This study investigated whether frontal lobe cortical morphology differs for boys and girls with ADHD (ages 8–12 years) in comparison to typically developing (TD) peers.Participants included 226 children between the ages of 8–12 including 93 children with ADHD (29 girls) and 133 TD children (42 girls) for which 3T MPRAGE MRI scans were obtained. A fully automated frontal lobe atlas was used to generate functionally distinct frontal subdivisions, with surface area (SA) and cortical thickness (CT) assessed in each region. Analyses focused on overall diagnostic differences as well as examinations of the effect of diagnosis within boys and girls.Girls, but not boys, with ADHD showed overall reductions in total prefrontal cortex (PFC) SA. Localization revealed that girls showed widely distributed reductions in the bilateral dorsolateral PFC, left inferior lateral PFC, right medial PFC, right orbitofrontal cortex, and left anterior cingulate; and boys showed reduced SA only in the right anterior cingulate and left medial PFC. In contrast, boys, but not girls, with ADHD showed overall reductions in total premotor cortex (PMC) SA. Further localization revealed that in boys, premotor reductions were observed in bilateral lateral PMC regions; and in girls reductions were observed in bilateral supplementary motor complex. In line with diagnostic group differences, PMC and PFC SAs were inversely correlated with symptom severity in both girls and boys with ADHD.These results elucidate sex-based differences in cortical morphology of functional subdivisions of the frontal lobe and provide additional evidence of associations among SA and symptom severity in children with ADHD. •Children with ADHD showed reductions in cortical surface area.•Boys with ADHD showed overall reductions in total premotor cortex surface area.•Girls with ADHD showed overall reductions in total prefrontal cortex surface area.•Surface area in the ADHD group was associated with symptom severity. Research on children with ADHD primarily focuses on boys due to the disproportionate prevalence of boys over girls with ADHD (2:1 to 9:1) , howeverThe limited literature on sex differences in ADHD has shown that boys and girls with ADHD differ in terms of clinical presentation and, to some extent, neuropsychological functioning. Clinically, boys are more commonly diagnosed with the combined subtype and show a greater preponderance of hyperactive/impulsive symptoms, whereas girls with ADHD are more often diagnosed with the inattentive subtype . In addiResearch examining neuroanatomical differences in children with ADHD is also predominated by male samples, limiting the opportunity to examine sex differences. In general, these studies have shown regional abnormalities in the frontal cortex , prefronVery few studies have examined sex differences in neuroanatomy among children with ADHD. Studies that have compared girls with ADHD to TD girls found evidence of smaller total brain volume and cerebellar volume in girls with ADHD (ages 5–16 years)  and reduThe current study builds upon the limited research on sex differences in cortical morphology in children with ADHD by directly comparing large samples of boys and girls with ADHD, matched on ADHD subtype, to same-sex TD peers. Furthermore, we examined functionally distinct sub-regions of the frontal lobe using a newly developed automated atlas . The use22.1Participants included 226 children, ages 8–12 years. The ADHD group comprised 93 children (29 girls), representing all three subtypes. The remaining 133 subjects (42 girls) comprised the typically developing (TD) group. The demographic information is summarized in Participants were recruited so as to provide a representative community sample. Recruitment was principally through advertisement in local public and private schools, with additional recruitment through community-wide advertisement, volunteer organizations, medical institutions, and word of mouth. A brief telephone interview was conducted with a parent to determine whether their child met the initial inclusion criteria. Next, a structured diagnostic interview using the Diagnostic Interview for Children and Adolescents-IV DICA-IV;  was condExclusion criteria for the all participants consisted of the following: (1) Full Scale IQ (FSIQ) score below 80 based on the WISC-IV, (2) history of intellectual disability, seizures, traumatic brain injury or other neurological illnesses, (3) psychotropic medications (other than stimulant medication for children with ADHD), (4) a WIAT-II Basic Reading score below 85, and (5) a DICA-IV diagnosis of Conduct Disorder, Mood Disorder, Generalized Anxiety Disorder, Separation Anxiety Disorder or Obsessive Compulsive Disorders. Given the high rates of comorbidity between ADHD and Oppositional Defiant Disorder (ODD)  and becaAn ADHD diagnosis was based on the following criteria: (1) an ADHD diagnosis on the DICA-IV psychiatric interview and (2) a T-score of 65 or higher on the DSM-IV:inattentive or DSM-IV:hyperactive–impulsive scales on the CPRS-R:L or a score of 2 or 3 on at least 6 out of 9 items on the Inattentive or Hyperactivity/Impulsivity scales of the ADHD-RS. This information was then reviewed by a child neurologist along with consideration of teacher ratings for a final confirmation. Participants in the TD group could not meet diagnostic criteria for any psychiatric disorder, other than Specific Phobia, based on DICA-IV and their scores had to be below clinical cutoff scores on the parent-report measures (CPRS-R:L and ADHD-RS). Participants with ADHD taking stimulant medication were asked to withhold medication on the day prior and day of testing.This study was approved by the Hospital Medical Institutional Review Board. Written consent was obtained from a parent/guardian and assent was obtained from the participating child.2.2Before each scanning session the participants completed a practice scanning session to acquaint themselves with the scanning environment. Participants entered the mock scanner room with an instructor and were guided through the sequence of events that occur on the day of their actual scan, including sliding into the scanner, wearing ear plugs, hearing loud MRI scanner noises, and being alone in the scanner for 10 min.All scanning acquisition was completed using a 3.0 T Philips 3T ‘Achieva’ MRI scanner . MPRAGE images  were checked for motion and only images with minimal motion were used for FreeSurfer processing. Atlas based regions of interest (ROIs) and total cerebral volume measurements were obtained using FreeSurfer . Within 2.3Data analysis was accomplished using SPSS Statistical Version 20 . In line with previous research, each participant's frontal lobe ROI cortical measurements were normalized by multiplying the raw cortical metric by the ratio of their respective diagnostic group's average total brain volume (TBV) and individual subject's total brain volume  . NormaliA hierarchical approach was used to assess the relationship between symptom severity, as measured by the CPRS-R:L ADHD Total Score, and SA in the ADHD group only. Since correlations with symptom severity were only tested in the ADHD group, unnormalized scores of SA were used. First, partial correlations were used to investigate associations between CPRS-R:L raw total score and PMC and PFC morphology while controlling for age. Second, for significant associations, follow-up partial correlations were used to investigate the association between CPRS-R:L raw total score and PFC and PMC ROIs within sex.33.1There were no significant diagnostic differences within sex or at the whole group level (ADHD vs. TD) for age, socio-economic status, sex, WISC-IV Perceptual Reasoning Index (PRI), and Edinburgh Handedness Inventory. Representation of the ADHD subtypes, current use of stimulant medication, and comorbid ODD and phobia did not differ in boys and girls with ADHD. Demographic information is summarized in 3.23.2.1F < 1, p = .947, or Diagnosis × Sex interaction, F = 0.24, p = .625. There was a significant Diagnosis × ROI interaction, F = 2.9, p = .023, ηp2 = .05, that was qualified by a significant Diagnosis × Hemisphere × ROI interaction, F = 2.8, p = .026, ηp2 = .049. Examination of post-hoc tests comparing diagnostic groups for each ROI within each hemisphere revealed no significant differences between ADHD and TD groups for any of the ROIs, p-values > .30, although there was a trend for reduced ACC CT in the ADHD group, p = .070, which may have driven this interaction.A 2 Diagnosis × 2 Sex × 2 Hemisphere × 5 ROI repeated measures ANOVA for CT of the PFC ROIs  revealed no significant effect of diagnosis, 3.2.2F = 13.6, p < .001, ηp2 = .058. This effect of diagnosis differed for boys and girls as evidenced by a marginal Diagnosis × Sex interaction, F = 3.59, p = .059, ηp2 = .016, such that the effect of diagnosis was significant for girls, F = 11.4, p = .001, ηp2 = .049, but not for boys, F = 2.57, p = .110, ηp2 = .011  revealed a significant effect of diagnosis (TD > ADHD), .011 see .F = 2.8, p = .026, ηp2 = .049. Post-hoc tests revealed that girls with ADHD showed smaller cortical SA in a much wider distribution of PFC regions than did boys with ADHD, including bilaterally in the DLPFC, left DLPFC: F = 6.4, p = .012, ηp2 = .028; right DLPFC: F = 5.0, p = .026, ηp2 = .022, as well as left ILPFC, F = 6.4, p = .012, ηp2 = .028, left ACC, F = 8.1, p = .005, ηp2 = .035, right mPFC, F = 7.8, p = .006, ηp2 = .034, and right OFC, F = 5.21, p = .023, ηp2 = .023. In contrast, boys with ADHD showed fewer PFC reductions compared to TD boys than did girls with ADHD, including the left mPFC, F = 3.9, p = .050, ηp2 = .017, right ACC, F = 9.4, p = .002, ηp2 = .041, and right OFC, F = 3.7, p = .055, ηp2 = .016. Pairwise comparisons are summarized in These effects were qualified by a significant Diagnosis × Sex × Hemisphere × ROI interaction, 3.33.3.1F < 1, p = .679, and no Diagnosis × Sex interaction, F < 1, p = .807. Additionally, all other interactions with Diagnosis were not significant.A 2 Diagnosis × 2 Sex × 2 Hemisphere × 3 ROI repeated measures ANOVA for the PMC ROIs  revealed no significant main effect of Diagnosis, 3.3.2F = 3.7, p = .057, ηp2 = .016. The effect of diagnosis did not significantly vary by sex, Diagnosis × Sex interaction: F = 0.6, p = .441, although it was qualified by a Diagnosis × ROI interaction, F = 5.2, p = .006, ηp2 = .045. Post-hoc tests revealed that SA was reduced in children with ADHD in the LPM, F = 4.2, p = .042, ηp2 = .018, and SMC, F = 3.9, p = .05, ηp2 = .017.A 2 Diagnosis × 2 Sex × 2 Hemisphere × 3 ROI repeated measures ANOVA for the PMC ROIs  revealed a marginally significant main effect of diagnosis (TD > ADHD), F = 5.2, p = .024, ηp2 = .033, but not for girls, F = 0.6, p = .433, ηp2 = .009, suggesting that PMC SA is reduced in boys with ADHD compared to TD boys, but not in girls with ADHD compared to TD girls  = 3.6, p = .03, ηp2 = .045, such that boys with ADHD showed significantly smaller cortical SA only in the bilateral LPM, F = 8.4, p = .004, ηp2 = .052. For girls, there was also a Diagnosis × ROI interaction, F = 4.9, p = .011, ηp2 = .13, such that girls with ADHD showed smaller cortical SA only in the bilateral SMC only, F = 4.1, p = .046, ηp2 = .056. Pairwise comparisons are summarized in Given the pattern of findings for the PFC and our interest in sex differences in ADHD boys and girls compared to their sex-matched peers, separate analyses (Diagnosis × Hemisphere × ROI) for each sex were also conducted to determine whether the Diagnosis × ROI interaction reported above for surface area was present among boys and girls . These analyses revealed a significant effect of diagnosis for boys, irls see . For boy3.4F = 7.9, p = .005, ηp2 = .04, as well as a significant Diagnosis × Sex × Hemisphere × ROI interaction, F = 3.2, p = .014, ηp2 = .07. In contrast, for children with comorbid ODD, while there was a main effect of Diagnosis on PFC SA, F = 8.7, p = .004, ηp2 = .05, there was no Diagnosis × Sex × Hemisphere × ROI interaction, F = 1.2, p = .297, ηp2 = .03. These results suggest that the diagnosis of ADHD, and not the presence of comorbid ODD, is driving the interaction findings observed in the whole group. There was also an effect of medication status for the PFC such that among the children currently prescribed with stimulant medication (n=65), a significant effect of diagnosis, F = 13.9, p < .001, ηp2 = .07, and a marginal Diagnosis × Sex interaction, F = 3.6, p = .058, ηp2 = .02, was observed, similar to the findings for the whole group. In contrast, these effects were not present among those that were not currently prescribed stimulant medication (n=28), diagnosis: F = 2.6, p = .108, ηp2 = .02, Diagnosis × Sex: F = .92, p = .340, ηp2 < .01. Analysis of ODD and medication status on PFC cortical thickness revealed no effect of ODD or medication status.For the PFC, separate analyses of children with ADHD with (n=35) and without (n=58) comorbid ODD compared to TD children revealed that for the ADHD without ODD group there was an effect of ADHD Diagnosis, F = 7.7, p = .006, ηp2 = .04, as well as a significant Diagnosis × ROI interaction, F = 5.0, p = .008, ηp2 = .05. In contrast, for children with ODD, there was no significant effect of diagnosis, F = .05, p = .83, ηp2 < .001, or a Diagnosis × ROI interaction, F = 2.4, p = .091, ηp2 = .03. These results suggest that the diagnosis of ADHD, and not the presence of comorbid ODD, is driving the findings observed in the whole group. Analyses of the effect of stimulant medication status on the PM SA revealed that both groups showed a significant Diagnosis × ROI interaction , suggesting that medication status had no impact on PMC SA findings from the whole group. Additionally, there were no significant main effects or interactions observed in any of the ODD or medication status subgroups for PMC cortical thickness.Similarly, for the PMC, separate analyses of children with ADHD with and without comorbid ODD compared to TD children revealed that for the ADHD without ODD group, there was an effect of ADHD diagnosis, 3.5r = .232, p = .026) but not PFC SA , age was included as a covariate in both PMC and PFC associations with symptom severity to be consistent.Partial correlations were used to assess relationships between Ranta atlas ROIs and symptom severity  in children with ADHD. Although age was only correlated with PMC SA . Follow-up analyses exclusively investigated symptom correlations with SA in each of the ROIs for each sex. Among boys, PMC SA was associated with symptom severity , whereas this correlation was not significant for girls with ADHD . However, it should be noted that the correlation coefficient was similar for boys and girls with ADHD, suggesting that the lack of significance among girls with ADHD may be due to reduced power. In contrast, PFC SA was significantly associated with symptom severity in both girls and boys with ADHD , although this relationship appears to be stronger among girls with ADHD  was associated with decreased ADHD symptom severity within the ADHD group. Additionally, PMC and PFC SAs were associated with ADHD symptom severity among boys, whereas PMC SA was not significantly associated with symptom severity among girls with ADHD, although the correlation coefficient was similar to that of boys suggesting a lack of power, and a strong association between PFC SA and symptom severity, was observed. Similar to the PFC SA diagnostic group differences seen in boys and girls with ADHD, a stronger association between PFC SA and symptom severity may be related to the earlier development of the PMC relative to the PFC and of girls relative to boys, such that ADHD-associated differences in PFC SA seen in the girls may predate that of boys. Previous work by Shaw and colleagues has shown that the rate of cortical thinning is associated with symptom severity as well as syndromatic and symptomatic remission . In thisTo our knowledge, only one other study has investigated sex differences in frontal lobe morphology in children with ADHD . AlthougDue to the limited research on sex differences in children with ADHD, we chose to focus our investigation on PMC and PFC regions in a group of relatively “pure ADHD” children . The ROI based approach used in this study allowed us to investigate functional subdivision of the frontal lobe, which has not been done. By doing so, we were unable to localize the clusters within the ROI that drove these sex and diagnostic differences. Additionally, the inclusion of hemisphere in our analysis revealed significant differences between boys and girls with ADHD, yet no clear laterality effect was observed. Although our data suggest differences in frontal lobe cortical development in boys and girls with ADHD compared to their TD peers, we were unable to test those differences in cortical development due to our cross-sectional data. Previous longitudinal research has shown a general reduction in volume across all lobes as well cerebellum in ADHD subjects ages 5–19 . FurtherThis study emphasizes the need for the investigation of sex-differences in ADHD, particularly in terms of brain structure and function, cognition, and behavior. In this study we were able to identify sex-based differences in SA, such that boys with ADHD showed more prominent PMC reductions in SA, while girls with ADHD showed more prominent PFC reductions in SA. We also found that greater SA was associated with lower ADHD symptom severity. Future research is needed to clarify the following: 1) whether boys and girls with ADHD follow the same developmental trajectory in SA, but with girls somewhat ahead of boys, and 2) how these reductions in SA are related to changing developmental cognitive and behavioral impairments. A greater understanding of sex differences in ADHD and trajectories of brain development and functional outcomes has important implications for possible remediation or therapies tailored differentially to boys and girls with ADHD.


This study aims to assess cognitive functioning differences among adolescents with retrospectively self-reported: ADHD and an onset of depression, only ADHD, only depression, and neither ADHD nor depression. Data from the Tracking Adolescents’ Individual Lives Survey (TRAILS) cohort was used in this study. Neuropsychological functioning was assessed in 1549 adolescents, at baseline and follow-up (mean ages 11 and 19 years). The Composite International Diagnostic Interview was used to classify adolescents into 4 groups: ADHD with onset of depression, only ADHD, only depression, and neither ADHD nor depression. Linear mixed effects models were used to analyse group differences in cognitive functioning at baseline and follow-up, and the change in cognitive functioning between these 2 time-points. Results showed a significant main effect of group on response time variability at baseline, working memory maintenance at follow up, and change in response time variability scores between baseline and follow-up. As compared to the healthy and depressed-only groups, adolescents with only ADHD showed longer response time variability at baseline and, which declined between baseline and follow-up. Adolescents with ADHD plus depression showed higher reaction time for working memory maintenance than the depressed only and healthy groups at follow-up. In conclusion, adolescents with self-reported ADHD show poorer cognitive functioning than healthy adolescents and those with only depression. Amongst adolescents with ADHD, specific cognitive domains show poor functioning depending on the presence or absence of comorbid depression. While adolescents with only ADHD have lower reaction time variability, those with comorbid depression have poorer working memory maintenance.The online version of this article (doi:10.1007/s10802-016-0160-x) contains supplementary material, which is available to authorized users. Attention Deficit Hyperactivity Disorder or ADHD is a neurodevelopmental disorder of childhood that often persists into adolescence and adulthood  in the following manners. First, as found in previous studies, comorbidities may increase the severity of cognitive deficits , an ongoing Dutch prospective cohort study on psychosocial development and mental health of adolescents. TRAILS involves bi- or triennial measurements from ages 11 onwards and consists of two separate cohorts: one population-based and another clinic-based. , of whom 84.2 % (N = 1584) completed the below-described diagnostic interview. . This gave a final sample size of 1549 adolescents. T1 is referred to as baseline and T4 as follow-up in following sections of the paper.Children were recruited from five municipalities in the north of The Netherlands, including both urban and rural areas. Primary school participation was requisite for inclusion. Of the 2935 children who met these criteria, 2230 (76.0 %) provided informed consent from both parent and child to participate in the study. The present study utilises data from the first and fourth wave. The first wave (T1) ran from March 2001 to July 2002, the fourth (T4) from October 2008 to September 2010 (T4). Mean age at T1 was 11.1 years (SD = 0.56), and 50.8 % were girls. Response rate at T4 was 83.4 % , suggesting limited overlap.Cognitive functions were assessed at baseline and follow-up using the Amsterdam Neuropsychological Tasks program (ANT) , version 3.0. The CIDI is a structured diagnostic interview that yields lifetime and current diagnoses according to the definitions and criteria of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). The CIDI has been used in a large number of surveys worldwide, and shown to have good concordance with clinical diagnoses  ADHD with an onset of depression (Group A+D), (2) only ADHD (Group A), (3) only an onset of depression (Group D), and (4) comparison: neither ADHD nor an onset of depression (Group C). Mean self-reported ADHD and depressive symptom scores  at the four assessment waves were plotted to visualise the approximate time-point of divergence in symptom scores amongst the four groups.d.Linear mixed effects models were used to analyse differences in cognitive functioning among these groups at baseline and follow-up as well as change in cognitive functioning between baseline and follow-up (slope). We adjusted for the effects of age at baseline, gender, and medication use in the analyses by including these variables as covariates. The (co)variance matrix was set to unstructured  for all analyses. For the cognitive outcome measures that showed group differences, we additionally plotted the standardized RTs per group at baseline and follow-up and estimated the effect sizes of comparisons with group C using Cohen’s A sensitivity analysis was conducted as a second step to determine if (lack of) differences in cognitive functioning among groups were due to the presence of psychiatric disorders other than ADHD or depression in the comparison group. For this, a new comparison group  was formed by excluding participants with CIDI diagnoses of other psychiatric disorders from group C, and the above-described linear mixed effects analyses were re-run to test cognitive functioning differences among groups A+D, A, D and H. Age at baseline, gender and medications were included as covariates.SD in the total sample).A second sensitivity analysis was additionally performed to explore the validity of the CIDI diagnoses. Data on parent-reported ADHD as assessed by the Diagnostic Interview Schedule for Children (DISC) were available for the parallel TRAILS Clinical (high-risk) Cohort at baseline. A comparison of the DISC with the CIDI outcomes showed that almost 80 % of children with an ADHD diagnosis at baseline according to the DISC did not have a CIDI diagnosis of ADHD in adulthood (note that both interviews required an onset of ADHD before age 7). Conversely, 80 % of those who had a CIDI diagnosis of ADHD also had a DISC diagnosis of ADHD in childhood. These results suggest the presence of relatively few false positives in our current sample (with the use of CIDI), yet many false negatives. To assess the possibility of false negative ADHD diagnoses using the CIDI, we reformed the comparison group by excluding participants with a high baseline CBCL or TCP ADHD symptom score   and graphs were plotted using MATLAB 2012b . All tests were two-tailed and a n = 56), and 19.6 % a diagnosis of depression (n = 303). Amongst those with ADHD, 37.5 % developed depression between baseline and follow-up (n = 21). These numbers are consistent with estimates of lifetime mental health problems obtained in late adolescence  and 12 participants from group A (n = 35). Using teacher-reports, these numbers were five in group A+D and seven in group A. Scores greater than 1.5 SD on either parent or teacher reports were found among 10 participants from group A+D and 13 participants from group A. Mean parent-reported ADHD symptom scores in group A+D and A were 0.87 (SD = 0.58) and 1.01 (SD = 0.45), respectively. Mean teacher-reported ADHD symptom scores were 1.41 (SD = 1.20) and 1.16 (SD = 1.18) for groups A+D and A, respectively.Parent- (CBCL) and teacher- (TCP) reports, available at baseline, were used to estimate the number of adolescents in the A+D and A groups with ADHD scores >1.5 SD. Parent-reports showed > 1.5 d = 0.53, p = .019), while group A had higher ADHD symptoms than groups D  and C . ADHD symptom scores at T4 of group A+D was higher than groups A , D  and C , and of group A was higher than groups D  and C . Depressive symptoms at T1 were higher amongst groups A+D , A  and D  than group C. At T4, mean depressive scores were high for group A+D as compared to group A , group D  and group C . For group D at T4, depressive symptoms were higher than group A  and group C .Figure r = 0.44; focussed attention: r = 0.37; response time variability: r = 0.50; working memory maintenance: r = 0.46; inhibition: r = 0.34; cognitive flexibility: r = 0.34; all p < .001). For further details on the association between baseline and follow-up cognitive functions in the TRAILS sample, please see Boelema et al.  = 3.92, p = .008, ɳ2 = 0.004; working memory maintenance at follow up: F = 2.56, p = .05, ɳ2 = 0.004, and; change in response time variability scores between baseline and follow-up: F = 3.35, p = .01, ɳ2 = 0.005. Baseline response time variability RT was higher in group A than group C (p = .001). Working memory maintenance RT at follow-up was higher in group A+D than group C (p = .007). Between baseline and follow-up, the slope of change in response time variability RT for group A was significantly more negative (p = .002) than that of group C. The covariates-corrected effect sizes for these three differences were d = 0.44, d = 0.60, and d = −0.47, respectively. Finally, results of post-hoc pairwise comparisons are presented in Table Linear mixed model analyses with sex, age, and ADHD and depression medication use as covariates revealed significant group differences in response time variability at baseline: F = 4.23, p = .005, ɳ2 = 0.003; working memory maintenance at follow up: F = 2.56, p = .05, ɳ2 = 0.002, and; change in response time variability scores between baseline and follow-up: F = 3.36, p = .01, ɳ2 = 0.004 and likewise indicated a higher baseline response time variability RT in group A than group C (p = .001); higher working memory maintenance RT at follow-up in group A+D than group C (p = .007); and a more negative slope of change in response time variability RT for group A relative to group C (p = .002). The effect sizes for these three differences were d = 0.52, d = 0.60, and d = −0.55, respectively.Figure n = 19; agoraphobia: n = 6; conduct disorder: n = 71; generalised anxiety disorder: n = 22; oppositional defiant disorder: n = 65; panic disorder: n = 13; separation anxiety disorder: n = 25; social phobia: n = 110; specific phobia: n = 110, total n = 323) to form a new group of 888 adolescents . Linear mixed effects analyses revealed group differences in baseline response time variability: F = 4.64, p = .003, ɳ2 = 0.007; change in response time variability between baseline and follow-up: F = 3.99, p = .008, ɳ2 = 0.005, and; follow-up working memory maintenance: F = 2.76, p = .041, ɳ2 = 0.005. Results of group and posthoc pairwise comparisons for response time variability and working memory maintenance were comparable to results from the main analysis. In addition, group differences in baseline processing speed were found: F = 2.90, p = .03, ɳ2 = 0.006. None of the group differences in processing speed remained significant after applying FDR corrections.For the first sensitivity analysis, participants from group C with psychiatric diagnoses (other than ADHD or depression) were excluded  = 7.05, p < .001, ɳ2 = 0.007; follow-up working memory maintenance: F = 3.62, p = .013, ɳ2 = 0.005, and; change in response time variability between baseline and follow-up: F = 5.42, p = .001, ɳ2 = 0.006. Results of group and posthoc pairwise comparisons for response time variability and working memory maintenance were comparable to the results from the main analysis. Additionally, group differences were found in baseline processing speed: F = 3.13, p = .025, ɳ2 = 0.006). Post hoc pairwise comparisons showed that group A was significantly slower (FDR corrected) than group C .For the second sensitivity analysis, 158 participants with a CBCL or TCP ADHD score with This study was aimed at assessing if ADHD with an onset of depression is associated with a unique cognitive functioning profile in adolescents with retrospectively self-reported ADHD and depression. Results show that cognitive functioning in adolescents with ADHD plus depression and only ADHD differed from the control groups either with or without depression. In particular, working memory maintenance of adolescents with ADHD plus depression at mean age 19 years was poor as compared to healthy adolescents and adolescents with only depression. Furthermore, the group of adolescents with only ADHD performed worse in response time variability at mean age 11 than the depressed and comparison groups. Our results also suggest that response time variability function improved between early adolescence and young adulthood in adolescents with only ADHD. We found no evidence, however, for cognitive functioning differences between adolescents with ADHD who did and did not develop depression.The presence of comorbidities in individuals with ADHD is believed to increase the severity of cognitive deficits . It can be speculated that the development of depression may have increased the cognitive burden associated with ADHD and led to working memory maintenance difficulties. Alternately, poor cognitive functioning may have led to the development of depression in adolescents with ADHD.Working memory maintenance, at age 11, of adolescents with ADHD and either with or without depression was comparable to that of the comparison group. Previous studies though, show impaired working memory in children with ADHD at an early age. Three related reasons as to why we did not find any group differences in working memory maintenance at age 11 in this study are worth mentioning. First, previous studies have been mostly based on recall tasks, which unlike recognition based tasks, such as the memory search task of the ANT, are more likely to show differences between children with and without ADHD early on  may still develop depression later on. This may have led to an incorrect grouping of adolescents, and possible under-estimation of effects. Third, we did not withdraw participants from stimulant medication prior to cognitive testing although this did not seem to influence our findings.Thus far, it has been difficult to pinpoint the exact cognitive profile associated with ADHD with affected cognitive domains varying widely across studies. Cognitive function is assumed to change throughout development in patients with ADHD and to generally improve with time ESM 2(DOC 116 kb)ESM 3(DOCX 42 kb)Below is the link to the electronic supplementary material.


Viperin is an antiviral protein that is upregulated by interferons and by ligands for a variety of innate immune receptors. It possesses diverse capabilities and functions in an array of viral infections. Studies have shown that it appears to be particularly important in defence against RNA viruses, such as West Nile, Dengue, and Chikungunya viruses, although the specific mechanisms involved are not well understood at the molecular level. Here we identify the mitochondrial antiviral signalling protein MAVS as a novel viperin interaction partner, most likely in mitochondria associated membranes, and characterize a more central, overarching role of viperin as a negative regulator of the interferon response, an ability that can be regulated by the viperin-MAVS interaction. This suggests a novel mechanism of viperin action in immune defence against RNA viruses by which it may prevent pathology from excessive immune responses. Virus Inhibitory Protein, Endoplasmic Reticulum-associated, interferon-inducible (viperin) is the product of the interferon stimulated gene (ISG) rsad2. It has been reported to play an antiviral role against a number of viruses, including Human Immunodeficiency Virus ). ). Virus cy Virus  and the cy Virus , 15. To cy Virus , and WNVMitochondrial antiviral signaling protein (MAVS), an adaptor molecule downstream of the cytosolic RNA receptors retinoic acid-inducible gene I (RIG-I) and melanoma differentiation-associated protein 5 (MDA-5), is critical for the innate immune response to RNA viruses. After being activated by their RNA ligands, RIG-I and MDA-5 bind to MAVS, which then oligomerizes and recruits downstream signaling molecules, including STING, TRAF2, TRAF3, and TRAF6. This results in the activation and translocation of the transcription factors IRF-3, IRF-7 and NF-κB to the nucleus and leads to the production of IFNs and inflammatory cytokines [ytokines , 17. Givytokines , 19 and ytokines .Pathology in viral infections is often a result of excessive inflammation, and various mechanisms exist to regulate this. A splice variant of MAVS, known as miniMAVS, inhibits MAVS signaling and its downstream effects , 21. Themitochondria-associated ER membranes (MAM), particularly upon the activation of its signaling pathways [Although MAVS was so named because it is found on mitochondria, it has also been shown to localise to peroxisomes and pathways –30. In iC57BL/6 mice were purchased from Jackson Labs and maintained alongside viperin knockout mice . MAVS knpcDNA3.1-HADHA, pcDNA3.1-HADHB, pcDNA3.1-myc-his and pcDNA3.1-viperin have been previously described , 11. AllCells were harvested, washed with PBS, and lysed on ice for 30 minutes in lysis buffer (1% CHAPS (Pierce) in PBS containing a protease inhibitor cocktail tablet (Roche)). After centrifugation at 800g for 10 minutes at 4°C to remove debris, lysates were sparated by SDS-PAGE and transferred onto PVDF membranes (Millipore). The membranes were probed using antibodies against viperin (MaP.VIP) [To conjugate antibodies to beads, Protein G Sepharose beads  were rotated with anti-viperin antibody or anti-MAVS antibody (Santa Cruz) overnight at 4°C. Beads were washed once with PBS and twice with 0.2M borate buffer, pH 9.0. Dimethyl pimelimidate dihydrochloride (Sigma) was dissolved in the borate buffer to a final concentration of 5.2 mg/ml and added to beads, followed by rotation at room temperature for 30 minutes. Beads were washed twice with 1.2% ethanolamine-HCl buffer, pH 8.0, and rotated for 2 hours, washed twice with 100mM glycine, pH 3.0, and twice with PBS. Beads were added to CHAPS lysates of the cells and rotated at 4°C for 2 hours. After 4 washes with 0.1% CHAPS in PBS the samples were separated by SDS-PAGE and transferred onto PVDF membranes.RAW 264.7 cells were stimulated with universal type I IFN (PBL Interferon Source) in cell culture medium  for varying lengths of time. Fractionation was performed using Percoll gradients as described .Cells were stained with MitoTracker Red (Thermo Fisher Scientific) for 30 minutes at 37°C, washed with PBS, and fixed with 2% paraformaldehyde in PBS for 15 minutes at room temperature. After washing in 10mM glycine in PBS and blocking with 5% normal goat serum (Invitrogen) in PBS, the cells were permeabilized with 0.5% saponin (Sigma) in 5% normal goat serum in PBS for 1 hour at room temperature. Staining was performed in permeabilization buffer. Primary antibodies used were the same as used for western blotting, except that a rabbit antiserum against calnexin was used. Secondary antibodies were the Alexa Fluor series from Thermo Fisher Scientific. Slides were mounted with ProLong Gold Anti-Fade Reagent (Thermo Fisher Scientific), viewed using a Leica SP8 model confocal microscope and the images were analysed using ImageJ software.Mouse bone marrow cells were isolated by flushing hind leg bones. Cells were counted and plated in culture medium  containing 30% medium from L929 cells secreting macrophage colony stimulating factor (MCSF). After 6 days, resulting BMM were counted and re-plated at desired densities in culture medium with 5% MCSF-containing L929 medium. Experiments were performed the next day. IFN was added directly, while poly(I:C) (Sigma) and 5’ppp-dsRNA (Invivogen) were transfected into cells using Lipofectamine 2000 (Thermo Fisher Scientific) in Opti-MEM (Gibco). After 1 hour the cells were re-suspended in culture medium. Fluorescein-tagged poly(I:C) was purchased from Invivogen. All other ligands were a kind gift from the laboratory of Dr. Ruslan Medzhitov.RNA was extracted from cells using the Qiagen RNeasy Mini Kit. This was converted to cDNA using the AffinityScript multi temperature cDNA synthesis kit (Agilent Technologies) and a BioRad PCR machine. Quantitative PCR was performed using SYBR Green from Life Technologies and Biotool. Analysis was performed using an Mx3000P (Stratagene) and the MxPro software (Agilent Technologies).Cells were harvested, washed with PBS, and collected using an Accuri C6 CSampler (BD Biosciences). Analysis was performed using FlowJo software. To test for activated caspase-3, cells were stained using the FITC Active Caspase-3 Apoptosis Kit (BD Pharmingen). To test for viperin, MaP.VIP was directly conjugated to Alexa 647 (Thermo Fisher Scientific).293T cells were transfected with pISRE-firefly luciferase and various combinations of viperin or MAVS constructs as required. Each transfection had an equal amount of DNA, attained by adding pcDNA3.1-myc-his as a control where necessary. Cells were transfected with poly(I:C) if necessary. 25 to 30 hours after transfection, cells were washed with PBS and lysed in passive lysis buffer (Promega) for 15 minutes at room temperature with gentle shaking. Lysates were centrifuged to pellet debris and supernatants used in luciferase assays (Promega) read using MikroWin 2010 software.endoplasmic reticulum (ER) is well established [Fig 1A). This overall distribution was also observed in 293T cells transfected with either wild type (WT) viperin or viperin tagged with a mitochondrial localization sequence derived from vMIA (MLS-viperin) [Fig 1B).The localization of viperin to the ablished , 33, butviperin) . WT vipebone marrow macrophages (BMM) stimulated with IFN, quantitating the percentage of the proteins that co-localized with each other and with markers for various intracellular compartments. Viperin co-localized with MAVS and the ER markers calnexin and Grp94, as well as the MAM marker FACL4, but not with mitochondria, detected using the specific dye MitoTracker . This pattern did not change with time . To determine whether the method of stimulation could affect localization patterns and whether viperin and MAVS could affect one another’s localization, WT, viperin knockout (KO), and MAVS KO BMM were stimulated with IFN or transfected with poly(I:C) or 5’ppp-dsRNA, which stimulate by interacting with MDA-5 and RIG-I, respectively [vice versa . This suggests that viperin and MAVS independently localize to the relevant compartments.We also used confocal immunofluorescence microscopy to examine viperin and MAVS distribution in mouse ectively –37, and Fig 3A). To show that the association was not dependent on overexpression, co-immunoprecipitations were also performed using RAW 264.7 cells stimulated with IFN or transfected with poly(I:C), which activates cells via MDA-5 and the MAVS pathway. In both cases viperin was co-immunoprecipitated with an anti-MAVS antibody and MAVS with an anti-viperin antibody, indicating that they interact under physiological conditions . Of note, some co-immunoprecipitation was observed even in extracts of unstimulated cells, likely a consequence of low basal levels of viperin present. To quantitate the extent of the interaction, a series of sequential immunoprecipitations were performed. The effective depletion of viperin from the extract left significant residual MAVS in the cell extract and vice versa, showing that only a fraction of the two components were co-associated . Although this may to some extent reflect dissociation of MAVS and viperin upon detergent extraction, it does correlate well with co-localization quantifications described in Figs 2.Given the involvement of both MAVS and viperin in defense against RNA viruses, as well as their co-localization in MAM, we considered the possibility that they might physically interact. Indeed, co-immunoprecipitations performed using detergent extracts of 293T cells co-transfected with viperin and MAVS demonstrated an interaction between the two . Western blots were checked to ensure that expression levels of the mutants were comparable to that of wild type viperin .As a preliminary approach to determining the regions of viperin that interact with MAVS, we generated a series of deletion mutants corresponding to short segments of viperin, such as an α-helix or a loop, based on its as yet unpublished crystal structure . The mutants were co-expressed with MAVS in 293T cells and immunoprecipitations were performed on detergent extracts of the cells followed by SDS-PAGE and quantitative western blotting. The data indicated that deletions at the N and C termini of viperin significantly reduced the viperin-MAVS interaction . Similarly, Western blots were checked to ensure that expression levels of the mutants were comparable to that of wild type viperin . Notably, when expressed in BMM using a doxycycline-dependent transduction system and analysed by confocal immunofluorescence microscopy, all of the mutants had a similar intracellular profile as WT viperin, consistent with the data in Fig 2 showing that the viperin-MAVS interaction does not affect viperin distribution .Because the structure of the N terminal region of viperin was undefined in the crystal structure, the sequence was assessed using the ConSurf program  to prediFig 5A). The focus was placed on these three ligands because IFNβ expression was very low with other modes of stimulation (data not shown).To determine whether the viperin-MAVS interaction affects the functional consequences of MAVS-dependent signaling, BMM from WT and viperin KO mice were transfected with poly(I:C) or 5’ppp-dsRNA or, as a control, stimulated with universal type I IFN. IFNβ expression was monitored by quantitative PCR. Surprisingly, we found that viperin KO BMM expressed significantly higher levels of IFNβ than WT BMM upon poly(I:C) transfection. A similar trend was also seen upon IFN and 5’ppp-dsRNA stimulation, but it was much less pronounced than with poly(I:C) . Co-expression with MAVS of the GFP derivative Venus, as a control, marginally reduced IFNβ expression, possibly because of promoter competition. However, the reduction caused by viperin co-expression was much more significant . Transfecting MDA-5 or RIG-I alone increased the signal to a much lesser extent than MAVS, but again the signal was reduced when viperin was co-transfected .To further examine the functional relationship between MAVS and viperin, we measured IFNβ expression in 293T cells expressing an IFNβ promoter (ISRE)-activated luciferase reporter construct. We found that poly(I:C) transfection alone was unable to elicit a strong response in these cells, as expected , and vipFig 6A and 6B), suggesting that viperin is indeed a negative regulator of MAVS-dependent signaling. To ensure that viperin KO macrophages have normal accumulation of transfected poly(I:C), we used fluorescent poly(I:C). There was no significant difference between the levels accumulated by WT and viperin KO BMM, when analysed via confocal immunofluorescence microscopy .Reduction in IFNβ transcripts in the absence of viperin could because of suppressed signaling or post-transcriptional effects of viperin. We therefore asked directly whether signaling was affected by measuring phosphorylation of IRF3, which in the MAVS signaling pathway precedes the transcription of IFNβ and other pro-inflammatory genes. In viperin KO BMM, there is increased IRF-3 phosphorylation, particularly at the 6h time point . This suggests that viperin-mediated inhibition of MAVS-mediated signaling may not dependent on a direct effect of viperin binding to MAVS. Potentially an indirect mechanism, involving sequestration of viperin via the MAVS interaction prevents viperin from acting in conjunction with other partners and pathways to inhibit IFNβ production. However, the majority of MAVS does not interact with viperin, based both on the fraction that co-immunoprecipitates as well as the small overlap in the intracellular distribution of the two components. This suggested that only the sequestration of viperin that is in the same subcellular region as MAVS, likely the MAM, is capable of interfering with signaling.We next asked whether the reduction in MAVS-dependent signaling mediated by viperin depended upon the viperin/MAVS interaction. To determine this we again used the 293T luciferase reporter system. MAVS was co-expressed with the viperin point mutants that significantly reduced the viperin-MAVS interaction shown in Fig 7B). This corresponds with interaction data shown in Fig 4A, and also indicates that, at least in the over-expression system used here, MAM localized viperin may not be the only form that can inhibit MAVS-dependent signals.The N-terminal α-helix of viperin, extending from residues 1–42, is essential for its localization to membranes and lipid droplets , 40. To Viperin is membrane bound by virtue of its N-terminal amphipathic α-helix. It was previously shown to associate with the cytosolic face of the ER and with lipid droplets, and this manuscript extends those findings by showing that a fraction is also localized to MAM. The MAM compartment is known to be enriched in cholesterol and is involved in multiple processes, including lipid transport, calcium homeostasis, oxidative metabolism, apoptosis, autophagy, signalling, and viral infections , 42. VipThe data presented here show that a fraction of both IFN-induced viperin and, as previously shown , 29, MAVThe mechanism by which viperin negatively regulates MAVS-dependent MDA-5 mediated signalling is unclear. A straightforward explanation would have been that the interaction between viperin and MAVS inhibits MAVS functions directly, for example by causing conformational changes in MAVS or competing for essential binding partners. In this case, however, one would expect that the interaction mutants would show a reduced capacity to inhibit IFNβ production. However, the converse was seen: the viperin-MAVS interaction appears to be required to restrain the inhibitory effect of viperin on IFNβ production, since viperin mutants with reduced interaction are better inhibitors of IFNβ production. It is possible that the mutant versions of viperin may have lost to varying degrees a functional capacity that is independent of their ability to bind to MAVS, and/or under basal conditions viperin could be inhibiting IFNβ production through the involvement of other as yet unknown factors and or even in a different pathway entirely. One possible explanation is that the interaction with MAVS sequesters viperin, preventing it from performing a critical inhibitory function. Although the molecular details of the inhibitory activity are unclear, at least in the over-expression system using 293T cells it does not depend on the N-terminal α-helix of viperin, suggesting that the effect of viperin on signalling is independent of membrane association.We hypothesize that when a virus enters the cell, MAVS signaling is initiated very quickly, sequestering the low levels of viperin that are initially induced and allowing the cell to initiate a functional antiviral response. Later in the infection we suggest that increased viperin expression, which peaks at between 6 and 8 hours after stimulation, overwhelms the sequestration mediated by its interaction with MAVS. This allows it to inhibit the pro-inflammatory response and prevent immune-mediated pathology. The hypothesis that the population of viperin that mediates the inhibitory effect functions outside a MAVS-associated complex is supported by the observation that the majority of viperin does not interact with MAVS, and indeed is distributed differently within the cell.The segregation of viperin into different subpopulations could also explain why a protein so widely thought to be involved in anti-viral defense is also a regulator. A key point may be that pathology in viral infections is often caused not directly by the virus itself, but by the host’s response to the infection, which can lead to cell death, tissue damage, and other systemic effects. Viperin is important for host survival in certain viral infections , 7, 45, S1 Table). Multiple ISGs were identified, including IFIT3 and TRIM56, which are directly involved in MAVS-mediated or related pathways. Others, such as ISG15, USP18, and UBE2L6, are involved in ISGylation. Notably, USP18, a negative regulator of IFN signalling, is down-regulated in viperin KO BMM, suggesting that viperin may be required for its expression. Viperin may work together with or influence USP18 function, but further experiments are required to address this possibility. Nevertheless, our data show that viperin functions as a negative regulator of MAVS-mediated signalling, particularly in the MDA-5 pathway, where its induction is clearly downstream of MAVS activation. It interacts with MAVS, most likely in MAM, and this interaction is important in controlling its inhibitory activity, likely by some form of sequestration.We attempted to look for support for the proposed role of viperin in the inhibition of MAVS-mediated signaling by examining overall mRNA expression in RNAseq experiments performed on WT or viperin KO BMM, either unstimulated or stimulated with IFN  Western blots showing that deletion mutants are expressed at similar levels to that of wild type viperin. Each set of blots is from an individual experiment. All the blots shown here cover the entire range of deletion mutants, with some overlaps. (B) Western blots showing that point mutants are expressed at similar levels to that of wild type viperin. Each set of blots is from an individual experiment. All the blots shown here cover the entire range of point mutants, with some overlaps.(TIF)Click here for additional data file.S1 TableA number of ISGs were expressed at significantly different levels in WT and viperin KO mouse BMM under basal conditions and upon IFN stimulation. Most of these were higher in WT than viperin KO cells in the absence of stimulation, suggesting that basal levels of viperin may enhance their expression. Descriptions were summarized from information provided in GeneCards :975–90).(XLSX)Click here for additional data file.


People with autism spectrum disorder (ASD) commonly experience symptoms related to attention-deficit/hyperactivity disorder (ADHD), including hyperactivity, inattention, and impulsivity. One-third of ASD cases may be complicated by the presence of ADHD. Individuals with dual diagnoses face greater barriers to accessing treatment for ADHD and respond less positively to primary pharmacologic interventions. Nonpharmacologic technology-aided tools for hyperactivity and inattention in people with ASD are being developed, although research into their efficacy and safety remains limited.The objective of this preliminary study was to describe the changes in ADHD-related symptoms in children, adolescents, and young adults with ASD immediately after use of the Empowered Brain system, a behavioral and social communication aid for ASD running on augmented reality smartglasses.We recruited 8 children, adolescents, and young adults with ASD  through a Web-based research signup form. The baseline score on the hyperactivity subscale of the Aberrant Behavioral Checklist (ABC-H), a measure of hyperactivity, inattention, and impulsivity, determined their classification into a high ADHD-related symptom group  and a low ADHD-related symptom group . All participants received an intervention with Empowered Brain, where they used smartglasses-based social communication and behavioral modules while interacting with their caregiver. We then calculated caregiver-reported ABC-H scores at 24 and 48 hours after the session.All 8 participants were able to complete the intervention session. Postintervention ABC-H scores were lower for most participants at 24 hours  and for all participants at 48 hours . At 24 hours after the session, average participant ABC-H scores decreased by 54.9% in the high ADHD symptom group and by 20% in the low ADHD symptom group. At 48 hours after the session, ABC-H scores compared with baseline decreased by 56.4% in the high ADHD symptom group and by 66.3% in the low ADHD symptom group.This study provides initial evidence for the possible potential of the Empowered Brain system to reduce ADHD-related symptoms, such as hyperactivity, inattention, and impulsivity, in school-aged children, adolescents, and young adults with ASD. This digital smartglasses intervention can potentially be targeted at a broader array of mental health conditions that exhibit transdiagnostic attentional and social communication deficits, including schizophrenia and bipolar disorder. Further research is required to understand the clinical importance of these observed changes and to conduct longitudinal studies on this intervention with control groups and larger sample sizes. Autism spectrum disorder (ASD) is a lifelong developmental disorder characterized by challenges in social communication and the presence of repetitive behaviors or restricted interests. Many people with ASD experience symptoms of inattention and hyperactivity, and approximately one-third of people with ASD have diagnosable attention-deficit/hyperactivity disorder (ADHD) ,2. ThereThe combination of ASD and ADHD has been linked to greater cognitive impairment ,11, geneIt is therefore important to address ADHD. While the leading approach has been psychopharmacologic medication, people with co-occurring ASD and ADHD have been found to be less likely to receive appropriate treatment for their ADHD  and appeThere has been growing interest in the use of cognitive training in ADHD, a nonpharmacologic approach that may use neurofeedback or novel digital approaches, or both. Recent studies have shown promise ,32, althLittle research has described the impact of digital interventions on people with ASD who demonstrate ADHD symptoms . Some prIn this pilot study, we explored the short-term effect of an Empowered Brain intervention on ADHD symptoms in a group of 8 children, adolescents, and young adults with ASD. We documented caregiver-reported ADHD symptoms as measured by the ABC-H. Further, we discuss the implications of these results on future research in the field.Empowered Brain is a combination of modern smartglasses and educational modules targeting socioemotional and behavioral management skills ,48. SmarFor example, Empowered Brain incorporates the Face2Face module, software that helps guide users to pay attention to socially salient visual stimuli , an affiliate of the Commonwealth of Massachusetts Department of Public Health.We recruited participants through a Web-based research interest form. Written consent was provided by the legal guardians of children and by cognitively abled adults. Participants between 7 and 17 years old provided written assent, when they were able to.We questioned all caregivers of participants as to whether they had a history of ADHD and whether they were currently receiving treatment for ADHD. Additionally, all participants had a baseline ABC-H and Social Communication Questionnaire (SCQ) .The ABC-H is a subscale of the ABC and measures key ADHD symptoms such as inattention, impulsivity, and hyperactivity. The ABC has been extensively used in the developmentally disabled population, and the ABC-H has been used as an outcome measure of studies that have investigated the treatment of ADHD in populations with concurrent ASD -47. In tFollowing these baseline assessments, we stratified the participants into high and low ADHD symptom groups based on their baseline ABC-H score. For the high ADHD group, we chose cutoff scores of 13 for male participants and 8 for female participants. These scores were determined by prior research that recorded the ABC scores for a sample of 666 people with developmental disorders, and found a mean ABC-H score of 13.38 for males and 8.12 for females .Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (DSM-5) [Diagnostic and Statistical Manual of Mental Disorders  specifically excluded a diagnosis of ADHD being made when an individual had a diagnosis of ASD. Therefore, while background information regarding ADHD history is important, we felt the ABC-H to be a more accurate measure of ADHD symptom load to determine the stratification into low and high ADHD symptom groups.Accordingly, we considered males with a score of 13 or higher and females with a score of 8 or higher to have high ADHD symptoms, and those with a lower score, to have low ADHD symptoms. Despite a history of ADHD diagnosis, we used the ABC-H as a stratification method, as it provided a numerical measure of recent (baseline) ADHD symptom burden. This numerical subscale allows for a more quantitative measure of change in rated items. While we obtained a clinical history of ADHD for the participants, the clinical diagnosis of ADHD in ASD is challenging , and it  (DSM-5)  that it All participants had a baseline SCQ  as a valAll participants were accompanied by a caregiver to the testing session. We oriented the participants and their caregivers to Empowered Brain and Google Glass and measured their ability to tolerate wearing the smartglasses. Once the participants showed they were able to wear the smartglasses for at least one minute, the participants were able to use Empowered Brain social communication modules and had a series of gamified experiences while interacting with their caregiver, including using Empowered Brain modules such as Face2Face and Emotion Charades ,Figure 3Individuals who had expressed interest via the website signup but who had a known history of epilepsy or seizure disorder were not enrolled in this study. Users who had any uncontrolled or severe medical or mental health condition that would make participation in the study predictably hazardous were also not eligible for enrollment. We obtained information regarding potential exclusions to this study directly from the caregivers of the participants.A total of 8 children, adolescents, and young adults with ASD signed up to take part in this research . All participants were able to use smartglasses and complete the coaching session. The high ADHD-related symptom group had a similar ASD severity to the low ADHD-related symptom group , but consisted of younger participants . Postintervention ABC-H scores were lower for most participants at 24 hours  and for all participants at 48 hours . At 24 hours after the session, average ABC-H scores decreased by 54.9% in the high ADHD symptom group and by 20.0% in the low ADHD symptom group. At 48 hours after the session, ABC-H scores compared with baseline decreased by 56.4% in the high ADHD symptom group  and by 6The high ADHD-related symptom group consisted of 4 participants who had an average ABC-H score of 25.75 at the start of the study . The lowWe noted that, while the participants in the high ADHD-related symptoms group were younger, they had a similar ASD symptom severity as measured by the SCQ to the low ADHD-related symptom group. It is perhaps not a surprise to find that the high symptom group was younger, given that the ABC-H subscale is weighted toward hyperactivity, and hyperactivity is an ADHD symptom that improves with age .While many people with ASD struggle with symptoms of ADHD, including hyperactivity, impulsivity, and inattention, considerable gaps in knowledge remain in regard to their optimum assessment and management . The comAll participants in this study managed to complete the Empowered Brain intervention session without any reported negative effects, and all participants tolerated using smartglasses for the duration of the testing session. This is important, as a major limiting factor in the use of and continued engagement with assistive technologies is their usability, tolerability, and associated negative effects.Most participants improved their ADHD-related symptoms following the intervention at both 24 hours  and 48 hours  after the session. We noted that 1 participant in the high symptom group had a greater reduction at 24 hours than at 48 hours, and that 1 participant in the low symptom group had an increase in ADHD-related symptoms at 24 hours followed by a large decrease from baseline at 48 hours.Mean participant ABC-H percentage changes showed a significant response in the high ADHD-related symptom group (>25% improvement in ABC-H score) at both 24 (54.9% reduction) and 48 hours (56.4% reduction). The low ADHD-related symptom group appeared to show a response at 48 hours (66.3% reduction), but not at 24 hours (20.0% reduction). While the response of the low ADHD-related symptom group appeared to be of greater magnitude, we, who include subspecialist clinicians, advise caution in assessing the low ADHD-related symptom group, given the low baseline and small absolute score changes. Such results may render the findings in this group as not being as clinically significant as the outcomes associated with the high ADHD-related symptom group. An alternative explanation may also be put forward, and that is that the technology is especially impactful for individuals with a milder ADHD symptom burden. Future larger studies would allow for more robust statistical analysis and conclusions to be made.There are several important limitations to this work that deserve mention. There was no control group, and the number of participants in this pilot study was relatively small (N=8), although this is a sizeable sample relative to other research on novel technologies in ASD, especially in regard to other smartglasses research ,48. WhilWe should certainly consider the potential for an expectancy effect  in usingIt would be useful for future research to incorporate a larger sample size, with more female participants. One can also see the benefit of age-matched neurotypical and ADHD-only controls. While the ABC-H is a very useful scale to use in this context, the use of broader ADHD-related measures would also provide for further insights. Despite our findings, the broader generalizability of our results to the wider ASD population will remain limited until further research is undertaken.We hope that this study can pave the way for more funding and interest to study the potential application of this emerging technology to not just dually diagnosed ADHD and ASD samples, but more broadly to other categorical psychiatric diagnoses that are also associated with both attentional and social communication impairments. Such diagnoses include schizophrenia, bipolar disorder, and anxiety disorder. While deficits in social communication occur across many psychiatric disorders, most digital social communication interventions have been studied in ASD alone . TherefoSmartglasses may have a particularly unique role in this respect, as they also contain a variety of quantitative sensors that are located more closely than any other wearable technology to the main perceptual apparatus of the brain. These sensors can collect and help analyze sensor data to help classify human behavior. This digital phenotyping approach aims to detect changes in affective and behavioral states associated with both improvements and deteriorations in psychiatric disorders, and to help to identify new methods to subtype disorders .Empowered Brain is being developed as a tool that can be used by caregivers, therapists, and educators to deliver socioemotional interventions to users with ASD. It is designed as a tool that can be used on a daily basis for 10 to 20 minutes per intervention. While this study reports on the impact of Empowered Brain on ADHD symptoms after a single intervention, further research is required to understand how the longitudinal use of this technology may affect ADHD symptoms in people with ASD. This technology also has the potential to address the attentional and social communication deficits that are transdiagnostically present across psychiatric disorders. Data collection via sensors that are proximally situated to the principal human perceptual organs may result in a more ecologically valid digital phenotyping approach. This digital phenotyping approach may aid the research of proposed developmental subtypes of a distinct ASD-ADHD combination disorder and, more broadly, psychiatric and brain injury-related disorders.Empowered Brain is a smartglasses-based social communication intervention that has been previously shown to improve social communication functioning in ASD. This study provides early evidence for the possible potential of Empowered Brain to reduce ADHD symptoms, such as hyperactivity, inattention, and impulsivity, in school-aged children, adolescents, and young adults with ASD. Our results also suggest that, despite concerns about increased distraction and reduced attentiveness, the Empowered Brain did not result in any increased ADHD symptoms in any of the participants at 48 hours after the intervention.


A single-nucleotide polymorphism (SNP) of the XKR4 gene has been linked to Attention-Deficit/Hyperactivity Disorder (ADHD). This gene is preferentially expressed in cerebellum, a brain structure implicated in this disorder. This study investigated the effects of this SNP on cerebellar development in children with and without ADHD. We collected 279 longitudinal T1-weighted structural images and DNA from 58 children with ADHD and 64 typically developing (TD) children matched for age, IQ, and gender. Groups were divided by the XKR4 rs2939678 SNP into A-allele carriers versus subjects homozygous for the G-allele. Cerebellar lobular volumes were segmented into 35 regions of interest using MAGeTBrain, an automated multi-atlas segmentation pipeline for anatomical MRI, and statistically analyzed using linear mixed models. We found decreased gray matter (GM) volumes in ADHD compared to TD children in bilateral lobules VIIIA, left VIIIB, right VIIB, and vermis VI. Furthermore, we found a linear age by gene interaction in left lobule VIIB where subjects homozygous for the G-allele showed a decrease in volume over time compared to A-allele carriers. We further found quadratic age × gene and age × diagnosis interactions in left lobule IV. Subjects homozygous for the G-allele (the genotype overtransmitted in ADHD) showed more suppressed, almost flat quadratic growth curves compared to A-allele carriers, similar to individuals with ADHD compared to controls. However, there was no interaction between genotype and diagnosis, suggesting that any effects of this SNP on cerebellar development are not specific to the disorder. Neuroimaging studies have implicated the cerebellum in Attention-Deficit/Hyperactivity Disorder (ADHD). However, findings have been inconsistent  and few Although not all studies of cerebellum volume in ADHD have been consistent, several cerebellar regions have been implicated multiple times in the disorder. Early studies reported smaller total cerebellar volume in children and adolescents with ADHD compared to their typically developing (TD) peers , as wellIn this study, we set out to investigate whether our previous findings of XKR4 gene effects on the cerebellum were regionally specific, stable over development and, particularly, related to ADHD diagnosis. We assessed the XKR4 rs2939678 SNP and measured regional cerebellar volumes in a longitudinal sample and ran mixed model regression analyses to investigate the effect of the SNP associated with ADHD on cerebellar development. We hypothesized that the associated polymorphism of XKR4 and diagnosis would both be associated with reduced volume, specifically in previously implicated areas, that changes would be stable over development and that there would be an interaction between genotype and diagnosis, where gene effects were greatest for those individuals affected by the disorder.The Medical Ethical Review Board of the University Medical Center Utrecht approved the study and its procedures.Table 1). Written consent was obtained from the parents with full knowledge of the purpose and procedure of the study and children provided written or verbal assent. To confirm inclusion criteria, the DISC-IV parent version (Table 1).One hundred and twenty-two children (64 TD and 58 children with ADHD) participated in this study from a larger ongoing longitudinal cohort for whom DAT1 and DRD4 had previously been determined . Groups  version  was admi version  for a di version  was usedFigure 1). Eighty-one children contributed at least a single follow-up scans , 51 had a third scan , and 25 had a fourth scan .There were a total of 279 scans available from these 122 children  or 160–180 1.2-mm contiguous coronal slices  with echo time (TE) 4.6 ms; repetition time (TR) 30 ms; flip angle 30°; field of view (FOV) 256 mm; in-plane voxel size 1 mm × 1 mm.1, an automated multi-atlas segmentation pipeline for anatomical MRI. Technical details of the segmentation can be found elsewhere  Full interaction between diagnosis, genotype and age, (2) a simpler model with two-way interactions terms and, (3) the simplest model including only main effects. The three models were then compared using the Akaike Information Criterion (AIC) to find the model fit that explained the most variance while reducing the number of parameters. In each model, gender and slice thickness were entered as covariates. The interrelated nature of the measures means that traditional methods for correcting for multiple comparisons, such as a Bonferroni correction, are overly stringent for this type of study and there is debate in the literature on how to deal with this issue. In this paper, we chose to not apply any correction, given that our main hypothesis was not confirmed even without correction for multiple comparisons. Lastly, we tested for differences in demographic indices using χ2 and 4-group ANOVA where appropriate.The best fit model for each lobule was determined in two steps. First, cubic, quadratic and linear age effects were fit for each lobule using a stepwise approach, where we stepped down to the quadratic model if the cubic model was not significant at p = 0.55), IQ (p = 0.76), gender  and slice-thickness .At baseline, groups were matched for age , where children with ADHD showed decreased volume compared to TD controls: in bilateral lobules VIIIA , left VIIIB (p = 0.013), right VIIB (p = 0.018), and vermis VI (0.024). There were no main effects of genotype. We did find an interaction between genotype and age in left lobule VIIB  and one between genotype and quadratic growth in left lobule IV . In this last area, there was also an interaction between diagnostic group and quadratic growth . There were no interactions between genotype and diagnosis. Nor were there any three-way interactions.There was a main effect of diagnosis in five areas . Furthermore, the sample size at follow-up was also limited due to attrition. This may have led to null findings for some of the higher order interactions. We also note that multiple comparison correction that was not applied in the current study and therefore suggest a need for future replication. Lastly, we suggest future studies examine whether XKR4 expression may influence ADHD development in the cortex.There are some limitations to our current study. We note that the sample size of the A-allele carrier groups at baseline was relatively small (In summary, we found decreased GM volume in several posterior lobules of the cerebellum associated with ADHD, similar to earlier studies. We found no evidence of main effects of XKR4 genotype on cerebellar volumes, and only limited effects on regional developmental trajectories. Furthermore, there were no interactions between genotype and diagnosis. In all, these findings suggest that any changes in cerebellum associated with ADHD are not due to effects of XKR4 genotype on cerebellar structure.All authors of this manuscript contributed substantially to the scientific process and the writing of the paper. Their contribution included the conception and design of the project, the running of the study, as well as the analysis and interpretation of data. In addition, all authors substantially contributed to either drafting or critically revising the manuscript for important intellectual content and state that they are entirely responsible for the scientific content of this paper.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.


Drosophila innate immune response. One of them, the Immune Deficiency (IMD) pathway, is under a very tight negative control. Although molecular brakes exist at each step of this signaling module from ligand availability to transcriptional regulation, it remains unknown whether repressors act in the same cells or tissues and if not, what is rationale behind this spatial specificity. We show here that the negative regulator of IMD pathway PGRP-LF is epressed in ectodermal derivatives. We provide evidence that, in the absence of any immune elicitor, PGRP-LF loss-of-function mutants, display a constitutive NF-κB/IMD activation specifically in ectodermal tissues leading to genitalia and tergite malformations. In agreement with previous data showing that proper development of these structures requires induction of apoptosis, we show that ectopic activation of NF-κB/IMD signaling leads to apoptosis inhibition in both genitalia and tergite primordia. We demonstrate that NF-κB/IMD signaling antagonizes apoptosis by up-regulating expression of the anti-apoptotic protein Diap1. Altogether these results show that, in the complete absence of infection, the negative regulation of NF-κB/IMD pathway by PGRP-LF is crucial to ensure proper induction of apoptosis and consequently normal fly development. These results highlight that IMD pathway regulation is controlled independently in different tissues, probably reflecting the different roles of this signaling cascade in both developmental and immune processes.NF-κB pathways are key signaling cascades of the  Drosophila innate immunity negative regulator PGRP-LF, is specifically expressed in non-immune tissues and plays an essential role during development, in absence of any infection. Lack of PGRP-LF function in these tissues inhibits apoptosis leading to incomplete genitalia rotation and tergite malformations. We show that such apoptosis inhibition results from the over expression of the negative regulator of apoptosis Diap1 specifically in PGRP-LF expressing cells. Our data highlight that proper negative regulation of immune signaling pathway in non-immune tissues is contributing to normal development and illustrate the growing evidence of the dual role of immune signaling pathway contribution to both immunity and in development processes.In multicellular organism such as mammals or insects, activation of innate immune responses occurs following detection of microbes by dedicated receptors called pattern recognition receptors. Such immune activation is taking place in immune competent tissue such as the skin, the digestive and respiratory epithelia and is under a tight negative control. Negative control is essential to finely adjust the duration and the intensity of the immune response to the level of infection. We found that the  Drosophila, bacteria infection triggers NF-κB cascades ) leading to the production of immune effectors and regulators . T. TDrosopgulators . The IMDgulators –10. Recegulators . These igulators –14. Thisgulators . Indeed,gulators –19. The gulators . Throughgulators –23 [24–2gulators . Some ofgulators . The numgulators , 28–31. gulators . This trgulators , 33. Plagulators . IMD patgulators , 35–40. ife span , 40. ImpAlthough IMD pathway is controlled at multiple levels along the cascade, the rationale behind this complex and multilayered regulation is not fully understood. It remains to be known whether this regulation is tissue specific and if yes, what are the consequences of IMD activation in each tissue. Our results show that PGRP-LF is expressed in ectodermal derivatives some of them with no known immune function. Phenotypic analysis of a newly generated PGRP-LF protein null allele demonstrates that its function is required for the formation of various epidermal derived adult structures. We showed that PGRP-LF's role in controlling developmental process is, like for the immune ones, mediated by a repression of the IMD pathway. Our results demonstrate that, in contrast to what has been shown in other tissues, IMD pathway activation in epidermal structures is blocking rather than triggering apoptosis. By preventing such IMD mediated anti-apoptotic signal, PGRP-LF is allowing normal development to take place. These results speak for the importance of a tissue specific regulation of NF-κB pathway in flies and for a strong link between immune and developmental processes.PGRP-LFGal4) in which 1.4 Kb of genomic DNA 5’ of the PGRP-LF coding region  and low levels in the fat body and in the midgut (when compared to foregut and hindgut), in accordance with FlyAtlas data BSC113 flies showed a strong constitutive expression of AttacinD in most ectodermal larval derivatives  genes transcription is differently regulated in different tissues  hatching as adults [PGRP-LFKO male escapers displayed defects in male genitalia orientation  or genitalia  was used  and the outer ring of cells of the A8 abdominal segment , both being cells in which induction of apoptosis is essential for proper development. Altogether, these results demonstrate that PGRP-LF function is needed, in the absence of bacterial infection, to prevent constitutive activation of IMD pathway in ectoderm, which will otherwise provoke developmental defects.The s adults . All aduentation . Theses ritories . To test mutants . Similar mutants . This suenitalia . Only onwas used . These lDrice, or overexpression of the apoptosis inhibitors P35 or Diap1 in tergite and genitalia anlage, give rise to adult flies presenting cuticle midline and genitalia rotation defects [PGRP-LF mutant phenotypes are due to apoptosis inhibition in ectodermal anlage, we overexpressed P35 in PGRP-LF expression domain. PGRP-LFGal4, UAS-P35 flies fully phenocopied PGRP-LF mutants. Although, such phenotypes were not observed with a weaker PGRP-LFGal4 driver, it occurred in flies heterozygous for the PGRP-LFKO allele  undergo caspase-dependent apoptosis and are progressively replaced by histoblasts that expand as the LECs die. Inhibition of apoptosis in LECs by P35 overexpression or by Drice inactivation  or PGRP-LFGal4 drivers was sufficient to mimic both cuticle and genitalia defects  has been shown to be sufficient for its activation and hence for IMD pathway triggering, endogenous proteases are good candidate for such PGRP-LC bacteria independent activators , 55. ConPGRP-LFKO mutant that we have generated is sublethal with few escapers showing tergites and genitalia defects but normal wings. We have demonstrated that these developmental defects are likely due to an apoptosis blockage. The previously characterized PGRP-LF200allele did not present cuticle and genitalia defects but had wing notchings that were also observed by reducing PGRP-LF levels via RNAi in wing imaginal discs. These defects were associated with ectopic activation of the JNK pathway and increased apoptosis. To try to explain these discrepancies, we have characterized the PGRP-LF200 allele that was obtained by P element mobilization. Our results show that if the PGRP-LF200allele has lost the white cDNA that serves as an eye marker for the P-element, it has kept some of the P element sequence 5’ to PGRP-LF coding region that might interfere with neighboring gene expression  or some domains only (RNAi to PGRP-LF) give rise to different phenotypes.The pression . Q-RT-PCal discs . This miGal4weak (this work), PGRP-LFGal4strong (this work), PGRP-LCGal4 (this work), UAS-nlsGFP BL#4775, UAS-myr-mRFP BL#7118, DdcGal4 BL#7010, AbdBLDNGal4 BL#55848, FngGal4 BL#9891, apmd544Gal4 BL#3041, enGal4, UAS-RFP BL#30557, Act5CGal4 BL#25374, UAS-mcd8CherryRFP BL#27392; AttacinD-Cherry (this work), Diptericin-Cherry [Gal4 DGRC#103634, His2Av-mRFP BL#23651, imdshadok [112 [ΔE12 [88c03881 [D55 [2c7c [E20 [EY0073 [KO [Prev1BL#63814, DriceΔ1 [The following strains were used in this work: PGRP-LFn-Cherry , Diap1-Gn-Cherry , hid5’F-12 [ΔE12 , dMyd88c88c03881 , DreddD555 [2c7c , RelishE [EY0073 , PGRP-LB0073 [KO , dTak1 [0073 [KO , Dcp-1Pr DriceΔ1 , UAS-P35PGRP-LFKO line was generated by homologous recombination. The PGRP-LF gene was replaced by a mini-white gene. DNA flanking the 5’ and 3’ ends used were respectively, 2,914 bp and 3,060 bp for PGRP-LF locus. Sequences were cloned in the pW25 vector [5 vector .Larval, pupal or adult tissues were dissected in PBS, fixed for 20 min in 4% paraformaldehyde on ice and rinse 3 times in PBT (PBS + 0.1% Triton X-100). For antibody staining on pupal cases, cleaved anti-Dcp-1 antibody  was used at 1:200. The tissues were mounted in Vectashield (Vector Laboratories) fluorescent mounting medium, with or without DAPI. Images were captured with either a Stereo Discovery V12 microscope or a LSM 780 Zeiss confocal microscope.Staged pupae (24 hours APF) were washed in water and mounted on a glass slide using a drop of silicon grease (Dow corning). The pupal case covering the caudal part of the abdomen was removed. A very wet filter paper was placed around the pupae to keep them hydrated. The pupae were covered with a cover glass in a small drop of water to avoid desiccation. High-vacuum silicone grease (Dow Corning) was also used to seal the chamber. In most cases, the animal survived the data acquisition and developed into an adult. Time-lapse images were captured using a Nikon Macroconfocal AZ100.RNA from whole larvae or dissected organs (n = 30) was extracted with RNeasy Mini Kit . Quantitative real-time PCR, TaqMan, and SYBR Green analysis were performed as previously described . PrimersErwinia carotovora carotovora 15 2141 (Ecc) cultured in Luria-Bertani medium at 30°C overnight. Bacterial cultures were centrifuged at 2500 g for 15 min at RT and resuspended in fresh Luria-Bertani medium. Cells were serially diluted in PBS and their concentration was determined by optical density (OD) measurement at 600 nm. For oral infection, flies were first incubated 2 hr at 29°C in empty vials and then placed in a fly vial with food. The food solution was obtained by mixing a pellet of an overnight culture of bacteria Ecc-15 (OD = 200) with a solution of 5% sucrose (50/50) and added to a filter disk that completely covered the agar surface of the fly vial. Septic injuries were performed by pricking adult females with a thin needle contaminated with Ecc-15.The bacterial strain used was Ecc (OD = 200) 5% sucrose (50/50). For septic injuries, adult females were pricked once with a thin needle contaminated with Ecc. At least two tubes of 20 flies were used for each survival assay and three replicates of this experiment were done. Survival was scored several times a day.For oral infections, adult flies were infected every 2 days with a solution of S1 FigPGRP-LF locus and of the PGRP-LF200 and PGRP-LFKO mutants. The gene map was adapted from FlyBase. The deleted segment in PGRP-LFKO that was replaced by the mini-white gene is indicated. The deletion in PGRP-LFKO starts at position 3L: 9,350,539 and ends at position 3L: 9,349,489. The PGRP-LF200 mutant was obtained by P-element mobilisation and screening for the loss of the white eye marker [PGRP-LF200 mutants (B) Relative gene expression of PGRP-LF, PGRP-LC and Diptericin mRNA in PGRP-LF200 and PGRP-LFKO mutants compared to controls. For (B), histograms correspond to the mean value ± SD of three independent experiments. Values indicated by symbols (*) are statistically significant . ns: not significantly different.(A) Schematic representation of the e marker . Sequenc(TIF)Click here for additional data file.S2 FigPGRP-LFGal4strong, UAS-nlsGFP and PGRP-LFGal4weak, UAS-nlsGFP larvae showing GFP expression in salivary glands, foregut, hindgut and cuticle and to a lesser extend in fat body. (B) mRNA enrichment values from Rp49, PGRP-LF and PGRP-LC in third instar larvae tissues. Data are from FlyAtlas. (C) A) PGRP-LCGal4, UAS-nlsGFP larvae showing GFP expression in trachea, foregut, hindgut and cuticle.(A) (TIF)Click here for additional data file.S3 Fig(A) Relative gene expression of PGRP-LC, UGP and PGRP-LF in PGRP-LFKO. (B) PGRP-LC mRNA expression in flies mutants for PGRP-LF and IMD pathway components. Histograms correspond to the mean value ± SD of three independent experiments. Values indicated by symbols (*) are statistically significant . ns: not significantly different.(TIF)Click here for additional data file.S4 FigPGRP-LF mutant larvae. Ectopic Diptericin-Cherry and Drosomycin-GFP expression are detected in the trachea and cuticle (Dipt-Cherry only) of PGRP-LF mutant larvae (either PGRP-LFKO or PGRP-LFKO/Df(3L)BSC113). (B) Ectopic expression of AttacinD-Cherry is detected in PGRP-LFGal4; UAS-nlsGFP expressing tissues of PGRP-LFKO mutant larvae. (C) Overexpression of Drosomycin-GFP expression in the trachea is suppressed in DreddD55; PGRP-LFKO double mutant larvae.(A) Overexpression of AMP reporter genes in (TIF)Click here for additional data file.S5 FigDiptericin expression, 24h after Ecc oral infection. PGRP-LF inactivation by RNAi  modifies IMD pathway inducibility in the fat body of Ecc orally infected flies as observed following complete inactivation of PGRP-LF in PGRP-LFKO/Df(3L)BSC113 flies. mRNA level in controls was set to 1, and values obtained with indicated genotypes were expressed as a fold of this value. Histograms correspond to the mean value ± SD of three independent experiments. Values indicated by symbols (*) are statistically significant . ns: not significantly different.Fat body IMD pathway activation, monitored by (TIF)Click here for additional data file.S6 Fig(A) Magnification of the pictures shown in (TIF)Click here for additional data file.S7 FigIMD in LECs with Ddc-Gal4 prevents normal dorsal epidermis fusion (arrow). Abnormal male genitalia orientation in flies overexpressing (3) P35, (4) IMD or (5) PGRP-LCa in AbdB expressing cells (white bar). Abnormal genitalia rotation and incomplete epidermis differentiation are both observed in PGRP-LFGal4strong/ UAS-IMD or PGRP-LFGal4strong/ UAS-PGRP-LCa flies. (B) Abdomen from adults overexpressing P35 under the control of (1) PGRP-LFGal4strong or (2 and 3) PGRP-LFGal4weak drivers. Incomplete fusion of dorsal epidermis and abnormal genitalia rotation are observed with PGRP-LFGal4strong or with PGRP-LFGal4weak when flies lack one copy of PGRP-LF gene. (C) Abdomen from adults overexpressing Diap1 under the control of (1 and 2) PGRP-LFGal4strong or (3 and 4) Act5CGal4 drivers. (D) Lateral views of PGRP-LFKO pupal cases expressing PGRP-LFGal4; UAS-nlsGFP and AttacinD-Cherry 24h APF. PGRP-LFGal4 and AttacinD-Cherry expression are both restricted to LECs and absent from histoblasts. The dashed lines indicate the boundary between the histoblasts and LECs.(A-C) Dorsal (d) and ventral (v) views of male or female adult abdomen showing incomplete epidermis differentiation (white arrow) and abnormal male genitalia orientation (white bar). (A) 1, 2: Overexpression of (TIF)Click here for additional data file.S8 FigDiap1-GFP4.3; PGRP-LFGal4, UAS-mcd8CherryRFP (A) or Diap1-GFP4.3; PGRP-LCGal4, UAS-mcd8-CherryRFP (B) third instar larvae or pupae 24h APF. (A) PGRP-LFGal4 is expressed in almost all dorsal LECs except in cells expressing strongly Diap1-GFP4.3 (arrows in A). (B) PGRP-LCGal4 is expressed in some dorsal LECs and is co-expressed with cells expressing strongly Diap1-GFP4.3 (arrows in B).Dorsal view of (TIF)Click here for additional data file.S9 FigDiap1-GFP4.3 in PGRP-LF mutant tissue when compared to controls. The dashed lines indicate the periphery of the control tissues. (B) Diap1-GFP4.3 is ectopically expressed in ectodermal derivatives of the larval gut of PGRP-LF mutants. Both the foregut (arrow) and the hindgut enterocytes (arrow head) express Diap1-GFP4.3 in PGRP-LF mutants compare to controls.(A) Confocal images of dissected larval trachea and hindgut showing enhanced expression of (TIF)Click here for additional data file.S10 FigHid-GFP expression is not induced in cells overexpressing IMD. Dorsal epidermis (A) and fat body (B) of enGal4, UAS-RFP/+ (control) or enGal4, UAS-RFP/+; UAS-IMD/+ (UAS-IMD) larvae are shown. In both LECs and fat body cells, expressing IMD do not induce expression of Diap1-GFP4.3 while in LECs p53 overexpression does (arrows). (C) ReaperGal4; UAS-nlsGFP expression is not ectopically expressed in LECs from third instar PGRP-LF mutant larvae.(TIF)Click here for additional data file.S11 FigIMD in the dorsal part of the wing pouch using apGal4 driver induces wing bubbles, a phenotype that is not suppressed by co-expression of the anti-apoptotic protein P35.Adult wings from 5d old males of indicated genotype. Overexpression of (TIF)Click here for additional data file.S1 TableGenetic interactions showing that lethality due to IMD gain-of-function is not suppressed, but rather enhanced, when apoptosis is blocked.(TIF)Click here for additional data file.