic (AUROC) curves was constructed to determine the cut‐off value of total aggression score for discriminating ADHD proneness.A total of 2,432 students participated in the survey, and 1,872 of them completed the questionnaire, indicating a response rate of 77.0%. Based on CASS(S), 33 (1.8%) subjects were classified as the ADHD group. AUROC curve analysis showed that a score of 68.5 points had higher sensitivity (83.3%) and specificity (69.4%) to discriminate ADHD proneness. ADHD proneness was significantly associated with higher aggression subdomain scores . Especially, anger and hostility had a stronger relationship with ADHD proneness than did physical and verbal aggression. A multivariable analysis demonstrated that ADHD proneness was significantly related to body mass index in the top 10% of the study population, alcohol consumption, gastrointestinal trouble, daytime sleepiness, and total aggression score of 68.5 points or higher. Adolescents who had total aggression scores of 68.5 points or higher showed a 9.8‐fold  higher risk of ADHD compared with those who had scores less than 68.5 points.Our results demonstrated that ADHD proneness was significantly associated with aggression propensity. In particular, anger and hostility were more closely associated with ADHD proneness than were other aggression subdomains. This large‐scale cross‐sectional study showed that ADHD proneness was associated with aggression propensity in adolescents. In subdomains of aggression, anger and hostility, which are inconspicuous behaviors, showed stronger association with ADHD tendency than did other aggression subdomains. ADHD refers to persistent and recurrent disturbances in age‐appropriate behaviors within the two domains of attention deficit and hyperactivity/impulsivity, which cause maladjustment in emotional and social aspects, as well as cognitive and behavioral aspects  and 2016 (12.1%) among children and adolescents ages 4 to 17  typically presents hyperactivity, impulsivity, and inattention as ADHD‐related symptoms, the manifestations of ADHD are highly heterogeneous  and conductive disorder (CD), which are classified as disruptive behavior disorders, coexist in ADHD patients at a high rate of 45%–84%, and 15%–56%, respectively Barkley, . A studyPreviously, aggression has been classified in a variety of ways. For example, the Buss‐Perry Aggression Questionnaire, one of the most widely used instruments to access aggression, classified aggression into four types; physical aggression, verbal aggression, anger, and hostility  and aggression subscales  has been assessed in only a handful of previous studies. Therefore, the initial aim of this study was to examine the association between ADHD proneness and aggression propensity, using subscales. The secondary aim was to identify the cut‐off value of aggression scores to discriminate ADHD proneness, thereby allowing for targeted intervention of ADHD proneness.22.1From April to May 2016, this cross‐sectional study was performed with students ages 11 to 19 from middle schools (7th‐9th grades) and high schools (10th‐12th grades) in Gwangju, Korea. With the assistance of statisticians from the Office of Education in the region, six clusters from Gwangju were formed based on sociodemographic characteristics. The questionnaire was distributed during researchers’ on‐site visit to schools. Each participant voluntarily completed the survey. After survey completion, a unique study identification was assigned to each participant in order to ensure confidentiality and anonymity. This study was approved by the Ethics Committee and Institutional Review Board of the Honam University, Korea (IRB number: 1041223–201510‐HR‐090–01). Informed consents were obtained from students’ parents. All procedures performed in this study involving human participants were in accordance with the ethical standards of the ethics committees, which approved the study, and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.2.2The survey was comprised of the revised short form of the Conners‐Wells Adolescent Self‐Report Scale (CASS[S]) and Buss‐Perry Aggression Questionnaire (BPAQ) , smoking status, alcohol consumption, parents’ attention, number of close friends, and academic performance. History of medical symptoms such as headache, muscle pain, scoliosis, gastrointestinal (GI) trouble, constipation, atopic dermatitis, sinusitis, asthma, unstable mood, fatigue or irritation, daytime sleepiness, and sleep induction time were also obtained.2.3A chi‐squared test was used to compare categorical variables such as demographic information and total aggression scores between participants with and without ADHD proneness. Since each of the subscales of aggression  was correlated with at least one other subscale, a multivariable analysis of variance (MANOVA), followed by a post hoc Tukey's‐b test, was conducted to examine differences in the subscales of aggression. To analyze the relationship between ADHD proneness and aggression propensity, Pearson's correlation coefficient was performed. A multivariable logistic regression analysis was conducted using the backward stepwise method, and area under the receiver operator characteristic (AUROC) curves were calculated to determine the cut‐off of total aggression scores for discriminating ADHD proneness. Odds ratio (OR) and adjusted OR (AOR) were estimated by univariate and multivariable analyses, respectively.P‐values less than 0.05 were considered statistically significant. All statistical analyses were conducted with the Statistical Package for the Social Sciences version 20.0 for Windows .3n = 898) and 52.0% were 10th‐12th graders (n = 974).A total of 2,432 students participated in the survey, and 1,872 of them completed the questionnaire, for a response rate of 77.0%. Their mean age was 15.0 ± 1.8 years, and 891 (47.6%) were boys. In terms of school grades, 48.0% of the students were 7th‐9th graders  and specificity (69.4%) to discriminate ADHD proneness Figure . The AURA total of 33 1.8%) adolescents were classified as the ADHD group based on CASS(S), and 57.6% of them were boys , and the AUROC was 0.897 (95% CI 0.845–0.949; Figure To assess the risk of ADHD in relation to total aggression scores, a multivariable analysis was conducted Table . Student4This study showed a significant association between adolescent ADHD proneness and aggression propensity. Among the subdomains of aggression, anger and hostility had stronger associations with ADHD proneness than did physical and verbal aggression.A recent study has reported that psychiatric disorders, especially ADHD, occur simultaneously with aggression in pediatric patients (Bartels et al., Anger and hostility indicate the affective and cognitive facets of aggression, while physical and verbal aggression constitute the instrumental facets of aggression (Reyna et al., The relationship between aggression and ADHD in adolescents is different from that in childhood. Hyperactivity is the most prominent among ADHD symptoms in childhood but decreases in adolescence (Fischer et al., Among baseline characteristics, obesity, alcohol consumption, GI trouble, and sleep problem were significantly associated with ADHD proneness in this study. The potential association between obesity and ADHD has already been reported in a meta‐analysis (Cortese et al., A limitation of this study relates to its cross‐sectional design. In addition, the prevalence rate of adolescent ADHD in our study was relatively lower than that of previous studies from 7.2% to 9.4% (Willcutt, The authors declare no conflict of interest.HJY, JMH and HSG have made substantial contributions to conception and design. Acquisition of data were performed by HJY, JMH and KK. Data analysis and interpretation were performed by GS, JY, JEC, and KEL. HJY and JMH have been involved in drafting the manuscript. The manuscript was revised by HSG. All authors reviewed and approved the final manuscript.https://publons.com/publon/10.1002/brb3.2030.The peer review history for this article is available at


Children fitted with hearing aids (HAs) and children with attention deficit/hyperactivity disorder (ADHD) often have marked difficulties concentrating in noisy environments. However, little is known about the underlying neural mechanism of auditory and visual attention deficits in a direct comparison of both groups. The current functional near-infrared spectroscopy (fNIRS) study was the first to investigate the behavioral performance and neural activation during an auditory and a visual go/nogo paradigm in children fitted with bilateral HAs, children with ADHD and typically developing children (TDC). All children reacted faster, but less accurately, to visual than auditory stimuli, indicating a sensory-specific response inhibition efficiency. Independent of modality, children with ADHD and children with HAs reacted faster and tended to show more false alarms than TDC. On a neural level, however, children with ADHD showed supra-modal neural alterations, particularly in frontal regions. On the contrary, children with HAs exhibited modality-dependent alterations in the right temporopolar cortex. Higher activation was observed in the auditory than in the visual condition. Thus, while children with ADHD and children with HAs showed similar behavioral alterations, different neural mechanisms might underlie these behavioral changes. Future studies are warranted to confirm the current findings with larger samples. To this end, fNIRS provided a promising tool to differentiate the neural mechanisms underlying response inhibition deficits between groups and modalities. Cognitive control develops continuously throughout childhood, and response inhibition plays an important role in ensuring that only appropriate responses are given ,2,3. TheIn addition, given that our everyday environment typically consists of complex multisensory features, and considering that audiovisual integration scaffolds cognitive development beyond language perception ,10,11, iIn ADHD, impairments of response inhibition are widely recognized as one core deficit of the diagnosis ,31,32. AThere is a need for studies utilizing simultaneous visual and auditory response inhibition paradigms to verify modality-(in)dependent mechanisms in TDC, and to clarify whether populations that exhibit or have an increased risk to develop behavior regulation difficulties show supra-modal or modality-specific deficits. To our knowledge, no study has directly compared auditory and visual response inhibition simultaneously in children with HL and children with ADHD. Disregarding the potentially different pathophysiology of response inhibition problems of both groups, this could provide insights into the variability of response inhibition difficulties across populations and sensory modalities. Therefore, the aim of the current functional near-infrared spectroscopy (fNIRS) study was the comparison of the behavioral performance and neural activity during an auditory and visual go/nogo paradigm of children with HL (not diagnosed with ADHD) and children with ADHD  to TDC. FNIRS is a versatile and non-invasive imaging technique that is less susceptible to motion artifacts than functional magnetic resonance imaging (fMRI). It is especially adequate for investigations of children with HAs and auditory tasks, as it is a quiet optical imaging technique for which the contraindications of fMRI do not apply . We expeM = 9.84, SD = 1.90) were included in the current study. Parental informed consent and children’s assent was obtained, and children were reimbursed for study participation. The study was approved by the local ethical committee (EK 188/15) and conducted in accordance with the Code of Ethics of the World Medical Association (Declaration of Helsinki). An unaided pure-tone audiometry was performed for all children with HAs within three weeks of study participation ; parental n = 52; teacher: n = 4 (in the HL group)) and the parental Child Behavior Checklist ). Children with ADHD treated with medication  were asked to stop their medication 24 h before participation. All children had normal or corrected to normal vision. Based on the unequal gender distribution  = 5.20, p = 0.07), we systematically controlled for an effect of gender in all behavioral analyses , 20 children with a previously assigned clinical diagnosis of ADHD (ADHD group) and 27 TDC (TD group) between the age of 6–13 years . irements . In the The multi-Ch ETG4000 optical topography system  was utilized to measure changes in oxygenated (∆HbO) and deoxygenated (∆HbR) hemoglobin concentrations. Measurements were recorded with a sampling frequency of 10 Hz and two wavelengths (695 and 830 nm). During the experiment, the children wore two × 3 × 5 probe sets that were placed symmetrically on each side of the head within an electroencephalography (EEG) cap . A total of 44 measurement Chs with 22 per probe set was placed at a Ch-to-Ch-distance of 3 cm. The receiving optode of the lowest row of each probe set  was positioned above the ear (above T3/T4 within the 10/20 system ), and thMetrics for signal quality control were the coefficients of variation (exclusion of HbO/HbR variations above 10% and exclusion of a variation difference between HbO and HbR exceeding 5% ) and excAfter quality control, the fNIRS data was preprocessed in MATLAB  with self-written scripts and scripts of the HomER2  = 5.20, p = 0.07) and a higher prevalence of male compared to female children with ADHD is frequently observed in clinically referred samples [The exclusion of participants due to poor Ch-quality led to a wide variation in group size and gender distribution between groups for the neural analyses. To account for the variation in group size in the neural analyses, the sample sizes of the ADHD and TD group were reduced while avoiding an unequal gender and age distribution. That is, three further male participants from the ADHD group and one male participant from the TD group were excluded , and gender as 2-level between-subject factor, as well as condition  as 2-level repeated within-subject factor. The interaction term of group-by-condition was included to explicitly evaluate whether the effect of condition varied between groups, or the effect of group between modalities. It should be noted that gender always remained in each model of the behavioral performance measures to take into account the unequal gender distribution between the groups. For the neural analyses, data analyses were conducted within the smaller sample consisting of n = 42 subjects, based on the gender matching procedure described in emmeans R package [2)Partial eta-squared  of all correct Go trials (Hits) and response variability . Prior to the analyses, RTs were log-transformed and RTs below 100 ms were excluded. Additionally, the speed-accuracy trade-off (SAT = correlation of z-transformed FA-rate and MeanRTgo), was analyzed by one-tailed Spearman’s rho, due to the expected negative relationship between RT and FA rates. Moreover, a study by van Belle, et al. [mu and sigma  as well as tau . The parameter estimates were determined by maximum likelihood estimation, using the R package retimes [For the behavioral data, separate independent LMMs were performed for the following DVs: FA rates , mean RTs . Due to the exploratory purpose of the current study, the smaller number of subjects included in the neural data analyses, and based on the decision to conduct Ch-wise comparisons of effects of condition, group and their interaction on activation patterns, we decided against correction for multiple comparisons (44 Chs). All neural analyses were therefore performed using LMMs with an uncorrected threshold of plotTopoMap function by Cui [t-tests).FNIRS activation maps per group and condition were created in MATLAB , using the modified n by Cui . The actp < 0.05 (uncorrected).Finally, exploratory analyses to assess brain-behavior correlations were conducted. Spearman correlations were computed between the FA rate and neural activation per group  and condition . Chs showing significant group or condition effects in the LMMs were entered into a correlation analysis. Results were considered significant with F = 60.43, p < 0.001, R2 = 0.51). Additionally, a group effect was revealed  = 3.64, p = 0.03, R2 = 0.11). Both children with HA  and children with ADHD  showed marginally higher FA rates than the TD group, while children with ADHD did not differ from children with HAs . Furthermore, male participants showed trend wise higher FA rates than female participants  = 3.41, p = 0.07, R2 = 0.06).An overview of all behavioral performance estimates per group and condition is given in go analyses, a group-by-condition interaction was identified  = 3.23, p = 0.047, R2 = 0.10). All groups showed lower RTs, i.e., faster reactions, in the visual than the auditory condition  = 76.38, p < 0.001, adjp < 0.001, R2 = 0.85; ADHD: F = 48.94, p < 0.001, adjp < 0.001, R2 = 0.72; TD: F = 165.18, p < 0.001, adjp < 0.001, R2 = 0.86). While groups did not differ in the visual condition (F < 1), a trend wise group effect on RTs was found in the auditory condition  = 3.81, p = 0.03, adjp = 0.06, η2 = 0.12). That is, children with ADHD showed faster reactions than TDC , but did not differ from children with HAs , which in turn were not distinguished from TDC .Next, using classical RTRTgo) was affected by condition  = 6.64, p = 0.01, R2 = 0.10) and group  = 3.20, p = 0.048, R2 = 0.10). RTs were more variable in the auditory than the visual condition. The ADHD group showed a marginally higher response variability than the TD group , while the HA group did not differ from the ADHD  nor TD  group.Response variability . TDC did not show a significant SAT in the visual condition , but only in the auditory condition .No significant SAT was identified for the two groups of interest  = 118.90, p < 0.001, R2 = 0.67) and group  = 6.43, p = 0.003, R2 = 0.18) on mu. Mu was smaller in the visual than in the auditory condition. Post-hoc comparisons of the group effect showed that children with ADHD reacted faster (lower mu) than the TDC . RTs of the HA group were marginally lower than the RTs of the TD group  and did not differ from the ADHD group . The group-by-condition interaction effect on mu was trend wise significant  = 2.83, p = 0.07, R2 = 0.09). This was due to the fact that the group effect was largely driven by the auditory  = 6.75, p = 0.002, adjp = 0.005, η2 = 0.19), in contrast to the visual condition  = 2.13, p = 0.13, adjp = 0.13, η2 = 0.07). Furthermore, according to sigma values of the ex-Gaussian distribution, response variability was higher in the auditory than the visual condition  = 39.12, p < 0.001, R2 = 0.40). Finally, for tau scores of the ex-Gaussian RT distribution, i.e., prolonged reactions, a main effect of condition  = 11.46, p = 0.001, R2 = 0.16) and group  = 4.59, p = 0.01, R2 = 0.14) was observed. All children showed higher tau scores in the auditory than the visual condition. Children with ADHD showed more inattentive responses than TDC . The HA group did not differ from the ADHD group  and were marginally more inattentive than the TD group .The comparison of the parameter estimates of the of the ex-Gaussian distribution yielded a significant effect of condition (t-tests). Descriptively, the activation maps of both children with HAs and children with ADHD differed from TDC: The HA group showed broader activation in the temporal cortex during the auditory condition and higher activity in the right inferior and left superior frontal cortex during the visual condition than TDC. Children with ADHD showed more diffuse activation patterns than TDC, with higher parietal activity and broader frontal activity, yet, lower, less focal recruitment of the right inferior prefrontal gyrus (IPFG).First, possible modality-specific  changes of HbO and HbR were inspected per group  by means of heat maps, depicting the neural activation of each condition contrasted against baseline  and the right frontopolar cortex showed higher ΔHbO in the visual than the auditory condition across groups. Contrary, higher ΔHbO in the auditory compared to the visual condition were revealed in the left pre-motor and supplementary motor area (pre/SMA), the left IPFG and right superior temporal cortex (STG). Moreover, the ADHD group showed higher ΔHbO than the TD group in the right supramarginal gyrus and the right primary somatosensory cortex. Only during the auditory condition, was a higher activation apparent in the ADHD group compared to the TD and HA group in the left supramarginal gyrus. Finally, while TDC showed no modality-specific activation in the right temporopolar region, the HA group showed higher ΔHbO in the auditory than the visual condition.Comparable to the ΔHbO, 4 Chs above the left DLPFC and right temporal areas revealed lower ΔHbR, thus likely demonstrating higher activation, during the auditory than the visual condition. Additionally, the ADHD group showed higher ΔHbR, thus likely lower activation, in bilateral parietal, and left temporal as well as frontal regions than the HA group, and lower activation than the TD group in the left STG and bilateral frontal areas, independent of modality. Finally, only during the auditory condition, children with ADHD showed higher ΔHbR, lower activation, than the HA and TD group in the right DLPFC. All the effects on ΔHbO/ΔHbR are listed in Brain-behavior correlations were revealed for the TD and ADHD group see . For theThe objective of the current study was to elucidate the neural basis of auditory and visual response inhibition in children with HL, fitted with bilateral HAs, and children with ADHD. In particular, it was examined whether a shared dysfunctional supra-modal or modality-specific neural activation could be identified that contributes to the inattentive and impulsive behavior compared to TDC.Generally, all children showed a higher FA rate and faster RTs in the visual compared to the auditory condition. In the present study, the response inhibition to nogo trials was thus superior in the auditory condition. Notably, reactions to auditory stimuli were however prolonged and highly variable. Previous studies similarly reported a high inconsistency and variability in responses to auditory stimuli, as reflected by an elevated omission rate and RT variability ,47.tau, independent of modality. Attention lapses of the children with HAs did not differ from the ADHD group either. The observed impulsive behavioral responses and elevated parental ADHD symptom ratings of the HA group are consistent with previous neuropsychological studies of children with HL [Despite the explicit exclusion of children with HAs with a diagnosis of ADHD, parental/teacher ratings of ADHD symptoms in the HA group were between the TD and ADHD group. In line with this, though contrary to our hypothesis, the current auditory and visual go/nogo task revealed that children with HAs did not differ from children with ADHD in their RTs or FA rates. Both the HA and ADHD groups showed faster, more impulsive reactions than TDC. Compared to the TDC, reactions were particularly faster during the auditory condition. The HA and ADHD groups, unlike the TDC, did not show a SAT in the auditory condition and therefore probably did not adjust their RTs as effectively in order to reduce FAs. While descriptively, FA rates for the HA group were particularly elevated in the auditory and for the ADHD group in the visual condition, both groups showed higher FA rates than the TDC across modalities. In addition, children with ADHD showed more attention lapses than TDC, as indicated by the ex-Gaussian parameter  with HL ,29. Desp with HL ,72. This with HL . The behAlthough the current neural findings should be inspected with caution due to the exploratory nature of the (uncorrected) analyses, the current study, to our knowledge, was the first to provide tentative indications of modality- and group-specific neural activations. While across groups, higher activity was detected in the temporal regions likely indicating auditory processing, differences between modalities beyond the temporal cortices were found, such as within the frontal cortex and the pre/SMA. The frontostriatal network, including the (inferior) frontal cortex and pre/SMA, plays a crucial role in response inhibition . The modNext to these modality-specific changes in HbO and HbR, the first indications of activation patterns specific to children with ADHD and specific to children with HL with bilateral HAs were found. While the ADHD group showed higher and less focal activation of right supramarginal and somatosensory cortices, lower activation in the left STG and bilateral frontal regions was observed. The observed effects were independent of stimulus modality. In particular, the largest effect, observed in the left IPFG (pars opercularis), and effects in other frontal regions that indicated higher ΔHbR, thus likely lower activation, in children with ADHD than TDC are in agreement with previous studies reporting a lower (right inferior) frontal activity in ADHD during response inhibition paradigms ,79,80,81Contrary to the ADHD group, the activation patterns of the HA group differed only from the TDC in the right temporopolar cortex. That is, children with HAs showed a modality-specific activation with higher activation during the auditory than the visual condition, whereas TDC showed a modality-independent activation pattern. The elevated activation during the auditory condition might reflect a higher effort required due to the HL to achieve a comparable performance level. Albeit poor response inhibition was observed in the HA group independent of modality, no supra-modal alteration in the activation patterns of the children with bilateral HL fitted with HAs were found. Yet, based on the current fNIRS probe configuration, we cannot rule out changes in neural activation entirely, since the amount of Chs utilized for the assessment was limited . FurtherThe current study provides first insights into the differences between auditory and visual response inhibition on behavioral and neural level across different pediatric samples. Hereby, fNIRS proved to be a suitable technique to investigate the current (auditory) task under a naturalistic and quiet experimental setting.The presented results, however, should be considered in the context of some limitations. Due to strict time constraints, we assessed auditory and visual response inhibition within one paradigm to allow both a direct comparison of the two modalities, and the comparison of the two groups of interest to TDC. This did not allow an event-related neural analyses and a contrast of cortical activation during nogo (successful/not successful) vs. go (successful/not successful) trials, due to the insufficient number of total trials. However, if response inhibition is considered the dominant mechanism underlying mixed go/nogo blocks ,83, the The current study provided first evidence for differences in response inhibition in children with HL and children with ADHD compared to TDC across and between the auditory and visual modality. Notably, children with HAs showed similar behavioral performance alterations in the go/nogo task to children with ADHD, suggesting that early sensory deprivation might put children at risk of developing response inhibition deficits. On the neural level, however, group-specific altered activation patterns compared to TDC were revealed, which might underlie the observed behavioral changes. While children with HL fitted with HAs mainly showed differences in neural activity during the auditory condition, children with ADHD showed alterations across modalities. The current study emphasizes the importance of neuropsychological investigations of visual and auditory response inhibition in children with HL. Furthermore, while the current study suggests that the observed behavioral difficulties appear not to be related to ADHD, the behavioral similarities between HL and ADHD warrant a careful screening of ADHD symptoms in children with HL to detect behavioral difficulties (in)dependent of ADHD, which consequentially, should be considered in rehabilitation programs. In addition, the current findings carry important implications for future ADHD investigations. Further studies examining complementary auditory to already existing visual paradigms in ADHD are warranted, as behavioral and neural alterations in response inhibition were found in both modalities within the current study. Replications with larger samples and different combined visual and auditory response inhibition paradigms are encouraged.


Bartonella bacilliformis (B. bacilliformis), Bartonella henselae (B. henselae), and Bartonella quintana (B. quintana) are bacteria known to cause verruga peruana or bacillary angiomatosis, vascular endothelial growth factor (VEGF)-dependent cutaneous lesions in humans. Given the bacteria’s association with the dermal niche and clinical suspicion of occult infection by a dermatologist, we determined if patients with melanoma had evidence of Bartonella spp. infection. Within a one-month period, eight patients previously diagnosed with melanoma volunteered to be tested for evidence of Bartonella spp. exposure/infection. Subsequently, confocal immunohistochemistry and PCR for Bartonella spp. were used to study melanoma tissues from two patients. Blood from seven of the eight patients was either seroreactive, PCR positive, or positive by both modalities for Bartonella spp. exposure. Subsequently, Bartonella organisms that co-localized with VEGFC immunoreactivity were visualized using multi-immunostaining confocal microscopy of thick skin sections from two patients. Using a co-culture model, B. henselae was observed to enter melanoma cell cytoplasm and resulted in increased vascular endothelial growth factor C (VEGFC) and interleukin 8 (IL-8) production. Findings from this small number of patients support the need for future investigations to determine the extent to which Bartonella spp. are a component of the melanoma pathobiome. Malignant melanoma is the sixth most common cancer reported by the Centers for Disease Control and Prevention (U.S. Cancer Statistics Working Group). Cutaneous melanoma maybe caused by a combination of sun exposure, genetic factors, and (as yet) unidentified environmental triggers . An umbrHelicobacter pylori to gastric cancer, Chlamydia pneumoniae with lung cancer, and Salmonella typhi with gallbladder cancer [Streptococcus bovis is associated with colorectal cancer [Bartonella. Importantly, there are numerous defined mechanism by which bacteria could contribute to the development of cancer [Signatures of bacterial infection, including detection of DNA, RNA, and lipopolysaccharides, have been reported in many human solid tumors . Recent r cancer . More rel cancer ,9. With l cancer ,11. In tl cancer ,13. Simil cancer ,15. An el cancer . They rel cancer . That stf cancer .Bartonella spp. are emergent and neglected bacteria of worldwide distribution [Bartonella spp. cause neurological symptoms, endocarditis, bacillary angiomatosis, bacillary peliosis, trench fever, and cat-scratch disease [B. bacilliformis in patients with verruga peruana, after acquiring the infection via cutaneous sand fly bites in South America [B. henselae has also been confirmed in association with immunocompromised cutaneous bacillary angiomatosis patients infected with HIV [Bartonella spp. can induce chronic intravascular infections in humans, including symptomatic and healthy immunocompetent individuals [Bartonella spp. [Bartonella spp. increase vascular endothelial growth factor C (VEGFC) secretion in association with cutaneous vasoproliferative tumor growth , which is also an important melanoma growth factor [Bartonella spp. exposure and infection in patients with cutaneous malignant melanoma. Our findings support the need for future studies to determine if Bartonella spp. are a prevalent component of the skin microbiome or if these bacteria contribute to the pathobiome leading to melanoma. ribution . In huma disease ,21,22. B disease . Histori America . Persistwith HIV , potentiividuals ,27,28. Iividuals ,30. Whatividuals ,29. For lla spp. ,29,31. Mh factor ,32. In tDemographic information, year of diagnosis, and patient reported co-morbidities for the eight malignant melanoma patients are included in Bartonella spp. serology and Bartonella Alphaproteobacteria growth medium (BAPGM) enrichment blood culture PCR results are summarized in B. henselae DNA was amplified and sequenced from blood or from BAPGM enrichment blood cultures from 3 of 8 melanoma patients . All patient DNA was subjected to both qPCR and conventional PCR (cPCR). Five patients were Bartonella spp. seroreactive, only one of whom was PCR/DNA sequence positive for B. henselae. The two remaining B. henselae PCR positive patients were immunofluorescence antibody assay (IFA) non-seroreactive at all screening dilutions to all four Bartonella spp. test antigens. B. henselae DNA was PCR amplified and sequenced from FFPE melanoma tissue blocks from patients 4 and 7.Previously, collected formalin-fixed paraffin embedded (FFPE) melanoma biopsy tissue from patients 4 and 7 were retrievable for hemi-nested PCR conducted at the University of Minnesota. Tissue sections from two patients, 4 and 7, FFPE tissue blocks were immunostained and examined using previously validated imaging protocols ,34. SectB. henselae and VEGF co-localized in the melanoma tissues from patients 4 and 7 , # 49882, Houston-1), had shorter dendritic processes as compared to non-infected melanoma cells -video of the co-culture was generated .Bartonella henselae co-cultured with melanoma cells induced production of VEGFC and interleukin 8 (IL-8)  . VEGFC wls alone a. IL-8 ccultures c.B. henselae. Importantly, B. henselae DNA was amplified and sequenced from enrichment blood cultures from patients 4 and 7 at North Carolina State University, and again years later from FFPE melanoma tissues at the University of Minnesota. For both of these patients, there was a 4-year time span between the initial tissue biopsy and the documentation of blood borne B. henselae infection.This study provides, serological and enrichment blood culture/PCR evidence that a subset of melanoma patients have been exposed to or are infected with Bartonella henselae DNA was amplified and sequenced from the blood or BAPGM enrichment blood cultures of three patients, two of whom were not seroreactive to any of the four Bartonella spp. IFA antigens. Previous studies have confirmed variation in the sensitivity of IFA assays depending upon the strain type used as antigen [Bartonella spp. bloodstream infections can be seronegative to the infecting species and strain used for IFA testing [ antigen ,37. In a testing ,40. WhetBartonella spp. can be difficult to detect by standard microscopic histopathological techniques [Bartonella spp. in the dermal lymphatics. Interestingly, Hong and colleagues using an experimental rat infection study found that B. tribocorum first invades the cutaneous lymphatics, prior to establishing intraerythrocytic and endothelial cell infections [Bartonella spp. appeared to co-localize with VEGFC within the lymphatic vessels. Interestingly, in addition to promoting endothelial cell proliferation, VEGFC plays a dominant role in lymphatic vessel growth [Bartonella spp., including B. henselae, stimulate VEGF production resulting in the proliferation of blood vessels [B. henselae also resulted in changes in cell morphology  contacted Dr. Breitschwerdt (infectious disease researcher) to pose the question: “Could Bartonella spp. infection be involved in the pathogenesis of cutaneous melanoma in people with minimal exposure to sunlight?” To initially address this question, blood from eight patients with a previous diagnosis of malignant melanoma were tested for serological or enrichment blood culture/PCR evidence of Bartonella spp. exposure/infection. Subsequently, the formalin-fixed, paraffin-embedded (FFPE) biopsy specimens from two of these patients were retrievable for molecular testing and attempted visualization of Bartonella spp. in their melanomas. Later, in an attempt to better understand our initial patient-oriented observations, a co-culture model using A375 melanoma cells inoculated with B. henselae was developed. The co-culture model facilitated visual localization of the bacteria and the use of assays to determine if the B. henselae influenced the cytokine expression of the cultured melanoma cells. For various reasons, these microbiological, imaging, and co-culture studies spanned a 7-year period from the time of blood collection and as long as 6 years from the time of initial melanoma diagnosis to initial microbiological testing.Given the documented association of Bartonella Species Infection among a Cohort of Healthy and Sick People) was obtained for the study and each individual provided a signed consent for testing and study participation. Dr. Reicherter submitted blood and serum samples from these eight melanoma patients to the Intracellular Pathogens Research Laboratory, Comparative Medicine Institute, College of Veterinary Medicine, North Carolina State University for Bartonella spp. serology and enrichment blood culture/PCR testing.During the month of August 2012, all patients previously diagnosed with melanoma that were being followed by a Dermatology Clinic in Oregon were offered the opportunity to participate in the study. Patients were included regardless of melanoma location, the time since initial diagnosis, and whether there had been reoccurrence or metastasis. Eight individuals agreed to participate in the study. Institutional Review Board approval  #1960, Detection of Bartonella spp. immunofluorescence antibody assay (IFA) serology (four independent IFA assays) was performed as previously described [Bartonella vinsonii subsp. berkhoffii, Bartonella henselae-Houston I and -San Antonio 2 strains and Bartonella koehlerae were used as antigens. Sera were screened at dilutions of 1:16, 1:32, and 1:64 and endpoint titer. Antibody titers of 1:64 or greater were considered seroreactive.escribed . Cell cuBartonella alpha-Proteobacteria growth medium (BAPGM) enrichment blood culture, as previously described [Bartonella spp. following DNA extraction from whole blood and from serum; (3)–(5) PCR following BAPGM enrichment of whole blood culture incubated for 7, 14, and 21 days; and (6) PCR from subculture isolates if obtained after sub inoculation from the BAPGM flask onto plates containing trypticase soy agar with 5% sheep blood that are incubated for 4 weeks. PCR specimen preparation, DNA extraction, and PCR amplification and analysis were performed in three separate rooms with unidirectional workflow to avoid DNA contamination. In addition, BAPGM cultures were processed in a biosafety cabinet with Hepa filtration in a limited access Biosafety Level III laboratory. PCR-negative controls were prepared using 5 μL of DNA from the blood of a healthy dog, and B. henselae (Houston 1 strain) at a concentration of 1 genome copy/ μL was used as a PCR-positive control during the entire course of this study. In no instance was B. henselae or DNA of any other Bartonella sp. amplified in the negative control lane on any PCR gel. To assess for potential contamination during blood sample processing into BAPGM, a non-inoculated BAPGM culture flask was processed simultaneously and in an identical manner with each batch of patient blood and serum samples tested. For all components of the BAPGM platform , PCR-negative controls remained negative throughout the course of the study. In addition, subcultures of non-inoculated BAPGM medium (culture control) at 7, 14, and 21 days did not yield bacterial growth. Aseptically obtained whole blood and serum specimens were tested by PCR and following escribed ,52. The Bartonella ITS region was performed using oligonucleotides 325s: 5′ CTT CAG ATG ATG ATC CCA AGC CTT CTG GCG 3′ and 1100as: 5′ GAA CCG ACG ACC CCC TGC TTG CAA AGC A 3′ as forward and reverse primers, respectively. Amplification was performed in a 25-µL final volume reaction containing 12.5 µL of MyTaq Premix , 7.5 µL of molecular–grade water, and 5 µL of DNA from each sample tested. Conventional PCR was performed in an Eppendorf Mastercycler EP Gradient® under the following conditions: a single hot-start cycle at 95 °C for 2 min followed by 55 cycles of denaturing at 94 °C for 15 s, annealing at 68 °C for 15 s, and extension at 72 °C for 18 s. Amplification is completed by an additional cycle at 72 °C for 1 min, and products were analyzed by 2% agarose gel electrophoresis with detection using ethidium bromide under ultraviolet light. Amplicons products were sequenced to establish species strain identification. Quantitative PCR screening of the Bartonella ITS region was performed using oligonucleotides 325s: 5′ CTTCAGATGATGATCCCAAGCCTTCTGGCG 3′ and 543as: 5′ AATTGGTGGGCCTGGGAGGACTTG 3′ as forward and reverse primers, respectively, and oligonucleotide BsppITS438probe: 5′ FAM-GGTTTTCCGGTTTATCCCGGAGGGC-BHQ1 3′ as TaqMan probe. Amplification is performed in a 25-µL final volume reaction containing 12.5 µL of SsoAdvanced™ Universal Probes Supermix , 0.2 µL of 100 µM of each forward primer, reverse primer, and TaqMan probe , 7.5 µL of molecular-grade water, and 5 µL of DNA from each sample tested. Quantitative PCR was performed in an CFX96® (Bio-Rad) under the following conditions: a single hot-start cycle at 95 °C for 3 min followed by 45 cycles of denaturing at 94 °C for 10 s, annealing at 68 °C for 10 s, and extension at 72 °C for 10 s. Amplification was completed by an additional cycle at 72 °C for 30 s. PCR negative controls were prepared using 5 µL of DNA from blood of a healthy dog. Positive controls for PCR were prepared by using 5 µL of DNA from a serial dilution (using dog blood DNA) of B. henselae genomic DNA equivalent to 0.1, 0.01, and 0.001 pg/µL. Positive amplification was assessed by analysis of detectable fluorescence vs. cycle values for qPCR. Positive amplicons products from either conventional or qPCR were sent for sequencing to establish species strain identification.Conventional PCR screening of Bartonella spp. The first round of PCR used previously published primers designed to amplify a region conserved in multiple species of Bartonella [Bartonella species using the Blast program. A 2mm cube of tissue was excised from each paraffin block with a new sterile blade and deparaffinized using two changes of xylene heated for 3 min to 56 °C between changes. Once the tissue was deparaffinized, DNA was extracted following the methods described for the AllPrep RNA and DNA Tissue kit from Qiagen . DNA was amplified using a Hemi-Nested PCR protocol for rtonella . These pBartonella henselae made in mouse at 1:100  plus anti-mouse IgG Alexa 488 made in donkey at 1:400 dilution (Jackson ImmunoResearch), anti-VEGFC made in goat at 1:200 , plus anti-goat IgG made in donkey conjugated to Alexa 568 at 1:800 (Jackson ImmunoResearch), and anti-LYVE1 made in rabbit at 1:400 , plus anti-rabbit IgG made in donkey conjugated to Alexa 647 at 1:800. Bartonella spp. made in chicken at 1:100 dilution , plus anti-chicken IgY conjugated to Alexa 568 at 1:400 dilution (Jackson ImmunoResearch), and nuclear dye TOPRO3 at 1:5000 . The anti-Bartonella spp. antibody recognized the gltA citrate synthase region, conserved in all Bartonella spp. The nuclear dye Syto9 at 20 micromolar  was used in Bartonella spp. antibody made in chickens is described in the supporting information Initially, approximately 2 × 2 × 2 mm blocks of lesional skin tissue were excised from the FFPE blocks with a new scalpel blade and the excised block pieces were deparaffinized . The tis2 at 37 °C. The green fluorescent protein (GFP) expressing plasmid pEGFP-C1 was transfected into A375 melanoma cells and selected using neomycin for a stable GFP expressing clone as previously described [4 cells/ml, after which the bacteria were directly added to the cell culture media of the A375 cells. The bacteria were added at a concentration of 5 × 105 cells per well. Media from triplicate wells of co-culture was collected at 24, 48, and 72 h post inoculation for cytokine analyses. For imaging, the A375-GFP cells were grown to confluence and then one plate was inoculated with B. henselae . The cells were fixed after 72 h of growth in the presence of B. henselae with 10% formalin for 30 min and then transferred to PBS. Then formalin fixed cells were immunostained with an antibody targeting Bartonella spp. and nuclear dye TOPRO3 or Syto9 and imaged by confocal microscopy. The cell line A375 was authenticated by IDEXX BioAnalytics  using short tandem repeat (STR) analysis in February 2020. The melanoma cell line A375 was obtained from the ATCC (# CRL-1619) and maintained in RPMI media supplemented with 10% fetal bovine serum in a humidified incubator with 5% COescribed . The melB. henselae were submitted for testing at the Cytokine Reference Laboratory . This is a Clinical Laboratory Improvement Amendments of 1988 licensed facility. Samples were analyzed for VEGF and IL-8, and tumor necrosis factor alpha  using the Luminex platform with multiplexing. The magnetic bead set was purchased from R&D Systems, Minneapolis, MN, USA. Samples were assayed according to manufacturer’s instructions. Fluorescent color-coded beads coated with a specific capture antibody were added to each sample. After incubation and washing, biotinylated detection antibody was added followed by phycoerythrin-conjugated streptavidin. The beads were read on a Luminex instrument , which is a dual-laser fluidics-based instrument. One laser determines the analyte being detected via the color coding; the other measures the magnitude of the PE signal from the detection antibody, which is proportional to the amount of analyte bound to the bead. Samples from all testing time points were run in duplicate for each of the assays. Values were interpolated using 5-parameter fitted standard curves.Samples of culture media supernatants collected at 24, 48, and 72 h from A375 cells inoculated with or without t-tests were performed using JMP statistical software . p-values were corrected to control the experiment-wise error rate using the Dunn-Sidak procedure [Student’s rocedure .Bartonella species infection among a cohort of healthy and sick people. Dr. Reicherter submitted blood and serum samples from eight melanoma patients who signed written informed consent to the Intracellular Pathogens Research Laboratory, Comparative Medicine Institute, College of Veterinary Medicine, North Carolina State University.All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutions and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. North Carolina State University (NCSU) Institutional Review Board (IRB 1960) provided ethical approval for this study. Written informed consent was obtained from the participants included in this study. The Institutional Review Board from North Carolina State University (IRB #1960) approved a research study investigating the detection of


Attention-deficit/hyperactivity disorder is frequently reported in individuals with Down syndrome, with considerable variation in the expression and severity of the symptoms. Despite growing evidence that gestational age predicts later symptoms of attention-deficit/hyperactivity disorder in the euploid population, this has not been studied in down syndrome. The current study is designed to investigate the influence of gestational age in later symptoms of attention-deficit/hyperactivity disorder in 105 individuals  with Down syndrome who were born at or after 35 weeks gestation. Maternal age at birth, maternal level of education, household income, as well as sex, chronological age, and cognitive level of the participant with Down syndrome were considered in our analysis. Results from this study show that gestational age is related to inattentive and hyperactive/impulsive symptoms in children and adolescents with Down syndrome. Therefore, gestational age should be addressed when considering symptoms of attention-deficit/hyperactivity disorder, as it may have implications for early interventions. More attention is needed toward the advancement of care and follow-up for infants with down syndrome who are born even late preterm or early term. A mean worldwide prevalence of ADHD of ~ 2.2% overall (range 0.1–8.1%) has been estimated in the general population aged < 18 years2, with a higher prevalence often reported in males3. ADHD is also commonly associated with other neurodevelopmental disorders such as down syndrome (DS), with research indicating a mean prevalence of ~ 36.3% overall (range 31–43.9%)6 and no differences in prevalence between males and females with DS5. Most of those with DS and a clinical diagnosis of ADHD are diagnosed as predominantly inattentive5. A challenge in interpreting such findings, however, is the extent to which these attention-related symptoms are invariably part of the DS phenotype or are better viewed as secondary comorbid challenges due to ADHD. The high prevalence of comorbid psychiatric conditions in DS7 may further complicate the proper diagnosis of ADHD because of the many overlapping symptoms. We propose, therefore, that it may be best to avoid categorical diagnoses and instead investigate dimensions of attention-related problems, characterized as continuous variables8, in relation to DS.Attention-deficit/hyperactivity disorder (ADHD) is characterized by inattention, including increased distractibility and difficulty sustaining attention, poor impulse control, and decreased self-inhibitory capacity, motor overactivity, and motor restlessness16, a key challenge is to identify mechanisms underlying this variability. In this vein, a study of 83 children and young adults with DS found no association between ADHD and age, sex, number of siblings, presence of heart disease, thyroid dysfunction, sleep disorders, or family history of ADHD5. Another study showed that ADHD symptoms in youth with DS were related to the dopamine receptor D4 gene on chromosome 1117 similarly to the euploid population19.Considering the variation in ADHD-like symptoms in the DS population and the high prevalence of other comorbid conditions20. Studies have shown that children born early preterm  are rated with more symptoms of ADHD, inattention, and hyperactivity/impulsivity than term-born children21. Various mechanisms explain the observed association between early preterm birth and ADHD symptoms, all based on a lack of brain development in utero relative to full term babies25. Some studies have shown that at gestational week 35, the weight of the brain is around 60% of what it will be normally at term26. In addition, children born prematurely are at higher risk for postnatal complications and are often exposed to factors that can promote neuronal damage27. Even children born late preterm  and early term  score higher on ADHD symptoms later in development compared to children born at gestational week 39 or later23. Some studies have shown that the negative association between gestational age (GA) and ADHD may be strengthened by factors such as young maternal age, maternal smoking during pregnancy28, and low levels of maternal education23. Also, sex has been shown to moderate the relationship between GA and ADHD symptoms in euploid preschoolers, with the association appearing to be stronger among girls21. Early maternal age at birth  has been associated with ADHD symptoms22. This same study found an incremental risk for ADHD with each declining week of gestation, even after adjusting for maternal age at childbirth22. These findings, which have implications for targeted early interventions in the euploid population, may also have implications for individuals with DS, irrespective of whether they are considered part of the DS-phenotype or a co-occurring condition.Drawing on studies in the euploid population, the association between prematurity and ADHD is well established30. This raises the possibility of even greater susceptibility to the negative effects of preterm and early term birth. The current study was designed to investigate the association between GA and later symptoms of ADHD in DS. The current study investigated this association in 105 children and adolescents with DS while taking into consideration potential confounding factors such as: chronological age (CA), sex, general cognitive level of participants with DS, maternal age at birth, maternal level of education, and family income.The fetal and neonatal brain in individuals with DS shows deviations from typical development. Whole brain and cerebellar volumes are smaller in DS from 21 weeks gestation, with cortical volumes deviating from that of the typically developing fetus around the third trimester34, a study of the cognitive and behavioral phenotype of individuals with Down syndrome and the factors influencing phenotypic variability. The study was conducted in accordance with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. Each site obtained their Institutional Review Board’s (IRB) approval to conduct the project. The progress of each site was monitored by the Emory Data Coordinating Center.Participants and measures reported in the present study are a subset of a larger multicenter project called The Down Syndrome Cognition Project (DSCP)Participants were recruited through clinics, community events/referral, conferences, advertisements, internet postings, and participation in past research projects. The participating mother provided written consent and participants with DS provided verbal or written assent (when capable) before collecting the data presented in this study.105 individuals participated in the present study; 49 males and 56 females; aged 6–18 years , all for whom English was the primary language spoken at home. Participants were included in the current study if full trisomy 21 had been verified by karyotype, the biological mother was available for participation, and CA of participants with DS was ≤ 18 years. Participants were excluded if they had other chromosomal anomalies, GA prior to 35 weeks, history of epilepsy or other seizure disorder, history of head injury, history of chemotherapy, accidental poisoning, untreated severe hearing or vision loss, or incident of loss of consciousness > 5 min.GA measured in weeks was reported by mothers, as was year of birth of mothers and year of birth of participants with DS. Information about previous ADHD diagnoses, ADHD medication, as well as other comorbid neurodevelopmental disorders, including ASD, was extracted from medical records if available and confirmed by mothers via maternal questionnaire. Maternal age (MA) at childbirth was computed as follows: year of birth of participant with DS–year of birth of mother. We also obtained socio-demographic information via maternal questionnaire as to the self-identified race/ethnicity of the participant with DS (defined by the participating mother), household income, paternal level of education, and maternal level of education.35 which reflects criteria for ADHD in the DSM-IV36 in individuals aged 6 -18. The Conners-3 contains two primary ADHD subscales (inattentive and hyperactive-impulsive) and other behavioral indices likely to co-exist with ADHD symptoms . In a normative sample, test–retest reliability coefficients ranged from 0.71 to 0.98, with strong discriminant validity between children with ADHD and other groups38. In a study of 154 children and adolescents with intellectual disability (ID), a Conners Parent Rating Scale total score of 42 provided a sensitivity of 0.9 and a specificity of 0.67 with an area under the curve of 0.84, with strong discriminant validity between children with ID with and without ADHD39. The parent version of the Conners-3 also has been used previously in other studies targeting ADHD symptoms of individuals with DS40, with mean T-scores consistent with diagnostic features of ADHD40. For our primary analyses, we used T-scores for the inattentive and the hyperactive-impulsive subscales as the primary symptoms of ADHD, as well as the global index T-score. Higher T-scores for each scale indicate more symptoms of ADHD endorsed by the parent informant.Symptoms of ADHD were assessed using the Conners Parent Rating Scale, Third Edition (Conners-3)41. The KBIT-2 assesses verbal and nonverbal cognition across a wide age range (4–90 years old). Our initial outcome was the KBIT-2 Composite IQ score (see Table 41. The formula used for age-correction was as follows: ((KBIT composite raw score/CA) × 100)44.This method is similar to that done for the Mullen Scales of Early Learning, another test of general cognition45, and, as is true for standard scores, this formula produces different adjusted scores for children of different ages who earn the same raw scores. The KBIT-2 age-corrected score showed no floor or ceiling effects, no correlation with CA (r = 0.1), and a strong correlation with the KBIT-2 IQ score (r = 0.9).General cognitive level was measured with the Kaufman Brief Intelligence Test, 2nd EditionThe first step consisted of a descriptive analysis of the sociodemographic and clinical parameters. Results are described using central tendency  and variability (standard deviation and range) for numeric variables, and absolute and relative frequencies for categorical variables in Tables p < 0.05. We then examined the contribution of GA to ADHD outcomes  in independent linear regression models. Multiple regression models were adjusted, when necessary, for potential covariates  to GA or an ADHD outcome, this covariate was included in the regression model). All predictors were added to each regression model simultaneously. The same analyses were conducted excluding participants taking ADHD medication to see if that impacted our results. Correction for multiple tests was performed to maintain a familywise alpha rate of p < 0.05.In order to decide whether our analyses needed to adjust for potential covariates, we first examined the association between GA and ADHD outcomes  for each of the following potential covariates: (1) CA of participant with DS at time of ADHD measurement, (2) KBIT-2 composite age-corrected score at time of ADHD measurement, (3) sex of participant with DS, (4) maternal age at birth, (5) maternal level of education and (6) family income. The computation of all correlations of interest was done using Pearson’s correlation coefficient for numeric variables and ANOVA models for categorical variables. Correction for multiple tests was performed in order to maintain a familywise alpha rate of 46. All analyses were performed using the statistical software package SPSS .Secondary analyses were conducted to rule out a possible link between CA of the participant and parental response bias on the questionnaires. We examined the association between CA of participant and the positive and negative impression scales from the Conners-3. In addition, in order to confirm that higher scores in the Conners-3 were related to ADHD, a one way-ANOVA was conducted with ADHD diagnosis (yes/no) as the independent variable and ADHD outcomes  as dependent variables. All the variables included in the models were normally distributed  and  for kurtosis). Correction for multiple comparisons was achieved by using the False Discovery Rate (FDR) procedureThe authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. Informed consent was obtained from the parent or guardian of each participant before testing.Table p = 0.01) and the Hyperactive-Impulsive subscale , as well as the Global Index of the Conners-3 . CA was not related to the positive  or the negative impression scores . In addition, the KBIT-2 composite age-corrected score at time of ADHD measurement was related to the Global Index of the Conners-3 . See supplementary Table We found no association of ADHD outcomes or of GA with maternal age at birth, maternal level of education, family income or sex of participants with DS. However, CA of participants with DS at time of ADHD measurement was related to T-scores for the Inattentive subscale  has been proposed as the main mechanism involved in long-term difficulties, including ADHD26. However, typically developing infants born even at a late preterm GA are at increased risk for morbidities in the immediate newborn period, including a higher rate of respiratory distress syndrome and transient tachypnea of the newborn when compared with term infants48. These problems could, in turn, lead to volumetric losses in specific brain regions and may partially explain the long-term difficulties related to ADHD symptoms21.The present study is unique in assessing association of GA at birth with ADHD-like symptoms at 6 to 18 years of age in a group of 105 individuals with DS. This retrospective study found that an earlier GA (limited to those with GA of 35 weeks or more) was associated with more symptoms of ADHD among children and adolescents with DS, after adjusting for CA and general cognitive functioning at time of ADHD measurement. Our results are in line with those studies of the euploid population showing that children born early term as well as those born late preterm scored higher on ADHD symptoms compared to children born at gestational week 39 or later29. Thus, we speculate that the effect of early GA on an already altered brain seen in DS may be greater than that for the euploid population. This would partly explain why we still see an effect of GA in long-term ADHD symptoms in our sample of late-preterm to full-term participants. Nevertheless, further longitudinal studies are needed to confirm this association and to examine the consequences of trisomy 21 molecular and behavioral levels. In contrast to the euploid population, the association between GA and long-term ADHD symptoms in DS was not more pronounced with inattention than with hyperactivity50. One reason for this difference might be the influence of trisomy 21 on brain development and its vulnerability to early GA. It could also be that we are not observing this differential pattern due to a lack of participants born early preterm and very early preterm in our sample relative to previous studies in the euploid population included50. Future studies should explore whether GA effects on ADHD symptoms in children and adolescents with DS by including those born before the 35th week of gestation.In the fetus with DS, differences in brain development and altered regional brain growth have been detected from 21 weeks of gestation when compared to controls; reduced cerebellar volume apparent in the second trimester, and significant alteration in cortical growth becoming evident during the third trimester, have also been reported52 and in the general population53. Taken together, these results suggest that although ADHD is chronic in nature, symptoms may present in different ways or in varying degrees as an individual moves through life stages54. One possible explanation may be that those with ID whose behavioral difficulties have been addressed over the years will have a range of learned strategies to use when ADHD-like symptoms become problematic55. However, it is important to note that our results are based on cross-sectional data and only participants from 6 to 18 years of age are included in our sample. In addition, we have no information on whether these families and their children have interventions to manage behavioral and cognitive difficulties typically observed in DS. Therefore, further longitudinal studies are needed to confirm the hypothesis that ADHD symptoms decrease over time in individuals with DS.Interestingly, the CA of the participants with DS was also related to ADHD outcomes. Our results showed that younger participants generally scored higher on inattentive, hyperactive, and general ADHD symptoms when compared to older participants. This finding is in line with previous research in DSImportantly, the relationship between GA and later ADHD symptoms was still significant after adjusting for CA at time of ADHD measurement, suggesting that GA contributes to the later ADHD symptoms in addition to CA at time of ADHD measurement. Because the effect size of GA limited to 35 weeks and older was small, it remains to be determined whether the contribution of GA to later ADHD symptoms is clinically meaningful. However, these preliminary findings strongly suggest that more studies are needed that include participants with GA below 35 weeks to better to understand the full impact of early GA.As expected, GA was not related to CA at time measurement, which rules out a potential confounding effect with ADHD symptoms. Therefore, this study adds to the growing body of evidence that indicates more attention needs to be paid toward the care and follow-up of infants born preterm, even those between GA of 35–39 weeks, perhaps even more so for those with DS.56. Note, however, that the CA of participants with DS in our study was not related to the negative or the positive impression score from the Conners-3. Therefore, the link between CA and the Conners-3 rating is not explained by a response bias in the parents. However, further longitudinal investigations are needed to understand the link between CA and ADHD symptoms in DS including different methods and environments of assessment.The fact that the degree of cognitive delay was not related to the main symptoms of ADHD suggests that hyperactivity, impulsivity and inattention-related symptoms in those with DS are not a consequence of the ID; therefore, ADHD difficulties may be best conceptualized as comorbid challenges. However, it is important to note that although general cognitive functioning was not related to subscales of hyperactivity, impulsivity or inattention, it was related to the CA of the participants with DS. Indeed, CA explained more of the variance in the outcomes of the Conners-3 than did GA. These results suggest that symptoms of inattention and hyperactivity/impulsivity as reported by parents are more severe in younger individuals with DS. Our results are in line with the statistics reported from the Centers for Disease Control and Prevention (CDC) stating a higher percentage of ADHD diagnoses for children aged 6–11 compared to those aged 12–1757; however, we had few mothers in the younger age range and thus would not have the power to identify this association. In addition, those studies showing a link between maternal age at birth and GA have included babies who were born before the 35th week of gestation58. Another interesting result of our study was the fact that the presentation and severity of ADHD symptoms was not related to sex, which is in line with previous research in DS52, but differs from the typically developing population59. In addition, the lack of association between the level of general cognitive functioning and the severity of ADHD symptoms is also in line with previous research conducted in individuals with DS4. Therefore, although attention deficits and the symptomatology associated with ADHD appear with greater frequency in people with DS62, ADHD-related symptoms in this population are not better explained by the degree of ID. Taken together, our results suggest the need for similar monitoring of ADHD symptoms in both males and females with DS, regardless of the level of ID, to ensure appropriate health care.Other factors included in the present study that have been shown to be likely to contribute to ADHD outcomes in the euploid population did not show a correlation in our study sample. These include sex and maternal age at childbirth. One reason may be related to the characteristics of our sample. For example, maternal age at birth of the participating mothers was between 25 and 45 years of age, and GA was ≥ 35 weeks. Previous studies have reported a link between younger maternal age at birth and later ADHD symptoms63. Bias may have occurred if the source of information to estimate GA is associated with both exposure (GA) and outcome (ADHD symptoms). Second, participants in the present study are part of a larger study (DSCP) in which GA < 35 was an exclusion criterion; including participants with GA < 35 would have increased our ability to examine the broader impact of fetal immaturity for those with DS. Our current results most likely underestimate this impact. Third, we relied on maternal reports of ADHD symptoms, which are not equivalent to a psychiatric evaluation. Finally, the current study is based on a cross-sectional evaluation of ADHD symptoms in relation to CA at time of ADHD symptom measurement.This study has several limitations. First, different methods are used to determine GA, for example, prenatal ultrasound or date of last menstrual periodIn summary, findings from the current study are promising but need to be considered as preliminary, suggesting that GA plays a role in the later emergence of ADHD symptoms in children and adolescents with DS. Therefore, more attention must be focused on the advancement of care and follow-up for infants with DS who are born even late preterm or early term. Further longitudinal studies including other perinatal , other methods of ADHD assessment and behavioral measures , as well as including individuals with GA < 35, are needed to further explore the effects of fetal immaturity in future development for those with DS.Supplementary Tables.