Escherichia coli via transcriptional upregulation of the toxin HokB. In the present study, we demonstrate that HokB inserts in the cytoplasmic membrane where it forms pores. The pore-forming capacity of the HokB peptide is demonstrated by in vitro conductance measurements on synthetic and natural lipid bilayers, revealing an asymmetrical conductance profile. Pore formation is directly linked to persistence and results in leakage of intracellular ATP. HokB-induced persistence is strongly impeded in the presence of a channel blocker, thereby providing a direct link between pore functioning and persistence. Furthermore, the activity of HokB pores is sensitive to the membrane potential. This sensitivity presumably results from the formation of either intermediate or mature pore types depending on the membrane potential. Taken together, these results provide a detailed view on the mechanistic basis of persister formation through the effector HokB.Bacterial populations harbor a small fraction of cells that display transient multidrug tolerance. These so-called persister cells are extremely difficult to eradicate and contribute to the recalcitrance of chronic infections. Several signaling pathways leading to persistence have been identified. However, it is poorly understood how the effectors of these pathways function at the molecular level. In a previous study, we reported that the conserved GTPase Obg induces persistence in  E. coli and discovered that these pores lead to leakage of intracellular ATP, which is correlated with the induction of persistence. Moreover, we established a link between persistence and pore activity, as the number of HokB-induced persister cells was strongly reduced using a channel blocker. The latter opens opportunities to reduce the number of persister cells in a clinical setting.There is increasing awareness of the clinical importance of persistence. Indeed, persistence is linked to the recalcitrance of chronic infections, and evidence is accumulating that persister cells constitute a pool of viable cells from which resistant mutants can emerge. Unfortunately, persistence is a poorly understood process at the mechanistic level. In this study, we unraveled the pore-forming activity of HokB in  Persister cells are rare, phenotypic variants in isogenic bacterial populations that are transiently dormant, thereby surviving treatment with high doses of bactericidal antibiotics. Following antibiotic removal, persister cells regrow and form a new population, which is again sensitive to the antibiotic . Persist2–Toxin-antitoxin (TA) modules are important mediators of persistence –10, alth–Escherichia coli, expression of the conserved GTPase Obg induces persistence through transcriptional activation of the type I toxin HokB. While deleting hokB does not influence persistence, overexpressing hokB increases the number of persister cells  reduces hokB-induced persistence, indicative of a direct link between pore formation and persistence. HokB pores lower the cellular energy status (ATP/ADP ratio) of the cells and cause leakage of intracellular ATP, thereby inducing dormancy.In the present study, we combine trans, working electrode) of the planar lipid membranes to mimic the asymmetry of the in vivo membrane. A voltage (up to ±200 mV) was applied to force insertion of peptides into the planar lipid membrane, as spontaneous insertion was inefficient. A schematic representation of the setup is depicted in Planar lipid bilayers are often used to assess ion channel activities  or the btrans compartment resulted in a higher conductance than applying a negative polarity. For the remaining 20% of pores, the conductance was independent of the sign of the applied voltage, possibly because breaking and reforming the bilayer results in contamination of the peptide to the cis side. To estimate the single-pore conductance, frequency distributions of the measured conductances at +100 mV were determined  layer . Download FIG S1, TIF file, 0.04 MB.Histogram of conductance measurements of 35 independent single-step insertions of HokB peptides in the bilayer using extracted Copyright © 2018 Wilmaerts et al.2018Wilmaerts et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the trans compartment results in higher pore currents than applying a negative polarity. This asymmetrical behavior is called ionic current rectification. The rectification ratio (α) is scored by dividing the conductance at negative potential over the conductance at positive potential (Current-voltage (I-V) measurements obtained from single-pore conductances using the synthetic lipids show asymmetrical behavior . Althougotential , giving cis or in trans, can react with the thiol-directed PEG reagent methoxy polyethylene glycolmaleimide , which would impede current flow  is estimated to be 2.55 nm , indicating that there was no reaction between mPEG5k-mal and a thiol. Conversely, upon the addition of mPEG5k-mal in trans, conductance decreased to 0.098 nS in a single step, resulting from the reaction between mPEG5k-mal and C46. These results indicate that, upon insertion, HokB crosses the bilayer with the N terminus, as depicted in in vitro results to the in vivo situation and taking the orientation of the HokB pores into account, a positive applied voltage corresponds to a polarized biological membrane.As HokB belongs to the Hok/Gef family, it is predicted to be a single-span membrane peptide . Also, cent flow . Consequ 2.55 nm , well ab10.1128/mBio.00744-18.2FIG S2 FIG S2, TIF file, 0.2 MB.TMHMM analysis  of the HCopyright © 2018 Wilmaerts et al.2018Wilmaerts et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the trans (1.00 nS) was far above the calculated single-pore conductance (0.12 nS), the single-step inhibition indicates that only one pore was formed. This can be explained by the fact that HokB pores display not only asymmetrical behavior but also pronounced nonlinear behavior, with a strong increase in conductance upon applying a positive voltage in increments -mCherry  and PALM (C and D). Fluorescence is homogeneously distributed over the entire cell when expressing mCherry (A) or PAmCherry (C). Fluorescence is located at the cell membrane when expressing mCherry-hokB (B) or PAmCherry-hokB (D). The color scale for PALM represents the minimal and maximal fluorescence intensity of a given spot . Download FIG S3, TIF file, 0.3 MB.Visualization of HokB localization in ven spot . (E) ExpCopyright © 2018 Wilmaerts et al.2018Wilmaerts et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the P < 0.05) with regions of higher red fluorescence intensity resulting from mCherry-labeled HokB (mCherry-HokB) clustering . Download FIG S4, TIF file, 0.1 MB.HokB-induced persistence is strongly reduced by the use of the channel inhibitor PEG 1000. PEG molecules and ethylene glycol were added at 10 mM. Values are means ± SEM from at least three independent experiments. Asterisks indicate statistical significance  The control strain (mCherry) does not result in the formation of fluorescent patches. Patch formation is not caused by the mCherry tag, as hokB expression also results in the formation of fluorescent patches. Download FIG S5, TIF file, 0.2 MB.(A) PEG 1000-FITC is located in fluorescent patches in the membrane. These patches are colocalized with the fluorescent patches visible after Copyright © 2018 Wilmaerts et al.2018Wilmaerts et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the hokB expression, 29.77% (±17.11% [SEM]) of the population is PI positive (PI+). This could result from the loss of membrane integrity upon hokB expression or from PI passage through HokB pores. To distinguish between these possibilities, we used redox sensor green (RSG), a fluorescent marker of metabolic activity that does not stain dead cells  compared to negative (PI−) cells. These results confirm that HokB forms pores in vivo through which PI can be transported.To further confirm the pore-forming activity of HokB, the permeabilization marker propidium iodide (PI) was used, which has a radius of 0.5 nm . PI cannad cells . ClearlyhokB expression lowers the electrical potential of the bacterial cell membrane (4(3)], a fluorescent stain that only enters depolarized cells  could leak through the pores. Therefore, we measured ATP levels in the supernatant during induction of hokB . We clea of HokB . Indeed, of HokB .hokB induction, were grown in lysogeny broth (LB), and single-cell lag times were calculated. Remarkably, the lag time of HokB-induced persister cells is significantly shorter compared to the control cells. On the other hand, expression of hokB does not affect the lag time of nonpersister cells  curve revealed an asymmetrical behavior regarding the polarity of the applied voltage, presumably resulting from the intrinsic asymmetry of the HokB peptide. Indeed, although the peptide is overall uncharged, the N terminus is positively charged, while the C terminus is negatively charged . We expeGylation  and demoGylation . BecauseThe nonlinearity of the I-V curve does not result from the formation of multiple pores, as the 100 mV step in the I-V curve has a single-pore conductance. Furthermore, conductance higher than the conductance for a single pore was impeded by mPEG5k-mal in a single step, indicative of the presence of a single pore. Indeed, in the case of multiple pores, a multistep decrease would be expected. Therefore, a high positive voltage induces the formation of mature pores, while intermediate pores are formed at lower applied voltages. With the experimentally defined orientation of HokB pores, a positive potential mimics a cell with a polarized membrane, indicating that mature HokB pores are formed in cells with a high membrane potential.In addition to a stepwise increase in current, most likely resulting from different intermediate steps in HokB pore formation, HokB pores display two other types of behavior. First, some HokB pores show multiple conductances with consecutive opening and closing of the pore, thereby resembling voltage-independent gating-like behavior. Second, some HokB pores show more noisy behavior. Whether these two HokB characteristics play a role in the formation and awakening of HokB-induced persister cells is currently unclear.in vivo. Upon addition of PEG 1000 at high concentration, hokB-induced persister formation was completely abolished, indicating that pores in vivo (~2-nm radius) are bigger than pores in vitro. As clusters of PEG 1000-FITC colocalized with clusters of the HokB peptides, the effect of PEG 1000 on persistence most likely results from blocking of the pore, although other effects cannot be excluded. Moreover, cells stained with PI resulting from hokB expression have a strongly depolarized membrane, which is linked with persistence . Bacteria were grown in lysogeny broth (LB) at 37°C, and liquid cultures were incubated with orbital shaking (200 rpm).ucts see . Other eMyc-His A-mCherry and pBAD/Myc-His A-PAmCherry was performed by PCR amplification of mCherry or PAmCherry from pRSET-B-mCherry .Construction of pBAD/-mCherry  or pRSETAmCherry  with priMyc-His A-mCherry-hokB and pBAD/Myc-His A-PAmCherry-hokB, PCR amplification of hokB from pBAD/His A-hokB  (For the construction of pBAD/d 20336)  with oveE. coli BW25113 containing pBAD/Myc-His A-mCherry or pBAD/Myc-His A-mCherry-hokB was grown overnight at 37°C under conditions of continuous shaking (200 rpm). The cells were then diluted 100-fold and induced for 4 h with 0.2% arabinose. After 4 h, the cells were pelleted by centrifugation  and resuspended in phosphate-buffered saline (PBS) buffer. The cells were spotted onto an agar pad and visualized using a Nikon Eclipse Ti-E inverted microscope with a CFI Plan Apochromat 100× objective with a numerical aperture (NA) of 1.45 and excitation at 580 nm. Data were analyzed using the NIS Elements Analysis 4.4 software .E. coli BW25113 containing pBAD/Myc-His A-PAmCherry or pBAD/Myc-His A-PAmCherry-hokB was incubated overnight at 37°C with continuous shaking (200 rpm). The cells were then diluted 100-fold in fresh LB medium for 2 h and induced with 0.2% arabinose for 3 h. The cells were pelleted by centrifugation  and resuspended in 10 mM ISO buffer  was performed on an inverted epifluorescence microscope  with a 60× total internal reflection fluorescence (TIRF) oil immersion objective lens . An electron-multiplying charge-coupled-device (CCD) camera  was used to capture images. Hokawo Imaging software V2.5  was used for recording. Photoconversion of PAmCherry was carried out with a 405-nm laser where the output power was adjusted for each experiment with a neutral density filter, based on the observed switching rate. A 561-nm laser was used for excitation. Fluorescence emission was collected with a 572-nm long-pass and a 590/40 band-pass filter. Lasers were obtained from Coherent, Inc. (USA), and optical filters were from Chroma . Images, typically 5,000 frames per experiment, were acquired with 100-ms exposure times. The PALM raw data were analyzed using Localizer software . Planar lipid experiments were conducted under symmetrical conditions in a buffer containing 150 mM NaCl and 10 mM Tris-HCl (pH 7.5). Holding voltages were applied with a 2-kHz low-pass Bassel filter with a 10-kHz sampling rate to the trans chamber. The resulting current was recorded using Ag/AgCl electrodes connected to a patch-clamp amplifier  and analyzed with the Clampfit 10 software package . Bulk solution conductivity was measured with the WTW Multi 3420 conductivity meter in combination with LR 925/01 electrodes and was determined to be 15.4 mS/cm. Synthetic HokB peptides (MKHNPLVVCLLIICITILTFTLLTRQTLYELRFRDGDKEVAALMACTSR) were ordered from Pepscan (The Netherlands) and New England Peptide (NEP) (UK). The peptides were dissolved in dimethyl sulfoxide (DMSO) to a concentration of 10 mM and stored at 4°C for up to 2 weeks. HokB peptides were added at the trans side to a concentration of approximately 0.05 mM. When no insertion was observed, more peptide was added to the chamber. For DPhPC lipids, measurements at +100 mV were used for the calculation of the conductance histogram. When the E. coli lipid extract was used, the activating potential (±100 mV) for that specific pore was used. When the observed ion current was unstable and no clear prevalent current was visible, the trace was excluded for further analysis. All measurements were performed at 25°C. The single-pore size was calculated from the single-pore conductance using the model of Hille (g and length l (assumed to be 30 Å) of the transmembrane domain in a solution with resistivity ρ (measured to be 0.649 Ω). The pore diameter d is then given by:A planar lipid bilayer was formed by the lipid monolayer opposition technique of Montal and Mueller . Membranof Hille . This motrans side of a newly formed bilayer. After pore formation, mPEG5k-mal (stock 10 mM) was added in a concentration of 0.6 mM, first in the cis compartment. After approximately 1 min, the same concentration was added in trans. mPEG5k-mal was purchased from Sigma-Aldrich (USA).For assessing pore open and closing time while gating, pores were considered at their equilibrium (when no new pores inserted in the bilayer). Pore orientation was assessed as described before . Peptide−1), and inducer (0.2% arabinose). For the polyethylene glycol (PEG) experiments, PEG  or ethylene glycol was added to the medium. Cultures were incubated for 16 h. All PEGs were purchased from Sigma-Aldrich (USA). Then, 990 µl of culture was treated with 10 µl of 0.5 mg ml−1 ofloxacin, and the control treatment was performed with 10 µl sterile water. After 5-h incubation, samples were serially diluted in 10 mM MgSO4 and plated on LB agar plates. For persistence measurements in exponential phase, overnight cultures were diluted 100-fold in 250 ml flasks containing the appropriate additives. Samples were taken after 1, 2, 3, and 4 h of incubation, and 990 µl was treated with 10 µl of 0.5 mg ml−1 ofloxacin and incubated for 4 h. Untreated samples were plated immediately. The number of CFU was determined after 48-h incubation at 37°C by plate counts. All statistical calculations were performed on log10-transformed data and were used to verify potential differences in persister fractions. Statistical comparisons were based on analysis of variance (ANOVA) with a Dunnett’s post hoc test for multiple comparisons.For the persistence assay in stationary phase, overnight cultures were diluted 100-fold in 250-ml flasks containing 100 ml LB medium, ampicillin . The cells were then diluted 100-fold, induced with 0.2% arabinose, and again incubated overnight (16 h). Because Perceval fluorescence is also influenced by pH, cells were diluted in buffered M63 (pH 7) in combination with 40 mM potassium benzoate and 40 mM methylamine hydrochloride to eliminate the transmembrane pH difference just before the measurement. Fluorescence was measured with a Synergy MX multimode reader . The excitation spectrum of Perceval shows a large peak around 490 nm and a smaller peak at 405 nm. ATP and ADP competitively bind with Perceval, but binding of ATP results in an enhancement of the 490-nm excitation and a reduction of the 405-nm peak , following the manufacturer’s specifications. After 5 min, bioluminescence was measured for every well. At every time point, the optical density (OD) (595 nm) was measured. To take into account the number of cells, the bioluminescence was divided by the OD.An overnight culture was diluted and induced in flasks containing 100 ml LB. After 1, 2, 3, and 4 h, 1-ml samples were taken. Samples were centrifuged for 10 min at 5,000 rpm. Protein concentrations were determined by the Qubit protein assay kit, in accordance with the manufacturer’s specifications .4(3)], fluorescence was measured using a 488-nm laser and a 520-nm filter. For propidium iodide (PI), fluorescence was measured using a 488-nm laser and a 620-nm filter. All stains were purchased from Invitrogen (USA). Data were analyzed using FlowJo V10 .Cells were grown as described above. The cells were diluted in PBS buffer (pH 7.4) and stained following the manufacturer’s instructions. Data were collected for a minimum of 50,000 cells using a BD influx cell sorter . For redox sensor green (RSG) staining and bis-trimethine oxonol ), purchased from Creative PEGWorks (USA), was dissolved in PBS buffer (pH 7.4) at a concentration of 3 mg ml−1. The cells were incubated for 30 min in the PEG 1000-FITC solution and then washed twice. After the cells were washed, they were spotted onto an agar pad and visualized using a Nikon Eclipse Ti-E inverted microscope with a CFI Plan Apochromat 100× objective with a numerical aperture (NA) of 1.45. Data were analyzed using the NIS Elements Analysis 4.4 software . Correlation between fluorescent patches was assessed using the chi-square statistical test.Cells were grown as described above. After overnight induction in 100-ml flasks, post hoc test for multiple comparisons.Cells were grown and treated with antibiotics as described above for the persistence assay in stationary phase. After treatment, cells were resuspended in LB, and a twofold dilution series was prepared. The cells were grown at 37°C with continuous shaking in a Bioscreen C system. Wells with the highest dilution that still displayed growth were selected for single-cell lag time calculation if the two consecutive wells displayed no growth . The Gom


The association between visual deficits and attention disorders has been reported but remains unproven.The objective of this study was to evaluate the risk of attention‐deficit hyperactivity disorder (ADHD) in children with amblyopia.Population‐based, cohort study.The dataset from the Taiwan National Health Insurance Research Database in 2000 to 2010.A total of 6817 patients aged <18 years with newly diagnosed amblyopia were identified. Four age‐ and sex‐matched controls without amblyopia were included for each patient, that is, 27268 controls.The primary outcome was the risk of ADHD. The secondary outcomes were age at ADHD onset and use of ADHD medication.P < 0.0001). The ADHD risk in the amblyopia group was 1.81 times that in the control group . After stratification by amblyopia subtype, the greatest risk was in the deprivation type  followed by the strabismic  and refractive  types. Age at ADHD onset was younger in the amblyopia group . The average duration of neuropsychiatric medication use was comparable between groups (P = 0.98).During a mean observation period of 7.18 years, the incidence of ADHD per 1000 person‐years was 7.02 in the amblyopia group and 4.61 in the control group (The ADHD risk is higher in children with amblyopia. One study showed that certain ophthalmic disorders, such as amblyopia, cataract and nystagmus, could affect the visuo‐attentional performance of children aged 4‐7 years.Visual acuity screening is compulsory for all preschool children at 4 years of age and an annual check of visual acuity is required in all school‐aged children in Taiwan. Any child who fails the vision screen is referred for a comprehensive ophthalmic evaluation. The National Health Insurance program in Taiwan is a mandatory general health insurance program that covers 99% of the 23 million individuals residing in Taiwan. To overcome the limitations of previous studies, we used this database to gather a large cohort for the present study, the aim of which was to compare the incidence and risk of ADHD between children with amblyopia and those without amblyopia.2We conducted a retrospective population‐based cohort study using the Longitudinal Health Insurance Database of Taiwan's National Health Insurance Research Database, which includes a million beneficiaries randomly selected from all insurers in the National Health Insurance program. The research protocol was approved by the Ethics Review Board of the National Taiwan University Hospital, Taipei, Taiwan.The study included patients aged <18 years who were newly diagnosed with amblyopia between 2000 and 2010. Patients with a history of neuropsychiatric medication intake and/or those with a previous diagnosis of ADHD before the study selection period were excluded. We also identified and recruited four age‐ and sex‐matched children without a diagnosis of amblyopia as controls for each patient.In clinical practice, children with suboptimal corrected visual acuity in one or both eyes due to disruption of visual stimuli were defined as amblyopes and coded as having amblyopia in the national health insurance system. The children were diagnosed with amblyopia on the basis of the amblyopia diagnostic codes 368.00, 368.01, 368.02 or 368.03  and the findings of visual acuity examinations. Patients with amblyopia were further stratified by subtype of amblyopia as strabismic, deprivation or refractive. The deprivation subtype was characterized by the presence of certain ocular anomalies obscurating the visual axis, such as cataract, ptosis or corneal opacity. The strabismic subtype was characterized by the presence of esotropia or exotropia. Cases with mixed diagnostic codes of both deprivation and strabismic subtypes were classified into deprivation subtypes. Cases that could not be categorized as the deprivation or strabismus subtype were categorized as the refractive subtype. All subjects were followed from the index date until the date of death, date of loss to follow‐up  or the date of the last follow‐up.The primary outcome in the study was the occurrence of ADHD. The diagnosis of ADHD was based on the ICD‐9‐CM codes 314.00, 314.01, 314.1, 314.2, 314.8 or 314.9. With regard to comorbidities, we collected data pertaining to delayed development, mental retardation, autism spectrum disorder, Tourette syndrome, paralysis, epilepsy, asthma, allergic rhinitis and allergic conjunctivitis.The secondary outcome was the age at onset of ADHD and the duration of neuropsychiatric medications use, including methylphenidate, atomoxetine and bupropion, in patients with ADHD according to the presence or absence of amblyopia.2.1χ2 or Fisher's exact test for categorical variables and the Wilcoxon two‐sample or Brown‐Mood test for continuous variables. The cumulative incidence of ADHD was estimated using the Kaplan‐Meier method. A Cox proportional hazards model was used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for the risk of ADHD in both study groups. Baseline characteristics which significantly associated with ADHD in the univariate analysis were included in a multivariate regression model for adjustment. All statistical analyses were performed using SAS version 9.1 software . A P value <0.05 was considered statistically significant.Differences in demographics and comorbidities between the amblyopia group and the control group were examined using the 3In total, 6817 children diagnosed with amblyopia and 27268 controls matched for age and sex were recruited for this study. The flowchart for the study is shown in Figure The mean age of the study subjects was 7.0 years (standard deviation (SD) 2.8 years), and 52.6% were female. Comorbidities, including delayed development, mental retardation, paralysis, epilepsy, asthma, allergic rhinitis and other allergic diseases, was more common in the amblyopia group than in the control group Table .The mean observation period was 7.18 years. The incidence of ADHD per 1000 person‐years was 7.02 and 4.61, respectively, in the amblyopia and control groups .The cumulative incidence of ADHD was significantly greater in the amblyopia group than in the control group . The durations of treatment with methylphenidate (P = 0.97), atomoxetine (P = 0.39) and bupropion (P = 0.39) were similar between the study groups.The median age at onset of ADHD was younger in children with amblyopia than in those without amblyopia , deprivation type (n = 636) and refractive type (n = 6003). Four hundred and four cases of esotropia and 1645 cases of exotropia without monocular visual acuity deficit were not included in our analysis. The distribution of amblyopia subtypes in the present study was similar to that in a previous study of 5232 children in Eastern TaiwanStrabismic amblyopia has also been reported to be uncommon in children from other East Asian countries, including Singapore 15%) and Korea 12.8%)..8%.12, 1% and KorP < 0.0001, log‐rank test). After adjustment for age, sex, and comorbidities, the presence of amblyopia was found to be associated with a 1.81‐fold increased risk of ADHD. With regard to the different underlying causes of amblyopia, the risk of ADHD was found to be highest in children with the deprivation type followed by those with the strabismic type. Children with refractive amblyopia had the lowest risk . Interestingly, this finding was compatible with previously reported visual prognoses for amblyopic eyes with different subtypes, with deprivation amblyopia showing the worst prognosis and refractive amblyopia showing the best.In the present study, the incidence of ADHD in children over 10 years of age was significantly higher in the amblyopia group than in the control group .In the present study, we calculated the duration of prescribed neuropsychiatric medications, including methylphenidate, atomoxetine and bupropion, in children who had ADHD with and without amblyopia. Psychosocial interventions, such as parental training in child behaviour and teacher training in classroom management, are recommended as first‐line management for children with mild to moderate ADHD, whereas stimulants and other medication are recommended for children with more severe ADHD.This study has some limitations. First, the diagnoses of amblyopia, ADHD and other comorbid diseases were entirely based on ICD‐9‐CM codes. The database did not include the severity of amblyopia or objective measures of visual acuity and refraction. We could only use the different subtypes of amblyopia as surrogates for the levels of visual performance. Second, there may have been instances where the subtype of amblyopia was misidentified. For example, we identified ptosis as deprivational amblyopia; however, ptosis may also cause refractive or strabismus amblyopia. Nevertheless, the findings of our study demonstrate the risk of development of ADHD in children with amblyopia. Our findings suggest that suboptimal development of visual acuity is associated with an increased risk of ADHD in children with amblyopia. Additional research effort should be directed towards longitudinal studies examining the functional correlation between severity of visual impairment and attention‐deficit and the mechanisms underlying the association between amblyopia and ADHD.None declared.


Attention-deficit/hyperactivity disorder (ADHD) is a risk factor for the development and persistence of substance use disorders (SUD). The prevalence of ADHD in patients with SUD varies across countries and cultures. So far, cross-cultural variance in ADHD prevalence rates among SUD patients was mainly ascribed to methodological differences between studies, leaving the role of societal and cultural practices in the ADHD-SUD link hardly acknowledged. The aim of the present mini review is to address this gap in the literature by providing evidence for the effect of socio-cultural practices on the ADHD-SUD link and suggesting directions for future research. To achieve this goal, we map the influence of socio-cultural factors on the ADHD-SUD link along three lines of research. The first line is concerned with the role of socio-cultural factors in the recognition, diagnosis and treatment of childhood ADHD. The second line of research is concerned with socio-cultural influences on substance use . Finally, we describe potential socio-cultural factors which may operate as mechanisms for reducing or increasing access to substance abuse treatment . Identifying socio-cultural influences on the ADHD-SUD link may provide further insight into the bidirectional association between ADHD and SUD in different contexts and encourage future research in the field. Attention-deficit/hyperactivity disorder (ADHD) and substance use disorders (SUDs) are inextricably intertwined. It has been estimated that one quarter of those suffering from SUD have comorbid ADHD . SubstanAnother explanation for the ADHD-SUD link is that ADHD-related symptoms, in particular impulsivity, lead to trying substances , 14. In In addition to behavioral, neuropsychological, and genetic pathways, the association between ADHD and SUD is greatly influenced by socio-cultural factors. Given that drug use is often much more than a simple action performed in order to experience a physical or psychological reaction , culturaInternational research revealed a wide variance in the prevalence of ADHD in SUD patients across countries and cultures , 21, eveThe associations between ADHD and SUD are usually examined in treatment-seeking SUD patients . TherefoUntreated childhood ADHD is a risk factor for the development of SUD . TherefoCulturally relevant factors, such as norms, medical approaches, beliefs, and values influence the way members of various cultural groups view and respond to problematic behavior in children . Cross-cA range of perceptions and attitudes may be responsible for avoiding or delaying help seeking for ADHD, including limited knowledge about ADHD , fear ofSocio-cultural barriers to accurate diagnosis and treatment of childhood ADHD may be further exacerbated in adult ADHD, especially among individuals in the criminal justice system . To qualDespite growing concerns about the under-diagnosis and under-treatment of mental health problems among certain socio-cultural groups , culturaWhile cultural diversity may be partly attributed to better screening, knowledge and awareness in Western cultural contexts, these factors may interact with environmental risk factors to affect ADHD risk . For exaCultural norms, beliefs and attitudes, including ideologies, practices, and symbols, have a central role in forming the expectations of individuals about potential problems they may face with drug use. Such cultural norms are represented in legends, proverbs, anecdotes, and jokes, as well as in fiction and entertainment  .Among the multiple influences of socio-cultural aspects on substance use and abuse, this section focusses on the role of three cultural processes which were particularly associated with delinquency and substance use; religious affiliation, acculturation and ethnic identity.Religious affiliations often play a protective role against drug use , 54. RelAlthough lower prevalence of SUD among traditional and religious cultures may indicate compliance with socio-cultural rules or greater social control, it may also indicate a society's failure to acknowledge problems of addictions . For exaAcculturation, the degree to which an individual identifies with his or her native culture, may also be related to substance use and abuse. The association between acculturation and substance use is equivocal, but overall greater levels of acculturation are associated with increased levels of substance use , 65. AccIn addition to acculturation, ethnic identity may also be associated with substance use in certain cultural groups. However, its role in predicting substance use remains elusive . Strong Socio-economic status (SES) has various contradictory effects on the ADHD-SUD link. Lower SES is associated with both an increased ADHD and SUD incidence [, for metThe link between ADHD and SUD is usually investigated in treatment-seeking SUD patients . TherefoOverall, studies suggest that racial and ethnic minority groups are less likely than non-minority groups to enter, receive, and complete treatment for SUD . Ethnic Treatment preference is a relatively neglected area of study in service disparities . PrelimiN = 25,159) suggested that treatment programs that are mandated by the criminal justice system might provide access to individuals resistant to care , indicated that CBT, when compared to a comparison group, was equally effective in minority and non-minority studies. However, when comparing pre-posttest effect sizes from groups receiving CBT between minority and non-minority studies, CBT's impact was significantly stronger in non-minority studies (N = 7 studies) including CBT, educational, individual and family interventions for SUD, concluded that culturally sensitive treatments were associated with significantly larger reductions in post-treatment substance use levels relative to their comparison conditions  in reducing substance use between studies with a predominantly White sample and studies with a predominantly Black and/or Hispanic sample ( studies . Several studies , 110, fo studies  in impro studies  revealed studies . Likewisnditions .This review highlights the role of socio-cultural aspects in the link between ADHD and SUD. These aspects include cultural factors such as perceptions of normal and abnormal behavior, behavioral norms, and attitudes and knowledge about mental health problems , 115 as Continued research on socio-cultural aspects along with biological aspects is required to understand the interplay of all factors in the ADHD-SUD link. Understanding the role of culture and context in the ADHD-SUD link may not only shed light on the current enormous variance in the prevalence of ADHD in SUD patients across cultures , but alsOS and CC contributed equally to the literature search, literature analysis, data integration, and writing the review manuscript.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. The reviewer CB declared a past co-authorship with the authors to the handling editor.


Recent studies highlight the role of excessive mind wandering in attention-deficit/hyperactivity disorder (ADHD) and its association with impairment. We believe assessing mind wandering could be especially relevant to individuals, including many females, who present with less externalising manifestations of ADHD. Using a new measure based on ADHD patient reports, the Mind Excessively Wandering Scale (MEWS), we previously found adults with ADHD had elevated levels of mind wandering that contributed to impairment independently of core ADHD symptoms. Using data from an online general population survey, the current study assessed the factor-structure, reliability, validity and measurement invariance of the MEWS. We also investigated sex differences in mind wandering, as well as ADHD symptoms, impairment and wellbeing in those with and without ADHD. The MEWS had a unidimensional structure, was invariant across sex, age and ADHD status, and accounted for unique variance in impairment and wellbeing beyond core ADHD symptoms. Among those with ADHD, we found no evidence for sex differences in mind wandering and among those without ADHD males had higher scores. We also found similar levels of hyperactivity/impulsivity, emotional lability, and impairment in males and females with ADHD, but males reported greater inattention and lower wellbeing. Results suggest the MEWS is a reliable and valid instrument measuring the same construct across sex, age and ADHD status, which could aid diagnosis and monitoring of outcomes. Although ADHD diagnosis is made based on the presence of core symptoms of inattention and hyperactivity/impulsivity2, other characteristic features, such as subjective reports of excessive mind wandering could aid the diagnostic process and/or monitoring of treatment outcomes3. Mind wandering is conceptualised as periods in time when attention and the contents of thoughts shift away from external sources and/or ongoing tasks, to unrelated internal thoughts or feelings4. Excessive mind wandering has been linked to impairment in ADHD9 and could reflect a core underlying symptom10.Given the extensive evidence that ADHD is not confined to childhood and also occurs in adulthood, identifying measures to aid diagnostic assessment and monitoring of treatment outcomes in this age group is of considerable interest to research and clinical practiceIn contrast to the core ADHD symptoms, mind wandering reflects internal thought processes, as opposed to directly observable behaviours. Excessive mind wandering may be particularly relevant to the assessment of ADHD in adolescence and adulthood when self-report plays a larger role in the diagnostic process. It may also be more difficult for individuals to reflect upon the behavioural symptoms that are currently used in the diagnostic criteria, while they may be better able to report on internal thought processes. Furthermore, the traditional symptoms of ADHD may not be obvious in people who have developed good adaptive skills that mask the behavioural symptoms of ADHD. Assessing mind wandering in ADHD could be especially relevant to individuals, including many females, who present with less externalising manifestations of ADHD. Thus, investigation of sex differences in mind wandering is especially pertinent as it does not depend on behavioural adaption to the same degree as traditional ADHD measures.3. The scale demonstrated a unidimensional structure with good internal consistency, and high sensitivity and specificity to discriminate between ADHD cases and controls, behaving in a comparable way to existing ratings scales of ADHD symptoms used in clinical practice. Adult ADHD cases showed elevated levels of mind wandering that contributed to impairment independently of the core ADHD symptom domains. Thus, excessive, uncontrolled mind wandering appears to be a common co-occurring feature of adult ADHD with specific implications for impairment in daily-life3.We recently developed and validated a new rating scale reflecting excessive mind wandering in ADHD: the Mind Excessively Wandering Scale (MEWS)12. Between-group differences  should not be analysed unless measurement invariance is held across the groups, yet this is rarely tested in empirical studies of psychiatric disorders12.The current study sought to further validate the MEWS in a large adult population sample, including those who report a diagnosis of ADHD, and assess measurement invariance of the scale across sex, ADHD diagnostic status, and age. Measurement invariance examines whether a scale captures fundamentally the same processes and construct across groups. Comparisons of group means for any scale is based on the assumption that the scale is measurement invariant across groups being compared, and a lack of invariance can render between-group comparisons meaningless and lead to incorrect interpretation of differences14, and persistence of ADHD across the lifespan, it is important that the scale is also measurement invariant across sex and age. Further, as previous studies show mixed results with regard to whether males and females are affected differently by ADHD in adulthood20, we examined sex differences within those with and without self-reported ADHD with regard to mind wandering, as well as inattention, hyperactivity/impulsivity, emotional lability, impairment and wellbeing. Given that sex differences in adult ADHD have received much less attention in the literature compared to childhood21, there is a clear need for additional research. Furthermore, given that mind wandering may account for unique variance in functional impairment beyond core ADHD symptoms, and impairment is the most frequent reason for referral, investigating sex differences in mind wandering is clinically relevant.Given the well documented sex differences in ADHDThis study uses data from a large online survey of individuals from the general population. The survey was advertised through King’s College London research recruitment page, ADHD user-group and information websites, and social media. The only exclusion criterion was participants could not be below 16 years of age. Data from 1484 participants  who fully completed the MEWS were used for analysis in the current study.M = 34.80, SD = 13.55) and were categorised into age groups as follows: 1) 16–23 years (n = 382), 2) 24–30 years (n = 360), 3) 31–45 years (n = 365), and 4) 46 + years (n = 372). Those with and without full MEWS data did not differ significantly for sex (χ2(1) = 1.05, p = 0.31) or age group (χ2(3) = 5.74, p = 0.13). Participants who endorsed a childhood or adulthood diagnosis of ADHD based on self-report were included in the ADHD group  and those reporting no diagnosis or ‘not sure’ (n = 59) were included in the non-diagnosed ADHD group (n = 1181).Participants were aged between 16–83 years . The study was carried out in compliance with the Helsinki Declaration of 1975, as revised in 2008. Participants provided informed consent online prior to completing the survey.3. While the MEWS was initially developed as a 15-item scale, previous psychometric evaluation and validation found 3 items had low factor loadings and that shortening the scale to 12-items did not reduce its sensitivity or specificity, so we use the 12-item measure.Excessive mind wandering was measured using The Mind Excessively Wandering Scale (MEWS)22. Previously it has been shown that spontaneous, but not deliberate mind wandering is associated with ADHD23.To assess validation of the MEWS, unintentional (spontaneous) and intentional (deliberate) mind wandering were also assessed with the Mind Wandering Spontaneous (MW-S) and Mind Wandering Deliberate (MW-D) self-report scales24. The Barkley Current Behaviour Scale Self-report was used to measure the degree to which a participant’s inattention and hyperactivity/impulsivity symptoms cause problems for them in major life domains 24. Emotional lability was assessed with the Affective Reactivity Index self-report measure of irritability25, and the Mental Health Continuum-Short Form assessed wellbeing 26.ADHD symptoms were assessed using the self-rated Barkley Adult ADHD Rating Scale which consists of 18 items that closely parallel the DSM-5 symptom criteria for ADHD; 9 items pertain to inattention and 9 to hyperactivity/impulsivityFurther detail on the measures, including Cronbach’s alpha, are provided in Supplementary Table 27 and Stata28.Statistical analyses were carried out using MPlus2(1) = 0.95, p = 0.33) or age group (χ2(3) = 2.64, p = 0.45); EFA was carried out on the first half (n = 742) and CFA (n = 742) on the second. EFA (oblimin rotation) and CFA were carried out using a structural equation modelling framework and the Robust Weighted Least Squares (WLSMV) estimator, since this does not make distributional assumptions and is more appropriate for use with categorical variables29. Goodness of fit was assessed based on the following30: standardised mean square residual (SMSR), root mean square error of approximation (RMSEA), Tucker-Lewis Index (TLI), and the comparative fit index (CFI). In line with recommendations, the following values were used as indicators of good-fit: SMSR < 0.0832, RMSEA < 0.0632, TLI values >0.9, and CFI close to 132. Of note, although chi-square is the traditional fit index used to evaluate model fit, it is very sensitive to sample size and can be inflated in large samples33 and so this was not used as a goodness of fit (GFI) index for the CFA model.First, we performed item factor analysis to identify the dimensionality of the MEWS, using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). We used a random number algorithm to split the sample into two halves, which did not significantly differ for sex . Then, if the fit indices were in line with the accepted cut-offs, partial invariance was held and the parameter remained unconstrained in the subsequent models. Of note, the nested chi-square difference test between two models (DIFFTEST) was not used due to its sensitivity to sample size 37.The total sample was used to test measurement invariance across sex, age, and ADHD status using multi-group CFA (MGCFA) for categorical variables (sex and ADHD status) and multiple indicators multiple causes (MIMIC) models for continuous variables (age). MGCFA is tested in a sequential/hierarchical manner where constraints are consecutively added to the model. The first step involves running an unconstrained model for all groups combined to test for configural invariance (whether the same factor structure is observed between-groups). This is followed by a series of constrained models where parameters (factor-loadings and thresholds) are constrained to be equal across groups. Metric invariance refers to when factor-loadings are equivalent across groups, and scalar invariance refers to when the factor-loadings and item-thresholds are equivalent across the groups. Certain parameters are fixed for model identification . However, if the magnitude of any direct effects is very small, then it is likely to have a trivial impact on the model38. In the baseline model, associations between the covariate and items are fixed to 0 and then modification indices are consulted, with modification indices >4 of the covariate on an item presenting DIF35. If the covariate shows an association with the latent structure , this provides evidence of population heterogeneity.MIMIC models allow covariates in the CFA modelTo assess the reliability of the scale we estimated internal consistency using Cronbach’s alpha and examined item-total correlations. Convergent validity was assessed to provide an indication of the degree of relationship between the scale of interest (the MEWS) and other scales measuring similar entities, by calculating Pearson’s correlation coefficients between the MEWS and the MW-S, ADHD symptom scales, emotional lability, and impairment. To examine discriminant validity, providing an indication of whether two measures that should not be correlated are actually not related, we calculated Pearson’s correlation coefficients between the MEWS and MW-D and wellbeing. We then examined ADHD case-control differences and conducted receiver operating characteristic (ROC) analysis to examine the capacity of the scale to discriminate between those with and without ADHD.We also carried out regression analysis in the ADHD group to assess whether mind wandering accounts for unique variance in impairment and wellbeing beyond that accounted for by the core ADHD symptoms, which would further emphasise the potential value of the scale. Specifically, a hierarchical regression was conducted with impairment/wellbeing summary scores as the dependent variable and inattention and hyperactivity/impulsivity summary scores entered in Step1, and MEWS summary scores entered in Step2.Sex differences across ADHD diagnostic status in mind wandering, as well as ADHD symptoms, emotional lability, impairment, and wellbeing, were tested using linear regression models adjusted for age. Cohen’s d was used as an indication of effect size where: d ≥ 0.20 is a small effect, d ≥ 0.50 a medium effect, and d ≥ 0.80 a large effect.All 12-items in the scale were included in the EFA model. The sample correlation matrix produced 1 eigenvalue >1 (8.55), in line with the scree plot , although RMSEA was higher than the recommended cut-off . Thus, model fit indices were similar to those for the CFA carried out above, with two out of three fit indices reaching acceptable levels, implying the factor structure is equivalent between males and females. Metric and scalar invariance both held in relation to the ΔCFI and ΔRMSEA.The configural model showed acceptable model fit according to TLI and CFI , although RMSEA was higher than the recommended cut-off . Thus, model fit indices were similar to the CFA results, with two out of three fit indices reaching acceptable levels, implying the factor structure is equivalent between those with and without a self-reported ADHD diagnosis. Both metric and scalar invariance held as assessed by ΔCFI and ΔRMSEA.Thus, the MEWS showed full measurement invariance across sex and ADHD status at the scalar level, and we are satisfied that there is no substantial measurement bias.I can only focus my thoughts on one thing at a time with considerable effort”) as a function of age. Assuming equivalent levels of mind wandering, increasing age was associated with increased scores for this item ; however, the magnitude of the direct effect is small. Further, consideration should be given to the fact that Item 12 appeared last in the scale and the effect could be an artefact of this. Results therefore indicate that age is not a concern regarding measurement non-invariance. Regarding population heterogeneity, the MIMIC model suggested that mind wandering increased with age.MIMIC analysis testing the direct effect of age on individual items suggested DIF for Item 12 , with no improvement in the reliability index gained by omitting items. Item-total correlations were all above 0.69. Similar results were found across sex and ADHD status. For males and females α was 0.95, with no improvement in the reliability index gained by omitting items, and item-total correlations all >0.64. Alpha was also high in those with ADHD (α = 0.91) and those without (α = 0.94), with no improvement in the reliability index gained by omitting items, and item-total correlations >0.48 in those with ADHD and >0.66 in those without ADHD.r = 0.76, p < 0.001), ADHD symptoms , emotional lability , and impairment   and a negative relationship with wellbeing .Demonstrating convergent validity, the MEWS correlated moderately-to-strongly with spontaneous mind wandering (MW-S 1) Table . It alsop < 0.001, d = −1.17), with the same pattern of findings for measures of spontaneous mind wandering (MW-S) , inattention , hyperactivity/impulsivity , emotional lability , and impairment . We also found higher scores for wellbeing in those without ADHD compared to ADHD cases  (see Supplementary Table p < 0.001); the closer the value to 1, the better the discriminant capacity of the measure, and so this indicates that in the current sample including individuals with self-reported ADHD the MEWS has good discriminant capacity. This was comparable to the inattention  and hyperactivity/impulsivity rating scales in the sample .We found elevated levels of mind wandering as measured by the MEWS in those with a self-reported diagnosis of ADHD compared to those without ADHD (R2 = 0.53). The addition of mind wandering in the model led to a significant increase in the variability accounted for by the model (R2Δ = 0.02), with an increase to 55.3%, FΔ = 8.34, p = 0.004. This indicates that mind wandering is having a small but significant effect beyond that of inattention and hyperactivity/impulsivity. Inattention was the most strongly associated (β = 0.56), followed by mind wandering (β = 0.19) and hyperactivity/impulsivity (β = 0.08). Only inattention and mind wandering were significantly associated with impairment in the model .Regression analysis in the ADHD group examining if mind wandering (measured by the MEWS) accounts for unique variance in impairment beyond core ADHD symptoms found that inattention and hyperactivity/impulsivity accounted for 53.4% of the variability in impairment (R2 = 0.10). The addition of mind wandering as a predictor led to a significant increase in the variability accounted for by the model (R2Δ = 0.04), with an increase to 15%, FΔ = 9.29, p = 0.003. Mind wandering was the most strongly associated , followed by inattention  and hyperactivity/impulsivity . This implies that excessive mind wandering in ADHD is having a small but significant independent negative effect on wellbeing beyond that accounted for by the core ADHD symptoms.Similar findings were found for the measure of wellbeing. Within those with self-reported ADHD, mind wandering accounted for unique variance in total wellbeing beyond core ADHD symptoms. Inattention and hyperactivity/impulsivity accounted for 10% of the variance in wellbeing , except greater wellbeing reported by females  and no significant difference in emotional lability (p = 0.17)  and lower wellbeing than females   and lower wellbeing than females .Overall (irrelevant of diagnostic status), males had significantly higher scores across all scales  using a large population sample. The scale showed measurement invariance across sex, age and ADHD diagnostic status, suggesting the MEWS is a reliable and valid instrument measuring the same construct across the studied groups. Among those with ADHD, we found no evidence for sex differences in mind wandering, nor were there sex differences in levels of hyperactivity/impulsivity, emotional lability, or impairment. However, males with ADHD reported higher levels of inattention and lower wellbeing than females with ADHD. Among individuals without ADHD, males had higher scores across all ADHD related scales and reported significantly lower wellbeing than females.39. It can be difficult to achieve good fit in large samples40 and fit indices should be interpreted with this in mind. Further, there is also debate regarding model fit indices and the ‘rules of thumb’, with a general consensus that strictly adhering to recommended cut-offs can lead to incorrectly rejecting an acceptable model 30 and that allowing model fit to drive the research process moves away from the theory-testing purpose of structural equation modelling31. Thus, we believe the results support the MEWS as measuring one unified construct of excessive mind wandering.In the current study, analysis involved a series of factor analysis models. EFA suggested that a 1-factor structure is appropriate for the MEWS. Model fit indices for the CFA model were acceptable, with three out of four fit indices suggesting acceptable fit for the unidimensional structure. The RMSEA exceeded the recommended cut-off, however this does not mean that one should automatically disregard the modelThis study is the first to test measurement invariance of the MEWS, which is important to establish for any new measure, and extends our previous findings. The MEWS had full scalar invariance across sex and ADHD diagnostic status. No sex differences were observed at the level of factor loadings or thresholds, indicating scalar invariance across sex in the total sample. This attests that the same latent construct of mind wandering is related to the items and their thresholds similarly for males and females. Measurement invariance also held in those with and without a self-reported diagnosis of ADHD . Thus, comparisons of mean scores across these groups is appropriate and meaningful, and any between group differences observed can be reliably interpreted as true differences in the latent construct of mind wandering. We also found each scale item functioned similarly across age, but that increasing age may be associated with higher levels of mind wandering , so age should be considered as an important covariate in analyses of mind wandering.Reliability and validity analysis showed the 12-item scale had high internal consistency in the total sample, as well as in males and females and those with and without self-reported ADHD. The MEWS demonstrated convergent validity, with moderate to strong correlations found between the MEWS and measures of core ADHD symptoms, impairment, and wellbeing (negative correlation). The MEWS showed strong correlation with another existing measure of spontaneous mind wandering but not with deliberate mind wandering, supporting the MEWS as specifically reflecting spontaneous mind wandering. Of note, the correlation between the MEWS and emotional lability was lower than demonstrated in our previous study, which may be due to different measures of emotional lability being employed in the studies. Regarding discriminant validity, both ROC analysis and examination of mean differences showed the MEWS distinguished between those with and without self-reported ADHD. Importantly, in the current sample the ROC analysis using the MEWS produced results comparable to those of the core ADHD symptom dimensions.41 emphasise the importance of linking symptoms to impairment, which may be a better measure of identifying those who would benefit from treatment rather than somewhat arbitrary symptom counts. Replicating our previous findings, among adults with ADHD, mind wandering accounted for unique variance in impairment above that of core ADHD symptoms of inattention and hyperactivity/impulsivity. The ability for the MEWS to account for unique variance beyond core ADHD symptoms demonstrates the value of the measure and its potential clinical utility. Similar findings were also found for wellbeing, further emphasising the value of the scale. Thus, findings indicate that mind wandering is associated with both increased impairment and reduced wellbeing even after accounting for levels of inattention and hyperactivity/impulsivity.The National Collaborating Centre for Mental Health42 showing higher ADHD symptoms in males than females in the general population, but similar symptom severity amongst those with a diagnosis, except for higher inattention in males. To our knowledge this is the first investigation of sex differences in those with and without ADHD in a population-based sample of adults, and we found that the pattern of sex differences for the behavioural ADHD symptoms in adults with and without ADHD is also reflected in the more internalised/subjective experience of excessive mind wandering .Examination of sex differences showed that among those without ADHD males reported greater levels of mind wandering compared to females, but among those with ADHD, males and females reported similar levels. A similar pattern was found for inattention and hyperactivity/impulsivity, with the exception that among those with ADHD males reported more inattention than females. This is in line with recent findings amongst youth45. It is possible that differing perceptions of behaviours and impairment in males and females also occurs in adulthood. This requires further investigation.Regarding impairment, males without ADHD reported greater impairment than females, but similar levels were reported among those with a self-reported ADHD diagnosis. Additionally, despite similar symptom levels and impairment in males and females with ADHD, females with ADHD reported significantly greater wellbeing, potentially indicating differing perceptions of behaviour in males and females with ADHD. In youth, studies show parents may under-rate ADHD symptoms and impairment in girls with ADHD compared to boys, suggesting sex-specific biases in perceptions of behaviour46, and was adopted in the most recent large-scale genome-wide association study of ADHD using 23 and me47. In addition, our findings replicate those of our previous study that included a clinical sample of adults with ADHD3.A strength of the current study is the large sample size including a large age range and representation of females, both of which are often a limitation of studies in the ADHD literature. However, some limitations should be considered. First, despite the online survey being a general population sample, it is not necessarily representative of the general population, but of those who chose to participate in an online survey. Our sample included significantly more females than males suggesting that females may be more willing to participate in such studies. Moreover, it may mean that the findings regarding sex differences are not generalisable. Further studies should examine if results are replicated across other populations and those with a more equal sex balance. Second, our definition of ADHD was based on self-report and not clinical diagnosis data. However, this approach has previously been employed in a survey designEnhancing our understanding of the broader range of symptoms or problems associated with ADHD and the phenomenology that underlies ADHD symptomatology has the potential to aid diagnosis and inform targets for interventions. Valid and reliable assessment of disorders is a prerequisite for clinical treatment and intervention, and the MEWS has been shown to be a reliable and valid measure of mind wandering in ADHD that discriminates between those with and without ADHD, with satisfactory sensitivity and specificity, and specific association with functional impairment. Finding measures to assess adult ADHD, a disorder primarily defined in behavioural terms, is of value, and mind wandering could be more useful when self-report is possible as it is the experience of the internal mental states rather than observed behaviours. The MEWS shows promise as a brief screening tool in the general population and could be a potential target for monitoring of treatment effects.The replicated finding that mind wandering had an independent effect on impairment beyond that of core ADHD symptoms of inattention and hyperactivity/impulsivity, indicates that symptoms of mind wandering are strongly linked to impairment and so may be an important target for therapeutic interventions. Further studies are needed to establish such interventions, but mindfulness training could be an area of future emphasis.Supplementary Online Content


Although attention-deficit/hyperactivity disorder (ADHD) and eating disorders (EDs) frequently co-occur, little is known about the shared etiology. In this study, we comprehensively investigated the genetic association between ADHD and various EDs, including anorexia nervosa (AN) and other EDs such as bulimia nervosa.N = 3,550,118). We first examined the familial coaggregation of clinically diagnosed ADHD and EDs across multiple types of relatives. We then applied quantitative genetic modeling in full-sisters and maternal half-sisters to estimate the genetic correlations between ADHD and EDs. We further tested the associations between ADHD polygenic risk scores and ED symptoms, and between AN polygenic risk scores and ADHD symptoms, in a genotyped population-based sample .We applied different genetically informative designs to register-based information of a Swedish nationwide population  and their relatives compared with individuals without ADHD and their relatives. The magnitude of the associations decreased as the degree of relatedness decreased, suggesting shared familial liability between ADHD and EDs. Quantitative genetic models revealed stronger genetic correlation of ADHD with other EDs  than with AN . ADHD polygenic risk scores correlated positively with ED symptom measures overall and with the subscales Drive for Thinness and Body Dissatisfaction despite small effect sizes.We observed stronger genetic association with ADHD for non-AN EDs than for AN, highlighting specific genetic correlation beyond a general genetic factor across psychiatric disorders. N = 1165) with clinically diagnosed EDs, the prevalence of ADHD symptoms was as high as 35% to 37% in BN and AN binge eating/purging subtype versus 18% in AN restricting subtype Attention-deficit/hyperactivity disorder (ADHD) and eating disorders (EDs)—including anorexia nervosa (AN) and bulimia nervosa (BN)—significantly impair the health and quality of life of the affected individuals Importantly, common treatment strategies for ADHD and binge eating–related symptoms exist. For instance, a stimulant medication, lisdexamfetamine, with well-established beneficial effects on ADHD symptoms The genetic liability for ADHD and EDs has been established separately by twin and family studies Although shared heritability has been reported across multiple psychiatric disorders The use of the Swedish national registers and CATSS was approved by the Regional Ethics Review Board in Stockholm, Sweden. In the CATSS, informed consent was provided by parents (for twins aged 9 or 12 years) and by twins themselves (aged 15 years) Using the unique individual identification numbers, we linked several registers in Sweden (data updated until December 2013). We acquired information on birth year, death date, and migration type and date from the Total Population Register We identified ADHD based on registered lifetime diagnosis and medication prescriptions CATSS is an ongoing study (since 2004) targeting all twins born in Sweden since July 1, 1992 Parent-reported ADHD symptoms were measured with a validated instrument, the Autism–Tics, ADHD, and Other Comorbidities inventory N = 3,550,118; age range = 8–44 years, mean = 26.6, SD = 10.3). To study familial coaggregation, we used data for full-siblings , maternal half-siblings , paternal half-siblings , and cousins .Analyses were performed in a Swedish nationwide population born in Sweden between 1970 and 2005 after excluding individuals who died or emigrated before 6 years of age and adoptees (We first estimated odds ratios (ORs) of any ED, AN, OED, and BN in individuals with ADHD compared with individuals without ADHD using logistic regression. We then evaluated familial coaggregation patterns of ADHD and EDs by estimating ORs of EDs in each type of relative of individuals with ADHD compared with the same type of relative of individuals without ADHD. If ADHD and EDs share genetic and/or family environmental causes, ORs of EDs would be above 1 in relatives of individuals with ADHD . We adjusted for birth year and sex and addressed nonindependence of data due to familial clustering with robust (sandwich) estimator of standard errors in all regression models. We further adjusted for ADHD in the relatives as sensitivity tests We used full-sisters and maternal half-sisters for the quantitative genetic analyses. Because the prevalence of EDs was too low in male individuals, we restricted the analyses to female individuals. We randomly selected one pair of full-sisters or maternal half-sisters from each family, resulting in 334,433 pairs of full-sisters  and 57,036 pairs of maternal half-sisters . Twin pairs were excluded because their genetic and/or environmental sharing was potentially higher than that of full-sisters who were not twins.Each binary trait  was analyzed in a liability threshold setting r2 > .1 within 1000 kb; with minor allele frequency ≥ 0.05 and acceptable imputation quality INFO ≥ 0.80) using 1000 genomes (European ancestry) as reference http://pngu.mgh.harvard.edu/purcell/plink/) p-value threshold p < 1.00 and used them for primary analyses p < .00001, p < .001, p < .01, p < .05, p < .10, and p < .50) were derived and standardized for sensitivity analyses.We derived ADHD and AN PRSs for 13,472 eligible individuals in CATSS using imputed genetic data . ADHD PRR2 between the full model and the nested model without PRSs. To account for the correlated nature of the data, we applied generalized estimating equations to estimate the regression coefficients (β) and the standard error [R package drgee We evaluated the associations between ADHD PRSs and the ED symptom score (dependent variable) and between AN PRSs and the ADHD symptom score (dependent variable) using linear regressions, adjusted for sex, birth year, and the top 5 principal components; variance in symptom score explained by PRSs was measured by the difference in N = 3,550,118; 2.2% in female individuals and 3.8% in male individuals) during the observed period. As shown in The prevalence of ADHD was 3.1% in the Swedish nationwide population . The ORs of OEDs  and BN  were higher than the OR of AN ; sex difference was not statistically significant , with ORThe ORs of EDs in the quantitative genetic modeling sample were comparable to those in the female population . AE modeAs shown in The phenotypic correlation between ADHD and each ED was comparable between sister types; OEDs manifested higher phenotypic correlation with ADHD than AN, which agreed with the observed pattern of ORs of OEDs and AN in individuals with and without ADHD. The cross-trait cross-sister correlations between ADHD and EDs were also higher in full-sisters than in maternal half-sisters, suggesting genetic effects on the association between ADHD and each ED. The coheritability with ADHD was estimated to be 73% for OEDs, suggesting that 73% of the phenotypic covariance between OEDs and ADHD was explained by genetic covariance of the two disorders. Approximately 58% of the phenotypic covariance between BN and ADHD and 42% of the phenotypic covariance between AN and ADHD were attributable to their genetic covariance. Genetic correlation with ADHD was numerically higher in OEDs , and potentially in BN , than in AN .R2 = .0012, p = .015) and the subscales Drive for Thinness  and Body Dissatisfaction  but not the subscale Bulimia   . In contp-value thresholds showed consistency in variance explained  but also in dimensional ED traits in the general population. The findings complement discussions about the categorical versus dimensional conceptualizations of mental disorders Our findings have important clinical implications. First, the observed associations and familial coaggregation patterns between ADHD and EDs suggest that family history may help with early detection and risk identification of the two disorders. ADHD has been shown to predict ED symptoms The genetic overlap between ADHD and EDs may in part reflect a more general genetic susceptibility to psychopathology Despite the fact that PRSs were statistically significantly associated with the phenotype measures, their effect sizes were generally small, possibly owing to 1) PRSs being based on tagged but not necessarily causal SNPs, 2) polygenic measures possibly not reflecting more complex genetic architecture Limitations need to be considered. First, register-based data captured only treatment-seeking individuals. Individuals who had EDs but did not seek treatment were therefore misclassified in our study. BN was not identifiable in the Swedish version of ICD-9, resulting in additional misclassification. If the misclassification of EDs was differential for ADHD diagnosis  and vice versa, the associations between ADHD and EDs might be overestimated. Nevertheless, the diagnosis of ADHD was less likely to influence the chance of discovering EDs in a relative, so the estimated familial coaggregation might be less biased. Second, the EDI-2 subscale Bulimia had low internal consistency and low variation, which might be due to the fact that participants in the CATSS (15 years old) might have not yet developed pathological binge eating behaviors that typically begin during late adolescence or early adulthood In conclusion, using 3 convergent methodological approaches, we observed significant genetic associations between clinically diagnosed ADHD and EDs as well as dimensional measures of ED pathology. The genetic association with ADHD was stronger in non-AN EDs compared with AN, highlighting specific genetic correlations beyond a general genetic factor across psychiatric disorders. We expect that as genetic sample sizes grow, PRSs will become more robust and the next iteration of PRS analyses will have greater statistical power. Nonetheless, our convergent results encourage clinical vigilance for copresentation of EDs  and ADHD and suggest that, at least in part, the observed association between these 2 presentations is due to shared genetic factors.