Supplemental Digital Content is available in the text Attention-Deficit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder, characterized by age inappropriate and impairing levels of inattention and/or hyperactivity/impulsivity. Pharmacotherapy is an important part of the ADHD multimodal treatment. The extent to which ADHD is pharmacologically over or under treated worldwide is controversial. We aimed to estimate the pooled worldwide rate of ADHD pharmacological treatment in individuals with and without the disorder.We will include published or unpublished studies reporting the rates of ADHD pharmacological treatment in participants with and without ADHD of any age group. Population-based, cohort, or follow-up studies, as well as data from insurance health system and third-party reimbursements will be eligible. Searches will be performed in a large number of electronic databases, including Medline, Embase, CINAHL, Cochrane, PsycINFO, Web of Science, and Scopus. The primary outcome will be the prevalence of ADHD pharmacological treatment in individuals with ADHD and without ADHD. Two independent reviewers will perform the screening, and data extraction process. Study quality/bias will be assessed with the Newcastle–Ottawa scale by 2 independent reviewers. To test the robustness of the findings, we will perform a series of sensitivity and meta-regression analysis. Analyses will be performed with R and STATA software.No IRB approval will be necessary. The results of this systematic review and meta-analysis will be presented at international conferences and published in peer-reviewed journals.PROSPERO 2018 CRD42018085233. The ADHD worldwide prevalence is estimated at around 5% and 2.5% in children/adolescents and adults, respectively.–4 Hyperkinetic disorder (HKD) as per the International Classification of Diseases, tenth edition is a more restrictive syndrome, requiring symptoms and impairment in both the inattention and hyperactivity-impulsivity domains, thus roughly equivalent to DSM-5 ADHD combined presentation. Its prevalence is estimated at around 2%.Attention-Deficit/Hyperactivity Disorder (ADHD), one of the most common neurodevelopmental disorders, is characterized, as per the Diagnostic and Statistical Manual of Mental Disorders, fifth edition,–9 at least for severe cases, or as a treatment strategy for patients who have not responded to nonpharmacological interventions.,11 Medications for ADHD include psychostimulant  and nonpsychostimulant drugs .Pharmacotherapy is part of the multimodal therapeutic strategy for ADHD and it is recommended as the first-line option in the most commonly used guidelines/practice parameters, and, related to this, if it is under or over treated with medications. Indeed, evidence from several countries shows that there has been an increase, over the last decades, in the prescription rate of ADHD medications.–16 However, to what extent the increase in prescription rates can be considered an “overprescribing phenomenon” remains to be elucidated.Currently, there is a controversy as to whether ADHD is under or over diagnosed prescription rates of ADHD medications would be expected at minimum around 2%. On the one hand, prescription rates higher than the worldwide prevalence of a more flexible ADHD definition, i.e. the DSM definition (5.9%–7.1%) would necessarily indicate an overtreatment, with possible unnecessary side effects. On the other hand, prescription rates lower than the prevalence of ADHD according to the more conservative ICD  definition (2%) would suggest that a portion of patients with ADHD are not benefitting from potentially useful medications. Indeed, ADHD may result in several serious consequences if left untreated. Children and adolescents might present a 1.53 risk of being unintentionally uninjured than controls. Similarly, the risk for car accidents for ADHD licensed drivers was found to be 1.36 times higher than for non-ADHD. As a consequence, the disorder is associated with a mortality rate of 5.85 per 10,000 person-years, mostly caused by accidents, whereas the rate in nonaffected subjects is around 2.21 per 10,000 person-years. Evidences show that the pharmacological treatment for ADHD can positively impact patients’ lives. Regular treatment can lower the risk of substance use among hyperactive/impulsive and combined subtypes, as well as the risk of car accidents,,24 unintentional injuries, emergency department visits, depression, and suicide. The medication can also benefit school work, classroom behavior, and reduce rates of criminality.Additionally, regardless of the possible increased prescription rate, it is not clear to which extent all individuals with ADHD, who would benefit from a pharmacological treatment of ADHD, indeed receive prescriptions of ADHD medications. Considering that some guidelines such as the National Institute for Health and Clinical Excellence (NICE) only recommend a pharmacological treatment for the most severe form of ADHD ,Therefore, addressing the question: “is ADHD under or over treated worldwide?” is a major public health need. To our knowledge, no systematic review with meta-analysis has been conducted to estimate the pooled rates of ADHD medications prescription worldwide. We aimed to fill this important gap in the literature. Here, we present the protocol of this systematic review/meta-analysis.2 to treatment in clinical trials.The overarching aim of this systematic review and meta-analysis is to estimate the worldwide prevalence of ADHD pharmacological treatment. We aimed to address the following primary questions: What is the prevalence of individuals with ADHD receiving and not receiving pharmacological treatment? What is the prevalence of individuals without ADHD receiving and not receiving ADHD treatment? Is there any significant difference in the rates of ADHD pharmacological treatment worldwide? In addition, we also aimed to address the following secondary questions: Are ADHD patients receiving doses of medications as recommended in international guidelines? What is the prevalence of individuals treated with ADHD medications for 3 or more weeks? We choose this time length based on the minimum time of response and efficacy3 and the Meta-Analysis of Observational Studies in Epidemiology (MOOSE). This protocol has been registered in the International Prospective Register of Systematic Reviews (PROSPERO), ID: CRD42018085233.The proposed systematic review and meta-analysis will be developed in accordance with the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA),3.13.1.1We will include published and unpublished population-based, cohort, or follow-up studies (independent of the length of treatment). Data from insurance health system and third-party reimbursements will also be eligible. For longitudinal studies, we will include data from the first wave, when available, or at the earliest time point. Randomized and nonrandomized clinical trials and studies only reporting prevalence or prescription rate of ADHD treatments without an ADHD diagnosis will be excluded.3.1.2 DSM-III, III-R, IV, IV-TR or 5, (any subtype) or ICD-9, and 10, or according to diagnostic instruments ; the presence of symptoms above a prespecified threshold on a validated ADHD questionnaire ; diagnosis of ADHD reported by participants and/or their caregiver ; diagnosis recorded in medical files or registers from health care agencies.Individuals from all age groups  with a primary diagnosis of ADHD, ADHD-NOS (not otherwise specified), and ADHD-U (unspecified) or HKD determined as follows: categorical diagnosis as per DSM-II,some ADHD participants with psychiatric comorbidities will be retained. However, we will exclude studies where all participants have ADHD plus one or more psychiatric comorbidities, since this may impact the rate of ADHD medications prescriptions . Similarly, studies that included some ADHD patients with IQ (intelligence quotient) lower than 70 or with neurological comorbidities will be accepted. If feasible, a sensitivity analysis excluding studies in which some participants have IQ < 70 and/or psychiatric/neurological comorbidities will be performed. Studies reporting ADHD medication misuse and abuse will be selected only if participants were accessed for ADHD diagnosis as described above.Studies including Controls will be considered as those individuals without any neuropsychiatric diagnosis.3.1.3 American Academy of Pediatrics, Canadian Attention Deficit Hyperactivity Disorder Resource Alliance, The European Network Adult ADHD, European Network for Hyperkinetic Disorders, and the National Institute for Health and Care Excellence,that is, psychostimulants  and, among nonpsychostimulants, atomoxetine. In the case of studies not reporting the number and/or percentage of ADHD individuals with/without treatment, we will contact study authors via e-mail to gather these data.We will consider studies on first and second line ADHD medications, according to the most commonly used international guidelines: American Academy of Child and Adolescent Psychiatry,We will exclude studies where the method to diagnose ADHD is not clear, even after contacting/attempting to contact the authors. We will also exclude studies using the pharmacological treatment of ADHD as a proxy for diagnosis since this will create a clear, misleading tautological approach to answer our research questions .3.1.4The primary outcome will be the worldwide prevalence of treatment with psychostimulants or atomoxetine in subjects with or without ADHD, ADHD-NOS (not otherwise specified) or ADHD-U (unspecified). For “treatment,” we will consider 2 approaches: any reported dose of the ADHD medications, and only the use of ADHD medications for 3 weeks or more.The secondary outcomes are prevalence of individuals receiving the recommended doses according to the international guidelines and, if feasible, the prevalence of ADHD medication use, considering treatment for 3 weeks or more.3.2Searches will be performed by a health Librarian at the University of Southampton, UK, who will work along with the authors to develop the search strategy. The search will be performed on the following databases using the same keywords and amending the Subject Heading as appropriate: Medline, Embase, CINAHL, PsychINFO, Web of Science, and Scopus. . The Pubmed syntax used will be:  OR adhd OR ADHD OR addh OR ADD OR attention deficit (disorder∗ OR syndrome∗) (hyperactiv∗ OR hyperkinetic∗) OR (MH “Attention Deficit Disorder with Hyperactivity) AND  OR  AND (cohort n (study or studies)) OR ”cohort analy∗“ OR (follow up n (study or studies)) OR ) OR longitudinal OR retrospective OR  OR (”cross section“ n [study OR studies]) OR ”cross sectional“ OR ”follow up“ OR [MH Health Care Surveys]) AND  AND ).3.2.1http://library.soton.ac.uk/resources): Business Source Premier; Research Starters; SciELO; AMED; Cochrane Database of Systematic Reviews; PsyArticles; Teacher Reference Centre; Eprints Soton; British Library Ethos; Science Citation Index; Social Sciences Citation Index; Science Direct; OAster; ERIC; SocIndex with Full text; Sports Discuss; RePec; Green File; PsycCRITIQUES. We will also search 25 additional sources . For this search, the following keywords will be used: “ADHD,” “prevalence,” “survey,” “trend,” “pharmacological,” “medication,” “epidemiology,” “attention deficit,” where only simple searches could be undertaken. We will not use any language or date restrictions.Using only keywords, the following databases will be searched as part of the University of Southampton EBSCO Discovery Portal . Two independent reviewers (LT and RM) will conduct the screening of titles and abstracts. Selected titles will have the full text included for a careful reading by 3 independent reviewers , thus ensuring that the study really fulfil the inclusion criteria. In this process, a third experienced researcher (CRMM) will evaluate and resolve any disagreement in the process whenever is necessary.After the search process, all abstracts will be uploaded to Covidence software  and a data extraction sheet. Independent reviewers working in pairs (LT and RM) will collect and compare the data extraction sheets. Discrepancies in the process will be resolved between the 2 reviewers. In case of no consensus, 3 senior researchers  will resolve the disagreement in the process. At this phase, authors from the selected studies will be contacted for additional information or clarification whenever necessary. After 3 failed attempts to contact the authors via e-mail, the study will be discarded.Studies reported in more than one publication will be identified as one entrance, and we will provide an appropriate description in the text. In these cases, the preference will follow this order: the first publication of the study, the largest sample size, and the most complete data.Reviewers will collect a pilot sample of 10 studies in order to test the integrity of the process of collecting and analysing the data.To assure the integrity of the data collection process, 2 independent reviewers (CRMM and GCAM) will transfer the data from extraction sheets to Excel tables, which will pass by a double-conference process. Discrepancies in this process will be resolved between the 2 reviewers.3.4The following information will be extracted:1.Study: Author, year of publication, country, continent, year of data collection, name, if any, given to the sample , and study design.2.Patient: age range, age mean, gender (n and %), method of diagnosis (physician/reported by caregivers), diagnostic criteria (DSM/ICD), comorbidities (% and type), co-medication, name of diagnostic questionnaire and rating scale (if described in the paper), socioeconomic status, level of care .3.Intervention: medication class and formulation, dose range, mean dose , and length of treatment .4.Primary outcomes: the total number of participants with ADHD, ADHD-NOS, ADHD-U and non-ADHD diagnosis receiving and not receiving ADHD pharmacological treatment, number of participants without any ADHD diagnosis receiving and not receiving ADHD pharmacological treatment.5.Descriptive information: type of diagnosis , the presence of comorbidities, Type (stimulant/nonstimulant) and the generic name of medication , and level of care .3.5 which is one of the most used methods to evaluate study quality of nonrandomized studies, as described in the Cochrane Handbook. With reference to a modified version used elsewhere, we will use the first 2 domains for the selection of the study groups and the comparability of the groups, as the third domain (exposure) does not fit for systematic reviews of prevalence studies. All four subitens from the selection domain can be rated 0 up to 1 point, whereas the comparability can be rated 0 up to 2 points. In total, each study can receive a minimum of zero  to a maximum of six points  We will use a modified version of the Newcastle–Ottawa scale (NOS),Two authors will independently access and score individually each study included. In a second step, results will be compared and in case of discordances without agreement, a third author (CRMM) will act as an arbitrator.3.6The authors will present a qualitative synthesis of data collected, a PRISMA flowchart, and tables. Additionally, the results of the meta-analysis and meta-regression analysis, if feasible, will be presented in the main text, forest plots and tables, respectively.To deal with incomplete or missing data, we will contact study authors to ask for additional information. However, to avoid zero cases, the Cochrane Collaboration-recommended approach of including 0.5 will be applied. Next, according to the distribution rate of normality tests, the best estimation method will be chosen and the Metaprop function will compute the independent prevalence rate and 95% confidence interval. As heterogeneity between the selected studies is expected, we will conduct a meta-analysis with the DerSimonian and Laird method of random-effect model using the pooled prevalence of pharmacological treated and untreated ADHD subjects. Heterogeneity between studies in the meta-analysis will be evaluated with the Cochran's chi-squared test (Cochran's Q), and the I2 where the interpretation is the following:Meta-analysis of odds ratios (OR) will be performed with the Meta package of R software, and normality tests will be accomplished. If feasible, results will be presented as adjusted and unadjusted ORs. We will first perform normality tests with the study rates, using Log, Logit, and Freeman-Tukey Double Arcsine transformation.0%–40%: heterogeneity might not be important30%–60%: may represent moderate heterogeneity50%–90%: may represent substantial heterogeneity75%–100%: substantial heterogeneity.Publication bias will be explored through the visual inspection of the funnel plot asymmetry, and Egger's linear regression test.3.6.1To explore the effect of individual studies in the prevalence rate and in heterogeneity, we will use the jackknife sensitivity analysis. The jackknife method is a usual procedure in the meta-analysis to test the stability of the results. The procedure is done by computing the results of the meta-analysis removing a different study at a time and then repeating the analyses.In addition, we will conduct a random-effects meta-regression analysis using the pooled prevalence of ADHD pharmacological treatment of ADHD subjects. The covariates to be used will be: continent where the study was performed, age group , the method of diagnosis , pediatrician, or a psychiatrist), diagnostic criteria (any version of DSM or ICD), class of pharmacological treatment (stimulant/nonstimulant), level of care , and study quality . The meta-regression analysis will be conducted with R and STATA 13.0 software.4This is a systematic review and meta-analysis; therefore, no IRB  approvals will be necessary. The competing interests are reported in the appropriate item, where all the authors stated their conflict of interests. The results of this study will be published in peer-reviewed journals, and conferences.CRMM conceived the study and drafted the protocol. RM, LT, GCAM, FC, SC, and LAR, contributed to the protocol design. CRMM and SC conceived the search strategy. All authors contributed to the development of inclusion and exclusion criteria. All authors read, contributed, and approved the final manuscript.Conceptualization: Carlos Renato Moreira-Maia, Samuele Cortese, Luis Augusto Rohde.Investigation: Rafael Massuti, Luca Tessari, Fausto Campani, Glaucia Chiyoko Akutagava-Martins.Methodology: Carlos Renato Moreira-Maia, Samuele Cortese, Luis Augusto Rohde.Project administration: Carlos Renato Moreira-Maia.Writing – original draft: Carlos Renato Moreira-Maia, Samuele Cortese, Luis Augusto Rohde.Writing – review & editing: Rafael Massuti, Luca Tessari, Fausto Campani, Glaucia Chiyoko Akutagava-Martins.


ADHD diagnosis at T1 was strongly associated with development of psychotic symptoms at T2  and psychotic disorder . Our findings that inattention symptoms and the diagnosis of ADHD are associated with subsequent psychotic outcomes in 22q11.2DS have important clinical implications. Future studies examining the effects of stimulant and other ADHD treatments on individuals with 22q11.2DS are warranted.Individuals with 22q11.2 Deletion Syndrome (22q11.2DS) are at substantially heightened risk for psychosis. Thus, prevention and early intervention strategies that target the antecedents of psychosis in this high-risk group are a clinical priority. Attention Deficit Hyperactivity Disorder (ADHD) is one the most prevalent psychiatric disorders in children with 22q11.2DS, particularly the inattentive subtype. The aim of this study was to test the hypothesis that ADHD inattention symptoms predict later psychotic symptoms and/or psychotic disorder in those with 22q11.2DS. 250 children and adolescents with 22q11.2DS without psychotic symptoms at baseline took part in a longitudinal study. Assessments were performed using well-validated structured diagnostic instruments at two time points  and T2 ). Inattention symptoms at T1 were associated with development of psychotic symptoms at T2 (OR:1.2,  Approximately 1 in 4000 individuals are affected by 22q11.2DS, rendering this the most common chromosomal microdeletion syndrome . While tNumerous studies of individuals with 22q11.2DS have observed a range of psychiatric and cognitive problems in childhood and adolescence; that is, prior to the typical age of onset for psychosis. These include anxiety disorders, Autism Spectrum Disorder (ASD) and intellectual disability . Attenti22.1n = 73) were excluded from the main analyses but included in sensitivity analyses .The International 22q11.2 Deletion Syndrome Brain Behavior Consortium (IBBC) was established in 2013 with the aim of harmonizing existing well-characterized cohorts of participants with 22q11.2DS with both phenotypic and genotypic data available . For theThe study was approved by the appropriate local ethics committees and institutional review boards. Each participant and his or her caregiver, when appropriate, provided informed written consent/assent to participate prior to recruitment.2.2Assessments were conducted using well-validated structured diagnostic instruments . ADHD sy2.3Standardized IQ scores were available across the sites using age-appropriate Wechsler scales and were examined as confounders. Taking into account that intellectual disability is frequently present in 22q11.2DS, some sites assessed the presence/absence of ADHD symptoms taking into account whether the individual with 22q11.2DS had intellectual disability. To account for this, we included ‘site assessment differences’ as a covariate variable. We also included age at baseline and sex as covariates.2.4Logistic regressions were conducted to examine whether T1 inattention symptoms and ADHD diagnosis (independent variables) predicted T2 outcome (dependent variable) status . We repeated the analyses by also including age, sex, IQ and the variable ‘site assessment differences’ (see confounders above) as covariates. We also examined whether longitudinal change in inattention symptoms and ADHD diagnosis were associated with psychotic symptoms and/or any psychotic disorder at T2. Change in inattention symptoms in relation to psychotic symptoms and psychotic disorder was examined using principal components analysis (PCA) following previously reported methods . The PCA33.1The sample started with a total of 323 individuals  aged 11.8 years at the first assessment (SD = 3.3) and 15.1 years (SD = 4.0) at the second assessment. Excluding 73 participants who reported psychotic symptoms at T1, our final sample included 250 individuals  with complete data on psychotic symptoms and ADHD diagnosis and 188 individuals  with complete data on psychotic symptoms and inattention symptoms . The mea3.2p = 0.01 and OR = 4.5, p < 0.001 respectively) (p = 0.15). ADHD diagnosis at T1 was associated with psychotic disorder at T2   . There w = 0.02) .Table 3Ap = 0.27) or with psychotic disorder at T2  (Table S2). There was weak evidence for associations between total ADHD symptoms (i.e. hyperactive-impulsiveness and inattention symptom scores combined) and development of T2 psychotic symptoms  but no evidence for associations with psychotic disorder at T2  (Table S2).Sensitivity analyses revealed no association between T1 hyperactive-impulsiveness symptoms at T1 and psychotic symptoms at T2 . We found significant age and IQ differences, with the group reporting psychotic symptoms at T1 being older than the group without psychotic symptoms at T1 and of lower mean IQ score. There were no significant mean differences in terms of inattention symptoms and ADHD diagnosis.Table S4 shows the summary statistics for change in inattention symptom levels and ADHD diagnosis over time in relation to psychotic symptoms at T2. There was no evidence that change over time in inattention symptom levels or ADHD diagnosis was associated with psychotic symptoms or psychotic disorder at T2 . Results4In the largest longitudinal study examining the presence of ADHD symptoms and diagnosis in individuals with 22q11.2DS to date, we observed that inattention symptom levels and ADHD diagnosis predicted the development of psychotic symptoms and were weakly associated with psychotic disorder. Moreover, we found that the presence of inattention symptoms at any time point rather than the change in inattention symptom levels over time was associated with psychotic symptoms. The evidence was weaker for the outcome of psychotic disorder, but this is likely due to low power, since in this young sample (mean age 14.3 years) only 6% were diagnosed with psychotic disorder.These longitudinal findings are in accordance with our previous study that found cross-sectional associations between inattention symptoms and psychotic symptoms in individuals with 22q11.2DS . PreviouThere are a number of potential explanations for our findings. One is that the 22q11.2 deletion increases risk for inattention symptoms and ADHD, which in turn increase risk for psychotic outcomes . AnotherOn the other hand, we did not observe cross-sectional associations between inattention symptoms/ADHD diagnosis and psychotic symptoms at T1. ADHD diagnosis was equally comorbid in those with and without psychotic symptoms and the mean levels of inattention symptoms were similar between the two groups. A previous study that examined the dimensional structure of a wide spectrum of psychopathology in 22q11.2DS has found evidence of a general psychopathology factor in addition to more specific factors  . TherefoWe did not observe association between hyperactive-impulsive symptoms and psychotic outcomes, which accords with cross-sectional studies of 22q11.2DS  and popu4.1Our study is the first to show that inattention symptom levels and ADHD diagnosis in those with 22q11.2DS are associated with later emerging psychotic outcomes. If inattention and ADHD are risk factors for future psychosis, then effective treatment is a priority for reducing the risk of psychosis in this high-risk group. However, if ADHD is a prodromal feature of psychosis in this group, then taking into account that stimulant medication is often prescribed for ADHD, future studies are needed to examine potential effects of such treatment in individuals with 22q11.2DS. A randomized controlled trial in thirty-four children with 22q11.2DS and ADHD indicated that methylphenidate can be safe and effective after a 6-month treatment and led to a 40% reduction of ADHD symptoms as reported by parents . InteresAlthough the link between ADHD and psychosis is not adequately studied , our fin4.2Although this study benefitted from recruitment of a number of sites of the 22q11.2 IBBC, resulting in a relatively large sample, the study may have been underpowered for some analyses . Moreover, the mean age at follow up was 14.3 years and therefore the individuals with 22q11.2DS had not yet passed the peak age of onset for schizophrenia. Therefore, the associations that we report are likely to represent an underestimate. Another limitation is that we could not consider the impact of medication, since at the time of this analysis medication information was not consistently reported from all sites. However, failing to adjust for medication is more likely to have attenuated the magnitude of association between ADHD symptoms and psychotic outcomes. Although the assessments were conducted by experienced clinicians and psychologists, we cannot exclude the possibility of diverse diagnostic practices across sites that might have influenced our findings. However, we attempted to account for differences between centres in our analyses and did not find that site assessment differences explained our findings. Ascertainment bias is also likely, considering that genetic testing was conducted on the basis of a phenotype that was sufficient to warrant genetic testing . Finally, taking into account that comorbidity is common in 22q11.2DS, it could be that other disorders , in addition to ADHD, might be longitudinally associated with psychotic outcomes in 22q11.2DS. However, this question was outside the remits of this study. Also, it could be argued that ADHD is more easily amenable to symptom reduction by treatment than other potential clinical risk factors for psychosis in 22q11.2DS . Interestingly, a recent study on 89 children with 22q11.2DS did not find longitudinal associations between autism spectrum disorders and psychosis .4.3Our study is the first to examine the longitudinal associations between ADHD symptoms and psychotic outcomes in 22q11.2DS. Our findings that inattention symptoms and ADHD diagnosis were associated with subsequent psychotic symptoms and psychotic disorder in 22q11.2DS have important clinical implications. Future studies examining the effects of ADHD medication in individuals with 22q11.2DS are warranted.Study concept and design: Maria Niarchou, Anita Thapar.Acquisition of data: Maria Niarchou, Marianne B.M. van den Bree, Samuel J.R.A. Chawner, Ania M. Fiksinski, Jacob A.S. Vorstman, Maude Schneider, Stephan Eliez, Marco Armando, Maria Pontillo, Donna M. McDonald-Mcginn, Beverly S. Emanuel, Elaine H. Zackai, Carrie Bearden, Vandana Shashi, Stephen Hooper, Michael J. Owen, Raquel E. Gur.Analysis of data: Maria Niarchou, Naomi Wray, Marianne B.M. van den Bree, Anita Thapar.Interpretation of data: Maria Niarchou, Naomi Wray, Marianne B.M. van den Bree, Anita Thapar, Michael J. Owen, Raquel E. Gur.Critical revision of the manuscript for important intellectual content: All authors.National Institute of Mental Health grants USA U01MH101719, U01MH0101720, Wellcome Trust Fellowship (M.N. 110222/Z/15/Z), R01 MH085953 (CEB), U54 EB020403 (CEB), Swiss National Science Foundation (324730_144260) to SE, National Center of Competence in Research (NCCR) “Synapsy-The Synaptic Bases of Mental Diseases” (51NF40-158776) to S.E.This study was funded by the The funding sources had no participation in any of the aspects of this study .None reported.


Purpose: Although alterations in resting-state functional connectivity between brain regions have been reported in children with attention-deficit/hyperactivity disorder (ADHD), the spatial organization of these changes remains largely unknown. Here, we studied frontal–parietal attention network topology in children with ADHD, and related topology to a clinical measure of disease progression.Methods: Resting-state fMRI scans were obtained from New York University Child Study Center, including 119 children with ADHD  and 69 typically developing controls . We characterized frontal–parietal functional networks using standard graph analysis (clustering coefficient and shortest path length) and the construction of a minimum spanning tree, a novel approach that allows a unique and unbiased characterization of brain networks.Results: Clustering coefficient and path length in the frontal–parietal attention network were similar in children with ADHD and typically developing controls; however, diameter was greater and leaf number, tree hierarchy, and kappa were lower in children with ADHD, and were significantly correlated with ADHD symptom score. There were significant alterations in nodal eccentricity in children with ADHD, involving prefrontal and occipital cortex regions, which are compatible with the results of previous ADHD studies.Conclusions: Our results indicate the tendency to deviate from a more centralized organization (star-like topology) towards a more decentralized organization (line-like topology) in the frontal–parietal attention network of children with ADHD. This represents a more random network that is associated with impaired global efficiency and network decentralization. These changes appear to reflect clinically relevant phenomena and hold promise as markers of disease progression. Even when in the resting state and not performing any task processing, the brain is still working. The spontaneous brain activity present in the resting state is not random and usually shows high temporal coupling across different brain regions. This creates a set of brain networks that are densely interconnected and distinct from others. These resting-state networks are not a reaction to any task, but are intrinsically generated by the brain itself , 2. To dGraph theory has been used to study the architecture of brain networks , 12 and It is difficult to compare networks reported in graph theory studies across different groups and conditions. A normalization step is required to allow comparison. Common approaches are thresholding and/or comparing the observed network with randomized networks generated from the observed network; however, these do not provide a unique or consistent solution . One potThe aim of the present study was to explore the alteration of the FPAN connectivity or topology in children with ADHD. Increasing evidence has demonstrated that ADHD was a developmental disorder and associated with developmental delay. Typical maturation during childhood involves a shift from a random towards more regular networks . We hypoIn the present study, we used concepts from graph theory to examine resting-state functional connectivity within the FPAN. We hypothesized that the functional networks in the FPAN would shift towards being more random in children with ADHD than in TDC. We used graph theory analysis to quantify publically available resting functional magnetic resonance imaging (MRI) data from 119 children with ADHD and 69 TDC. We calculated several measures derived from the SW and MST to assess local integration, global efficiency, and relative node importance within the networks and hypothesized that brain networks of participants with ADHD would display lower global efficiency and local integration than brain networks of TDC, and that this would be accompanied by a loss of centrality of individual brain regions within the FPAN. An analysis was then conducted to determine correlations between SW and MST parameters and ADHD-related disability, as measured using the ADHD symptom score. We hypothesized that, in children with ADHD, SW and MST would be associated with ADHD symptom score.http://fcon_1000.projects.nitrc.org/indi/adhd200/). We first selected 191 participants between the ages of 7 and 14 years from New York University Child Study Center and excluded 7 participants whose IQ , gender, or diagnosis information were missing, resulting in the 188 participants for further analysis, including 119 children with ADHD  and 69 TDC children , detailed in The data we used in this study are publicly available from the ADHD-200 Consortium  were assessed using Conners’ Parent Rating Scale-Revised, Long Version (CPRS-LV).High-resolution T1-weighted 3D MPRAGE images covering the whole brain were acquired for each participant on a Siemens 3.0-Tesla Allegra MRI scanner at the NYU Center for Brain Imaging . Functional imaging was performed in a single run using a blood oxygenation level-dependent (BOLD) contrast sensitive gradient echo-planar sequence . During this scan, participants were asked to relax with their eyes open.Image preprocessing was performed using the DPARSF data processing assistant for resting functional MRI (rsfMRI) . Preprochttps://www.nitrc.org/projects/gretna) and Brain connectivity toolbox (https://www.nitrc.org/projects/bct/). The functional connectivity derived from 16 brain regions forming FPAN  and path length (L) were calculated in terms of Watts and Strogat (1998). Briefly, characteristic path length is defined as the average shortest path connecting any two nodes in the graph. The path length is used to measure how well a network is connected; a small value indicates an average short distance between any two nodes. The cluster coefficient is defined as the number of actual edges connecting the neighbors of a node divided by the maximum number of edges possible between neighboring nodes. The cluster coefficient of a network is used to measure how many local clusters exist in the network. A high cluster coefficient indicates that the neighbors of a node are often also directly connected to each other, that is, they form a cluster.random) but with increased cluster coefficients (Crandom):λ = L/Lrandom≈1 and γ = C/Crandom > 1  as the edge to construct an acyclic subnetwork, equivalent to a MST as obtained by using the Kruskal algorithm . Brieflymax, which is the BC of the node with the highest BC in the tree to measure the BC of the tree. A decreased value of BCmax in the tree indicates a decreased global efficiency and a decreased “hub” strength. Hierarchy is an indicator of the balance between efficient communication paths and overload of hub nodes, which is defined asIn terms of the information about the topological properties of the MST, we can compute several measures to characterize the topology of the tree, including the diameter, normalized leaf fraction, kappa (degree of divergence), betweenness centrality, and hierarchy. The diameter, which is the largest distance between any two nodes, is defined as the longest shortest path in the network. The normalized leaf number is defined as the number of nodes with a degree of 1, divided by the maximum number of leaves possible given the size of the tree, and is used to measure the integration in the network . A decrewhere L is the leaf number, m is the number of vertices −1, and BCmax is the maximum value of betweenness centrality. The value of hierarchy ranges between 0 and 1. If leaf number = 2, tree is a line-like topology, and hierarchy approaches 0. If leaf number = m, tree is a star-like topology, and tree hierarchy approaches 0.5. When the number is between 2 and m, tree hierarchy can have higher values .Statistical differences in age, handedness, gender, verbal, and performance IQ were evaluated using T test Table 1.t = 0.217, p = 0.828), handedness , and performance IQ ; gender  and verbal  IQ showed differences between ADHD and TDC children. In the subsequent analysis, gender and verbal IQ were used as covariates.F = 0.472, p = 0.493], detailed in r = 0.023; p = 0.754) was observed between the FPAN mean strength and the ADHD scores, detailed in After controlling for gender and verbal IQ, no significant group differences were observed for the FPAN mean strength  or path length , detailed in r = 0.040, p = 0.590) or path length and ADHD symptom score , detailed in No significant group differences were observed in SW topology clustering coefficient , leaf number , tree hierarchy , and kappa , detailed in r = 0.175, p = 0.017; leaf number: r = −0.208, p = 0.004; tree hierarchy: r = −0.218, p = 0.003; kappa: r = −0.212, p = 0.004), detailed in F = 0.724, p = 0.396] or eccentricity , detailed in r = −0.016; p = 0.829; eccentricity: r = 0.112; p = 0.129), detailed in A significant group difference was observed for diameter , bilateral ventral intraparietal , and left and right ventral occipital lobe , which also correlated with ADHD scores , detailed in To further examine the regionally nodal characteristics of brain networks, the group difference in nodal eccentricity was tested in the MST topology. Eccentricity was significantly greater in children with ADHD than in TDC in the left intraparietal sulcus [ADHD: 7.328 ± 1.595; TDC: 6.783 ± 1.617, To our knowledge, this is the first study to investigate SW and MST properties of FPAN topology in children with and without ADHD. We found that, although brain functional networks exhibited economical SW topology in both groups, children with ADHD had greater MST diameter and lower leaf number, tree hierarchy, and kappa than TDC, and these variables were also associated with ADHD symptom score.Since Watts and Strogatz proposed and quantitatively described SW networks , it has In the present study, MST analysis showed that diameter, leaf number, tree hierarchy, and kappa were altered in ADHD. Children with ADHD had greater diameter and lower leaf number, tree hierarchy, and kappa, and these variables significantly correlated with ADHD symptom score, indicating their clinical relevance. Decreased leaf number and increased diameter indicate a decreased global efficiency , suggestA low kappa value corresponds to a low number of highly connected nodes or “hubs.” The number of hubs is associated with the resilience of the network against attack. To further explore the damaged “hub” regions in the FPAN in children with ADHD, we further computed the eccentricity of each region. The eccentricity of a node is measured by the longest distance between that node and any other node. The closer a node is to the center of the tree, the lower its eccentricity. Low eccentricity indicates high global efficiency and centrality. We found greater eccentricity, reflecting lower global efficiency and centrality, in the left IPS, bilateral vIPS, and bilateral vOC. In general, these brain regions were concerned in ADHD studies. Previous studies found that the centrality in the IPS and vIPS regions of the FPAN was associated with alertness and the efficiency of the executive control system , 49. ConIn summary, this is the first study to reveal the topological properties of the FPAN in children with ADHD using resting-state functional MRI. We performed MST analysis of brain networks. This addresses the threshold and normalization problems encountered with conventional approaches, and was sensitive to changes in brain topography in children with ADHD. Clustering coefficient and path length were not successful in identifying deficits in the FPAN, whereas the MST parameters of leaf number, diameter, tree hierarchy, and kappa captured the tendency of ADHD brains to deviate from a more centralized organization (star-like topology) towards a more decentralized organization (line-like topology). This corresponds to a decreased global efficiency and weak integration. There were also differences in nodal eccentricity of the IPS, vIPS, and vOC in children with ADHD, reflecting a decreased efficiency and decentralized topology that was associated with deficits in alertness and executive function in attention processing. In addition, MST parameters were associated with clinical features of ADHD. These findings enhance our understanding of the underlying pathophysiology of ADHD and may facilitate evaluation and monitoring of clinical status in ADHD.Despite the advantages of this study, some limitations should be noted. First, when using MST, we only used the “core” connections. This means that some information may have been lost. For example, clustering coefficient is a measure that cannot be examined in MST. To address this, we derived this information from SW topology. Previous studies found that, among children with ADHD, there are gender differences in brain structure ; howeverThis study was carried out in accordance with the recommendations of the IRBs of NYU and the NYU School of Medicine with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the IRBs of NYU and the NYU School of Medicine.YW analyzed the data and wrote the draft of the paper. CZ and FT amended and proofread the draft of the paper. CZ, FT, DW, MH, and MK participated in the discussion and offered some good ideas. All authors reviewed the manuscript.This research was supported by the National Natural Science Foundation of China (No. 31662083). The 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.


Is attention-deficit/hyperactivity disorder (ADHD) associated with higher early mortality risk among patients in Taiwan?In this Taiwan nationwide population-based cohort study, there were 275 980 patients with ADHD and 1 931 860 matched controls. After adjustment for potential confounders, patients with ADHD had significantly elevated early mortality risk for suicide, homicide, and unintentional injuries compared with the non-ADHD group.These findings suggest that ADHD may be associated with excess mortality from injury causes. This nationwide cohort study in Taiwan evaluates whether attention-deficit/hyperactivity disorder (ADHD) is associated with higher risk of mortality from all causes, suicide, unintentional injury, homicide, and natural causes. Few studies have investigated levels of mortality in patients with attention-deficit/hyperactivity disorder (ADHD), and findings have been inconsistent and lacking information on specific causes of deaths.To investigate the association between ADHD and causes of death in Taiwan.A nationwide population-based cohort study was conducted using a cross-national Taiwanese registry. The ADHD group comprised 275 980 individuals aged 4 to 44 years with a new diagnosis between January 1, 2000, and December 31, 2012. All individuals with ADHD were compared with 1 931 860 sex- and age-matched controls without ADHD.The association between ADHD and mortality was analyzed using a Cox regression model that controlled for sex, age, residence, insurance premium, outpatient visits, congenital anomaly, intellectual disability, depression disorder, autism, substance use disorder, conduct disorder, and oppositional defiant disorder. The analysis of suicide, unintentional injury, homicide, and natural-cause mortality was performed by a competing risk adjusted Cox regression controlling for other causes of mortality and potential confounding factors.Data on mortality from all causes, suicide, unintentional injury, homicide, and natural causes collected from a national mortality database.There were 275 980 individuals with ADHD and 1 931 860 comparison individuals without ADHD in this study. Sex and age at index date were matched. The mean (SD) age was 9.61 (5.74) years for both groups. Most of the participants were male . A total of 4321 participants from both cohorts died during the follow-up period (15.1 million person-years), including 727 (0.26%) from the ADHD group and 3594 (0.19%) from the non-ADHD group. Of those who died, 546 (75.1%) in the ADHD group and 2852 (79.4%) in the non-ADHD group were male. After adjusting for potential confounders, compared with the non-ADHD group, patients with ADHD showed higher overall mortality  and higher injury-cause mortality from suicide , unintentional injury , and homicide . No increased risk of natural-cause mortality was observed after adjustment.In this study, ADHD was associated with higher injury-cause mortality, particularly that due to suicide, unintentional injury, and homicide. Although the risk of injury mortality was significantly higher in patients with ADHD than in the non-ADHD group, the absolute risk of mortality was low. The Danish population-based cohort study by Dalsgaard et al8 described a 2-fold higher mortality rate in individuals with ADHD compared with those without it , and London and Landes9 showed similar results, with an adjusted odds ratio of 1.78 . A 33-year follow up study11 of 207 boys with ADHD and 178 boys without ADHD and showed higher injury deaths among the boys with ADHD . However, shortcomings of previous studies have included insufficient number of deaths for cause-specific analysis,11 short follow-up periods,9 and limited capacity to adjust for important potential confounders such as comorbid psychiatric disorders.9Despite functional impairments and adverse health consequences associated with ADHD, investigations of mortality associations are scant, although all suggest higher risk.Understanding specific causes of mortality, including natural, unintentional injury, suicidal, or other injury causes of deaths, may provide insight for further definite interventions to reduce the risk of mortality in patients with ADHD. Hence, we designed this study to investigate and compare the risks of both overall and cause-specific mortality after controlling for possible confounders in people with or without ADHD who were identified using a large population-based data set.12 deidentifying personal information and filing health care receipts. In this nationwide cohort study, we extracted information from the National Health Insurance Research Database on medical use among individuals aged 4 to 44 years for whom an ADHD diagnosis  was recorded between January 1, 2000, and December 31, 2012. The age range of 4 to 44 years was chosen because ADHD was unlikely to be diagnosed outside this range. The date of the first ADHD diagnosis was defined as the index date. The index date for participants in the comparison group was assigned as the date of the first ADHD diagnosis of their matched counterparts with ADHD. Sex- and age-matched comparison participants without a recorded diagnosis of ADHD were also selected at a ratio of 1:7  reporting guidelines.The institutional review board of the National Taiwan Normal University approved this study. Written informed consent from study participants was not required because information from the National Health Insurance Research Database and the Mortality Register is anonymized and deidentified. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (ICD-9 codes E950 to E959 (suicide) and E980 to E989 . Mortality due to unintentional injuries was defined as ICD-9 codes E800 to E949. Mortality by homicide was defined as ICD-9 codes E960 to E969. Mortality by natural cause was defined as having causes other than suicide, unintentional injury, and homicide.The main outcome measure for our cohorts was all-cause mortality. Deaths due to suicide, unintentional injury, homicide, and natural causes were also extracted as variables of interest. Because suicide mortality statistics are often underestimated and misclassified, suicide was defined as having ICD-9 codes 740-759), intellectual disability (ICD-9 codes 317-319), depressive disorder , anxiety disorder , autism (ICD-9 code 299), substance use disorder , and conduct disorder or oppositional defiant disorder (ICD-9 codes 312 and 313.81) before the index date. Outpatient visits within the year before the index date, which served as an indicator of medical service use, was also a covariate and was classified into 3 categories: (1) 0 to 10, (2) 11 to 20, and (3) 21 times or more in a year.Demographic variables included age, sex, levels of income, and urbanization. The level of income served as an indicator of economic status and was classified into 3 categories of monthly income (given in New Taiwan dollars [NT$]): (1) less than NT$20 000, (2) NT$20 000 to NT$39 999, and (3) NT$40 000 and higher (US$1 = NT$32.1 in 2010). Other covariates included the presence at baseline of congenital anomaly .13 method, and adjusted cumulative incidences were calculated. Competing risk-adjusted Cox regression models14 were fitted to estimate the association of ADHD with specific-cause mortality after adjustment for covariates. Competing risk-adjusted hazard ratios (HRs) with 95% confidence intervals were calculated. Because the data fitted the proportional hazard assumption, Cox regression analysis was appropriate for the analysis. For multivariate analyses, model 1 incorporated adjustment for demographic variables and outpatient visits in the previous year, and model 2 incorporated further adjustments for baseline comorbidities of congenital anomaly, intellectual disability, depressive disorder, anxiety disorder, autism, substance use disorder, conduct disorder, or oppositional defiant disorder diagnosed before the index date. Secondary analyses were performed after stratification by sex.All-cause mortality was analyzed using a Cox regression model. Other causes of mortality during the follow-up period were considered as competing risk events for each of the specific-cause mortality outcomes . Modified log-rank test results were obtained using the Fine and Gray14 Two-tailed P < .05 (log-rank test) was considered statistically significant.Data management was performed using SAS statistical software version 9.4 (SAS Institute). Cumulative incidences and Cox model calculations in the competing risk analysis were performed using the package cmprsk in R statistical software version 3.5.3 .A total of 275 980 study participants with ADHD and 1 931 860 comparison participants without ADHD were identified. P < .001), suicide mortality , unintentional injury mortality , homicide mortality , and natural-cause mortality .Compared with the unadjusted value , the strength of association between ADHD and all-cause mortality decreased slightly after model 1 adjustments  and more substantially after model 2 adjustments  were made. After adjustments for competing risks and covariates in model 2, having the diagnosis of ADHD remained associated with higher mortality from injury causes, including suicide , unintentional injury , and homicide . However, no significant association was found between ADHD and mortality from natural causes after full adjustment .In what we believe to be the largest sample evaluated to date, we investigated associations of ADHD with both all-cause and cause-specific mortality, incorporating adjustments for multiple potential confounding factors. Our overarching finding was that injury rather than natural-cause mortality was higher in individuals with ADHD than in a comparison cohort. Although unintentional injuries accounted for the highest number of deaths from injury causes, the highest excess risk of mortality in the ADHD group was for suicide.9 However, another study by Barbaresi et al7 reported no increased risk of mortality among patients with ADHD, with standardized mortality ratios of 1.88 .Our finding of an association between ADHD and all-cause mortality is consistent with those reported by previous studies.8 The longest follow-up study10 also showed higher rates of injury deaths among boys with ADHD than in a comparison group , but the low sample size cannot allow for further multiple analysis to control confounders or detect the separate effect of different types of injuries. On investigating cause-specific mortality further, we found that the ADHD group had higher suicide, unintentional injury, and homicide mortality rates than the comparison group. Previous studies have failed to identify a statistically significant risk of unintentional deaths in ADHD,9 although they have been limited by sample size. For example, the standardized mortality ratio was 1.70  in the study by Barbaresi et al,7 with only 3 deaths due to unintentional injuries in their ADHD cohort. That study7 also showed significantly increased suicide deaths in patients with ADHD, but the authors were not able to adjust for confounding factors such as comorbidity. Some studies9 have shown that demographic characteristics  and psychiatric comorbidities, such as oppositional defiant disorder, conduct disorder, and substance use disorder, partially account for the risk of death in individuals with ADHD. In our study, after full adjustment for sociodemographic variables and comorbid psychiatric diagnoses, associations with natural-cause mortality were attenuated to near-null values, but increased risk for suicide or unintentional injury deaths held even when we controlled for comorbidities such as depression.Our finding for higher injury mortality was also similar to that reported by Dalsgaard et al.15 and unintentional injuries might result from an underestimation of the consequences of risk-taking behaviors. Previous studies have also described increased traffic unintentional injuries in children with ADHD and other mental disorders,17 and working memory impairment and impulsivity in ADHD could potentially be responsible.19 Medication use has been reported to have the potential to reduce such risks.20 On the other hand, poor quality of life, lack of social support, and emotional dysregulation in children with ADHD were shown and may also be associated with increased risk of suicidal behaviors.21Underlying mechanisms associated with increased injury deaths in patients with ADHD, and the possible mitigating effects of treatment, warrant further investigation. Behaviors such as inattention, hyperactivity, and impulsivity may increase the risk of unintentional injuries,8 that reported higher mortality risk in girls and women than in boys and men. Referral bias might be a reason because female patients with ADHD have been found to be referred for further evaluation less often than male patients.22 Therefore, women who receive a medical referral and receive a diagnosis of ADHD may present with much more severe behavioral symptoms and problems, thus accounting for greater mortality risk. In addition, girls with ADHD have been reported to receive less treatment with medication than boys, which may also contribute to their higher mortality risk.23 We found that men with ADHD were at a slightly increased risk of unintentional injury-related death compared with men without ADHD, a male predominance that was also previously reported for unintentional injury.25 However, other studies have not found sex differences in the risk of unintentional injury-related mortality in patients with ADHD.26Potential sex differences were noted in our study, in that female patients with ADHD had significantly increased all-cause mortality risk in fully adjusted models, which was not present in male patients with ADHD. This finding is consistent with those of a Danish study8 also reported unintentional injuries to be the most common cause of death in this patient group; however, of 107 deaths, information on cause was available for only 79 cases.Although the risk of suicide-related mortality was significantly higher in patients with ADHD than in those without ADHD in our study, the absolute risk of mortality was low and suicide deaths were rare (n = 117), with natural-cause deaths (n = 408) and unintentional injury deaths (n = 188) accounting for a substantially higher number of deaths than suicide in the ADHD cohort. One previous study27 Several studies have supported the evidence that ADHD medication can effectively reduce the risk of physical injury,28 fracture,24 traffic crashes,20 brain injury,30 and suicide.31 However, further research is still needed to estimate the potential effect of medication on injury mortality, including earlier identification and treatment initialization. Teaching emotional regulation, providing safety tips, educating on protective gear, and environmental modification may also be helpful.21Findings from our study emphasize the importance of clinicians prioritizing the prevention of risk factors for injury-caused premature deaths in patients with ADHD, rather than compounding the stigma associated frequently with ADHD.32 Some covariates adjusted for in our analyses would have provided incomplete estimation of underlying parameters of interest . For example, ADHD onset was measured by first recorded diagnosis, and the prediagnosis impact of ADHD has to be assumed; in addition, controlling for the baseline covariate of depression might be biasing downward the effect of ADHD if depression served as a mediator of ADHD to suicide. Future exploration of the possible effects of ADHD treatments and consideration of other confounders is required. Fourth, although the present study provided support that the population with ADHD is at risk for higher mortality due to injury causes, it did not reveal what might drive that risk. Further studies are warranted to explore the underlying mechanism.To our knowledge, this is the first study using a national database to investigate associations between ADHD and different causes of mortality after controlling for associated comorbidities. The population-based cohort design diminished the likelihood of selection bias, beyond issues of access to diagnosis discussed later, and its prospective nature reduced the risk of reverse causality. We were also able to incorporate adjustment for a range of potential confounders. Notwithstanding, several limitations should be borne in mind when drawing inferences from our findings. First, the ADHD cohort was defined from routine health care data by medical diagnosis rather than by structured research-quality clinical interviews; furthermore, it is important to bear in mind that many patients with ADHD will not receive a clinical diagnosis and our findings cannot be assumed to generalize to those with undiagnosed disorder. Second, our study used observational data from the population in Taiwan, and its generalizability to other international settings cannot be assumed. Third, we were not able to consider and analyze the effects of ADHD medications or other potential contributing factors, such as family history and psychosocial stress.This study found that ADHD was associated with higher mortality, particularly increased risk of mortality from injury causes, compared with mortality in a control group without ADHD. The highest excess risk of mortality in the ADHD group was for suicide, even after adjusting for the comorbidities such as depression. The natural-cause mortality was attenuated to near-null values after adjustment for sociodemographic variables and comorbid psychiatric diagnoses. It is imperative to explore the underlying mechanisms of injury deaths in patients with ADHD to help develop effective prevention methods.


However, its delivery through the application of MK-4 to the skin is hampered due to the photoinstability and phototoxicity of MK-4. This study aimed to evaluate the potential of ester prodrugs of MKH for its delivery into the skin to avoid the abovementioned issues. The ester prodrugs, MKH 1,4-bis-N,N-dimethylglycinate hydrochloride (MKH-DMG) and MKH 1,4-bis-hemisuccinate (MKH-SUC), were prepared using our previously reported methods. Photostability was determined under artificial sunlight and multi-wavelength light irradiation, phototoxicity was determined by intracellular ROS formation and cell viability of UVA-irradiated human epidermal keratinocyte cells (HaCaT), and delivery of MKH into HaCaT cells was assessed by measuring menaquinone-4 epoxide (MKO) levels. MKH prodrugs showed higher photostability than MK-4. Although MK-4 induced cellular ROS and reduced cell viability after UVA irradiation, MKH prodrugs did not affect either ROS generation or cell viability. MKH prodrugs enhanced intracellular MKO, indicating effective delivery of MKH and subsequent carboxylation activity. In conclusion, these MKH prodrugs show potential for the delivery of MKH into the skin without photoinstability and phototoxicity.The effective delivery of menahydroquinone-4 (MKH), an active form of menaquinone-4 (MK-4, vitamin K Menahydroquinone-4 (MKH), the fully reduced and active form of MK-4, is a cofactor for γ-glutamyl carboxylase (GGCX), which catalyzes the post-transcriptional carboxylation of vitamin K-dependent proteins. MKH is produced by the enzymatic conversion of vitamin K1 and K3 in the body [Menaquinone-4 (MK-4) or vitamin KSkin application of vitamin K exhibits several beneficial effects such as suppressing pigmentation and resolving bruising ,3,4, pro2) [Because vitamin K is highly unstable in light, it should be strictly protected from light exposure during manufacturing, preparation, storage, and treatment ,11,12. F2) . Given tN,N-dimethylglycinate (MKH-DMG) and hemi-succinate (MKH-SUC) derivatives, can act as delivery systems for MKH without a reductive activation step [It has been shown that the main photodegradation product of MK-4 is MK-4 chromenol (MKC), which is produced from the naphthoquinone structure and isoprenyl side chain of MK-4. We have previously reported that ester-type prodrugs of MKH, such as the 1,4-bis-ion step ,15,16,17ion step ; this vaTo evaluate the photostability of the MK-4 and MKH derivatives in skin application, 1 μM solutions of MK-4, MKH-DMG, or MKH-SUC in ethanol were irradiated with artificial sunlight  at 25 °C with and without shading, and the final amounts of MKH derivatives and their monoesters, MK-4 and MK-4 chromenol, were determined by LC-MS/MS. The relative irradiance of artificial sunlight at wavelengths of 300 to 800 nm is almost equal to that of natural sunlight, according to the manufacturer. MK-4 and MKH-DMG concentrations decreased in sunlight irradiation according to an apparent first order rate A, but weFollowing sunlight irradiation, MK-4 in ethanol was mainly converted to MK-4 chromenol. This photochemical result is consistent with previously reported results in polar solvents ,12. In cTo evaluate the effect of irradiation wavelength on photostability of MK-4 and MKH-ester derivatives, 1 μM solutions of MK-4, MKH-DMG, and MKH-SUC in ethanol were irradiated with a xenon light source monochromatic light at 279, 341, 373, 404, or 435 nm, and the concentration of each compound was measured by LC-MS/MS. The log of concentration of each compound was plotted against irradiation energy , and the1 exhibits phototoxicity against cultured epidermis upon UVA irradiation [Some pharmaceutical substances are photosensitizers that can lead to the generation of reactive oxygen species (ROS) that cause oxidative damage to skin cells. It has been also shown that vitamin Kadiation . Therefop-nitrosodimethylaniline-based ROS assay (2), MK-4 exhibited increased formation of singlet oxygen in an irradiation energy-dependent manner similar to that of ketoprofen, the positive control, whereas MKH-DMG and MKH-SUC showed little generation of singlet oxygen, comparable to that of sulisobenzone, the negative control  after UVA irradiation in the presence or absence of MK-4 and MKH derivatives. Intracellular ROS generation was determined using the cell permeable probe 2′,7′-dichlorofluorescein diacetate (DCFH-DA), which rapidly reacts with hydroxyl radicals. Cells without drug treatment or UVA irradiation were used as the control. ROS generation and cell viability are shown in None of the compounds increased intracellular ROS levels in the absence of UVA . Followi2O2.None of the compounds affected cell viability in the absence of UVA irradiation . After UBased on these results, it appears that MKH derivatives would be useful for skin application without producing singlet oxygen related skin surface toxicity and ROS related cytotoxicity induced by photo irradiation.The potential of MKH derivatives and MK-4 as dermal delivery systems of MKH were assessed by measuring intracellular MKH levels. However, accurate measurement of MKH is difficult because MKH is readily oxidized to MK-4. In γ-glutamyl carboxylation of vitamin K dependent protein (VKDP), MKH acts as a cofactor of γ-glutamyl carboxylase (GGCX) and is stoichiometrically converted to menaquinone-4 epoxide (MKO). Thus, MKO levels in HaCaT cells can reflect the amount of MKH delivered into the cell and subsequently converted in the carboxylation of VKDP. In addition, MK-4 level in cells after MKH prodrugs treatment indicates the oxidative product of MKH.In this study, the intracellular concentration of MKO and MK-4 in HaCaT cells over time after treatment with MK-4, MKH-DMG, or MKH-SUC (5 μM) was determined by LC-MS/MS .MKO (0–72 h)) and MK-4 (AUCMK-4 (0–72 h)) were calculated using the trapezoidal method and are shown in MKO (0–72 h) for MKH-DMG and MKH-SUC was 1.023- and 1.641-fold that of MK-4, respectively. These results indicate that MKH-DMG and MKH-SUC can act as MKH prodrugs and effectively deliver MKH to keratinocytes.After MK-4 treatment, MKO and MK-4 levels immediately increased and reached a plateau after 12 to 24 h. Following MKH-DMG and MKH-SUC treatment, MKO levels were significantly increased, but the increase in MKO levels with MKH-SUC was faster than that with MKH-DMG. The areas under the concentration vs time curves over 72 h for MKO  cells in a previous study—the uptake and reconversion rates of MKH-SUC in HCC cells were faster than those of MKH-DMG . TherefoIn conclusion, MKH-DMG and MKH-SUC could act as MKH prodrugs for skin application without photoinstability and phototoxicity. This ideal strategy is a safer and more efficient way to deliver MKH than using the quinone form MK-4. Therefore, MKH prodrugs have the potential to be used for skin diseases which require the activity of vitamin K dependent proteins for treatment, even under direct sunlight irradiation. Further studies that can reflect the actual skin environment using human origin skin models such as 3-dimensional skin models or flesh skin tissue samples are needed.N,N-dimethylglycinate hydrochloride (MKH-DMG) and menahydroquinone-4 1,4-bis-hemisuccinate (MKH-SUC) were synthesized in our laboratory using previously reported methods [MK-4 was purchased from Seebio Biotech, Inc. . Menaquinone-4 epoxide (MKO) was kindly provided by Eisai Co., Ltd. . Menahydroquinone-4 1,4-bis- methods . Other c2.Human epidermal keratinocyte cell line HaCaT was obtained from CLS Cell Lines Service GmbH . Cells were maintained in DMEM  with 10% FBS  and 1% penicillin/streptomycin (Life Technologies) at 37 °C under an atmosphere of 5% COSolutions of MK-4 and MKH derivatives in ethanol (1 µM) were irradiated with artificial sunlight  at 12,000 lx in quartz cells. Illuminance was measured using a digital luminometer . Irradiation samples (1 µM in ethanol) were irradiated with artificial sunlight at 12,000 lx, and with monochromatic light  using a multi-wavelength irradiation spectrometer . Irradiation intensity was measured using an irradiation energy measurement power meter . Concentrations of MK-4, MK-4 chromenol, MKH-DMG, MKH-mono-NN-dimethyl glycinate (MKH-mono-DMG), MKH-SUC, and MKH-mono-succinate (MKH-mono-SUC) in each solution were analyzed by LC-MS/MS as described below .MK-4 and MKH derivatives were dissolved in a phosphate buffer  containing 0.2% polyoxyethylene hydrogenated castor oil 40 , 2% dimethyl sulfoxide, and 0.1% glycerol. The solutions were treated according to the singlet oxygen assay method   and irra5 cells/well in 96-well plates and cultured overnight. Thereafter, cells were washed with PBS and incubated with 10 µM DCFH-DA solution in PBS at 37 °C for 1 h. Following incubation, test compound solutions in PBS described above were added to each well and re-incubated for 1 h. After incubation, cells were irradiated with UVA at an irradiation intensity of 15 J/cm2 and the fluorescence intensity  was measured using an Infinite M200 PRO (Tecan Life Sciences).Intracellular ROS generation was measured using 2′,7′-dichlorofluorescein diacetate  as a fluorescent probe. HaCaT cells were seeded at 1.0 × 105 cells/well in 96-well plates and cultured overnight. Thereafter, cells were washed with PBS, and test compound solutions in PBS described above were added to each well and re-incubated for 1 h. After incubation, cells were irradiated with UVA at an irradiation intensity of 15 J/cm2. After irradiation, cells were washed twice with PBS and replaced in culture medium. After 24 h incubation, cell viability was measured using a CellTiter-Glo® Luminescent Cell Viability Assay .HaCaT cells were seeded at 1.0 × 104 cells/well in 24-well plates and allowed to attach for 48 h. Cells were cultured in medium containing 5 µM MK-4, MKH-DMG, or MKH-SUC, then medium was removed and cells were washed twice with PBS. Cells were collected in 500 µL of PBS and sonicated. Cell homogenates were combined with an equal volume of methanol and three times volume of n-hexane, vortexed for 2 min, and centrifuged at 1750× g for 10 min. The organic layer was evaporated under N2 gas. The residue was reconstituted with 20 μL of methanol, and subjected to LC-MS/MS, as described below. The protein concentration of the cell homogenate was determined using a BCA protein assay kit .HaCaT cells were seeded at 5.0 × 102 gas. Residues were re-dissolved in a volume of medium equal to the evaporated ethanol, diluted 40-fold, and added to the cells for up to 48 h. Measurement of intracellular MKO was carried out using the same method as described above  and Shimadzu HPLC System (system controller (CBM-20A), pump (LD-20AD), degasser (DGU-20As), UV detector (SPD-20A), and auto injector (SIL-20AC HT)). Separations were performed on a CAPCELL PAK C18 UG120  using a mobile phase of 10 mmol/L ammonium acetate and 0.1% acetic acid in methanol and water (97:3) at a flow rate of 0.4 mL/min. Column temperature was maintained at 40 °C. The mass spectrometer was equipped with an electrospray ionization and was run in positive ion mode. Identification and quantitation were based on MS/MS-multiple reaction monitoring mode using transition ions as follows: p < 0.05 was considered statistically significant. Data were analyzed using GraphPad Prism 6 (GraphPad Software).Statistical significance was determined using Dunnett’s test.


Motorcycling is one of the main causes of injury, and motorcyclists are vulnerable to road traffic injuries. Attention Deficit Hyperactivity Disorder (ADHD) in adults is presumably one of the determinants of road traffic injuries and motorcyclists’ risky behavior. Despite the few studies on the relationship between motorcycle injuries and adult ADHD, their association has not been investigated using standardized instruments. This study aimed to analyze the relationship between motorcyclists’ adult ADHD and risky riding behaviors.This community-based, cross-sectional study was performed on 340 motorcyclists in Bukan city, west Azerbaijan province, Iran in 2015 and 2016 using a cluster-random sampling in seven areas of the city. According to the city map used by Bukan’s Health Centers, the city was divided into 14 clusters. Then, seven clusters (out of 14) were selected randomly. To reach the anticipated sample size, the data were collected from these seven clusters. In this study, the data collection instruments were: standard Motorcycle Rider Behavior Questionnaire (MRBQ), Conners' Adult ADHD Rating Scales (CAARS) questionnaire and a checklist designed by the researchers. The Stata 13 software package was used to analyze the collected data. Pearson correlation coefficient and multiple linear regression were performed to study the linear relationship between ADHD screening and MRBQ scores.All 340 participants were male and the mean age was 30.2 years (SD=9.1). In addition, 22.1% of motorcyclists had a history of motorcycle crash. Bivariate analysis showed a significant association between risky riding behaviors and age, motorcycling records, and mean of riding hours per day . Multivariate analysis confirmed the correlation between ADHD and risky riding behaviors in all subscales  (p less than 0.05).Those with a high ADHD screening score are more likely to have risky riding behaviors. It is predicted that the annual death toll of injuries will rise to 1.9 million in 2030 if no effective actions and measurements are taken.2 Though death and injury rates have declined in developed countries over the last few years, low- and middle-income countries (LMICs) have simultaneously shown an increase.5 Nevertheless, few studies have been conducted on this issue and they do not provide enough strong evidence to improve road traffic safety in all related aspects, in developing countries. 6 It has therefore been concluded that this problem has not been taken into consideration properly.3 About 62% of deaths caused by road traffic injuries are reported from 10 countries including Iran.7 Like other Asian countries, motorcyclists in Iran are among the most vulnerable groups.8 Compared to other drivers, they are at a higher risk of injuries; for example 7 times more than car drivers and 5.5 times more than truck drivers.9 Undoubtedly, to reduce injuries and death tolls caused by injuries in LMICs including Iran, motorcyclists should be given appropriate priority.11 Despite their high vulnerability in Iran,9 there is not enough applied research in related fields.12 Road traffic injuries are a major but neglected public health challenge requiring efforts for sustainable prevention. The road traffic system is the most complex and the most dangerous system that people have to negotiate.13Traffic crashes represent a major challenge to public health; 14 at motorcycle accidents, three main components can be ascertained, including: factors related to vehicles (such as motorcycles), environmental factors , and human factors (such as riders).With a systemic glance 15 Attention Deficit Hyperactivity Disorder (ADHD), one of the most common psychiatric disorders in childhood and adolescence,16 is a serious, chronic and debilitating mental disorder. It affects about 2.8 to 3.9 million school children in the US and may continue into adulthood.17 About 50% to 65% of children with ADHD show symptoms of the disease in their adulthood.18 Its prevalence in adults is four percent.19 Adults with ADHD may be distracted by the slightest stimuli, take impulsive decisions in the case of riding behaviors, and be prone to multiple and severe injuries.20 Barkley et al. indicate that riders with adult ADHD show a high level of inattention in riding test.21 Other studies reveal that motorcyclists with adult ADHD display abnormal behavior such as speeding, riding without license and causing crashes.24 Since studies on the relationship between motorcyclists’ adult ADHD and risky riding behavior using standard tools are rarely available, this study aims to determine the association between adult ADHD score and risky motorcycle riding behavior.Although there is plenty of research on road safety resulting in many findings on the first two factors, few studies have been conducted on the third factor addressing how human factors, especially psychological factors, can lead to risky riding behaviors and motorcycle injuries.Study type and participants12 the primary sample size of 227 was estimated. Finally, it was multiplied by a design effect coefficient of 1.5. Then the final sample size of 340 was calculated.The present cross-sectional survey was conducted on 340 motorcyclists in Bukan city, west Azerbaijan province, Iran, from January 2015 to January 2016. By means of random cluster sampling, the city was divided into 14 clusters according to the geographical areas covered by urban health centers; then seven clusters were selected randomly. The data were collected from motorcycle repair shops, motorcyclists’ homes and workplaces in each cluster until the expected sample size was obtained. The sample size of 340 participants was gathered equally from the seven selected clusters. Sample size was estimated using Sampsi command of Stata V.11. Considering the most similar available study conducted by Abedi et al., assuming a standard deviation of 22.96, 95% confidence level and an accuracy ofInclusion and exclusion criteriaThe inclusion criteria in the study were as follows: 1. The interviewee rode a motorcycle at least 3 times a month. 2. The interviewee was over 15 years old.3. The interviewee was a resident of Bukan City.4. The interviewee was alert at the time of completing the questionnaire. The exclusion criteria were as follows:1. Having no motorcycle riding experience in the last month.2. Having a medical history of major mental disorders in the past.3. Lacking informed consent to participate in the study. 4. Lacking motivation to participate in the study and complete the questionnaire. ToolsThe main variables, study outcomes and measuring tools are explained as follows:271. Background variables included age, sex, marital status, education level, and socio-economic status. The available Persian tool of SESIran (ultrashort version) was used in order to measure socio-economic status (SES).2. Variables related to motorcycle riders included having a motorcycle license, the average riding hours a day, the average number of motorcycle riding days a week.15 and translated and adapted by Motavallian et al. in Persian in 200928 The questionnaire consists of 48 items and the scores ranges between 0 and 192. The answer options are based on 5-point Likert scale: (never=0), (rarely=1), (sometimes=2), (often=3), and (most of the time=4). Behavior scores of the questionnaire were normalized into a range of 0 to 100. The Cronbach’s alpha for subgroups was estimated to be in a range of 73-93%.3. Riding behavior assessment variables included riding on the wrong side of the road, speeding, not wearing a helmet, carrying unauthorized cargo, and other dangerous riding behaviors such as tailgating and doing acrobatics. The standard questionnaire of MRBQ was used to assess the behavior. Both validity and reliability of the questionnaire had already been evaluated by Elliott et al. in 2007,29 The answer options were based on 4-point Likert scale including , , , and . The internal consistency of the Persian version was 82-97% based on Cronbach’s alpha for its subscales. The content validity was confirmed for all four subscales using modified Kappa over 0.76.4. The short-form Persian questionnaire of Conners' Adult ADHD Rating Scales (CAARS) was used to measure ADHD variables. This questionnaire includes 30 questions and four subscales including attention disorder , impulsivity index , general index of ADHD symptoms and lack of attention , and ADHD index . This scale was translated into Persian in Tabriz in 2013.Statistical analysisThe data were analyzed using the Stata v.13 statistical software package (Texas Stata Corp.) and using descriptive statistical methods such as reporting frequencies, percentages, means and standard deviations. The point estimates and their 95% confidence intervals were calculated and reported for key variables. Through a preliminary bivariate analysis, the relationship between ADHD screening score and riding behavior score was assessed using Pearson correlation coefficient. Three complementary multivariate statistical models were developed including various ADHD subscales in each model. Multiple linear regression analysis was done using normalized scores of MRBQ as the outcome variable. Other potential confounders and cofactors were included in constructing the multivariate models . The score extracted from subscale D of Conner’s questionnaire was used as the main predictor variable (model 1) and subscales A and B were considered as the main predictors in the other two models. The three subscales were not used simultaneously in a single model due to their intrinsic mutual multicollinearity. Additionally, in order to evaluate the multivariate analysis models, the normal distribution of errors was examined by obtaining and plotting residuals; the multicollinearity between variables was examined by estimating a variance inflation factor (VIF); and the linear relationship between independent and dependent variables was tested by drawing scatter plots. All the statistical tests were interpreted as two-sided, with statistical significance level below 0.05. In the current study, 340 motorcyclists were examined. All participants were male ; and 32% of them had an academic education (95% CI: 27.8-37.8). Regarding a history of riding motorcycles, 9.7% of participants reported riding experience for less than 6 months (95% CI: 6.7-13.4), 10.6% reported 6-12 months (95% CI: 7.7-14.4) and those with more than 12 months riding experience comprised the remainder 79.7% (95% CI: 75%-84%). 67.3% of participants reported riding a motorcycle more than 4 days a week, and 15.6% reported consistent use of a helmet. The average hours of riding was 2.1 per day and the maximum MRBQ score was 116. The most common risky behaviors by most of the survey participants were as follows:1. Poor control of the motorcycle in turns (for example U-turns)2. Riding with lights off in the dark3. High speeding on freeways4. Running a red light5. Carrying heavy loadsA linear correlation pattern was observed between riding behaviors of motorcyclists and adult ADHD scores . Using P20 A couple of studies31 clarify that risky riding behaviors decline after the disorder is cured, confirming the relationship between ADHD and risky behaviors. Furthermore, all types of crashes and injuries in patients with ADHD were more frequent compared to the control group.32 However, a clinical trial study discovered an independent relationship between adult ADHD and risky behaviors when riding.33According to the findings, the higher ADHD screening scores, the riskier the motorcyclists’ behavior. Some problems such as distraction, lack of focus, intolerance for waiting, nervousness, irritability and risk-taking may affect motorcyclists’ riding behaviors.34 Accordingly, hyperactive teenagers experience more traffic crashes than other teenagers,35 as well as hyperactive adolescents compared to others.37The multivariate analysis and multiple scatter plots revealed the maximum correlation between B subscale score (with symptoms of impulsivity and hyperactivity) and risky riding behaviors (r=0.80), and the minimum correlation between D subscale score (with symptoms of impulsivity and hyperactivity) and risky behaviors. The possible reason could be that MRBQ is most often used to measure impulsivity and active riding behavior of motorcyclists. Also, motorcyclists with ADHD are more prone to impulsive and sudden behaviors such as doing a wheelie and riding at high speeds. The behavior scores related to A and D subscales increased and reached their peaks at the age of 45 years. Such pattern would not be observed among riders older than 45 years since the pattern of this disorder changes with aging. In other words, as people get older, impulsivity and hyperactivity behaviors are replaced by behaviors like laziness, restlessness and disquiet.38 Conversely, our study could highlight different age ranges as factors affecting both different crash-cause behaviors as well as ADHD subscales.Comparing to another study of 46 motorcyclists involved in crashes indicated no significant relationship between ADHD and motorcycle crashes.39The findings of a study conducted by Safiri et al. (2011) were in line with the results of the current study because both studies indicated that adults with ADHD behaved in more risky ways which could lead to crashes causing trauma.40 This is consistent with our finding that the greater the ADHD screening score, the lower the frequency of helmet use.A study conducted in 2011 found that there is an inverse relationship between motorcyclists’ ADHD screening scores and the rate of helmet use.41Contrary to the results of the current study, subscale A with attention deficit symptoms played a preventive role in injuries caused by motorcycle crashes in another study. This could be influenced by participants’ economic situations as well as the diversity of motives and purposes to use motorcycles.According to the current study, motorcyclists with ADHD experienced more risky behaviors than others. Moreover, hyperactivity can be considered as a risk factor too. So, screening and diagnosis of this psychological disorder in vehicle drivers, especially motorcyclists, would play a significant role in reducing risky behavior patterns and subsequent crashes and injuries.In this study, identification of personality disorders that could affect risky riding behaviors was not possible due to the lack of psychiatric interview and screening. This could be the main limitation of the current study.AcknowledgementsThe authors appreciate the friendly and sincere participation and collaboration of Dr. Leili Abedi, Dr. Mahmoodi and all other colleagues who helped us to conduct this research.