Objective: Attention-deficit hyperactivity disorder (ADHD) is common in adulthood, and it is associated with different high- risk behaviors, particularly substance use. Evidence suggests a high prevalence of ADHD in adults who take methamphetamine (METH). This study aimed at comparing functional level, quality of life, and psychiatric comorbidities in METH users with and without adult ADHD (A-ADHD).Method: In this cross-sectional study, 134 patients who had a history of METH use (at least once in lifetime) were selected from among inpatient and outpatient referrals to a psychiatric hospital. DIVA was performed for those who were positive on the Conners' Adult ADHD Rating Scales–Self-Report-Screening Version (CAARS-SR-SV). The Global Assessment of Functioning (GAF) and World Health Organization Quality of Life Scale-Brief (WHOQoL-BREF) were used to assess the participants’ level of functioning and quality of life, respectively. Psychiatric comorbidities including substance use disorders were evaluated using the Structured Clinical Interview for DSM-IV-Axis I (SCID-I). Results: Among the METH users, 10.4% were diagnosed as having A-ADHD. A-ADHD was more prevalent among female METH users than males. The hyperactive-impulsive and combined types were more common than the inattentive type. Opiates and cannabis were the most commonly abused drugs by the 2 groups, while sedative-hypnotic use was significantly higher in the individuals with A-ADHD. Substance-induced mood disorder was the most prevalent comorbidity in the 2 groups and was higher in those with A-ADHD. quality of life and the GAF scores were significantly lower in those with A-ADHD and duration of METH use was higher Compared to the METH users without A-ADHD, (p>0.05).Conclusion: This study provided some preliminary findings supporting the prevalence of Adult ADHD among METH users and its negative impacts on their global functioning and quality of life. To provide more effective intervention for METH users, detection and treatment of those with A-ADHD can be of clinical value. Attention-deficit hyperactivity disorder (ADHD) is a common and disabling mental health problem in adults, with a reported prevalence of up to 5% in the general population . ApproxiAdult ADHD (A-ADHD) is associated with a substantially higher risk of a lifetime history of nicotine or illicit drug use .The higher rate of comorbid substance use with A-ADHD has been due to some shared genetic components , or sharabuse , 7. SomePsychostimulants are among the first-line medications of choice. However, there is an important controversy regarding the stimulant use for adult ADHD in substance-abusing populations. While some authors are concerned about the risk of psychostimulant medication abuse and dependence, methylphenidate has shown to be effective in decrease of substance use, recurrence, and craving . However One important predictor of disability, which is commonly comorbid with METH use, is ADHD . ExistinParticipants and ProcedureThis cross-sectional study was conducted among all outpatients or admitted referrals to Roozbeh psychiatric hospital in Tehran from June 2015 to October 2016. The participants were 18 to 65-year-olds who reported a history of at least one-time METH use in their lifetime. They were not included if they had any cognitive disorders  or intellectual disability. In case of acute intoxication or withdrawal of substances or delirium, the assessments were postponed to a later time when the participant was ready to cooperate with the study assessments. A board-certified psychiatrist evaluated the psychiatric diagnoses of all participants including substance use problems. Then, to screen ADHD symptoms, confirm the diagnosis, and check comorbidities, the patients were referred for further clinical evaluation using the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID I). The participants filled the Conner’s Adult ADHD Rating Scale Self-report- Screening Version. For those who had the score of 55 or higher, the semi-structured Diagnostic Interview for Adult ADHD (DIVA) was performed by a trained resident of psychiatry to check if the criteria of A-ADHD were fulfilled. To ensure the accuracy of information, if any of the family members were available, they were asked to come to the hospital and answer the questions of the DIVA interview. The patients were asked to complete the World Health Organization Quality of Life Scale-Brief (WHOQOL BREF) to assess their quality of life. The Global Assessment of Functioning (GAF) was also used to rate the level of general functioning.This study was approved by the ethical committee of Tehran University of Medical Sciences. The aims and process were introduced and informed consent was obtained from all participants. The study did not intervene on the medication or non-pharmacologic treatments being provided to the participants. The participants were allowed to quit the study whenever they wanted.InstrumentsConner’s Adult ADHD Rating Scale- Self-report: Screening Version (CAARS-SR-SV) The CAARS-S: S provides a useful dimensional evaluation system for both research and clinical use . It is aStructured Clinical Interview for DSM-IV Axis I Disorders (SCID I)The SCID-I is a widely used semi-structured diagnostic interview to assess the presence of mental disorders based on DSM-IV criteria for axis I disorders. It was first developed after the publication of DSM-III and was then updated according to DSM-IV and DSM-5. The interview takes approximately 1 hour to complete . SharifiGlobal Assessment of Functioning (GAF)The GAF was first introduced in 1987 to rate Axis V of the DSM-IV and describes symptoms and functioning. GAF is a 100-point scale, with 10-point intervals. The most severely poor functioning patient is described with 1 to 10 and the healthiest with the score interval of 91 to 100.Diagnostic Interview for Adult ADHD (DIVA)DIVA is a semi-structured diagnostic interview to assess adult ADHD and provides a thorough evaluation based on the diagnostic criteria of DSM-IV-TR. The DIVA has 2 parts: the first part deals with the core symptoms using a list of concrete and realistic examples for each criterion and the second part deals with the functional impairment due to symptoms in 5 areas. DIVA has been reported to be a reliable diagnostic tool for clinical and research purposes . The PerWorld Health Organization Quality of Life Scale-Brief (WHOQOL BREF)The WHOQOL BREF is a 26-item questionnaire extracted from the 100-item World Health Organization Quality of Life Scale. It requires 10 minutes to administer and assesses 4 domains of quality of life. Each item is scored on a 5-point Likert Scale, from 1  to 5 . The WHOQOL-BRIEF has been validated in the general population and also in various patient groups including smokers and alcoholics . Nedjat Statistical AnalysisDescriptive statistics were expressed in mean and standard deviation or percentages as appropriate. Differences in characteristics between participants were assessed by t tests. Prevalence of AADHD, its subtypes, and other Axis I disorders were estimated for the total sample and for each gender separately; moreover, gender differences were tested by exact chi- square test. Regression analyses were used to investigate associations with the patterns of substance use. Also, Pearson correlation was applied to consider the association of quality of life and other variables. P-values were considered significant at the level of p < 0.05. Data were analyzed using IBM SPSS Statistics 21.0 software.A total of 134 patients , with the mean age of 34.89(SD = 8.41) years, were enrolled in the study. Among them, 10.4% had been diagnosed as A-ADHD. Hyperactive-impulsive, combined, and inattentive presentation were found in 35.7%, 35.7%, and 28.5% of the participants, respectively. No significant differences were found between the groups in age, gender, education level, occupation, and marital status although the rate of A-ADHD in females was higher than in males . Among tOf those with A-ADHD, 50% had more than 3 comorbid disorders, while half of the other group had only 2 concurrent disorders. Rate of comorbidity in all participants was 0 in 1.5%, 1 in 23.1%, 2 in 35.8%, 3 in 27.6%, 4 in 9.7%, and 5 in 2.2%. The most common disorders were substance- induced mood disorders, mood disorders, psychotic disorders, and substance- induced psychotic disorders. Substance- induced mood disorder was more common in participants with A-ADHD. Almost all  the participants met the criteria for at least one other Axis I disorder . In global functioning, those with A-ADHD obtained lower scores on the GAF scale than those without A-ADHD although the difference was not significant. Moreover, 50% of all participants had the GAF score of lower than 20 to 30.Finally, we did not find any significant difference between those with and without A-ADHD in WHOQOL scores . WHOQOL The present study was conducted to evaluate the prevalence of adult ADHD (A-ADHD) in methamphetamine (METH) users and compare global functioning, quality of life, and comorbidities in those with and without A-ADHD.We found the prevalence rate of A-ADHD to be as high as 10.4% among METH users. This rate was up to 3 times higher than in Iranian general population; Arabgol et al. showed that 3.7% of Iranian university students were diagnosed as A-ADHD . HoweverThe rate of A-ADHD among females with METH use was insignificantly higher than in males in the recent study. Disney et al. reported the higher odds ratio for nicotine and cannabis dependence in ADHD-affected girls than in ADHD-affected boys . We found higher rates of divorce and separation among the participants with A- ADHD, a fact consistent with preceding findings , 30. ThiAge of first substance use was the same in our participants, both with and without A-ADHD, while age of diagnosis of substance dependence correlated with the presence of A-ADHD and higher percentage of the individuals with A-ADHD (92.8% vs. 75.9%) met the criteria for substance dependence. Some previous studies reported that the first age of substance use was not different in groups with and without A-ADHD, however, those with A-ADHD started regular substance use at a younger age and had higher probability of substance dependence and shorter intervals between the age of first use and the age of diagnosis of abuse or dependence . NonetheBeiderman et al. reported that cannabis was the most common substance in individuals with ADHD . There aThe higher rate of concurrent comorbid disorders among those who suffered from A-ADHD was consistent with previous studies, showing higher rates of concurrent psychopathology , 33. SubPrevious studies reported lower GAF scores in patients with A-ADHD than those without it . In thislower scores in GAF and each of 4 domains of quality of life were found in those with A-ADHD. Sedative-hypnotics use decreased psychic and physical quality of life; with increasing first age of METH and sedative-hypnotics use, physical quality of life reduced. Unexpectedly, cocaine use was associated with improvement in physical quality of life, but cocaine use in those participants was transient and brief (no history of abuse or dependency was detected). However, to explain these findings, additional studies are needed. Higher percentage of persons with a history of physical disorders in those with A -ADHD in comparison to non A-ADHD group confirms that common health problems and diseases in adults with ADHD can also affect their quality of life. Our findings showed that environmental quality of life in single and married individuals was higher than in divorced or separated participants and in males was superior to females. Difference in all subscales of Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q) in patients with ADHD has been already shown and represents low quality of life in participants with A-ADHD .This was one of the limited studies on A-ADHD in METH users, while most studies have been conducted on the METH use in adults with ADHD. There are possible reasons for different findings in our study including different types of instruments used for A-ADHD evaluation, sample size, and methods of sample recruitment in different studies. We used both self-report questionnaire and structured interview to check the psychiatric diagnoses, while in some research the diagnosis was made by screening measures. However, the findings should be considered in light of some limitations. First, the participants were selected from a tertiary hospital whose referrals come from different regions of the city and even the country with diverse psychosocial background and ethnicities. They usually suffered from more severe psychiatric disorders and higher rate of comorbidities, and this might lead to selection bias and might also limit the generalizability of our findings. Second, self-report measurements of quality of life may be subject to bias. Third, the statistical analysis might have been affected by the small number of individuals with A-ADHD among the participants, which led to an unbalanced distribution of sample size. Finally, the predominance of male participants in the study may hinder the generalizability of the findings.This study supports the fact that ADHD in adults can affect their tendency to use illegal drugs and substances. A-ADHD also appears to play an important role in METH-use associated disability including declines in quality of life and global function level. Moreover, it increases the rate of concomitant psychiatric disorders. Targeted ADHD screening and treatment can help improve real world outcomes for individuals with METH use disorders.


This study aimed at assessing the prevalence of eating disorders (EDs) and ED symptomatology in children with obesity, and at investigating whether EDs occur more often among individuals with a comorbid attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Seventy-six children  were recruited at an outpatient obesity clinic. The adolescents completed ED instruments including The Eating Disorder Examination Questionnaire (EDE-Q) and The Eating Disorder Inventory for children (EDI-C). The parents of all participants were interviewed regarding the child’s psychiatric morbidity. Diagnoses of ADHD and ASD were collected from medical records. Anthropometric data were compiled. Eight participants (11%) fulfilled the criteria for a probable ED and 16 participants (21%) had ADHD and/or ASD. Two adolescent girls had a probable ED and coexistent ADHD and ASD. No other overlaps between EDs and ADHD/ASD were observed. Loss of control (LOC) eating was present in 26 out of 40 (65%) adolescents, seven of whom had ADHD, ASD or both. LOC eating was not overrepresented among teenagers with ADHD and/or ASD. Weight and shape concerns were on a par with age-matched adolescents with EDs. EDs and ED behavior are more common among children/adolescents with obesity than in the general population. There is no substantial overlap between EDs and ADHD/ASD in adolescents with obesity. Loss of control (LOC) eating is overrepresented in overweight/obese children;Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder are more prevalent in children and adolescents with obesity than in peers without obesity;Both LOC eating and ADHD are conditions characterized by impulsivity.What is already known about this subject:Eating disorders with a binge eating symptomatology were overrepresented among children and adolescents with obesity;The majority of adolescents with obesity had weight and shape concerns in parity with adolescents with eating disorders;Two thirds of the adolescents with obesity reported concurrent LOC eating, regardless of whether or not they met the criteria for ADHD or autism.What this study adds:Obesity in children, adolescents and adults is perhaps the most salient global health problem of our time. The number of children and adolescents worldwide with obesity was estimated to be 110 million in 2013, and the age-standardized prevalence was 5% among children, with much higher numbers in some countries (range 2%–30%) [According to the fifth edition of the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental disorders DSM-5) , the ons , the onApart from EDs, other psychiatric disorders and symptoms can contribute to the development of overweight and obesity in childhood. Attention-deficit/hyperactivity disorder (ADHD), a psychiatric disorder characterized by symptoms of inattention, impulsivity and hyperactivity with childhood onset, has been found to be a risk factor for obesity in both children ,7 and adADHD is characterized by impulsive behavior. BED and LOC eating also exhibit a lack of inhibition . AccordiThe population of children and adolescents with autism spectrum disorder (ASD) shows an overrepresentation of extremely high body mass index (BMI) . Weight At the Obesity Center at the Queen Silvia Children’s Hospital in Gothenburg, Sweden, we examined 76 children and adolescents with obesity regarding EDs and associated cognitive and behavioral symptoms. A previous publication based on the same sample indicated that a variety of neurodevelopmental disorders—ADHD and ASD, in particular—are prevalent in children with obesity [Seventy-six children and adolescents (37 girls and 39 boys) were recruited at the Obesity Center at the Queen Silvia Children’s Hospital in Gothenburg, Sweden. In accordance with the inclusion criteria, the participating children had all been recently referred to the unit, were 5–18 years old and both the parents and the patient were fluent in Swedish. In total, 134 children and adolescents were invited to participate in the study and 58 declined participation. Those who declined differed from those who took part only in terms of fasting glucose levels, where those who declined had statistically significantly higher levels [Two ED instruments, the Eating Disorder Examination Questionnaire (EDE-Q)  and the The Eating Disorder Examination Questionnaire (EDE-Q) is a self-report questionnaire, which consists of 36 items and generates the four subscales, “Dietary restraint”, “Eating concern”, “Shape concern” and “Weight concern” . Items mThe Eating Disorder Inventory for children (EDI-C) , a self-The Development and Well-Being Assessment (DAWBA)  was usedThe neurodevelopmental disorders of ADHD and ASD were assigned based either on medical records or the DAWBA (only pertaining to ADHD) .The study was approved by the regional ethical review board in Gothenburg, Sweden (718-09). Written informed consent was obtained from both children and parents.2 tests (including Fisher’s exact test and continuity correction) were used to compare categorical data, including (1) EDs in individuals with and without ADHD/ASD; (2) LOC eating in individuals with and without ADHD/ASD; (3) depression in individuals with and without EDs, and (4) LOC eating in males and females. Statistical significance was defined as p < 0.05. All data were analyzed using IBM SPSS version 24 .BMI is presented as the standardized deviation score (SDS) in order to compare patients of different ages. Means, standard deviations (SDs) and ranges were calculated for descriptive purposes. Non-parametric tests were used, due to scale scores not being normally distributed. To analyze differences between groups  in terms of continuous variables (BMI SDS and age), the Wilcoxon (Mann–Whitney) rank sum test was performed. The Chi-squared χAnthropometric data including gender, age and BMI SDS are presented in Eight participants were classified as having a probable ED. Four had probable BED , and four  had a milder variant of the same disorder, “Other specified feeding or eating disorder, Binge eating disorder”, (OSFED-BED), according to the DSM-5 see . Sixteenp = 0.164). Coexistent ADHD + ASD were present in two adolescent girls with probable BED and OSFED-BED, respectively. No other person with an ED had comorbid ADHD or ASD. Major depression was not overrepresented among those with an ED .The BMI SDS did not differ between those with an ED and those without an ED  (p = 1.00).Forty individuals completed the EDE-Q and 26 (65%) of them reported LOC eating. There was no difference regarding BMI SDS and age between those who reported LOC eating and those who did not (= 0.130) . Nine in= 0.130) . Nine inp = 0.32).N = 76) completed the EDI-C questionnaire. The EDI-C showed that all age groups with obesity, irrespective of gender, had mean scores above the normative data regarding the three symptom subscales   . FurtherUsing the Swedish norms for girls with EDs aged 13–17, the scores for the age-matched girls with obesity were above the cutoff for two of the three symptom subscales and six of the eight psychological subscales and above the cutoff for the total scale . Body diThis study aimed at investigating the prevalence of EDs, including LOC eating, in a clinical sample of children and adolescents with obesity. The prevalence of EDs  was 10.5%, which is elevated compared with the general adolescent population . FurtherBED and the milder variant of the disorder, OSFED-BED, occur in approximately 1%–4% of adults in the general population ,25. PrevLOC eating was surprisingly common in our teenage sample, engaging two thirds of the group, and the symptom was equally distributed across genders. In a recent review, the prevalence of LOC eating in young people who are overweight and obese is 31.2% . In accoIn accordance with Egbert and colleagues , we havePrevious studies have shown shared risk factors between obesity and EDs, including body dissatisfaction and weight-related teasing . Both riRo et al.  reportedThere are some limitations of the study that need to be discussed. Firstly, the patients were all tertiary referrals, and several of them had been considered to be treatment-refractory, and therefore referred to a university hospital clinic. Accordingly, the study group cannot be deemed to be representative of children and adolescents with obesity in general, and the many severe cases may bias the results. However, a strength of this study was that EDs and associated cognitive and behavioral symptoms were assessed using a consecutive approach for all new referrals at a university clinic.Secondly, the sample was relatively small, and some of the statistical calculations would probably not have resulted in trends but in statistically significant differences if the subgroups had been larger .Thirdly, no control group was included. However, we had access to Swedish normative data and Swedish cutoff scores for EDs, which enabled us to interpret the severity of the ED symptomatology in the group of young individuals with obesity. Regarding the EDI-C, we compared with Swedish normative and ED data . SwedishFourthly, the instruments used for assessing ED symptoms were only adjusted for children from age 10 (EDI-C) and 12 years (EDE-Q), respectively, and therefore only approximately half the sample could complete the EDE-Q, while 57 individuals were in the age range for completing the EDI-C. We had to divide the patients into subgroups due to different norms for age and gender, resulting in few individuals in each subgroup. With respect to the EDI-C, there are only cutoff data for EDs regarding adolescent girls . For this reason, we could not draw any conclusions as to whether preadolescent children and adolescent boys were at risk of developing an ED, since no Swedish cutoff data were available. However, the ED self-report instruments used are established and standardized ED instruments. The EDI-C, which was used in this study, is preferable to the EDI-2 in adolescents, since the statements are addressed to youths and not to adults.Fifthly, the LOC eating variable was only based on one question from the EDE-Q. However, the individuals had to declare LOC eating behavior at least once a week, on average, during the last 28 days in order to fulfill the LOC eating criterion. The meta-analysis by He et al.  observedSixthly, none of the self-report questionnaires regarding ED symptomatology were tailored to children and adolescents with obesity. EDs, including LOC eating, in children and adolescents with obesity have so far been overlooked both in clinical settings and in research . Future A strength of this study is that the ADHD diagnoses were either based on information from medical records or assigned using a well-established parental interview format (the DAWBA). Diagnoses of ASD were collected from medical records. With regard to ASD, this diagnosis has, to our knowledge, not previously been reported or examined in combination with traditional EDs in young people with obesity. ASD and ADHD often coexist, and ASD may therefore occur in parallel with ADHD in the children with obesity that we are investigating.To conclude, in our clinical population of children and adolescents with obesity, both EDs and LOC eating were overrepresented compared with the general population. ADHD and ASD also exhibited an increased prevalence, but the overlap between EDs and ADHD/ASD was not impressive.


ADHD) is more commonly diagnosed in males than in females. A growing body of research suggests that females with ADHD might be underdiagnosed or receive alternative diagnoses, such as anxiety or depression. Other lines of reasoning suggest that females might be protected from developing ADHD, requiring a higher burden of genetic risk to manifest the disorder.Attention deficit hyperactivity disorder . Second, we tested whether females and males with ADHD differed in ADHD genetic risk burden. We used three different diagnostic definitions: registry‐based clinical diagnoses, screening‐based research diagnoses and algorithm‐based research diagnoses, to investigate possible referral biases.We tested these two hypotheses, using common variant genetic data from two population‐based cohorts. First, we tested whether females and males diagnosed with anxiety or depression differ in terms of their genetic risk for ADHD PRS than males [OR(CI) = 1.39 (1.12–1.73)] but there was no sex difference for screening‐based [OR(CI) = 1.15 (0.94–1.42)] or algorithm‐based [OR(CI) = 1.04 (0.89–1.21)] diagnoses. There was also no sex difference in ADHD PRS in individuals with ADHD diagnoses that were registry‐based [OR(CI) = 1.04 (0.84–1.30)], screening‐based [OR(CI) = 0.96 (0.85–1.08)] or algorithm‐based [OR(CI) = 1.15 (0.78–1.68)].In individuals with a registry‐based clinical diagnosis of anxiety or depression, females had higher ADHD risk may be more likely to manifest or be diagnosed as anxiety or depression in females than in males. Contrary to some earlier studies, the results do not support increased ADHD genetic risk in females with ADHD as compared to affected males.This study provides genetic evidence that  Attention deficit hyperactivity disorder (ADHD) is a common and impairing disorder, with a prevalence of approximately 5% in childhood  = .26), depressive symptoms (rg = .45) and anxiety disorders (rg = .40)  = .45), depression (rA = .67–.77), affective problems (rA = .34–.48) and anxiety (rA = .45–.58)  is a population study of all twin children born in Sweden since July 1992  have been collected since 2008 from the participants at initial recruitment to the study. Samples were genotyped using the Illumina PsychChip genotyping chip. Standard quality control (QC) and imputation procedures were performed in the sample; for details see . Notably, the registry‐based diagnoses are subject to potential referral and diagnostic biases, whereas the screening‐based diagnoses are less likely to be affected by sex‐specific biases.Data on clinical diagnoses given by specialist services were obtained from the Swedish National Patient Register (NPR) through linkage using each individual's personal identification number. The NPR contains information on inpatient psychiatric care from 1987 and specialist outpatient consultations from 2001. It includes best‐estimate specialist diagnoses according to ICD‐10  codes WHO, . ICD codAs part of the CATSS research study, parents completed the Autism‐Tics, ADHD and Other Comorbidities inventory (A‐TAC)  contains details of all available data through a fully searchable data dictionary. Ethics approval was obtained from the ALSPAC Ethics and Law Committee and Local Research Ethics Committees.The Avon Longitudinal Study of Parents and Children (ALSPAC) is a large, well‐characterised longitudinal study   were derived using the standard method . To test the second hypothesis, that females with ADHD have an increased burden of ADHD genetic risk, we examined the association between ADHD PRS and sex, in children with ADHD.drgee package), using family ID to cluster the data to account for related samples, adjusting for age. In ALSPAC, analyses were run using logistic regression models. Males were the reference sex, coded as ‘0’ and females were coded as ‘1’ for all analyses.Analyses in CATSS were run using generalised estimating equations in R  was associated with sex. We also tested whether including age at first diagnosis as a covariate affected the results.To determine whether sex differences in severity of symptoms affected the registry‐based results in CATSS, analyses were adjusted for screening‐based measures of: (a) parent‐reported ADHD symptom severity and impairment, and (b) parent‐ and self‐reported anxiety and depression symptom severity.p < .002), for all definitions , screening‐based (CATSS) and algorithm‐based (ALSPAC) diagnoses of ADHD, anxiety and depression are shown in Table ns Table .Table There was no statistically significant difference in ADHD PRS between females and males with ADHD, for any ADHD diagnostic definition Table .p‐value thresholds are shown in Figures Results using ADHD PRS derived based on different In CATSS, females were older than males at first registry‐based clinical diagnosis of ADHD [OR (CI) = 1.11 (1.02–1.20)], with somewhat wider confidence intervals for anxiety [OR (CI) = 1.14 (1.00–1.29)] and much wider confidence intervals for depression [OR (CI) = 0.93 (0.81–1.07)]. Including age at first diagnosis as a covariate did not substantially affect the results Table .In CATSS individuals with registry‐based diagnoses of anxiety or depression, males had more ADHD symptoms and were more likely to have impairment from ADHD symptoms, whereas females had more self‐reported anxiety and depressive symptoms at age 18, though parent‐reported symptoms did not differ by sex Table . AdjustiThe results of this study suggest that ADHD common genetic risk burden is higher in females with clinically recognised anxiety and depression than in affected males, but that this finding does not extend to diagnostic definitions based on whole sample research screening in the general population. No sex differences in ADHD genetic burden were found in individuals with ADHD based on clinical or research diagnostic definitions.Consistent with studies showing genetic overlap across ADHD and other psychiatric phenotypes  and ALSPAC  are free from referral biases as they were obtained for all individuals . In CATSS, high symptom levels reported by parents or adolescents at age 18 were used as diagnostic proxies. In ALSPAC, computer algorithms were applied to obtain a broad indicator of parent‐ or adolescent‐reported problems across ages 7–18 years. In contrast, Swedish registry‐based diagnoses are independent of the study protocol and liable to referral and diagnostic biases; they reflect ‘real‐life’ clinician's diagnoses, which are more sensitive to factors such as impairment and incorporate clinically relevant information from multiple informants. Despite these rather different diagnostic definitions, the sample sizes for comparisons within diagnostic groups were similar so differences in statistical power are unlikely to account for differences in effect sizes.However, given these measurement differences, it is possible that the group of CATSS individuals who received registry‐based diagnoses are more severely affected compared to individuals meeting screening cutoffs. Indeed, CATSS individuals who screened positively for anxiety or depression at age 18 years and also had registry‐based diagnoses scored higher on parent‐ and self‐reported measures than those in the screened group who had not received a registry‐based diagnosis  diagnostic definitions. However, the target sample sizes of those with psychiatric diagnoses were low, limiting statistical power, and the effect sizes were modest, though typical for PRS studies of psychiatric phenotypes (e.g. Demontis et al., This study provides genetic evidence that ADHD risk may be more likely to manifest as anxiety or depression in referred females than in males and may partly explain the lower prevalence of diagnosed ADHD in females. Replication of these findings in other population genetic datasets that have study‐independent information for clinical diagnoses is needed to confirm these results. This study suggests that females presenting with clinical symptoms of anxiety or depression might benefit from additional careful screening for ADHD, particularly if they have a family history of ADHD.ADHD is more commonly diagnosed in males than females in clinical and population samples.This general population study suggests that ADHD genetic risk might more commonly manifest as anxiety or depression in females than in males.The results do not support an increased burden of common genetic risk variants in females with ADHD.Females at familial risk for ADHD, with anxiety and depression problems would benefit from careful screening for ADHD.Data S1. Polygenic risk score calculation.Table S1. Association between ADHD, anxiety and depression diagnoses with sex.Table S2. Association of ADHD PRS with sex of individuals with ADHD, anxiety and depression registry‐based diagnoses in CATSS, including age at first diagnosis as a covariate.Table S3. Association between variables related to severity of clinical presentation and sex.Table S4. Association of ADHD PRS with sex of CATSS individuals with registry‐based diagnoses of anxiety or depression, after adjusting for severity of clinical presentation.Table S5. Mean symptoms in CATSS individuals screening positively for anxiety or depression, depending on whether they also received registry‐based diagnoses.Figure S1. Variance explained in diagnostic outcomes by ADHD PRS derived using variable p‐value thresholds.Figure S2. Variance explained in sex by ADHD PRS derived using variable p‐value thresholds, in individuals with diagnostic outcomes.Figure S3. Variance explained in sex by ADHD PRS derived using variable p‐value thresholds, in individuals with diagnostic outcomes, excluding individuals with ADHD.Click here for additional data file.


The corresponding benzylidyne complex [PhC≡W{OC(CF3)Me2}] (WPhF3) was prepared by cleaving the W≡W bond in W2F3 with 1-phenyl-1-propyne. The catalytic alkyne metathesis activity of these metal complexes was determined in the self-metathesis, ring-closing alkyne metathesis and cross-metathesis of internal and terminal alkynes, revealing an almost equally high metathesis activity for the bimetallic tungsten complex W2F3 and the alkylidyne complex WPhF3. In contrast, Mo2F6 displayed no significant activity in alkyne metathesis.The molybdenum and tungsten complexes M While the field of olefin metathesis has seen significant progress in the past decades –5, the sI , was employed, which gave rise to the corresponding molybdenum and tungsten benzylidyne complexes .–20.I (16omplexes –20.II) introduced by A. Fürstner and co–workers is frequently used in the total synthesis of natural products  (MoF6) represents the first alkyne metathesis catalyst capable of effective and highly selective terminal alkyne metathesis [3)Me2}3] (WF3) showed excellent catalytic performance not only in the metathesis of internal but also, for the first time with the metal tungsten, terminal alkynes at room temperature  , MoF6 retathesis –53. Latetathesis . It was 3)Me2}3] , WF3 shoperature . Our stuperature –57. The perature .2(OR)6 2Me, Mo2F6; M = W, R = OC(CF3)Me2, W2F3), which draw upon the most catalytically active alkylidyne complexes MoF6 and WF3. R. R. Schrock synthesized the first alkylidyne complex which was able to undergo alkyne metathesis, [t-BuC≡W(Ot-Bu)3] (V), originally from [NEt4][t-BuC≡WCl4] [V by a stoichiometric alkyne metathesis reaction of the ditungsten complex [(t-BuO)3W≡W(Ot-Bu)3] with MeC≡Ct-Bu 3W≡W(Ot-Bu)3] complex has not been directly employed in catalytic alkyne metathesis.Based on these insights into the structure–activity relationship of alkyne metathesis catalysts, we wanted to establish an alternative and convenient access to highly active catalysts. Herein, we report the systematic study on the metathesis performance of bimetallic hexaalkoxide complexes MuC≡WCl4] ,58–61. SeC≡Ct-Bu  62]. Ev. Ev2(OR)ny years –64, it dny years –6165–67.V can be enhanced by adding an external ligand like quinuclidine to the reaction mixture [2(MMPO)6]  was isolated which catalyzed alkyne metathesis of 1-heptyne at elevated temperatures   serves as an excellent starting material for compounds of the type Mo2X6  [2{OC(CF3)2Me}6] (Mo2F6) was first isolated by D. Rogers and his group by salt metathesis of [Mo2Cl6(dme)2] with 6 equiv of NaOC(CF3)2Me (The dimeric molybdenum complex [Molkoxide) . The des(CF3)2Me  73]. Th. Th2Cl6Me2}6] (W2F3), can be prepared by the reaction of [NaW2Cl7(THF)5] with 6 equiv of NaOC(CF3)Me2 [2(NMe2)6] with the alcohol HOC(CF3)Me2 [2(NMe2)6] is easily accessible from WCl4 and LiNMe2 and has emerged as an important starting material for various dinuclear tungsten compounds [3)Me2 was required to drive the reaction to completion and led to the formation of the complex [W2{OC(CF3)Me2}6(NHMe2)] (W2F3·NHMe2) Me2 , but thi(CF3)Me2 ,88, whic(CF3)Me2 . [W2(NMeompounds . M. H. Compounds . The ami3·NHMe2) . The add2{OC(CF3)2Me}]6 is 2.309(3) Å [2(MMPO)6] [2(OCHMe2)6(py)2] (py = pyridine) [2(NMe2)6] (1.95(2)–1.99(2) Å) [2Cl2(NMe2)4] (1.935(8)–1.937(9) Å) [2 ligand compared to the negative NMe2 ligand and indicates a weak bond between the tungsten and the nitrogen atom. Coordination of the NHMe2 ligand to W1 affords markedly longer W1–O bonds (1.905(2)–1.970(2) Å) than the W2–O bonds (1.818(2)–1.930(2) Å). The W1 atom is coordinated in an almost square-pyramidal fashion (τ5 = 0.25) [4 = 0.89) [3W≡WX3 complexes [2(NMe2)6] has been observed before, e.g., in [W2(OAr)6(HNMe2)]   , and 2.3yridine) . The W1–99(2) Å)  and   . The 13CV  as 2-butyne scavenger. The conversion versus time diagram  and WPhF3 (1 mol %) and stirred in the presence of molecular sieves (MS 5 Å) as 2-butyne scavenger and n-decane as internal standard at room temperature  showing a slower initiation rate compared to the alkylidyne complex WPhF3. For the bimetallic complex W2F3, an additional initiation step is required, in which the W≡W triple bond is cleaved and catalytically active alkylidyne species are formed. Therefore, the conversion of the substrate with catalyst W2F3 is significantly slower at the beginning of the reaction. The initial catalyst turnover frequencies were calculated from the conversion of 1-phenyl-1-propyne after one minute (TOF1min). The TOF of the alkylidyne complex WPhF3 reaches 78 min−1 (1.30 s−1), while W2F3 has a significantly lower TOF of 13 min−1 (0.21 s−1) after one minute; this value is based on the formation of two catalytically active alkylidyne species upon treatment with the alkyne substrate. After 10 minutes, the alkylidyne complex WPhF3 has accomplished nearly full conversion and after 20 minutes, catalyst W2F3 achieves the same conversion of the starting material. The maximum conversion of around 97% is reached for both catalysts within 60 minutes. Accordingly, we aimed at further monitoring the substrate scope of the complexes including the metathesis of terminal alkynes as well as ring-closing alkyne metathesis (RCAM).para-substituted phenylpropynes , a reaction which is of large interest for the application of alkyne metathesis, but often leads to product mixtures. Therefore, (trimethylsilyl)propyne and (trimethylsilyl)acetylene were chosen as reaction partners in ACM, since this reaction proved to be quite efficient in the past [W2F3 (0.5–1 mol %) in the presence of molecular sieves 5 Å and stirred for two hours at room temperature. The isolated yields of the ACM are summarized in W2F3 is able to introduce a trimethylsilyl protecting group to alkynes.propynes , entry 5propynes , entry 6the past ,54,100. MoF6 and WF3 as the most catalytically active alkylidyne complexes [W2F3 as the bimetallic analogue to mononuclear WF3 is highly active in the metathesis of internal and even terminal alkynes and also promotes alkyne cross-metathesis efficiently. The Mo2F6 complex, however, does not exhibit satisfactory alkyne metathesis activity, which we attribute to its low solubility. Furthermore, the corresponding mononuclear benzylidyne complex WPhF3 is easily accessible from the dinuclear W2F3 complex and performs equally well compared to the latter.Previously, we have reported the optimum level of fluorination in omplexes . Thus, wW2F3 is a highly active alkyne metathesis pre-catalyst and does not have to be converted into an alkylidyne species prior to catalysis could be beneficial for future applications of alkyne metathesis since this protocol represents a convenient approach to alkyne metathesis catalysts in two steps starting from WCl4.The finding that CCDC 1850924−1850926 contain the supplementary crystallographic data for this paper. These data can be obtained free of charge via http://www.ccdc.cam.ac.uk/data_request/cif.File 1W2F3·(NHMe2), W2F3 and WPhF3.Experimental section, NMR spectra, catalysis procedure and product characterization, crystallographic details for


Drosophila, it is thought that peptidoglycan recognition proteins (PGRPs) SA and LC structurally discriminate between bacterial peptidoglycans with lysine (Lys) or diaminopimelic (DAP) acid, respectively, thus inducing differential antimicrobial transcription response. Here, we find that accessibility to PG at the cell wall plays a central role in immunity to infection. When wall teichoic acids (WTAs) are genetically removed from S. aureus (Lys type) and Bacillus subtilis (DAP type), thus increasing accessibility, the binding of both PGRPs to either bacterium is increased. PGRP-SA and -LC double mutant flies are more susceptible to infection with both WTA-less bacteria. In addition, WTA-less bacteria grow better in PGRP-SA/-LC double mutant flies. Finally, infection with WTA-less bacteria abolishes any differential activation of downstream antimicrobial transcription. Our results indicate that accessibility to cell wall PG is a major factor in PGRP-mediated immunity and may be the cause for discrimination between classes of pathogens.In   •PGRP-SA equally recognizes Lys- and DAP-type peptidoglycans (PGs)•S. aureus and triggers a robust responsePGRP-LC binds to •When WTAs are removed, immunity depends on both PGRP-SA and -LC•Accessibility to PG plays a central role in bacterial sensing Drosophila antibacterial response. Vaz et al. challenge this dogma by showing that accessibility to PG plays a central role in bacterial sensing and that structural discrimination is much less stringent than previously thought.It is widely believed that preference in recognition of structural features of bacterial peptidoglycan (PG) drives specificity in the  As the first line of host defense, innate immunity is activated by a non-clonal system of receptors . These rDrosophila, there is differential transcriptional activation by nuclear factor κB (NF-κB) pathways, depending on the bacterial type -N-acetylmuramic acid (MurNAC) linked to a stem peptide of d- or l- (or meso-) amino acids, in which the third amino acid is lysine (Lys) in Gram-positive bacteria and diaminopimelic acid (DAP) in Gram-negative bacteria and in certain Gram-positive bacilli. Circulating PGRP-SA is thought to interact preferentially with Lys-type PG and thus activate the Toll pathway , strongly activates IMD through PGRP-LC , the authors of the report argue that the presence of an Lys instead of a DAP would destabilize the docking interaction. Moreover, the absence of positively charged residues in the same region of PGRP-SA would be consistent with preferred binding to Lys-type PG , increased PGRP-SA binding to whole bacteria by 1,000× and made the PGRP-SA-dependent clearance of S. aureus independent of Toll  are anionic polymers of glycerol- or ribitol-phosphate that conceal the PG layer from direct interaction with the extracellular environment. Removal of WTAs from  of Toll .S. aureus as the Lys-type representative, we used B. subtilis as the DAP-type model. We found that in a hemolymph-like buffer, both PGRPs were able to bind in vitro both bacteria with exposed PGs at their surface, as well as their purified and quantified PG. When WTAs were removed, PGRP-SA was able to bind significantly more both types of bacteria, while PGRP-LC was able to bind significantly more only to B. subtilis and at the margin of statistical significance to S. aureus. In addition, there was no measurable preference of PGRP-SA binding to any of the two PGs in vitro, while PGRP-LC showed a quantifiable 5× preference for DAP-type PG. Despite that, PGRP-LC co-localized with the cell surface of both S. aureus and S. aureusΔTagO ex vivo and activated a robust antimicrobial response that was statistically comparable to that mediated by PGRP-SA. Following infection with S. aureus or B. subtilis, differential AMP induction was observed. However, when WTAs were removed, antimicrobial responses per bacterial number became statistically indistinguishable across the course of infection, indicating that more accessibility to PG equalized downstream transcription. At the level of the whole organism, flies that were double mutant for PGRP-SA and PGRP-LC were more susceptible than single mutants to infection with WTA-less bacteria, while the growth of WTA-less bacteria showed a statistically significant increase in double mutant flies compared to the single fly mutants.In this study, we address the importance of accessibility to PG in PGRP-mediated recognition of whole bacteria in more general terms. In addition to Drosophila. Given the evolutionary conservation of innate immunity in most metazoans, our results have implications for animals when PGRPs are used as recognition receptors of whole bacteria.We argue that accessibility to PG is one of the main determinants of PGRP specificity in S. aureus and B. subtilis) that carry PGs that represent a wide range of bacteria and bacilli. In general, bacterial PG can be divided into two groups: group A (in which crosslinking between stem peptides occurs between positions 3 and 4), which is the most common among pathogenic bacteria . PG of the A3 group is very common among Gram-positive bacteria . PG of the A1 group is very common among Gram-negative bacteria.We chose to use two bacteria , which is not frequently found among bacteria  was used as a control. Our results are shown in We hypothesized that differential activation of immunity by different bacterial species may not be due to the structural discrimination of PG, but instead is due to differential PG accessibility. To test this hypothesis, we compared the S. aureus NCTC and B. subtilis EB6 binding  and B. subtilisΔTagO   .ΔTagO mutants was not a result of the mCherry protein tag. To this end, we constructed and purified mutant versions of mCherry-PGRP-SA that carried either or both of the mutations C48 to Y and C54 to Y  to visualize the fluorescent protein bound to the bacterial surface, PGRP-LC binding to S. aureusΔTagO was significantly increased .PGRP-LC binding to o 13,402 . Binding p value . NevertheusΔTagO C showed B. subtilisΔTagO. PGRP-LC showed no discrimination between the wild-type parental strains. When WTAs were removed, B. subtilisΔTagO was the preferred strain of PGRP-LC, while binding to S. aureus increased but not as much. Nevertheless, the latter result was contrary to expectations, as PGRP-LC was not supposed to bind Gram-positive bacteria. Therefore, we wanted to explore the interaction of live S. aureus bacteria with primary macrophages expressing PGRP-LC on their membrane.These results indicated that PGRP-SA showed no apparent discrimination between the two wild-type strains of bacteria. However, when WTAs were removed, PGRP-SA had a preference for in vitro binding experiments used an mCherry-PGRP-LC construct that only included the PGRP ectodomain of the protein, so we wanted to ascertain that when expressed in Drosophila cells, transmembrane PGRP-LC was also able to bind to S. aureus and B. subtilis wild-type strains and their WTA-less mutants. To this end, we used a UAS-PGRP-LCx-GFP transgene , which did not happen following challenge with heat-killed Gram-negative bacteria or live Staphylococcus carnosus (Gram positive). We also observed that the fluorescent signal of the GFP linked to the extracellular domain of PGRP-LCx detached from the cell membrane and co-localized with bacteria away from the cell surface and in the extracellular space. However, this was observed both after challenge with live S. aureus (S. aureusΔTagO (B. subtilis and B. subitilisΔTagO (S. aureus (up to 0mins:10secs) and S. aureusΔTagO (0mins:11secs-0mins:20secs).in vitro results as presented in hml-GAL4; UAS-PGRP-LCx-GFP larval hemocytes indicated abundant interactions of cleaved PGRP-LCx at the level of the bacterial surface with both wild-type and WTA-less bacterial strains, irrespective of PG type. Moreover, this indicated that the use of only the PGRP-LC ectodomain was a meaningful way to test the binding of the receptor to PG, as (at the cellular level) it showed the same engagement with bacteria as the full-length protein.Therefore, in keeping with our S. aureus and B. subtilis. Briefly (see the full protocol in N-acetyl groups without affecting the sugar molecules and avoiding any WTA contamination) and chromatographically separated. The areas of chromatogram peaks were quantified in comparison to controls in which the concentration of glucosamine and muramic acid were known. With this method, we were able to determine exactly the amount of glucosamine and muramic acid used in our binding assays and therefore used precisely quantified PG. In turn, this helped in the use of PG suspensions with the same concentration of MurNAc in the binding reactions.To circumvent the caveats of previous studies , we condB. subtilis PG  showed a statistically significant difference with PGRP-SA/PG co-immunoprecipitation intensity at 4 × 106 U, while PGRP-LC/PG co-immunoprecipitation intensity was at 6 × 106 U .Our results indicated that contrary to previous observations , given ttilis PG A. PGRP-Lris-NaCl B. In thiuishable B. Bindin × 106 U C. This iproposed . NeverthΔTagO PG C. This i4 a.u. at saturation) and Lys-type PG (2.7 × 104 a.u. at saturation) .To confirm the above results, we performed saturation-binding experiments, in which a fixed amount of each PGRP was individually mixed with increasing amounts of either PG to reach saturation binding . Contrary to previous results , PGRP-SAuration) B. This w-type PG . The KD 4 a.u. at saturation) over Lys-type PG (4 a.u. at saturation) and bound significantly more DAP-type PG than PGRP-SA , indicating comparable numbers of PG-associated receptors in the PGRP-PG pellet at saturation. However, the KDs were different, indicating tighter binding of PGRP-SA to Lys-PG  PGRP-SAseml mutant flies, suggesting that PGRP-LC did contribute to the final sum of host survival following S. aureus infection . The picture was different in PGRP mutants, in which growth of both parental bacterial strains . Our results are shown in  strains A and 6B ugh time B and 6D.nfection A. Of notnfection .Figure 6S. aureusΔTagO growth showed increasing statistically significant differences between PGRP-SAseml; PGRP-LCΔE12 and PGRP-SAseml mutants from 24 to 36 h post-infection , whereas as a proxy for PGRP-LC/IMD signaling pathway activity, we measured the induction of the AMP gene diptericin (dipt).To trace signaling activation over time downstream of the two PGRPs following infection and ascertain whether the bindings we have observed led to the induction of immune activity, we measured AMP gene expression. As proxy for the PGRP-SA/Toll signaling pathway, we used the AMP gene w1118 flies with B. subtilis induced a robust differential activation of antimicrobial peptide gene expression with almost 100× more dipt than drs at 48 h , S. aureusΔTagO (1mins:12secs-2mins:13secs), B. subtilis (2mins:14secs-3mins:23secs), B. subtilisΔTagO (3mins:14secs-4mins:34secs), Schneider medium control (4mins:35secs-5mins:44secs) and heat killed S. aureus (5mins:45secs-6mins:56secs).ex vivo phagocytosis by moesin-GFP-labeled primary larval hemocytes. When infected with S. aureus, hemocytes started exhibiting the hallmarks of cell death  , while PGRP-LC interacts with DAP (found in Gram-negative bacteria and Gram-positive bacilli). The idea of structural discrimination at the level of the stem peptide resulted from a combination of observations, including PG binding assays, structural work, and in vivo infection experiments. However, there are several concerns with the experiments that support this Lys/DAP dichotomy or with the interpretation of the data. A summary of these follows.In First, the PG binding experiments were conducted with a buffer that is often used to solubilize proteins, but that was very different from hemolymph (where interactions between PG and PGRPs take place).Second, the PG used for binding as well as infection experiments was quantified only by weight and not by the number of disaccharide GlcNAc-MurNAC added to the binding reaction.in vivo. In the context of polymeric PG binding, the small difference of a carboxyl group on the Cε with d-chirality in DAP may not be as important for downstream signaling. Moreover, superposition of the two structures showed that the electrostatic potential at the surface of both PGRPs suggests that binding to both types of PG in solution is probable.Third, the structural data available and previously described referred to the binding of monomeric PG, whereas PGRP-SA and PGRP-LCx are both able to bind polymeric PG and may do so in vitro. Moreover, binding of PGRP-LC to Lys-type bacteria was recorded ex vivo, and this binding resulted in a robust AMP induction that was statistically higher than the one elicited through PGRP-SA, considered the bona fide receptor for Gram-positive bacteria , accessibility to PG is a major factor restricting binding, recognition, and downstream signaling. Structural discrimination may still be important when monomeric PG fragments are the only means of “accessing” PG (in Gram-negative bacteria).Drosophila, challenged by a wide variety of pathogens, each of which interacts rarely with it , has been considered a productive host strategy. However, we believe that it would have been detrimental for the host to further specialize its non-enzymatic PGRP receptors to PG-stem peptide variants, as this would essentially decrease even more the effective number of possible productive host-pathogen recognition interactions, especially in an animal such as  with it . Put it athogens .Drosophila PGRPs (including SA and LC) have shown that there is no strong co-evolution interaction, and as such, no need for specialization (Evolutionary studies on lization . We proppetros.ligoxygakis@bioch.ox.ac.uk).Further information and requests for resources reagents should be directed to and will be fulfilled by the Lead Contact, Petros Ligoxygakis (E. coli strains DH5α and BL21(DE3) (both for construction and expression of the recombinant proteins), B. subtilis EB6 and EB6ΔtagO (EB1451) strains  and NCTC Δ tagO ( strains  were groC Δ tagO  were groseml (PGRP-LCΔE12 (Drosophila Stock Centre), w; UAS-GFP::PGRP-LCx  containing the PGRP-LCx isoform, was used to amplify the PGRP domain (region 966 bp to1500 bp of the CDS) with the pair of primers (sequences from 5` to 3`): “GGGAAGGGAATTCAACCAAACGGACTTGGATG” (forward) andPlasmid IP15793 (“TGCGGCCGCAAGCTTTTAGTGATGGTGATGGTGATGGATTTCGTGTGACCAGTGCG” (reverse). Subsequently, the fragment was cloned into the EcoRI and EagI restriction sites of the pET21a backbones of the mCherry_PGRP-SA and rPGRP-SA vectors . A 6x Hiseml; PGRP-LCE12Δ I and III chromosome of semmelweis flies and PGRP-LCΔE12 flies were balanced through cross with. For each F1 of these two independent crosses, flies with both balancers were selected and the cross between female virgins seml/FM7 and TM2/+ with males FM7/y and TM2/PGRP-LCΔE12 was set. Of this progeny, we selected female virgin flies that phenotypically presented both balancers and male flies that were not FM7 (hence were seml genotype) but presented TM2 phenotype.For construction of the double mutant PGRP-SAst instar larvae, the parents were removed and checked for both the seml mutation as well as for PGRP-LCΔE12. Briefly, gDNA was extracted and the PGRP-LCΔE12 was amplified by PCR using the primers “CACACGCTGCCATATCAGAC” and “TATCGGTTTTCCTGGGTGAG”  for amplification of the semmelweis/PGRP-SA gene were sent to sequencing to confirm the genotypes. Females and males that did not present balancers, i.e., homozygous for both semmelweis and PGRP-LCΔE12 genes were collected. Finally, single crosses between one of these females and one male were set to obtain a homogeneous population of homozygous flies for seml and PGRP-LCΔE12. Three different lines from three different single crosses were obtained, of which both the parents and progeny genotype was confirmed by PCR and sequencing. Results obtained from survival and CFU studies were similar for all lines tested. For construction of the single mutants, the respective mutant flies balanced with the Bl#27336 flies were used and a similar approach as for the double mutant was followed. Again, three stocks for each single mutant, with one female and one male as progenitor parents for the whole stock were established. This was to ensure the PGRP-SAseml, PGRP-LCΔE12 and the double mutant, were in a similar genetic background. Results obtained from survival and CFU studies were similar for all lines tested.Several single crosses between such females and males were set. After confirming the existence and viability of 1GGGTGAG” . The cor2SO4.10H2O (7.3mM), NaH2PO4.H2O (34mM), Na2HPO4.7H2O (5mM), CaCl2.2H2O∗ (2mM), MgCl2.6H2O∗ (14.4mM), KCl (25mM). Please note that the final solution has a short shelf-life before precipitation occurs. We found that the easiest way to prepare this solution was to use the salt concentrations as above to prepare the final HemoBuffer solution. Furthermore, we found that CaCl2.2H2O and MgCl2.6H2O salts precipitate the solution if added together with the rest of the salts. Therefore, we found it useful to prepare a 10x concentration Stock Solution of HemoBuffer without CaCl2.2H2O and MgCl2.6H2O and prepare a fresh HemoBuffer solution by dilution and adding the CaCl2.2H2O and MgCl2.6H2O to the desired concentration.This buffer (referred to in the text as HemoBuffer) was prepared according to previous studies . After quantification of the Glucosamine and Muramic acid in each PGN sample, the final PGN suspensions were adjusted to the same amount of Muramic acid for further studies.2O and lyophilized O/N. Finally, the acid-free hydrolysed material was resuspended in 150 μL MilliQ H2O.Three repeats for each PGN sample and three different batches of quantification were performed because as PGN is insoluble in aqueous solution, these repeats minimize potential errors in the quantification. The pure PGN suspension was left O/N stirring at RT for maximum homogenization. 20 μL of the suspensions were hydrolysed in 3 M HCl at 95°C for 2 h (150 μL reaction volume). The hydrolysed suspension was lyophilized until it was completely dried and resuspended in 500 μL of MilliQ H3COO and MilliQ H2O. The MilliQ H2O as all the eluents were in MilliQ H2O of resistivity ≥ 18 MΩ, filtered with 0.2 μm ϕ pore filter and degassed for 15 min in an ultrasonic bath. Between the eluents pump and the injection valve it was used a BorateTrap™ column to remove borate contamination from eluents. An AminoTrap™ (Thermo Scientific Dionex AminoTrap) was used as a pre-treatment column to remove the amino acids from the samples, thus only the sugars passed to the CarboPac PA10 column (Thermo Scientific CarboPac PA10) where they were separated. Each injection was done in triplicates.For monosaccharide separation 10 μL of the samples were injected in a Thermo Scientific Dionex ICS-5000 system, in 18 mM NaOH constant and a gradient of 1 M NaCHN-acetylglucosamine and N-acetylmuramic acid. If the hydrolysis was complete, only Glucosamine and Muramic acid should be detected because the N-acetyl groups were removed by the acid treatment. Also these same samples HCl treated were injected, to determine if the hydrolysis had not destroyed the sugar molecules. After HCl treatment, only Glucosamine and Muramic acid should be detected and the areas of the peaks should be similar to the areas of the non-hydrolysed Glucosamine and Muramic acid standards because, theoretically, it was injected the same concentration for all of them.To assess if hydrolysis had been complete, it was injected non-HCl treated Glucosamine, Muramic acid, Injection of 1 mM of Ribitol, Glycerol and Mannosamine (HCL and non-HCL treated) to determine whether the PGN was indeed pure or still had WTAs attached.2∼1, the equation was used for the quantification of Glucosamine and Muramic acid in each PGN sample. Since N-acetylglucosamine and N-acetylmuramic acid are converted into Glucosamine and Muramic acid, respectively, under this hydrolysis conditions, we can control if total sample hydrolysis has occurred. In a total hydrolysis scenario no N-acetylglucosamine and N-acetylmuramic acid should be detectable  System software and thus the correspondent number of moles was calculated. PGN suspensions to be used in the co-precipitation assays were made in MilliQ HCo-precipitation or pull-down assays intended to determine the binding affinity of the PGRPs to both pure PG and to live cells, i.e., whole bacteria. The PG pull down assays are quantitative assays performed with the non-fluorescent tagged rPGRPs and analyzed by SDS-PAGE. Due to the non-solubility of the PGN in aqueous solutions, the amount of protein that binds is harvested with it. The bacterial binding assays are qualitative and were performed with the mCherry_PGRPs for microscopy visualization.−1 nmol of Muramic acid/μL of PG were thoroughly mixed and 20 μL were taken and spun down for 3 min at RT, 16.1 x1000 g. The supernatants were carefully removed, in particular the NCTC Δ tagO who’s PGN does not pellet well like the others and hence it is easily aspirated. To the pellets it was added 0.3 mg/mL final concentration of either PGRP-SA or PGRP-LC in a 200 μL reaction volume, filling up the volume with the reaction buffer . The mixes were incubated at 25°C for 30 min, without shaking and then centrifuged for 5 min at RT 0.8 × 1000 g. The pellets were washed with 200 μL of reaction buffer and centrifuged for 5 min at RT, 3.2 x1000 g. The pellets were finally resuspended in 20 μL of 2X SDS LB and boiled for 5 min. The samples were centrifuged for 3 min at RT, 16.1 x1000 g. The supernatants were recovered (20 μL) into a fresh tube. This collection step allows the loading on the gel to be quick, clean and guarantees that only the supernatant and not bits of PG were loaded, which is important for comparing and quantifying the binding affinities. The full supernatant volume was loaded on a 12% SDS-PAGE gel. Resulting bands were visualized by Coomassie Blue Staining and both imaging and quantification were performed using a Gel Doc™ EZ Gel . For quantification purposes of the bindings, each experiment was repeated in two different days, with two different batches of buffers (made fresh).For the assays, PG suspensions at 2.89x10600nm ∼0.5 and 1 mL aliquot was centrifuged for 5 min at RT, 16.1 x1000 g. The cells were washed with 500 μL of HemoBuffer and centrifuged again. They were resuspended in 0.3 mg/mL final concentration of either mCherry_PGRP-SA or mCherry_PGRP-LC in a 200 μL reaction volume, filling up the volume with Hemo buffer and incubated at RT for 5 min without shaking. The “cells-bound PGRPs” complexes were harvested for 5 min at RT, 7.5 x1000 g. The pellets were washed twice with 200 μL of Buffer. Finally, the pellets were resuspended in the left-over volume of the washings and 2 μL was loaded on a 1.2% (w/v) Agarose-PBS slides (it does not dissolve in HemoBuffer). Images were acquired with a GE Healthcare DeltaVision Elite integrated imaging system, in the conventional mode at 25°C using an Olympus 150x 1.45 NA TIRF Objective  using the SoftWoRx software .Bacteria were grown to ODThis was performed in Image-J. Briefly, a threshold was applied to the phase image to obtain a mask that harbors the cells. Since PGRPs bind exogenously this mask was slightly dilated to encompass the fluorescence signal. The mask was processed by the watershed algorithm to separate the area of cells in close proximity and the resulting mask was used to create a list of Region of Interest (ROI), with each ROI harboring a different object. The list of ROIs was used to measure the fluorescent signal intensity after subtracting the background fluorescence. The average signal intensity of each ROI was used as a measure of the binding intensity.B. subtilis 5.0, B. subtilis Δ tagO 7.0, S. aureus 0.5 and S. aureus Δ tagO 0.7. 500μL of these cultures was centrifuged at RT for 10min, 3380 x g. The cells were washed once with 1mL of PBS  and resuspended in 500μL of PBS. 32.2 nL of bacterial suspension was injected in thorax of 3-5-day old flies using a nanoinjector . The infected flies were kept at 25°C and monitored for 72h every 12h. For determination of the CFUs, infected flies were collected at different time-points, homogenized and plated in the appropriate media and incubated at 25°C for 24h-48h. Survival curves and CFUs were determined for at least 3 independent experiments for each infection with (n = 30/infection).Bacterial cultures were grown overnight. Optical density was adjusted with the appropriate medium culture as follows: rp49 forward: AAGAAGCGCACCAAGCACTTCATCrp49 reverse: TCTGTTGTCGATACCCTTGGGCTTdiptericin forward: ACCGCAGTACCCACTCAATCdiptericin reverse: GGTCCACACCTTCTGGTGACdrosomycin forward: AGTACTTGTTCGCCCTCTTCGCTGdrosomycin reverse: CCTTGTATCTTCCGGACAGGCAGTTotal RNA was extracted from whole flies  from three biological repeats upon injection using the Total RNA Purification Plus kit (Norgen Biotek), and cDNA was prepared from 0.5 mg total RNA using the Maxima First Strand cDNA synthesis kit (Thermo Scientific). The reaction conditions involved a step at 25°C for 10 min followed by a 15-minute step at 65°C and ending with a 5 min step at 85°C. QPCR reactions were carried out with the SensiFASAT SYBR No-ROX kit (Bioline) in a Corbet Rotor-Gene 6000 qPCR machine (QIAGEN) using 2 μl of cDNA template diluted tenfold and 400nM of each primer. Expression values were calculated using the DDCt method and normalized to rp49 expression levels. List of primers as follows:w UAS-GFP::PGRP-LCx virgin females were crossed with HmlΔGal4. Primary macrophages from F1 third instar larvae were used as described below. All other videos were done using primary macrophages from Moesin-GFP third instar larvae.For microscopy of the GFP::PGRP-LCx binding to live bacterial cells, 2O followed by 50% (v/v) bleaching and vortex. The larvae were quickly washed three times with autoclaved MilliQ H2O and left swimming while the slides were prepared. Into previously washed metal slides (100% (v/v) Ethanol) with a 1.0 mm coverslip it was put Schneider medium supplemented with 5% Fetal Calf Serum. The larvae were bled into the medium and the macrophages were let settle for 1 h at RT in a humid chamber.Three third instar larvae were washed in 1 mL of ddH2O) and incubated for 5 min at RT, without shaking. The cells washed with 200 μL of Schneider and resuspended in 100 μL of Schneider. Finally, they were dilute 1/10 in Schneider in a 200 μL final volume.200 μL of an O/N culture were harvested at RT and washed with of Schneider. The cells were resuspended in 200 μL of Schneider with 0.5 μL of a DAPI solution . Statistical significance for CFU data was determined by Student’s t test. To determine statistical significance between them, estimated survival probability curves were analyzed using the Log-rank (Mantel-Cox) and Wilcoxon tests.


N = 48) and to parents of normally developing children (control group) (N = 87), and the intake of dietary omega-3 LC-PUFA, such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), was estimated. Children with ADHD consumed fatty fish, lean fish, mollusks, crustaceans, and chicken eggs significantly less often (p < 0.05) than children in the control group. The estimated daily omega-3 LC-PUFA intake (EPA + DHA) was significantly below that recommended by the public health agencies in both groups, and was significantly lower in children with ADHD  compared to normally developing children. Dietary intervention to increase the consumption of fish and seafood is strongly advised and it is especially warranted in children with ADHD, since it could contribute to improve the symptoms of ADHD.Omega-3 long-chain polyunsaturated fatty acids (LC-PUFA) play a central role in neuronal growth and in the development of the human brain, and a deficiency of these substances has been reported in children with attention deficit hyperactive disorder (ADHD). In this regard, supplementation with omega-3 polyunsaturated fatty acids is used as adjuvant therapy in ADHD. Seafood, particularly fish, and some types of nuts are the main dietary sources of such fatty acids in the Spanish diet. In order to assess the effect of the intake of common foods containing high amounts of omega-3 polyunsaturated fatty acids, a food frequency questionnaire was administered to parents of children with ADHD ( There is a growing evidence that several mental disorders, although they show an underlying genetic predisposition , are proPrevious studies refer to the fundamental role afforded by omega-3 LC-PUFA in several essential metabolic functions, given their implication in diverse neuronal processes, as well as in cell growth, the function of cell membrane, hormonal, and immunological cross-talk, and gene expression regulation ,22,23. A1)Evaluation of the pattern of consumption of the main dietary sources of food containing omega-3 LC-PUFA in children with ADHD and in a control group.2)Estimation of the daily intake of omega-3 LC-PUFA (EPA + DHA) in the two groups.3)Evaluation of the influence of age, sex, and body mass index (BMI) upon omega-3 LC-PUFA intake.Although many studies on omega-3 LC-PUFA supplementation in ADHD have been published in recent years ,14, mostAn observational case-control study was carried out in Valencia (Spain) in 2016–2017. The study participants were recruited among patients (children and adolescents) with ADHD undergoing child psychiatrist consultation. Neurologically healthy children (control group) were recruited from two public schools in Valencia (Spain). Attention deficit hyperactive disorder was confirmed based on the DSM-IV diagnostic criteria using a standard neurodevelopment examination and interview . The parents of children with ADHD were interviewed during ordinary consultation with the child psychiatrist. Clinical information  was retrieved by reviewing the medical records in the psychiatrist consultation of children with ADHD. Body mass index was calculated as weight in kilograms divided by the square of height in meters. For children and adolescents, BMI is age- and sex-specific, and is often referred to as BMI-for-age. According to the international guidelines, BMI was grouped into four categories: underweight (BMI less than the 5th percentile), normal or healthy weight (5th percentile to less than the 85th percentile), overweight (85th percentile to less than the 95th percentile), or obese  .The chilThe study protocol was approved by the local Ethics Committee of the University of Valencia  (protocol number H1397475950160). Parents signed the informed consent in order to participate in the study.The parents completed the food frequency questionnaire (FFQ) about their children’s diet and were also instructed to report all beverage and supplement consumption. The instrument was a semi-quantitative food questionnaire that was comprised of 136 food items, and is validated in Spain . SpecifiParents self-reported fish and nuts consumption in their children. Fish was defined as “any kind of fish, including fish sticks and canned tuna fish, shellfish, crustaceans and mollusks.” Participants reported: (a) how often they consumed fish ; and (b) the type of fish they typically consumed.The items of the three-day semi-quantitative food questionnaire  related n < 50) or Kolmogorov–Smirnoff (n ≥ 50) tests. As a result of non-normal data distribution, we used nonparametric tests, e.g., the Mann–Whitney U-test (when comparing quantitative variables between two groups) or the Kruskal–Wallis test (when comparing quantitative variables among three or more groups). Correlation analysis between quantitative variables was performed with the nonparametric Spearman test. In order to control the effect of intervening variables, partial correlations were performed. Differences between categorical variables were evaluated with the chi-squared test. In the case of food frequencies, we applied the z-test for differences between proportions to determine which of the five to seven categories differed between the control and ADHD groups. To quantify the effect size for two groups comparison we calculated Cohen’s d. Statistical significance was considered to be p < 0.05. The SPSS version 24.0 statistical package  was used throughout.In the univariate analysis, variables were represented as absolute frequencies and percentages for categorical variables, and as the mean ± standard deviation (SD) for continuous (quantitative) variables. In the bivariate analysis, we first checked for normal or non-normal data distribution for quantitative variables using the Shapiro–Wilk (p = 0.64) or mean age (p = 0.86). Regarding the weight distribution of the subjects, 18.5% (n = 25) of the sample had low weight (percentile < 5), 36.3% (n = 49) showed normal weight (percentile 5–84), 23.7% (n = 32) were overweight (percentile 85–94), and 21.5% (n = 29) were obese (≥95 percentile). Significant differences in weight distribution were observed between the control and ADHD groups (p < 0.0001). In relation to BMI, low weight was significantly more prevalent in the control group compared to the ADHD group (p < 0.0001), while obesity was significantly more frequent in the ADHD group compared to the control group (p < 0.001) (The characteristics of the study sample are shown in < 0.001) .p < 0.001) , “twice–four times a week”  and “five–six times a week” . Significant differences were also observed in the case of fatty fish   , “once–three times a month” , “once a week” , and “twice–four times a week” .The reported average energy intake was approximately 1705 kcal. Of this amount, 51% corresponded to carbohydrates, 34% to fat, and 15% to protein. Fish intake was significantly lower in children/adolescents with ADHD than among the controls for all types of fish and seafood, except codfish. Significant differences were recorded in relation to lean fish  (< 0.001) A; the z-ed test) B; the z-p < 0.001; chi-squared test); the z-scores analysis showed significant differences for the intake category “once a week” . The same applied to the intake of shellfish  (p < 0.05); the z-scores analysis showed significant differences for the intake category “twice–four times a week” . Likewise, significant differences were observed in the intake of mollusks  (p < 0.001); the z-scores analysis showed significant differences for the intake category “once a week” . Lastly, significant differences were recorded in the intake of crustaceans  ; the z-scores analysis showed significant differences for the intake categories “once a week”  and “five–six times a week” . In contrast, the intake of codfish was not significantly different between the two groups (p = 0.23).Significant differences were recorded in the intake of smoked fish  (p = 0.07), omega-3 LC-PUFA supplements (p = 0.26), or omega-3 fatty acid-enriched milk (p = 0.14). The intake of omega-3 fatty acids from nuts were not included in the calculation of daily EPA + DHA intake, since these foods contain other omega-3 LC-PUFA different from DHA and EPA, and because no significant differences in the intake of dry fruits were observed between the ADHD and control groups.There were no significant differences in relation to the consumption of nuts  (p < 0.05), and eggs , but not to other foods (p > 0.05).Significant differences in food intake were observed between females and males in relation to fatty fish and shellfish  (p < 0.05), fatty fish (p < 0.01), mollusks (p < 0.05), and other types of fish and seafood less frequently consumed (p < 0.05).The estimated ingestion of omega-3 LC-PUFA (EPA + DHA) in the diet was 109.87 ± 80.27 mg/day for the control group and 78.42 ± 56.64 mg/day for the children with ADHD ( = 0.45) . The anap < 0.05) and crustaceans . No significant differences were observed in the estimated daily amounts of omega-3 LC-PUFA (EPA + DHA) between sexes (p = 0.17) or among children in the different weight categories (p = 0.57).There was a significant correlation between the mean daily intake of EPA + DHA and the frequency of intake of fatty fish . The correlation between mean daily omega-3 LC-PUFA intake and age no longer proved significant  after controlling for the intervening variables, e.g., group, sex, and weight categories, suggesting that these contribute significantly to the association between omega-3 LC-PUFA intake and age.In contrast, a significant and direct correlation was observed between the intake of omega-3 LC-PUFA and of the age of the children . This finding agrees with those of a recent meta-analysis concluding that the prevalence of obesity in ADHD is 40% higher than in the general population ,52. The Our study has a number of limitations. First, the cross-sectional observational design involved limits regarding inferences about causality between insufficient intake of omega-3 LC-PUFA and the worsening of ADHD symptoms. Second, there were a number of issues related to the completion of records. Data referred to intake may contain errors due to inaccuracies in recorded quantities and they are based on parents’ reports rather than children’s. However, we are confident that the self-reported information provided by parents about the nutritional assessment of their children was adequate because they showed interest in the study and they received training and support in filling out the food records. Furthermore, the attrition rate was low. We, therefore, think that the study has a good internal validity. A third limitation is the fact that we did not measure the intake of omega-3 LC-PUFA coming from other sources. Nevertheless, we are confident about the main role of fish and seafood as the principal source of EPA + DHA in the Spanish diet ,39.In our sample of children with ADHD and controls (age- and sex-matched with the ADHD subjects), there were considerably more boys than girls , whicDespite these limitations, our study underscores the need for greater attention to the education of parents and children regarding healthy dietary habits in Spain, and as such, education is the most promising and practical complementary management strategy in ADHD. Given that fish consumption is the main source of dietary omega-3 LC-PUFA , interveThe intake of seafood in particular fish, is reduced in children with ADHD compared to typically developing children and this may contribute to reduced intake of some omega-3 LC-PUFA such as EPA and DHA, essential nutrients for a proper brain development and function. Further research is required to clarify associations between ADHD symptomatology, eating patterns and health status.


While pharmacotherapy and psychosocial interventions are recommended as the primary frontline treatment for attention deficit hyperactivity disorder (ADHD), alternative approaches to managing ADHD are becoming increasingly popular among patients and their families. Supplementation with polyunsaturated fatty acids (PUFAs) is an example of this. PUFA supplementation is not recommended by guidelines for managing ADHD; however, patients may still decide to use it. To provide direction to healthcare professionals (HCPs) managing ADHD, eight international experts in the field of adult and child ADHD came together for the Continuum Education Board: Omega Supplements in ADHD meeting. This commentary summarises the panel's consensus that current evidence suggests PUFA supplementation has a small beneficial effect on behaviour in children with ADHD, and that further high-quality research is needed to clearly evaluate and define its role in the management of ADHD of children, adolescents and adults. The panel concluded that in cases where patients use PUFA supplementation, HCPs should be comfortable explaining the potential gains that they may have and their possible side effects. The panel also concluded HCPs should not reinforce the idea that PUFA supplementation should replace treatment approaches with a more robust evidence base for managing ADHD. Primary frontline treatments recommended for attention deficit hyperactivity disorder (ADHD) may make use of both pharmacotherapy and psychosocial interventions. However, alternative approaches to managing ADHD are becoming increasingly popular among patients and their families . SupplemIn an attempt to provide direction to HCPs managing ADHD, on 29 August 2017, eight international experts in the field of both adult and child ADHD came together for the Continuum Education Board: Omega supplements in ADHD meeting. The meeting served as a forum in which a panel of experts could assess the current landscape of PUFA supplementation in light of accumulating data, and provide practical recommendations to help HCPs make evidence-based decisions for patients and their families seeking alternative treatments. Details from the panel’s consensus are summarised here, along with recommendations for future research.Omega-3 PUFAs, such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), are essential nutrients, and DHA is highly abundant in the mammalian brain . By alteInflammation, which could be associated with neuropsychiatric disorders, might be reduced with EPA and DHA . In contIn line with these observations, recent findings have shown that some individuals with ADHD have low blood and plasma levels of omega-3 PUFAs . Such a PUFAs have been assessed across many psychiatric conditions. Meta-analyses of omega-3 PUFA trials in patients with depression have resulted in inconsistent conclusions. One analysis concluded that omega-3 PUFA supplementation does not have a significant benefit on depressive symptoms . MeanwhiIn ADHD, clinically meaningful effect sizes have been observed in some studies using PUFA supplements. Several prospective, interventional studies have suggested that omega-3/6 PUFA supplements – either alone or in combination – offer improvement in cognitive performance  and enhag effect size (g): 0.38, p<0.0001) and their cognitive performance .12Meta-analyses mainly report a small effect size in ADHD , althougVariations in the inclusion criteria for meta-analyses may account for these conflicting results in terms of significance or non-significance. It should be noted that Cochrane reviews are stricter in terms of what data they will typically include to calculate effect size, so fewer studies usually contribute to the meta-analysis. It should also be noted that studies included also vary in sample size, trial length, dosage, supplement composition and whether participants are concurrently taking stimulant medication. In summary, current evidence suggests that PUFA supplementation has a small beneficial effect on behaviour in children with ADHD.Although effect sizes on ADHD symptoms are small compared with established stimulant treatments, research suggests there are virtually no severe side effects of PUFA supplements. The most frequently reported side effects are dyspepsia and incidental nosebleeds .In addition, there have been reports of PUFA supplement products being highly oxidised, with oxidation levels exceeding recommended averages . This isResearch has also suggested that certain subsets of patients  may stand to benefit more than other groups of patients . It has It is evident that further high-quality research is needed to clearly evaluate and define the role of PUFA supplementation in the management of ADHD for children, adolescents and adults . First, Blood PUFA levels should be routinely analysed and monitored in future trials as it would allow researchers to study compliance, likely responders, and correlations between PUFA blood levels and ADHD symptoms. Furthermore, circumstantial findings suggest that individuals with certain dietary deficiencies may stand to benefit more from PUFA supplementation, yet, to our knowledge, no prospective investigation has taken place to test this hypothesis, and it should be a focus of future research. This information may enable patient stratification in the future.Additionally, future research should aim to clarify the difference in efficacy between omega-3 and omega-3/6 combination PUFA supplements. Future clinical trials should also include data on oxidation values as well as average measured contents of EPA and DHA in the supplements used in the studies.Much interest has been generated in identifying patient populations more likely to respond to PUFA supplementation. One study has suggested that PUFA supplements might have a higher impact on a subgroup of patients with the inattentive presentation and other neurodevelopmental problems . To thisOther unanswered questions exist regarding the optimal age in which to use PUFA supplements. In animal studies, where there is an existing omega-3 PUFA deficiency, it has been shown that maternal supplementation during the pre-/post-natal period restores processes affected by the deficiency if given prior to the 21st day of life , suggestInterest in PUFA supplementation as a possible treatment for a wide range of diseases and conditions has increased remarkably among the public and the media. Their growing popularity is likely attributable to their tolerable safety profile and concerns about the over-medicalisation of children.As a result, HCPs are increasingly asked by patients and their families about the role of PUFA supplements in neurodevelopmental disorders, such as ADHD. Commonly, PUFA supplements are requested by those who are not keen to use, would like to delay using or have not tolerated more traditional pharmacological treatments for ADHD. Many of these patients and families want to try PUFA supplementation as a first step, before starting a stimulant or other ADHD treatments. Some individuals request to use them in combination with stimulant treatment, either because they believe this will enhance the therapeutic effect or improve tolerability.In these scenarios, HCPs should ensure patients and their families are aware that, in all likelihood, PUFA supplements typically do not have as much effect on ADHD symptoms as stimulants but that they are generally well tolerated. HCPs should not necessarily advise patients and families against using PUFA supplements, so long as their use does not deter them from using first-line treatments which have a stronger evidence base. It is important to mention that PUFA supplements have been associated with minor dyspepsia.HCPs should also advise patients and their families to try to find the purest source of PUFA supplements available, ensuring that the preparation contains EPA, DHA and vitamin E (added to prevent oxidation of fatty acids) and that, ideally, they contain no flavours or colours. In situations where a patient wishes to use a PUFA supplement instead of stimulant medication, HCPs should advise them to take at least 750 mg of both EPA and DHA per day for at least 12 weeks before evaluating the response (recommendation of the expert panel). HCPs should discuss with patients and their families the available clinical evidence for PUFA supplements and other treatments to ensure they are making an informed choice.PUFA supplementation, in particular omega-3 PUFAs, may produce small but statistically significant reductions in ADHD symptoms while having a tolerable safety profile. Accumulating evidence suggests that they may offer benefits outside of ADHD symptom control, including improvements in sleep quality and cognitive function, but more research is needed to confirm these additional benefits. The variation in results from the meta-analyses conducted, however, highlights the need for caution when interpreting studies. Moreover, HCPs should consider each patient on an individual basis, taking into account individual preference, current ADHD severity and treatment history before discussing PUFA supplementation. In cases where PUFA supplements are used, HCPs should be comfortable explaining the potential gains that PUFA supplementation may have and its possible side effects. Furthermore, HCPs should not reinforce the idea that PUFA supplementation should replace treatment approaches with a more robust evidence base for managing ADHD.


Many studies have shown abnormal functional connectivity in children with attention deficit hyperactivity disorder (ADHD) by using resting-state functional magnetic resonance imaging (rs-fMRI). However, few studies illustrated that to what extent these findings were consistent across different datasets. The present study aimed to assess the consistency of abnormal functional connectivity in children with ADHD across the four datasets from a public-assess rs-fMRI ADHD cohort, namely, ADHD-200. We employed the identical analysis process of previous studies and examined a few factors, including connectivity with the seed regions of the bilateral dorsal anterior cingulate cortex, bilateral inferior frontal gyrus, and bilateral middle frontal gyrus; connectivity between default mode network and executive control network; stringent and lenient statistical thresholds; and the ADHD subtypes. Our results revealed a high inconsistency of abnormal seed-based connectivity in children with ADHD across all datasets, even across three datasets from the same research site. This inconsistency could also be observed with a lenient statistical threshold. Besides, each dataset did not show abnormal connectivity between default mode network and executive control network for ADHD, albeit this abnormal connectivity between networks was intensively reported in previous studies. Importantly, the ADHD combined subtype showed greater consistency than did the inattention subtype. These findings provided methodological insights into the studies on spontaneous brain activity of ADHD, and the ADHD subtypes deserve more attention in future studies. Attention deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders in children . It is ap < 0.05, cluster size > 10 voxels) (Voxel-wise metrics mainly include amplitude of low-frequency fluctuation (ALFF) , regiona voxels) . These fFunctional connectivity was one another widely used measurement in the rs-fMRI studies on ADHD. Functional connectivity was defined as the correlation between the time course of a particular brain region (seed region) and all other voxels in the brain , and it The seed-based functional connectivity and connectivity between ECN and DMN inform our understanding about the pathological mechanism of ADHD. However, to what extent the functional connectivity results are consistent across individual datasets remains unclear. To address this issue, the present study examined the abnormal functional connectivity based on the datasets of ADHD-200. ADHD-200 is one of the most widely used multi-site MRI cohorts of ADHD, and it contains 10 independent datasets from eight different sites . These dhttp://fcon_1000.projects.nitrc.org/indi/adhd200). The ADHD-200 cohort contains both functional and anatomical MRI data contributed by eight institutions. Each dataset was approved by the research ethics review boards of each institution. Signed informed consent was obtained from all participants or their legal guardian before participation.The data we used in this study are publicly available from the ADHD-200 Consortium  were also excluded because the TR of NeuroImage was not the same as the TR of the other four datasets. The PKU2 and PKU3 datasets only had male subjects, so the female subjects in NYU and PKU1 datasets were excluded to remove potential confounding effect of gender on the results. Left-handed subjects were also excluded from each dataset. There is no significant difference in age between children with ADHD and TDC across all datasets in the present study. After case-by-case age matching between ADHD and TDC, 58 subjects from NYU, 30 from PKU1, 56 from PKU2, and 38 from PKU3 were included in the current study. Demographic information of all subjects is summarized in The datasets were first selected according to the following criteria  and Resting-State fMRI Data Analysis Toolkit (REST) (http://www.restfmri.net). The first 10 time points were removed for signal stabilization and participant adaptation. And then, the number of left time points for NYU, PKU1, PKU2, and PKU3 is 170, 230, 230, and 230, respectively. The unified number of time points (first 170 volumes) was employed for all of the four datasets. Slice timing correction and image realignment to correct head motion were followed. The head motion criteria, that is, head motion <3 mm translation or <3° rotation in any direction, were employed, referring to previous studies (3) and smoothed with an 6 × 6 × 6 full-width-at-half-maximum (FWHM) Gaussian kernel. The head motion parameter measured by Friston-24 model, global signal effect, white matter (WM), and cerebrospinal fluid (CSF) signals were further regressed out as nuisance covariates. The time course of each voxel was linearly detrended and band-pass filtered with frequencies ranging from 0.01 to 0.08 Hz.The preprocessing was carried out using the Data Processing Assistant for Resting-State fMRI (DPARSF) , which it (REST)  . Moreover, asymmetry of the human brain was mentioned intensively . The mean time course of each seed region was extracted as reference time course. Then, the functional connectivity was calculated as Fisher’s Z-transformed Pearson correlation coefficient between the reference time course and the time course of each voxel in the brain.The functional connectivity analyses were performed based on the seed regions of interest (ROIs), including R_dACC, R_IFG, and R_MFG. The three seed regions were defined as a sphere with a 6-mm radius (34 voxels) centered at the coordinates reported by Weissman et al.  converteensively , 36, so p < 0.001, Gaussian random field (GRF) corrected). Then, the mean time courses were extracted based on the ECN and DMN masks in each subject. These masks were unified for the subjects of all the datasets, and therefore, there was no network difference across the datasets. The network connectivity was further calculated through the Pearson correlation between the mean time course of DMN and the mean time course of ECN.A public DMN mask created by Yeo et al.  was emplp < 0.001, GRF corrected), and the networks were constructed for each dataset. Functional connectivity with the seed region of PCC was calculated [6-mm spherical ROI centered at MNI coordinates: x = 1, y = −55, z = 17, reported by Vincent et al. .Functional connectivity maps of the seed regions of R_dACC, R_IFG, R_MFG, L_dACC, L_IFG, and L_MFG were compared between the groups of children with ADHD and TDC. Two-sample p < 0.05, cluster size > 10 voxels) was also used for each dataset.At the same time, to reduce the possibility of false-negative results, a more lenient threshold  based on Cohen’s equation :t-test, as follows,According to equation of independent two-sample d and t-value can be obtained, as follows:The relationship of Cohen’s  t maps into SES map for each dataset. The same threshold was applied to the SES maps of each dataset. A high level SES of 0.8 was used, which corresponded to t = 3.08, 2.16, 2.96, and 2.50  for NYU, PKU1, PKU2, and PKU3, respectively.According to Equation (3), we transformedt maps and SES maps were binarized and overlapped among the four datasets. The number of overlapped voxels across four and three datasets was quantified using the Dice overlap coefficient , PKU1, PKU2, and PKU3 used the ADHD Rating Scale (ADHD-RS) IV to determine the ADHD subtypes, and NYU used Conners’ Parent Rating Scale-Revised, long version (CPRS-LV), to identify the ADHD subtypes. There were 19, 6, 12, and 7 participants with the ADHD combined subtype, and 10, 9, 16, and 12 participants with the ADHD inattention subtype in NYU, PKU1, PKU2, and PKU3, respectively. Each subtype matched the health control with age. All the above analysis procedures were repeated based on the data of each ADHD subtype.In the current study, there were two ADHD subtypes in all of the four datasets, that is, the ADHD combined subtype and the ADHD inattention subtype. The information on subtypes was provided by ADHD-200 directly. According to the diagnostics illustration provided by ADHD-200  = 2.69, p = 0.01  The abnormal seed-based functional connectivity of ADHD was not consistent across datasets. (2) For each dataset, the negative connectivity between ECN and DMN did not show any significant difference between ADHD and TDC. (3) In a subtype analysis, the combined subtype showed more consistent results across datasets as compared with the inattention subtype.p < 0.05, cluster size > 10 voxels). Notably, the inconsistency could also be observed in three datasets from the same research site, PKU. Furthermore, in each dataset, the SES of the abnormal connectivity was small, and no overlaps of the SES maps were observed from more than three datasets. These findings suggest high inconsistency of abnormal functional connectivity in children with ADHD, and such inconsistency may be related to the heterogeneity of ADHD , the National Natural Sciences Foundation of China , the National Basic Research Program of China (973 program 2014CB846104), and Zhejiang Fundamental Public Welfare Research Program (LGJ19C090001). HZ is supported by Scientific Research Staring Foundation from Hangzhou Normal University.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.