Although the body of research concerning neurodevelopmental disorders is vast, there is a scarcity of longitudinal studies beyond late adolescence, and of studies taking co-existing disorders into account. The present study aimed to investigate outcome in adulthood for children with attention-deficit/hyperactivity disorder (ADHD) combined with developmental coordination disorder (DCD) diagnosed at 6.6 years of age.n = 51) and a registry-matched  group of the same county and age.Out of a screening-based population cohort of 589 individuals, 62  diagnosed with ADHD+DCD at mean age 6.6 years naïve to stimulant treatment were followed into adulthood through national registries. Results were compared to a screen- and assessment negative population matched group from the same cohort . The ADHD+DCD group had significantly higher rates of psychiatric diagnoses, prescriptions of psychoactive medications and occurrence of sick pension than both comparison groups. Further, the ADHD+DCD group had significantly lower educational attainment compared to both comparison groups, more years with unemployment, and overall higher welfare recipiency. Rates of pain diagnoses and analgesic prescriptions did not separate the groups.At 30 to 31 years of age, five deaths had occurred; one in the ADHD+DCD group and two each in the comparison groups. In time to event analyses of the composite outcome of any psychiatric disorder, psychotropic prescription, sick pension or criminal sentence, events occurred at a significantly higher rate in the ADHD+DCD group (ADHD+DCD entailed a less favorable outcome in adulthood compared to a non-clinical comparison group and a registry-matched population. Neurodevelopmental disorder diagnosed upon school entry is of prognostic utility with respect to function in adulthood, and warrants early identification and management.The online version contains supplementary material available at 10.1186/s12888-021-03154-w. Although it is now well established that individuals with neurodevelopmental disorders often meet diagnostic criteria for more than one disorder, this fact has generally not been reflected in longitudinal outcome studies of attention-deficit/hyperactivity disorder (ADHD) in adulthood . OutcomeWith a view to emphasizing this coexistence of disorders, the concept of ESSENCE was launched by Gillberg . ESSENCEMost long-term outcome studies of ADHD report an association with lower academic and occupational achievement, psychiatric comorbidity, substance use/abuse, risk of accidents and relationship problems , 6. PutaDCD is characterized by a delay in the development of gross and fine motor skills, poor motor planning and coordination, resulting in difficulties or inability to acquire common, everyday skills dependent on integration of executive, cognitive and emotional processes .Although recognition of DCD varies with diagnostic practices across countries, when ascertained it occurs in a severe form in 5% of children , 10, andAmong very few studies reporting on the trajectory of DCD into adulthood, a recent prospective cohort study of women with autism and/or ADHD revealed that one in four had a history of DCD in addition to ADHD and/or ASD. In this group chronic pain was reported by 77% . AlignedIn addition to describing the outcome in adulthood of ADHD with coexisting DCD, the aim was also to prospectively test whether an association to pain of unknown etiology and prescription of analgesic medications can be replicated.The original study was initiated in 1992 with a view to validating a physician-led school-entry screening for NDD and to establish the rate of such disorders in a population-based sample of children , 18, ResWe now conducted a registry-based follow-up study 24 years later of the group with ADHD+DCD and the original comparison group with no NDD, with data sources tracking participants from birth until 2017 .Based on research of minimal brain dysfunction (MBD) in the 1970’s , the diaWith the increasing clinical use of DSM-III-R and DSM-IV, DAMP as a diagnostic entity was supplanted by attention-deficit/hyperactivity disorder (ADHD), conferring clinical focus on the reported behavioral component and a gradual decline of neuromotor examination of children. The operationalized definition of DAMP is equivalent to ADHD with coexisting developmental coordination disorder (DCD) as defined in DSM-IV and its subsequent revisions . This haA participant flow diagram is depicted in Fig. n = 310) in a 5:1 ratio to the index cohort . To minimize bias  the RM group was drawn at age 7 from the general population in the same county  and matched for sex , the Prescribed Drug Register (PDR), the Longitudinal Integration Database for Health Insurance and Social Studies  and the National Crime Register. Utilizing unique personal identification numbers assigned to all citizens at birth, Statistics Sweden  linked all sources and provided de-identified individual-level data. Data was collected for the period 1993 to 2017 (Study inclusion at age 7 to age 30 or 31). Clinically meaningful endpoints were constructed in accordance with review articles and other registry-based follow-up studies –26. A prFrom the LISA-register we obtained data on grades, education, occupation, welfare benefits due to sick pension, sick leave, social circumstances or unemployment, and family demographics. The register integrates yearly sociodemographic data of all citizens 15 years or older since 1990. Education level is reported on a 7-point ordinal scale; 1 = less than 9 years, 2 = 9 years, 3 = 1–2 years of high school, 4 = 3 years of high school, 5 = 1–2 years of undergraduate college, 6 = 3 or more years of undergraduate college, 7 = graduate studies. Occupational skill level is reported according to International Standard Classification of Occupation on a 5-point ordinal scale; 0 = No vocation reported in the register , 1 = Manual work not requiring education beyond elementary school level , 2 = Requiring education programmes at upper secondary and tertiary level of no more than 2 years  3 = Requiring practical or vocational tertiary education programmes of 2–3 years in length , 4 = Requiring theoretical and research-oriented tertiary education programmes and third-cycle programmes of at least 3 years, normally 4 years or longer in length .The national crime register covers all lower court sentences in Sweden since 1973. Crime was defined here as the occurrence of a sentence. Violent crime was defined in accordance with previous registry-based studies as “homicide and attempted homicide, aggravated assault (an assault that is life-threatening in nature or causes severe bodily harm), common assault, robbery, threatening behavior, harassment, arson, and any sexual crime” . Drug-reThe prescribed drug register provided data on all medications dispensed from a pharmacy since 2005 (99% coverage). Psychotropic drugs were defined as class N01-N07 according to the Anatomic Therapeutic Chemical classification system (ATC).From the national patient register, we retrieved all ICD-10 (1997–2017) diagnoses from inpatient (99% coverage) and outpatient care  , 28. TheCaregivers signed informed consent on behalf of their children in the original study. Swedish law states that research of interest for patients with similar ailments as that being studied may not require explicit consent, if it poses minimal risks to the individual and is unattainable by other reasonable means. A waiver of consent was therefore approved from the regional ethics review board of Gothenburg university (Dnr 172–18) for the study’s registry-based follow-up with deidentified data.n = 55 + 46), reporting significantly poorer outcome among those with ADHD+DCD (58% vs 13% in the comparison group) ) and more years with occurrence of unemployment (d = 0.55 [95% CI 0.17 to 0.93]). The occurrence welfare recipiency  in the group with ADHD+DCD was significantly higher than for both comparison groups , and the total sum of welfare benefits among recipients was significantly higher among those with ADHD+DCD compared to the PM group (Table d = 0.64 [95% CI 0.26 to 1.02]).Social and demographic data is reported in Table n = 10) were most likely Autism Spectrum Disorder (ASD) + ADHD (n = 3), ASD only (n = 3), ADHD (n = 2), Epilepsy (n = 1) and unknown (n = 1). No significant differences were found across the three groups in occurrence of welfare recipiency due to unemployment (p = 0.2), sick leave (p = 0.68), social circumstances (p = 0.27), any criminal conviction , traffic-related crime (p = 0.54), or drug-related crime (p = 0.64), .Causes of sick pension in the ADHD+DCD group , five were diagnosed with ADHD, three with ASD and four with ADHD and ASD. In the RM group (n = 11), five were diagnosed with ASD, three with ADHD and three with intellectual disability. In the PM group one participant was diagnosed with ADHD. There were no registered diagnoses of DCD (ICD-code F82). No suicide attempts or prescriptions of medications for substance use disorders  were registered in any group. Among the psychotropic prescriptions, stimulants were prescribed at significantly higher rates , accidents (p = 0.86), prescriptions of anxiolytics (p = 0.06), antidepressants (p = 0.09), antiepileptics (p = 0.14), neuroleptics (p = 0.63), sedatives (p = 0.69), analgesics (p = 0.58) or opioids (p = 0.93), although a nominally higher rate of events generally occurred in the ADHD-DCD group  were almost non-existent in the area. Hence, because only 25% of those with ADHD+DCD received a formal clinically registered diagnosis of NDD (e.g. ADHD or ASD) in primary pediatric or psychiatric care services, and a minority (10%) was prescribed stimulants after 2005, we consider the study to mainly portray the natural course of the “syndrome”.In comparisons, results generally exhibited a uniform direction of increase or decrease, with the PM group at the better end, RM in between, and ADHD+DCD group at the poorer end. When the uniform direction was present but differences were statistically insignificant, this may likely have been due to insufficient power rather than being a true null-result.d − 0.62) [In terms of education and occupational proficiency, the ADHD+DCD group exhibited a shift toward lower attainment. This is consistent with a recent Danish report of completed educational grades in final high-school examinations, wherein ADHD was associated with both fewer completed grades and lower grades (Cohens  − 0.62) . Out of absence of any significant work experience. Further, participants differ strikingly in terms of average recipiency of welfare benefits in adulthood, where median sums are almost 10 times higher in the ADHD+DCD group compared to the PM group. In contrast, the occurrence of welfare recipiency in the last year of follow-up showed no meaningful difference  [registered diagnoses (register did not cover primary care) of affective disorders from these prescriptions  . On the 4,595 . On = 232) participated in a clinical follow-up at a mean age of 27 years. Similarly, no disorder was diagnosed at adult follow-up in 38% of participants with ADHD in childhood. ADHD persisted in 38%, of which 57% had a co-occurring psychiatric disorder , compared with 35% of controls. However, differences in measurement methods both at study inclusion  and follow-up  precludes definite conclusions, especially regarding psychiatric characteristics. Positive predictive value of childhood NDD:s in the NPR is generally good (> 80%) in recent years [When comparing results to the only previous follow-up study of ADHD+DCD conducted at 22 years of age . Rates ont years , 40. Butnt years . In lighStrengths of the study includes the population-based sampling, providing the full panorama of the condition at study, the long follow-up time, valid comparison groups and low attrition rate. However, the study is somewhat limited by the modest sample size of the index cohort with ADHD+DCD. This did not allow for meaningful analyses subgrouping ADHD with or without DCD, and made inferences on rare, but important events  impossible. Absence of face-to-face assessments precludes information from subtle clinical findings or repeated neuropsychiatric assessments, physical exam and the experiences reported from participants themselves. Apart from prescription medications, data sources are lacking on the study populations utilization of primary care. Ideally, longitudinal studies combine registry data and clinical assessments for comprehensive profiling of participants.In conclusion, ADHD+DCD diagnosed at school-entry was associated with a less favorable outcome in early adulthood compared both to matched peers without NDD and a registry-drawn group from the same county. The objective nature of neuromotor function tests opens up the possibility that children at risk of adverse outcome in adulthood might be detected prior to school-entry and receive proper support early in education.Additional file 1.


The objective of the present study was to investigate whether the polygenic liability for attention-deficit/hyperactivity disorder (ADHD) and the psychosocial environment impact the risk of ADHD in interaction or independently of each other. We conducted a register- and biobank-based cohort study of 13,725 individuals with ADHD and 20,147 randomly drawn population-based controls. These 33,872 cohort members were genotyped on the Infinium PsychChip v1.0 array (Illumina). Subsequently, we calculated the polygenic risk score (PRS) for ADHD and extracted register data regarding the following risk factors pertaining to the psychosocial environment for each cohort member at the time of birth: maternal/paternal history of mental disorders, maternal/paternal education, maternal/paternal work status, and maternal/paternal income. We used logistic regression analyses to assess the main effects of the PRS for ADHD and the psychosocial environment on the risk of ADHD. Subsequently, we evaluated whether the effect of the PRS and the psychosocial environment act independently or in interaction upon the risk of ADHD. We found that ADHD was strongly associated with the PRS . All risk factors pertaining to the psychosocial environment were associated with an increased risk of ADHD. These associations were only slightly attenuated after mutual adjustments. We found no statistically significant interaction between the polygenic liability and the psychosocial environment upon the risk of ADHD. In conclusion, we found main effects of both polygenic liability and risk factors pertaining to the psychosocial environment on the risk of ADHD—in the expected direction. ADHD is characterized by hyperactivity, inattention, and impulsiveness3—all to an extent, which causes significant burden on those affected, their families and society as a whole10.Attention-deficit/hyperactivity disorder (ADHD) is a childhood-onset neurodevelopmental disorder with a prevalence of approximately 5–7% among children/adolescents11 in the entire spectrum of mental disorders13. Accordingly, recent studies focusing on both common- and rare genetic variants have identified genes associated with ADHD16. Also, a number of early adverse psychosocial factors have consistently been linked to ADHD21. Furthermore, there is a growing body of literature supporting the hypothesis that genetic and psychosocial risk factors do not only have direct effects on the risk of ADHD, but also interact24. However, most studies on the combined effect of genetic and psychosocial risk factors for ADHD are based on relatively small samples of patients and healthy controls volunteering for study participation, who have self-reported historical data on their psychosocial environment29. The combination of the use of healthy controls and self-reported historical data on psychosocial environment introduces a substantial risk of selection and recall bias31. Relatedly, most prior gene–environment interaction studies in ADHD have focused on candidate genes in the dopaminergic and serotonergic system that were not replicated in the recent GWAS of ADHD29. Therefore, studies of the effect of interaction between genetic risk and psychosocial environment upon the risk of ADHD, which avoid the abovementioned threats to internal validity are needed. Here, we aimed to conduct such a study using data from the Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH) case-cohort32. Specifically, the aim of the study was twofold:I.To investigate the main effects of the polygenic liability for ADHD and the psychosocial environment on the risk of ADHD: Here, we will investigate the association between a polygenic risk score (PRS) for ADHD, maternal/paternal education, maternal/paternal work status, maternal/paternal income and maternal/paternal history of mental disorder and the risk of developing ADHD in a population-based sample.II.To investigate polygenic by psychosocial risk factor interaction on the risk of ADHD: Here, we will test whether there are interactions between the genetic liability (PRS) and the risk factors pertaining to the psychosocial environment  with regard to the risk of developing ADHDThe specific causes of ADHD remain largely unknown, but a number of twin studies have suggested that the disorder is among the most heritable  and psychosocial information for each individual  was extracted from nationwide Danish registers. Since the establishment of the iPSYCH case-cohort was not based on opt-in participation32, the risk of selection and attrition bias is minimal. Furthermore, as proxy information on the psychosocial environment is registered routinely for all individuals with an address in Denmark17, there is virtually no recall bias either. Therefore, this dataset allows us to investigate the combined contribution of genetic and psychosocial risk factors for ADHD in a population-based sample virtually without the impact of the typical biases affecting studies of this type.This study was based on data from the iPSYCH case-cohort, which consists of 86,189 singletons born in Denmark between May 1, 1981 and December 31, 2005, who resided in Denmark on their 1st birthday32. To further mitigate confounding by population stratification, we computed the orthogonalized Gnanadesikan-Kettenrin robust Mahalanobis distance of the ten leading ancestral principal components, and excluded individuals who had a logarithm-distance larger than three (1120 with ADHD and 1730 population controls)36. This led to inclusion of a total of 33,872 individuals, namely 13,725 with ADHD and 20,147 population controls. There were 771 sibling constellations (2–4 cohort members with the same parents) within this population. For 454 (58.9%) of these constellations, all siblings were in the ADHD group, for 154 (20.0%), all siblings were among the population controls, and for 163 (21.1%) the sibling constellation represented a mix of individuals with ADHD and population controls. A total of 750 (97.3%) of the sibling constellations consisted of two siblings. The median age at diagnosis of ADHD was eleven years (interquartile range: 9 years) and total of 593 (4.3%) of the individuals with ADHD were also registered with a diagnosis of oppositional defiant disorder or conduct disorder  either prior to or at the time of the ADHD diagnosis.In this study, we focused on the individuals that were included in the iPSYCH case-cohort due to an ADHD diagnosis (ICD-10 code F90.0) as well as the iPSYCH population controls for whom there were valid genotypes and who had parents that were both born in Denmark38, the Danish Psychiatric Central Research Register 34, the Danish Education Register (education)39, the Danish Register on Personal Labour Market Affiliation (work status)40, the Danish Register on Personal Income and Transfer Payments (income)41, and the Danish Neonatal Screening Biobank42 (genotypes generated via the Infinium PsychChip v1.0 array (Illumina) for obtaining PRS for ADHD)32. Linkage of information from these six sources is made possible by the unique personal registration number, which is assigned to all individuals residing in Denmark38.For the 33,872 individuals in the study cohort, we extracted data from six sources, namely the Danish Civil Registration System 15. The 23 genotyping batches of the iPSYCH sample were split into five groups of approximately equal size, aiming for an equal number of ADHD cases within each group. Five leave-one-out analyses were then conducted, using four of five groups as discovery datasets for estimation of SNP effect sizes, while estimating PRS for the remaining target group. The GWAS meta-analyses of the discovery samples were conducted using an SNP list filtered for minor allele frequency >0.01 and an imputation threshold score above 0.8 intersecting across batches. INDELs and variants in the extended MHC region (chromosome 6: 25–34 Mb) were also removed. Meta-analysis and “LD-clumping” of significant SNPs were conducted using the ricopili pipeline43. PRS was then estimated for each target sample using a range of meta-analysis p-value thresholds , multiplying the natural log of the odds ratio of each variant by the allele-dosage of each variant. Whole-genome PRS were obtained by summing values over variants for each individual. The PRS was standardized within target groups. The significance of the case-control score difference was tested by standard logistic regression including principal component and dummy variables indicating genotyping batch as covariates and the proportion of variance explained was estimated for each p-value threshold by comparing the full model with a reduced model without PRS and thus including covariates only (i.e. Nagelkerke’s R2). The standardized score for the p-value threshold with the highest Nagelkerke’s R2 (p < 0.2) was used in the subsequent analyses. The standardized PRS for ADHD was divided into 50 groups each representing 2% of the distribution among the randomly drawn population controls.The PRS for ADHD for each individual was estimated as described in Demontis et al17, this was not possible in the present study due to restrictions enforced by the Danish Neonatal Screening Biobank. Therefore, in this study, we focused on the psychosocial environment in the family of the cohort members instead, as there is a well-known association between this construct and concrete adverse incidents among children50. Specifically, we focused on maternal/paternal history of mental disorders, maternal/paternal education, maternal/paternal work status, and maternal/paternal income.While we have previously used a register-based operationalization of Rutter’s indicators of adversity in relation to ADHD33. The following categories were defined based on diagnoses from the International Classification of Diseases, 8th revision (ICD-8), which was used as diagnostic reference from 1969 to 1993 and from the International Classification of Diseases, 10th revision (ICD-10), which was used from 1994 and onwards: Schizophrenia and related disorders , Mood disorders (ICD-8: 296.x9 (excl. 296.89), 298.09, 298.19, 300.49, 301.19. ICD-10: F30-F39), Neurotic, stress-related, and somatoform disorders (ICD-8: 300.x9 (excl. 300.49), 305.x9 305.68, 307.99. ICD-10: F40-F48), and other mental disorders not listed under the categories above (ICD-8: 290–315. ICD-10: F00-F99)51. The categories were hierarchical and mutually exclusive such that schizophrenia and related disorders trumped mood disorders, which trumped neurotic, stress-related, and somatoform disorders, which trumped other mental disorders.At the date of birth of the cohort members, we assessed whether their parents were registered with a diagnosis of a mental disorder in the Danish Psychiatric Central Research Register39 using the following levels: primary school, high school or vocational education (e.g. carpenter or bricklayer), short- or medium-length higher education , long academic education (master level university degrees or PhD).Information regarding the parents’ highest completed level of education in the year of the birth of the cohort members was extracted from the Danish Education Register40 using the following levels: unemployed or otherwise outside the labor marked, student in education, blue collar worker, self-employed, clerical worker or leading wage-earner.Information regarding the parents’ primary work status in the year prior to the birth of the cohort member was extracted from the Integrated Database for Labor Market Research41. The income was scaled to 2004 level using the price index from the World Bank. The income of the mothers and fathers of the randomly drawn population controls was used to create income quintiles. Individuals with missing values were placed in the lowest quintile.The parents’ income in the year prior to the cohort members’ birth was extracted from the Registers on Personal Income and Transfer Payments52. Lastly, we evaluated whether the PRS (continuous) interacted with the risk factors pertaining to the psychosocial environment upon the risk of ADHD. As a sensitivity analysis, we challenged the necessity for excluding ancestral principal components outliers, by repeating the analyses outlined above, without exclusion of individuals (1120 with ADHD and 1730 population controls) based on ancestral principal components outliers54. Analyses were conducted using SAS 9.4 and R version 3.5.1.The associations between the PRS for ADHD, the risk factors related to the psychosocial environment and ADHD were assessed using logistic regression. Odds ratios and 95% likelihood ratio-based confidence intervals were computed. For the main effects of the PRS for ADHD and the risk factors related to the psychosocial environment, crude odds ratios for ADHD adjusted for sex and year of birth were computed. To assess whether the impact of the psychosocial factors was mediated through the genetic liability for ADHD, we calculated odds ratios that were also adjusted for the PRS. Furthermore, to investigate whether the PRS effect was partly explained or confounded by the psychosocial environment, we calculated odds ratios that were fully adjusted for all psychosocial factors. To explore the polygenic liability distribution across case-control status and the factors pertaining to the psychosocial environment, we calculated population marginal meansThe study was approved by the Danish Health Data Authority, the Danish data protection agency, The Danish Neonatal Screening Biobank Steering Committee and the Danish Scientific Ethics Committee.The characteristics of the cohort members—including information regarding the PRS for ADHD and the risk factors related to the psychosocial environment—are shown in Table Column 1 in Table The population marginal means of the PRS for ADHD adjusted for sex and year of birth are displayed in Figure The combined effect of the PRS for ADHD in quintiles and each of the psychosocial risk factors  is shown in Fig. p-values for interaction range from 0.06 to 0.48).These plots are predominantly indicative of independence between the effects of the PRS for ADHD and the psychosocial risk factors upon the risk of ADHD  upon the risk of ADHD. Furthermore, the associations with the PRS for ADHD and paternal education, paternal income, and maternal work status were largely independent with little indication of any gene–environment interaction.13. Also, it is in line with the recent GWAS, which identified the first genome-wide significant loci for ADHD15. Notably, the association between the PRS for ADHD and the risk for ADHD reported here remained almost unchanged when adjusting for the psychosocial risk factors, which included the maternal and paternal history of mental disorder. Thus, the PRS effects were not explained by parental psychopathology or socioeconomic factors, and furthermore, the impacts of the psychosocial factors were not mediated the genetic liability for ADHD. This suggests that manifest mental disorder in the parents is not a requirement for transmission of genetic risk for ADHD13.That the PRS for ADHD is strongly associated with the development of ADHD in this sample is consistent with a substantial body of evidence suggesting that ADHD is among the most heritable conditions among the mental disorders21. The present study corroborates these findings using a relatively broad definition of psychosocial adversity, which likely taps into a “background” environment where some of the more specific insults that have been associated with subsequent development of ADHD—such as early severe deprivation55, maltreatment56, and inconsistent parenting24—are also more likely to occur.Psychosocial adversity operationalized in a vast variety of ways has been associated with increased risk of ADHD in a large number of studies29. However, these prior studies have (i) tended to be based on small case-healthy control samples, (ii) used self-reported historical data on psychosocial environment, and (iii) focused on individual candidate genes (predominantly in the dopaminergic and serotonergic system) that were not replicated in the recent GWAS of ADHD29. For these reasons, the results of the present study are most likely more internally valid than those from the prior studies on this topic.In this study, we found no support for interaction between the polygenic liability for ADHD and the psychosocial environment upon the risk of ADHD. This is in contrast with results from prior studies that have investigated the role of gene–environment interaction in the etiology of ADHD15, genes involved in synapse formation (FOXP2)58, neuroplasticity (SORCS3)60, and dopaminergic homeostasis (DUSP6)62 may be playing an important role. Determining whether this is indeed the case, will require larger GWAS of ADHD to allow for sufficient estimation of PRSs for specific genetic pathways.The results of this study raise the question as to which specific genetic pathways are responsible for the observed dose-response association between the PRS for ADHD and development of ADHD. Based on the results from the recent GWAS of ADHD32. Hence, children who were diagnosed with ADHD outside psychiatric hospital settings, e.g. by private practicing psychiatrists or by pediatricians, do not appear as “cases” in this study —as these practitioners do not report diagnoses to the Danish Psychiatric Central Research Register, which provided the diagnostic data for this study. Therefore, our results might not generalize to patients with less severe ADHD than those diagnosed at psychiatric hospitals. On the other hand, an advantage of using register data is that the validity of the ADHD diagnoses in the register has been evaluated and found to be appropriate for research purposes64. Secondly, gene–environment correlation may threaten the internal validity of the results65. Specifically, the parents of the cohort members may create a family environment that is correlated with the cohort members’ genotype—an effect of so-called genetic nurture, in which environmental influences are misidentified as genetic66 In order to counteract this effect, we have adjusted the analyses involving the PRS for ADHD for the parents’ history of diagnosed mental disorder. However, since this adjustment only takes relatively severe psychopathology into account, which has led to treatment at psychiatric hospitals, this does not rule out the possibility that passive, or evocative67, gene–environment correlation may have led to an overestimation of the effect of gene–environment interactions on the risk of ADHD due to confounding65. Third and finally, it is broadly recognized that PRSs are not yet very informative at the level of the individual and therefore not clinically useful in psychiatry69. However, this may change with the results of future GWAS that will likely to explain a larger fraction of the polygenic liability for ADHD and other mental disorders.There are limitations to this study, which must be taken into account by the reader. First, due to the biobank- and register-based nature of this study, we were only able to include individuals with ADHD who received a diagnosis of ADHD during inpatient or outpatient treatment at a psychiatric hospital in DenmarkIn conclusion, based on a study of 13,725 individuals with ADHD and 20,147 population controls, we report strong and independent main effects of genetic liability and psychosocial adversity upon the risk of ADHD—in the expected direction. In contrast, we found no significant interactions between the polygenic liability and the psychosocial environment upon the risk of ADHD, and the genetic liability in individuals with ADHD was increased across all psychosocial factors. Future studies should address if specific genetic pathways and environmental factors are responsible for these results. This line of research may lead to identification of targets for both treatment and preventive measures.Supplementary Material


Approximately 20% of children with attention-deficit hyperactivity disorder (ADHD) experience clinical levels of impairment into adulthood. In the UK, there is a sharp reduction in ADHD drug prescribing over the period of transition from child to adult services, which is higher than expected given estimates of ADHD persistence, and may be linked to difficulties in accessing adult services. Little is currently known about geographical variations in prescribing and how this may relate to service access.To analyse geographic variations in primary care prescribing of ADHD medications over the transition period (age 16–19 years) and adult mental health service (AMHS) referrals, and illustrate their relationship with UK adult ADHD service locations.n = 9390, 99% diagnosed <18 years), regional data on ADHD prescribing over the transition period and AMHS referrals, were mapped against adult ADHD services identified in a linked mapping study.Using a Clinical Practice Research Datalink cohort of people with an ADHD diagnosis aged 10–20 in 2005 , as well as in referral rates to AMHSs, range 4–21% (P<0.001). There was no obvious relationship between service provision and prescribing variation.Differences were found by region in the mean age at cessation of ADHD prescribing, range 15.8–17.4 years (Clear regional differences were found in primary care prescribing over the transition period and in referrals to AMHSs. Taken together with service mapping, this suggests inequitable provision and is important information for those who commission and deliver services for adults with ADHD. This is a key developmental stage when multiple other transitions are likely, such as changing educational setting or leaving home for the first time. The National Institute for Health and Care Excellence (NICE) guidelines recommend that prescribing of ADHD medication for adults should happen via shared-care agreements between primary and secondary care.2 The principle of shared care assumes that the young person will be in the care of an adult mental health service (AMHS) with the general practitioner (GP) continuing to prescribe.3 However, problems could arise, because of the lack of adult ADHD services, because there is no shared-care agreement or because GPs are not prepared, trained or supported to prescribe.5Rates of primary care prescribing of attention-deficit hyperactivity disorder (ADHD) medication for young people with ADHD in the UK appear to decline more steeply than expected given the rate of symptom reduction from follow-up studies.7 Disruption of care during transition adversely affects young people with mental health conditions8 whereas untreated ADHD can worsen health, education and occupational outcomes.10 For those young people who continue to require medication, cessation of prescribing could be related to lack of service provision. Studies have suggested that there are gaps in provision of adult ADHD services and a shortage of specialist services.12 Population prescribing studies suggest higher incidences of ADHD diagnosis and prescribing in young people in areas of socioeconomic deprivation,13 however, this is unsurprising given the strong link between deprivation and the prevalence of ADHD.14Evidence is increasingly emerging of low rates of successful transition and poor-quality transition experiences for people with ADHD.To our knowledge, no study has examined regional differences in prescribing for young people with ADHD in the UK during the transition period. Knowledge and understanding of any regional variations in prescribing rates through the transition, and potential links to availability of dedicated adult ADHD services may allow commissioners and practitioners to address inequalities of provision. The current study aimed to analyse regional variation in prescribing patterns of ADHD medication and rates of referrals into AMHSs for young people with ADHD aged between 16 and 20 from 2005 to 2013, using the Clinical Practice Research Datalink (CPRD). It also aims to explore relationships between prescribing patterns, referral rates and service locations.15The CPRD is a large database of anonymised patient records including diagnoses, prescribed drugs and referrals to secondary care services. The primary care section is contributed to by over 670 GP practices across the UK and contains the records of over 11 million patients. It covers up to 6% of the UK population and is broadly representative in terms of age, gender, ethnicity and geographical location of practices.16 Data on services were gathered from over 2600 informants from across the UK; patients, health workers and National Health Service (NHS) commissioners. Data were collected via an online survey, freedom of information requests to commissioners (90% response rate) and surveillance reports. A total of 44 NHS dedicated adult ADHD services were identified, consisting of 29 ADHD; 7 ADHD and autism spectrum disorder; and 8 neurodevelopmental services.17The data source for service locations was the 2018 UK mapping study, a national survey of adult ADHD services, run as part of the ‘Children and Adolescents with Attention Deficit Hyperactivity Disorder (ADHD) in Transition from Child to Adult services’ (CATCh-uS) study of transition in ADHD.1 This allowed us to study prescribing over the transition period . To be included, individuals had to have a diagnosis of ADHD coded in their primary care record (n = 9390). Of included patients, 98.6% (n = 9261) had their first ADHD clinical code coded under the age of 18. ADHD diagnoses were defined as any of the 22 CPRD medical codes and primary care Read terms (based on ICD-10 F90 or DSM categories) that relate to an ADHD diagnosis . Patients were defined as having an ADHD prescription if any prescription record had an ADHD-related medication code, including categories of stimulants and non-stimulants for ADHD.1 Rare cases of patients with narcolepsy, for which ADHD medication may be prescribed (n<20) were excluded from the analysis.We used a cohort from the CPRD of young people aged between 10 and 20 in 2005, for the study period that ran from 1 Jan 2005 until 31 Dec 2013.Regions were defined by the NHS strategic health authority (SHA) boundaries, in which reporting GP practices were situated during the study period.18 and focused on changes in prescribing of ADHD medication through the transition period (defined as 16–19 years of age) and incidences of referral to AMHSs. The CPRD did not supply dates of birth, therefore age bands were assigned, with, for example, age-band 14/15 indicating the year of their 15th birthday. We defined this transition period as being between the year of their 16th birthday, which commonly marks the end of children's services, and the year of their 19th birthday, which is when the transition to adult services should be completed, according to NICE guidance.19The first phase of analysis used Stata version 15.0First, analyses were carried out to examine differences in prescribing prevalence by region. The proportion of patients with an ADHD prescription at any point was calculated, followed by the proportion of others with a prescription in each age band from 14/15 years to 19/20 years, to cover the transition period and 1 year either side. For each region, the difference in the proportion of patients with an ADHD prescription between the beginning and end of the transition period was then reported. The denominator for each age band only included patients who had records for the full year in question.Age at cessation of medication by region was then examined, with cessation defined as a gap of more than 6 months in prescriptions. This was chosen to allow for uncertainty in estimating prescription length as ADHD prescriptions are typically provided for between a 1- and 2-month duration, and to account for any medication ‘breaks’ that may occur. When calculating age at cessation, the cases of patients that were censored, as they still had a prescription at the time of leaving the database (i.e. lost to follow-up or at the age boundary of the cohort) were excluded from the analysis. As full details of date of birth are not provided by CPRD, to calculate the age of cessation date of birth was designated as 1 July for each individual, minimising error each way to a maximum of 6 months. Mean age of cessation was calculated with confidence intervals, and a one-way ANOVA run to explore differences in means by region.2-test. Given that referral might have been for non-ADHD related treatment, we also described the proportion excluding the cases of patients potentially referred for a psychiatric comorbidity. The first definition used was ‘cases without any other psychiatric diagnoses’. However, as diagnoses are not coded as reliably as prescription data in the CPRD,20 and common comorbidities such as autism spectrum disorder are not consistently treated in AMHSs, a second definition was also used of ‘cases without a prescription for any other psychotropic medication’.Patients were defined as having a referral to an AMHS if they were coded with a referral to adult psychiatry, a community psychiatric nurse or clinical psychology. The proportion of patients referred by region was calculated, examining differences in proportions using the χ21 and maps created to illustrate changes in patterns of prescribing and rates of referral to AMHSs by region. Locations of dedicated NHS services for adults, as identified in the 2018 CATCh-uS study17 were plotted on the same maps.Linear regression was used to examine the association between region (independent variable) and the age of cessation (dependent variable) and subsequently adjusted for referral to an AMHS as a covariate. The second phase of analysis used a geographic information system, QGIS 2.18, to analyse and display the service mapping data alongside the prescribing data. Shapefiles for UK countries and SHA regions were importedWe 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. All procedures involving human patients were approved by the following: for the CPRD data-set, the Independent Scientific Advisory Committee on behalf of the National Research Ethics Service Committee (protocol number 13_213); for the 2018 CATCh-uS mapping study, the University of Exeter Medical School Ethics Committee (REC Application Number: 15/07/070).n = 7876) were male, 25% (n = 2335) had a recorded diagnosis of a psychiatric comorbidity, 62% (n = 5780) had at least one recorded prescription for an ADHD medication, and 25% (n = 2336) had a prescription for any other (non-ADHD) psychotropic medication. Following censoring, 3476 patients (37%) had complete data that allowed us to calculate age of cessation of ADHD medication. Patients who were censored were similar to those that were uncensored with respect to medication duration and year of birth.There were 9390 eligible patients: 84% (Scotland was the region with the highest percentage of patients (75%) with at least one ADHD prescription at any point, whereas Yorkshire and the Humber had the lowest (48%). There were differences by region in the proportion of patients that had an ADHD medication prescribed for every age band, see The drop in the proportion of patients with an ADHD prescription between the year of their 16th birthday and the year of their 19th birthday (age bands 15/16 and 18/19) was 19% for all patients; but varied by region from 6% in the North East to 25% in the North West, see F = 6.18, P<0.001.The mean age of termination (or interruption) of medication prescription was 16.6 years  . A one-w2 = 121.60, P<0.001. When patients with any other non-ADHD psychiatric diagnosis were excluded from the data-set, the overall proportion dropped to 9%, and varied by region from 3 to 15%  = 49.12, P<0.001). When patients with a prescription for any other psychotropic medication were excluded, the percentage of those referred was even lower (7%), and also varied by region from 3 to 11%  = 27.73, P>0.001).The percentage of patients with ADHD referred to any AMHS was 11% , but varR2 = 0.0013, F = 4.56, P = 0.03). However, when referral to any AMHS was added to the model,  = 83.55, P<001), region was no longer a predictor and only referral to any AMHS was a significant predictor of age of prescription cessation.There was a marginal association between region and the age of cessation of ADHD medication prescription in the unadjusted model . Although medication has been recommended by NICE for management of adult ADHD, as the 2008 guidance evidence suggests GPs may feel unsupported to prescribe ADHD medications to adults, with issues such as lack of training or lack of available support from a specialist service identified as barriers to prescribing.10 The regional differences in prescribing and referrals found in this study support available qualitative evidence of unsupported transitions and findings of limited adherence to and inconsistencies in implementation of the NICE guidelines on transition.12Regardless of local prescribing and secondary care arrangements, if a young person does not transition into adult services, they are unlikely to continue to receive treatment into adulthood. Young people with ADHD are already at a higher risk of a range of negative health, educational and occupational outcomes compared with the general population, and without treatment, these risks are increased.15Strengths of this study include a large population-based sample of primary care records. To our knowledge this is the first time primary care ADHD medication prescribing in the transition age group among adults with a childhood diagnosis and referrals to AMHSs have been analysed by region. It is also the first time regional quantitative data on primary care prescribing and referral rates have been explored in comparison with national UK data on the locations of adult ADHD services. A key limitation of this was the time lapse between the study period for CPRD data (2005–2013) and the date of the service mapping study (2018). The provision and organisation of mental health services are constantly evolving and some services identified in 2018 may only have been recently commissioned. In addition, although the CPRD data-set automatically includes all primary care prescriptions, those issued through a secondary mental health service may be missing.27 which taken with evidence of regional variations in prescribing, are indicative of gaps in provision. But it is also possible that evidence of higher rates of continued prescribing at age 17/18 in some regions might reflect the cases of patients where a failure to review need had led to an inappropriate continuation of prescribing.Although we were able to analyse patterns of regional variation, we had no information on the severity of the ADHD diagnosis for each patient, and could not determine whether prescribing decisions were clinically appropriate or inappropriate. We were also unable to adjust for continuing symptom severity over time. There is considerable evidence emerging from qualitative and quantitative research of the premature cessation of ADHD medication through transition,2 guidance states that once a young person is stable on ADHD medication, prescribing should be through shared care, however, in some patients with complex cases secondary services may have prescribed for longer than the 6-month time period defined as medication cessation in this study. If this prescribing is not recorded in CPRD these patients may have been inaccurately recorded as having stopped medication. In addition, we may have underestimated referral rates, as although CPRD records referrals from primary care into AMHSs, if referrals are made using free-text letters these can only be captured by scanning the free text, which we did not have access. Similarly, free-text references to referrals between child services and AMHSs would not be included. However, this limitation is likely to apply across all regions, and is unlikely to have influenced the significant variation in referral rates found in our analysis.NICEA further study weakness is the size of regions analysed. Although SHA reflected the structure by which healthcare was organised during the CPRD study time period, their large size means they include multiple NHS trusts and many GP practices, which may vary in their arrangements for adults with ADHD. The size of defined regions also made it difficult to incorporate geographic deprivation measures into the analysis, as deprivation varies at much smaller geographies than this. Future research would benefit from using smaller geographic areas.Finally, our sample frame was young adults with a childhood diagnosis of ADHD. Another important gap in adult services for ADHD is assessment, diagnosis and treatment for those who present as adults for the first time. Given our sample frame, we cannot comment on this important aspect of access to services, which should be addressed using an alternative sample frame. It would be interesting to see if regional variation in this related group of patients followed a similar regional pattern.28 Large and unchanging regional health inequalities in England point to the need for targeted interventions to improve the equity of access to care more generally.29 Studies of variation can help to increase accountability for mental health service provision, and indexing regional differences in prescribing and referral rates is one way of highlighting inequity. This data can contribute to planning regional service development and provision and, ultimately, to addressing health inequalities in people with ADHD.In conclusion, these findings, combined with evidence that more than one in ten commissioners are failing to meet expected Mental Health Investment Standards, point to unequal provision of resources for mental health.


Aims: This study examined medication use for attention-deficit/hyperactivity disorder (ADHD) among children and adolescents by gender in Finland during 2008–2018. Methods: Aggregated data on medication use for ADHD from 2008 to 2018 were extracted from the nationwide register on reimbursed prescriptions. The annual prevalence of ADHD medication use was calculated as the number of children (6–12 years) and adolescents (13–17 years) per calendar year with at least one ADHD medication purchase divided by the number of children and adolescents in the population. Population prevalence for children was also examined by birth month. Results: In 2008, the prevalence rates for males were 1.26% in children and 0.93% in adolescents, and for females 0.21% and 0.14%, respectively. In 2018, the prevalence rates for males were 4.42% in children and 4.21% in adolescents, and for females 0.99% and 1.28%, respectively. Male-to-female ratios decreased during the study period from 6.0:1 to 4.5:1 (children) and from 6.6:1 to 3.3:1 (adolescents). ADHD medication use was more common among males and females (aged 6–12 years) born in May–August or September–December than among males and females born in January–April. Conclusions: The prevalence of ADHD medication use has continued to increase in Finland. Although use has increased more rapidly among females resulting in lower male-to-female ratios, medication use among females is considerably lower compared with males. Consequently, gender discrepancy in 2018 was relatively large, particularly among children. Future studies should also consider reporting annual prevalence by children’s birth month. Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by behavioural symptoms of inattention, hyperactivity, and impulsivity. ADHD is further associated with considerable social functioning deficits –3. Poole6Pharmacotherapy is an important part of ADHD treatment . Stimula1414Recent findings indicate that male-to-female ratios in medication use among child and youth population range from 2:1 to 6:1 , with th171925This paper extends the findings from recent Nordic and international comparison studies , 15 by eData on ADHD medication purchases reimbursed by the National Health Insurance in 2008–2018 were extracted from the Finnish Prescription Register for children and adolescents aged 6–17. Use of ADHD medication was defined as at least one purchase of methylphenidate, atomoxetine, dexamphetamine, or lisdexamfetamine per calendar year. The annual prevalence of ADHD medication use was calculated as the number of children and adolescents with at least one reimbursed purchase of ADHD medication during the calendar year divided by the number of children and adolescents in the total population at the end of the year. The population was stratified by sex into two age groups: children (6–12 years) and adolescents (13–17 years). In Finland, the cut-off date for school eligibility is December 31. Thus, ADHD medication use in children by birth month was examined as follows: (a) born between January and April, (b) born between May and August, (c) born between September and December. According to national regulations, the study required no ethical approval.In 2008, the prevalence of ADHD medication use in the child population was 1.26% among males and 0.21% among females. During the study period, the prevalence increased steadily for both sexes. By 2018, the prevalence had increased to 4.42% among males, and to 0.99% among females .In the adolescent population, the prevalence of ADHD medication in 2008 was 0.93% among males and 0.14% among females, but had increased to 4.21% among males and to 1.28% among females by 2018. Among males, ADHD medication use was more common in children than in adolescents throughout the study period, whereas among females, medication use has been slightly more common in adolescents than in children since 2013.In children, ADHD medication use was associated with birth month across genders. Data further showed that ADHD medication use was more common among males born later in the calendar year  when compared with their peers born in January–April across the whole study period. Among females, birth month and ADHD medication use were similarly associated .Finally, among children receiving ADHD medication, the male-to-female ratio decreased during the study period from 6.0:1 to 4.5:1 , but theFrom 2008 to 2018, the prevalence of ADHD medication use among Finnish children and adolescents increased steadily. This probably stems from a greater awareness of ADHD and changes in diagnostic and treatment practices ,16. For Comparing the results to other Nordic countries is somewhat difficult, as the trends beyond 2013 are unknown –16. HoweOur study agreed with a recent population study from 13 countries and showed that the gender discrepancy in ADHD medication use is relatively large in Finland . We obseOur study agreed with prior studies indicating that younger relative age within the school year is associated with increased ADHD medication use –27. AlthThe results revealed that gender discrepancy has decreased more rapidly among adolescents than among children, and that among male prevalence rates for adolescents were lower relative to children across the whole study period. However, among females, prevalence has been slightly higher for adolescents since 2013. Prior studies show that the female gender may relate to increased adherence to pharmaceutical treatment in adolescence  and thatThe major strength of our study is that the Prescription Register covers the whole Finnish population. The major limitation is that register data are based on claims data from pharmacies and it is unknown whether the medication is actually used.Importantly, due to the increase in ADHD medication use there is a need for prospective population-based studies that examine the effectiveness and safety of pharmacotherapy, availability and adherence to the multimodal treatment components of ADHD, as well as the transition processes in children and adolescents in more detail.


Children with attention-deficit/hyperactivity disorder (ADHD) often demonstrate sensory processing difficulties in the form of altered sensory modulation, which may contribute to their symptomatology. Our objective was to investigate the neurophysiological correlates of sensory processing deficits and the electrophysiological characteristics of early information processing in adult ADHD, measured by the P1 event-related potential (ERP).We obtained ERPs during a Go/NoGo task from 26 adult patients with ADHD and 25 matched controls using a high-density 128-channel BioSemi ActiveTwo recording system.ADHD patients had a significantly reduced P1 component at occipital and inferotemporal scalp areas compared to controls. The reduction was associated with inattention and hyperactivity symptom severity, as measured by the Conners’ Adult ADHD Rating Scale. ADHD patients with higher inattention scores had significantly smaller P1 amplitudes at posterior scalp sites, while higher hyperactivity scores were associated with higher P1 amplitudes.Deficits in early sensory processing, as measured by the P1 ERP component, are present in adult ADHD patients and are associated with symptom severity. These findings are suggestive of bottom-up cognitive deficits in ADHD driven by impairments in early visual processing, and provide evidence that sensory processing problems are present at the neurophysiological level in this population. Attention-deficit/hyperactive disorder (ADHD) affects around 3–6% of children  and persResearch of childhood ADHD suggests  that besTo gain insight to the neural mechanisms associated with symptoms of psychiatric disorders, including ADHD, electro-encephalography (EEG) and event-related potentials (ERPs) are commonly employed. Due to its high temporal, and - with high-density EEG – good spatial resolution, EEG offers a detailed understanding of specific cognitive dysfunctions.While current research focuses mainly on the later timeframe of information processing, the presence of ADHD is thought to affect not only the top-down attentional selection but also the early, bottom-up sensory processing , 14. GenIn case of children with ADHD a reduction in the P1 component has been demonstrated using a wide range of paradigms including oddball –21, stopIn the adult ADHD literature, Woltering et al.  in theirWith high-density EEG, due to its excellent time-resolution and topographical information on the whole scalp area, it is possible to gain a more detailed insight into the early sensory (‘bottom-up’) processes. In the current study, in addition to focusing on the region of interest electrodes that were predominantly examined in prior studies, our main goal was to conduct a detailed topographical analysis of the early processing of the sensory information in adult ADHD patients and healthy controls based on high density (128-channel) EEG recordings. Previous research which examined the topographical distribution of early ERP components in ADHD patients either relied on sparse spatial sampling, or used a lower number of electrodes. However, as shown by Srinivasan et al. , ‘ … theGiven the limited and somewhat controversial and methodologically diverse ERP data on adult ADHD, this study with its Go/NoGo paradigm previously successfully used in functional imaging studies , 35 aimsn = 9) was on methylphenidate medication monotherapy, three patients were receiving bupropion  while fourteen patients were medication-naive. ADHD patients on stimulant medication were required to go off their medication 24 h prior the EEG session. The study complied with the ethical standards of the Declaration of Helsinki, and received approval from the Ethical Committee of Semmelweis University. All participants gave written Informed Consent for the study.Fifty-one subjects participated in the study, including 26 adult ADHD patients and 25 healthy control subjects. Healthy controls were matched to the patients on age (±5 years), gender and level of education. Control subjects were excluded in case of neurological or psychiatric history. In control subjects, the absence of a current psychiatric condition was confirmed with the Symptom Checklist 90R (SCL-90R) . No contParticipants were seated in a dimly lit room; a computer screen was placed at a viewing distance of approximately 50 cm. The applied Go/NoGo paradigm was previously used and described by Durston et al. . In accoADHD symptom severity was described by the Conners’ Adult ADHD Rating Scale-Self-Report: Long Version  across core psychopathological domains of ADHD: inattention, hyperactivity, impulsivity and problems with self-concept . The totEEG was recorded using a 128-channel active electrode system (BioSemi ActiveTwo). The electrode cap covered the whole head with an equidistant-layout. Eye movements were monitored by two electrooculogram (EOG) electrodes placed below the left and above the right external canthi. Data were digitized at a sampling rate of 1024 Hz, with a band-pass filter of 0.5-70 Hz using the BioSemi recording system with average reference. Data were stored and analysed off-line subsequently using the Electromagnetic Source Signal Imaging (EMSE) Suite as well as the Statistical Analysis System (SAS 9.4) software. Artefact rejection, including the exclusion of eye movement artefacts based on horizontal and vertical EOG, and subsequently the exclusion of epochs with a voltage exceeding ±90 μV on any EEG or EOG channel was conducted applying automatic artefact rejection criteria. For stimulus-locked ERP, epochs of 900 ms duration from 100 ms prestimulus to 800 ms poststimulus were extracted from the continuous EEG. The -100 ms timepoint was selected in order to establish pre-stimulus baseline, while the 800 ms post-stimulus timepoint was chosen to cover most of the stimulus presentation period, ending before its offset. Our selected timeframe for the ERP epochs is similar to that used in the literature by others who investigated ERP responses in adult ADHD patients  occurring in the window from 120 to 150 ms post-stimulus . When inSince early visual ERP components such as P1 typically exhibit polarity reversal in the posterior-to-anterior direction , at the p < 0.01 in each of the two study groups). We also investigated the distribution of error rates, and found that it - similarly to reaction times - deviated from the normal distribution in both study groups (p < 0.01). Since the distribution of reaction times and error rates was right skewed with increasingly higher values occurring with increasingly lower frequency, these behavioural data were analysed by applying the Generalized Linear Mixed Model (GLIMMIX) analysis with a logarithmic link function to compare the two study groups. This approach makes allowance for non-normally distributed data, such as the right skewed distribution of behavioural data in our study. Measure of central tendency for the reaction time and commission error rate in each group was characterized by the mean and 95% confidence limits, which were derived as backtransformed data from the GLIMMIX procedure from logarithmic to the original units (msec or error rate).Performance was assessed with measures of the mean reaction time and commission error rates. For reaction times, large values that exceeded the upper threshold of 1 s and small values that were below the threshold of 250 msec (and were therefore unlikely to be stimulus-locked responses) were excluded from the analyses. Therefore, the accepted reaction time range was between 250 and 1000 ms (inclusive). Less than 0.5% of the individual reaction time values were rejected in each of the two groups on the basis of these threshold criteria . We checked the distribution of the reaction times after excluding values that were outside the accepted range. As indicated by the Kolmogorov-Smirnov D-statistic, the distribution of reaction times deviated from the normal distribution . Amplitude (voltage) values within the time-window of interest (120-150 ms) were used as dependent variable in the HLM. Group, time (sampling point) and their interaction were applied as independent variables; age and gender and level of education served as covariates in all analyses. A separate analysis was performed for each scalp site of interest . For these topographical analyses using the full set of the 128 channels, the False Discovery Rate (FDR)-corrected p-values  were comIn order to delineate the topographical distribution of the differences, we investigated whether the EEG recording from multiple individual channels aggregated into electrode clusters with respect to group differences. We defined electrode clusters as a group of at least five adjacent scalp derivations with significant group difference in the same direction.For scalp sites of interests that yielded a significant group difference in the primary analysis after Bonferroni correction for multiple testing, we conducted additional analyses to test whether psychopathological variables served as covariates in explaining the significant alterations in early sensory activity. These covariates included the total score on the CAARS Hyperactivity, Impulsivity, Inattention, and Problems with Self-Concept domains. In subsidiary analyses, we also investigated whether comorbidity (present/absent) and medication status  impacted our results. In these analyses, the latter variables were included as additional covariates in the HLM model.Basic demographic and clinical characteristics of the study population are provided in Table n = 4), and anxiety disorders (n = 4) or both (n = 3). Approximately half of the 26 patients had psychopharmacological treatment ; these included patients who received methylphenidate , and 3 patients who had antidepressants (n = 2) or anxiolytic (n = 1).The control and the ADHD group did not differ in main demographic variables, including age and gender. As shown by Table p = 0.7670). Overall, ADHD patients were less accurate on commission  trials (p < 0.001) than on omission trials. Commission error response rates were on average 8.85% in ADHD, and 3.04% in control subjects  using the analysis of covariance (ANCOVA) procedure controlling for age, gender and education as implemented in SAS software version 9.4 . Behavioural data are summarized in Table  p < 0.00 than on (Table ). Besides Type-I error-probabilities the table provides the covariance adjusted Least-Squares Mean (LSMean) estimates of the ERP amplitudes for both the ADHD and the control group.To demonstrate the scalp-distribution of ERPs, Fig. Table . BesidesSince in the adult ADHD EEG literature midline electrodes traditionally have been used as electrode sites of interest where ERP amplitudes are investigated in more detail, besides our ‘whole brain’ approach, we also focused on ERP analyses at Fz, FCz, Cz, Pz and Oz 10–20 midline electrodes. Considering that our results showed that ADHD patients have significantly reduced NoGo P1 amplitude at occipital and inferior-temporal areas including Cz, Pz and Oz electrodes sites, focusing on midline electrode sites enabled comparison of our results with the literature.Figure Dimensional associations between the P1 ERP component and psychopathological variables, including the severity on the CAARS Hyperactivity, Impulsivity and Inattention subscales were examined using the data of all participants combined. The analysis was conducted for those midline electrodes where a significant group-difference was present in the P1 time-window. Based on the HLM model, we determined the LSMeans for the P1 ERP amplitude for low and high severity of CAARS Hyperactivity, Impulsivity and Inattention subscales in order to interpret the direction of the associations.p < .0001; F = 58.56, p < .0001; F = 17.74 p = 0.0001, respectively). Investigation of the direction of the relationship revealed smaller P1 amplitudes among those subjects who had higher severity on Inattention as compared to subjects with lower subscale severity. Hyperactivity scores were also associated with ERP changes at Cz and Pz sites , with the opposite direction: patients with higher hyperactivity scores had significantly higher P1 amplitudes. The relationship between altered early ERP activity and CAARS symptom dimensions is shown in Table After corrections for multiple comparisons, we found that the Inattention factor was related to ERP changes at Cz, Pz and Oz electrode sites , with sThe main finding of our EEG study is that adults with ADHD showed a reduced P1 amplitude. The P1 is the first positive ERP component present around 100 ms after stimulus, associated with basic visual processing and spatial attention. ERP amplitude is thought to reflect the activation level of the activated central nervous system neuronal population . TherefoWhile in the ADHD literature later ERP components are more commonly studied, in schizophrenia research the P1 component is considered an endophenotype measure  with conBased on both parent-reported measures and psychological assessment, sensory profile of children significantly differs from their typically developing peers, including the visual domain . These dThe above mentioned P1 amplitude alterations were not only present on occipital regions , but we also found significant differences between ADHD and control groups regarding the P1 ERP amplitude on left inferior-frontal and inferotemporal EEG channels. Prior studies found that the left inferior frontal gyrus (IFG) plays a crucial role in top-down control, and is reciprocally connected to more posterior regions, including lateral temporal cortices. For example, in a phonological test using functional magnetic resonance imaging (fMRI), Bitan et al.  examinedOur second goal was to investigate whether alterations in the early sensory processing stages in ADHD are related to psychopathological symptoms. We found that the P1 amplitude reduction correlated with symptoms of inattention as measured by the Conners’ Adult ADHD Rating Scale . This asIn particular, the P1 amplitude alteration was associated with higher symptom severity on the CAARS scale regarding inattention at central/posterior electrode sites, while patients with higher hyperactivity scores had a higher (less attenuated) P1 component. These findings are consistent with the idea that symptom presentation in ADHD may not be a unitary phenomenon, and may reflect multiple aetiologies. They are also in line with the causal model of Sokolova et al. , which cAlthough ERP research has grown extensively in the past decades, besides a need for a more rigorous approach to increase the consistency and generalizability of electrophysiological findings , it is nLimitations of our study include that a subset of patients received medication. However, in our subsidiary analyses we examined the impact of medication status on our findings, and found that results remained statistically significant after the adjustment for medication status. We should also note that although the two groups differed regarding task performance, the relatively good task performance in the ADHD group combined with the low probability of NoGo stimuli did not allow for separate analyses on correct and false NoGo trials.The current investigation revealed altered P1 amplitudes in adult ADHD patients, indicating that early sensory deficits are present in this patient population. This finding and its relationship to ADHD symptomatology are suggestive of bottom-up cognitive deficits in ADHD which are driven by impairments in early visual processing, and provide evidence that sensory processing problems are present at the neurophysiological level in this population. Since dysfunctional early stages of information processing can result in deficits in later stages, further research efforts should address these alterations more explicitly.


Halophytophthora species have been traditionally regarded as brackish water oomycetes; however, recent reports in inland freshwater call for a better understanding of their ecology and possible pathogenicity. We studied the distribution of Halophytophthora fluviatilis in 117 forest streams by metabarcoding river filtrates taken in spring and autumn and by direct isolation from floating leaves. Pathogenicity on six Fagaceae species and Alnus glutinosa was assessed by stem inoculations. The distribution of H. fluviatilis was correlated with high mean annual temperatures (>93.5% of reports in Ta > 12.2 °C) and low precipitation records. H. fluviatilis was therefore widely distributed in forest streams in a warm–dry climate, but it was mostly absent in subalpine streams. H. fluviatilis was primarily detected in autumn with few findings in spring (28.4% vs. 2.7% of streams). H. fluviatilis was able to cause small lesions on some tree species such as Quercus pubescens, Q. suber and A. glutinosa. Our findings suggest that H. fluviatilis may be adapted to warm and dry conditions, and that it does not pose a significant threat to the most common Mediterranean broadleaved trees. Phytophthora and Pythium, but they also include less studied genera such as Halophytophthora. The genus Halophytophthora comprises a group of oomycetes predominantly inhabiting marine ecosystems. They are mostly found in brackish and saline waters where they can tolerate different levels of salinity [Halophytophthora spp. are restricted to saline environments. For instance, H. vesicula and H. spinosa were isolated in a low-salinity river in Japan [Halophytophthora species from freshwater streams in Oregon. In Europe, knowledge of freshwater Halophytophthora spp. is scarce. Besides several reports in brackish water, only the work by Ďatková [H. fluviatilis from river streams in Czech Republic. Interestingly, this same species was isolated from freshwater streams in Virginia by Yang et al. [Plant pathogens constitute a major threat for natural ecosystems . Amongstsalinity ,3,4. Recin Japan . Reeser in Japan  also rec Ďatková  recovereg et al. .Halophytophthora spp. Most of the described Halophytophthora species have been isolated in tropical and subtropical regions [Halophytophthora species seem to be more widespread than previously thought, pointing to the need of increasing our understanding of their distribution.Little is known about the ecology and climatic requirements of freshwater  regions ,9,10 or  regions ,5,11, bu regions ,13,14. IHalophytophthora species can act as plant pathogens and cause disease to forest species. Some Halophytophthora spp. have been described as early colonizers of fallen mangrove leaves [Zostera marina) germination was significantly reduced in seeds infected by H. zostera [It is currently unknown whether e leaves , and in e leaves ,3,16. Ne zostera , indicatHalophytophthora fluviatilis across forest streams along a Mediterranean-subalpine gradient in Catalonia (NE Spain). Distribution was studied by metabarcoding river filtrates taken in spring and autumn using Phytophthora-specific primers [Phytophthora spp., in addition to one single cluster of Halophytophthora, corresponding to H. fluviatilis. Metabarcoding was coupled with an isolation campaign of 28 streams in a N–S gradient from which H. fluviatilis isolates were obtained. Pathogenicity of H. fluviatilis was assessed by stem inoculations on some abundant Fagaceae species in Mediterranean forests in Southern Europe including Quercus faginea, Q. ilex, Q. pubescens and Q. suber, and more Central European species, such as Fagus sylvatica and Castanea sativa. Pathogenicity tests also included Alnus glutinosa as a riverbank species with well-known susceptibility to oomycetes.In this research, we studied the distribution of  primers  which amWe surveyed 117 streams in Catalonia (NE Spain) in two different seasons, autumn 2018 and spring 2019 . Due to the lack of running water, 5 and 7 streams were missing in autumn and spring, respectively. Our stream network covered a climatic gradient spanning from areas with a subalpine climate with minimum temperatures below 0 °C in winter to coastal areas with mild winters. In the gradient, mean temperatures ranged from 7 to 17.2 °C and precipitation from 386 to 1180 mm. Streams also run through areas with different geology, such as sedimentary limestone or metamorphic bedrock, rendering soils with high and low pH values (from 3.4 to 8.5). Sampling locations were chosen to be easily accessible, containing mainly forest in the upstream catchment area and with minimal presence of agricultural land or urban areas. At each site, 6 L of water was collected with a bucket and filtered through an 8 µm membrane  attached to the pump of an agricultural hand sprayer with a polysulfone filter holder as in Redondo et al. [® Soil kit . Libraries were prepared using tagged primers described by Redondo et al. [Phytophthora-specific primers developed by Drenth et al. [® NGS Clean-up and Size Select protocol . For library preparation, DNA concentrations were measured with QubitTM, and samples were pooled in equimolar mixtures prior to sequencing. Three pools including a total of 251 samples were sequenced, each one in a SMRT PacBio cell at ScilifeLab  yielding a total output of 732,610 reads.Filters were cut in half and DNA was extracted using the NucleoSpino et al. , based oh et al. . Brieflyncbi.nlm.nih.gov/genbank/ (accessed on 3 February 2021)). The H. fluviatilis cluster was the 10th most abundant OTU . Sequences were de-multiplexed, filtered and clustered using a similarity threshold of 99.5% with the bioinformatics SCATA pipeline (scata.mykopat.slu.se). Quality filtering was performed by keeping only those reads with mean quality of 2 or higher, containing both primers and tags with a similarity threshold of 90% and being longer than 700 bp. A total of 236,990 reads passed quality control. In order to compare with previous studies in Sweden, the same clustering parameters as in Redondo et al.  were useAcer spp., Amelanchier spp., Buxus spp., Celtis spp., Cornus spp., Corylus spp., Crataegus spp., Fagus spp., Fraxinus spp., Hedera spp., Lingustrum spp., Morus spp., Pinus spp., Platanus spp., Populus spp., Prunus spp., Quercus spp., Rhamnus spp., Salix spp., Ulmus spp., Viburnum spp. and Vitis spp. Some leaves could not be identified. After collection, leaves were placed in Falcon tubes and kept cold in a portable cool box. In the laboratory, leaves were rinsed with distilled water and briefly surface-sterilized with 70% ethanol. Small sections of necrotic leaf tissue were plated onto CMA-PARPBH selective medium [Phytophthora-like hyphae were transferred onto V8A media [In autumn 2019, we surveyed 28 of those same streams used for metabarcoding distributed in a N–S gradient . Floatin8A media  and storH. fluviatilis (similarity with voucher KF734963 > 99.9%), the remaining 179 isolates were Phytophthora species.DNA was extracted from isolates via the NaOH fast extraction procedure . The ITSH. fluviatilis isolates on one-year old seedlings of Alnus glutinosa  and six Fagaceae species, namely Castanea sativa (7.4 mm Ø), Fagus sylvatica (5.5 mm Ø), Quercus faginea (5 mm Ø), Q. ilex (5.5 mm Ø), Q. pubescens (4.1 mm Ø) and Q. suber (4 mm Ø). Inoculations were performed on six replicates per tree species and isolate. Inoculations were carried out by removing the bark and inserting a 5 mm Ø agar plug from a 3-week-old culture of H. fluviatilis growing on V8A media. Controls were inoculated with a sterile V8A plug. Wounds were wrapped with Parafilm® and seedlings were kept in a climate chamber for 7 weeks . After 7 weeks, the vertical length of bark necrosis was measured by gently scraping the bark. The presence of necrosis at the point of inoculation was also noted. Attempts of re-isolating the pathogen were performed by plating pieces of necrotic tissue onto selective media and observing growth after 72 h.Pathogenicity trials were run with the Climatic data were obtained from the Meteorological Service of Catalonia (meteo.cat) website and processed with the R package “Meteoland” . The seaH. fluviatilis and the climatic, water and soil variables was evaluated by logistic regression using the logit transformation as a link function and assuming a binomial distribution. Overdispersion of relative abundance data was accommodated by using a quasibinomial distribution. Logistic regression analyses were carried out with the glm function of the R package “Tidyverse” [H. fluviatilis reads was compared between autumn and spring by a mixed model using location as a random factor. Lesion length obtained in the inoculation test was compared between inoculated and non-inoculated seedlings across tree species with an ANOVA in JMP Pro . For each seedling, we averaged the lesion above and below the inoculation point. In order to meet the normality assumption, lesion length was log-transformed. The association between the presence and relative abundance of dyverse” . The perHalophytophthora fluviatilis was found widespread across the sampled area  (H. fluviatilis. Precipitation in spring and summer months was negatively associated with the presence of H. fluviatilis. Neither the temperature and pH of stream water at the time of sampling nor the soil pH were significant for the presence of H. fluviatilis (led area A. H. fluctively) C. It wasctively) B. The yeviatilis D. H. fluviatilis was detected by metabarcoding in about a third of them (28.6%). However, isolates could only be obtained from two streams in the gradient from which H. fluviatilis had not been detected by metabarcoding  and assessed its pathogenicity on common broadleaved tree species. Our findings suggest that climate may be limiting H. fluviatilis presence; however, the biological mechanisms underlying its susceptibility to cold and rainy conditions require further study. At first glance, H. fluviatilis does not seem to pose a major threat to main forest species in this area. However, further understanding the host range and the pathogenic status of H. fluviatilis may be useful to clarify the role of this oomycete in Mediterranean-subalpine ecosystems. The genus H. fluviatilis in our network of streams was restricted to warm and dry areas. Climatic factors have been shown to limit the establishment and distribution of some oomycetes [H. fluviatilis was mainly detected in streams of regions with a temperature higher than ca. 12 °C, and its presence was negatively associated with precipitation in spring and summer months. In the studied region, precipitation is negatively correlated with temperature (r = −0.77); therefore, it is difficult to disentangle one effect from the other. However, when restricting our analysis to areas with a warm climate (data not shown), there was no association between precipitation and presence or relative abundance of H. fluviatilis, thereby indicating a temperature effect. Given the aquatic lifestyle of H. fluviatilis, our results agree with Redondo et al. [Phytophthora species with an aquatic lifestyle in contrast with those found in terrestrial ecosystems. Indeed, one would expect H. fluviatilis to be resistant to cold because of its functional traits [Halophytophthora spp. [H. fluviatilis resistance traits could be adaptations to conditions experienced in ephemeral waterbodies, i.e., periodic drying where resting structures will enable survival until the next rain event. Ephemeral waterbodies also experience fluctuations in salinity that might provide a niche for H. fluviatilis which is adapted to slight saline conditions [The presence of omycetes . In our o et al.  who showl traits , such ase r = −0.7; therefl traits ,28, and l traits ,30. A stora spp. , indicatH. fluviatilis could also be explained by competitive exclusion, i.e., H. fluviatilis is outcompeted in colder environments by other organisms. It is not possible to discard this possibility without a deeper knowledge of the niche of H. fluviatilis and the associated microbial community. In our study, a single Halophytophthora OTU was present in the metabarcoding data, which at least discards possible competition within the same genus, as seen for other Phytophthora species [The observed distribution of  species . HoweverH. fluviatilis community dynamics than isolations from floating and sunken leaves. While H. fluviatilis was detected by metabarcoding in ca. a third of the streams in a N–S gradient, isolation was only successful in 7.1% of the rivers after screening almost two hundred isolates. Metabarcoding seems to be a good technique for studying the distribution of H. fluviatilis and could be applied to other environments to further increase our understanding of its ecology. In our study, metabarcoding enabled a more detailed analysis of the H. fluviatilis could be pathogenic to forest species. While our study showed that H. fluviatilis may be weakly pathogenic to Q. pubescens, Q. suber and A. glutinosa, these results should be taken with caution. Even if necrosis at the inoculation point occurred and lesions were significantly larger than the control, it is unclear whether H. fluviatilis could cause disease in field conditions. In parallel with the H. fluviatilis pathogenicity assessment, several known pathogenic Phytophthora species such as P. cambivora caused much larger lesions than H. fluviatilis in a study with the same plant material and tree species (7.9 mm vs. 0.6 mm).We also tested whether H. fluviatilis in a Mediterranean-subalpine context. H. fluviatilis was restricted to stream sites with an average temperature higher than 12.2 °C and was rare in streams flowing from subalpine areas with heavy rainfall and low mean annual temperatures. We also found that H. fluviatilis could be slightly pathogenic to Q. pubescens, Q. suber and A. glutinosa. These results provide a better understanding of H. fluviatilis ecology, but more research will be needed to understand its ecology and functioning in freshwater ecosystems.In this study, we showed that climatic factors seem to restrict the distribution of