The object of the current study is to explore the neural substrate for effects of atomoxetine (ATX) on inhibitory control in school-aged children with attention deficit hyperactivity disorder (ADHD) using functional near-infrared spectroscopy (fNIRS). We monitored the oxy-hemoglobin signal changes of sixteen ADHD children (6–14 years old) performing a go/no-go task before and 1.5 h after ATX or placebo administration, in a randomized, double-blind, placebo-controlled, crossover design. Sixteen age- and gender-matched normal controls without ATX administration were also monitored. In the control subjects, the go/no-go task recruited the right inferior and middle prefrontal gyri (IFG/MFG), and this activation was absent in pre-medicated ADHD children. The reduction of right IFG/MFG activation was acutely normalized after ATX administration but not placebo administration in ADHD children. These results are reminiscent of the neuropharmacological effects of methylphenidate to up-regulate reduced right IFG/MFG function in ADHD children during inhibitory tasks. As with methylphenidate, activation in the IFG/MFG could serve as an objective neuro-functional biomarker to indicate the effects of ATX on inhibitory control in ADHD children. This promising technique will enhance early clinical diagnosis and treatment of ADHD in children, especially in those with a hyperactivity/impulsivity phenotype. •We assessed the effects of atomoxetine administration to ADHD children using fNIRS.•Normal healthy control subjects recruited the right IFG/MFG during go/no-go tasks.•Pre-medicated ADHD children exhibited reduced right IFG/MFG activation.•The activation was acutely normalized by atomoxetine, but not by placebo.•The right IFG/MFG activation may serve as an objective neuro-functional biomarker. ADHD isThe non-stimulant drug, atomoxetine (ATX) as well as the stimulant drug, methylphenidate (MPH) have been recommended as primary medications for the improvement of executive function in ADHD patients . Conventin vitro studies, that ATX acts on the NA system, mainly located in the locus coeruleus with axonal projections to the prefrontal and parietal cortices , affordable price, tolerance to body motion and accessibility , which, Conversely, it is often difficult to assess neuroactivation patterns during locomotor tasks with fMRI-based neuroimaging, and this can often cause problems in the neuro-functional assessment of school-aged ADHD children with hyperactivity. In fact, the rejection rate of fMRI studies is high: one study enrolling a relatively young sample of children (6 years and older) rejected 50% of ADHD subjects and 30% of normal control subjects . The higThus far, several fMRI studies on the effects of ATX have provided evidence of up-regulation of middle and inferior frontal gyrus activation in healthy control subjects e.g., , as withThe lack of evidence associating a neuropharmacological mechanism with therapeutic improvement is tantamount to a missed opportunity for appreciating how ATX works, and such understanding is a vital step toward developing an objective, evidence-based neuropharmacological treatment for ADHD children. Thus we performed the current fNIRS study in order to assess acute neuropharmacological effects of ATX on inhibitory functions of ADHD children.In the current study, we enrolled sixteen ADHD children and age- and sex-matched control subjects, and examined the neuropharmacological effects of ATX on inhibition control, utilizing a within-subject, double-blind, placebo-controlled design. We hypothesized that the ADHD subjects would exhibit hypoactivation in the right middle and inferior frontal gyri in comparison with control subjects, and that ATX would normalize hemodynamic responses during a go/no-go task while a placebo would not.22.1Sixteen clinically referred, right-handed Japanese children with a mean age of 8.9 years  who met the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) criteria for ADHD participated in the study . The Wec2.2On each examination day, ADHD subjects underwent two sessions, one before drug (ATX or placebo) administration, and the other at 1.5 h after drug administration. Before each pre-administration session all ADHD subjects underwent a washout period of 2 days. We allowed subjects to take off the probe during waiting periods between the first and second sessions. Each session consisted of 6 block sets, each containing alternating go (baseline) and go/no-go (target) blocks. Each block lasted 24 s and was preceded by instructions displayed for 3 s, giving an overall block-set time of 54 s and a total session time of 6 min. In the go block, we presented subjects with a random sequence of two pictures and asked them to press a button for both pictures. In the go/no-go block, we presented subjects with a no-go picture 50% of the time, thus requiring subjects to respond to half the trials  and inhibit their response to the other half . Specifically, the instructions read in Japanese, “You should press the button as quickly as you can. Remember you want to be quick but also accurate, so do not go too fast.” Participants responded using the forefinger of the right hand. A go/no-go ratio of 50% was selected as it has been most often used in former neuroimaging studies . We presAfter ADHD subjects performed the first session, either ATX (Strattera) or a placebo was administered orally. The experimental design was as previously described . All pat2.3We calculated the average reaction times (RT) for go trials, and accuracy rates for go and no-go trials in each go/no-go block for ADHD and control subjects. We averaged the accuracy and RTs across go/no-go blocks, and subjected the resulting values to statistical analyses as described in a subsequent section. We calculated mean RT for each participant by taking the average of RTs for correct go trials in the go/no-go block. We computed accuracy for go trials by dividing the number of correct responses  by the total number of go trials for the go/no-go block. Similarly, we computed accuracy for no-go trials by dividing the number of correct inhibitions  by the total number of no-go trials in the go/no-go block. We set the statistical threshold at 0.05 with the Bonferroni method for multiple-comparison error correction .2.4We used the multichannel fNIRS system ETG-4000 , utilizing two wavelengths of near-infrared light (695 and 830 nm). We analyzed the optical data based on the modified Beer–Lambert Law  as previFor statistical analyses, we focused on the oxy-Hb signal because of its higher sensitivity to changes in cerebral blood flow than that of deoxy-Hb and total-Hb signals , its higWe set the fNIRS probes so that they covered the lateral prefrontal cortices and inferior parietal lobe, referring to previous studies . Specifi2.5We preprocessed individual timeline data for the oxy-Hb and deoxy-Hb signals of each channel with a first-degree polynominal fitting and high-pass filter using cut-off frequencies of 0.01 Hz to remove baseline drift, and a 0.8 Hz low-pass filter to remove heartbeat pulsations. Note that Hb signals analyzed in the current study do not directly represent cortical Hb concentration changes, but contain an unknown optical path length that cannot be measured. Direct comparison of Hb signals among different channels and regions should be avoided as optical path length is known to vary among cortical regions . Hence, 2.6post-pre and ATXpost-pre contrasts); and (4) inter-medication contrasts: differences between ATXpost-pre and placebopost-pre contrasts. To screen the channels involved in go/no-go tasks in normal control subjects, we performed paired t-tests (two-tails) on target vs. baseline contrasts. We set the statistical threshold at 0.05 with Bonferroni correction for family-wise errors. For thus-screened channels, we performed comparisons between control and ADHD for the following three ADHD contrasts: (1) pre-medication, (2) post-placebo, and (3) post-ATX. We performed independent two-sample t-tests (two-tails) on these contrasts with a statistical threshold of p < 0.05. To examine the medication effects on ADHD subjects, we performed paired t-tests (two-tails) with a statistical threshold of p < 0.05 for comparison between ATXpost-pre and placebopost-pre . We performed all statistical analyses with the PASW statistics (version 18 for Windows)  software package.We statistically analyzed oxy-Hb signals in a channel-wise manner. Specifically, for control subjects, who were examined only once, we generated a target vs. baseline contrast for the session. For ADHD subjects, we generated the following contrasts: (1) pre-medication contrasts: the target vs. baseline contrasts for pre-medication conditions (either placebo or ATX administration) for the first day exclusively; (2) post-medication contrasts: the respective target vs. baseline contrasts for post-placebo and post-ATX conditions; (3) intra-medication contrasts: differences between post- and pre-medication contrasts for each medication  comparisons are summarized in The average accuracy for go and no-go trials and RT for correct go trials in the go/no-go block for control and ADHD subjects and ADHD inter-medication  and control subjects, respectively. In ADHD subjects, Pearson's correlation coefficient was −0.043 (p = 0.871), while that in control subjects was −0.023 (p = 0.934): In neither analysis did we find any significant correlation with a meaningful effect size. Further, we compared the two correlation coefficients, but did not find any significant difference . This led us to conclude that there was no correlation between IQ and the activation in the right CH 10 in either group.44.1Our current study, using a double-blind, placebo-controlled, crossover design, provided the first fNIRS-based neuropharmacological evidence of the acute ATX effect on inhibitory control in school-aged ADHD children. Through assessing cortical activation data of ADHD and healthy control subjects performing a go/no-go task reflecting function of the motor-related inhibitory network, we revealed that the right IFG/MFG is a neural substrate of ATX effects in ADHD children based on the following findings. First, ADHD children exhibited reduced cortical activation in the right IFG/MFG during go/no-go task blocks compared to control subjects. Second, the reduction of right IFG/MFG activation was acutely normalized after ATX administration in ADHD children. Third, the ATX-induced right IFG/MFG activation was significantly greater than placebo-induced activation during go/no-go task blocks.The recovered right IFG/MFG activation in ADHD children detected by fNIRS measurements after ATX administration is consistent with our previous studies using MPH . These r4.2One of the most commonly used experimental paradigms for evaluating response inhibition is the go/no-go task, in which subjects are generally required to inhibit a prepotent response when no-go stimuli are presented within a sequence of go stimuli . This isIn general, a go/no-go task allows the assessment of detailed aspects of inhibitory response controls reflected in a variety of parameters : Errors These inconsistencies among the results of both studies represent the difficulty in interpreting behavioral parameters compared with brain activation patterns for detecting cognitive dysfunction in ADHD children.4.3In our current study, we detected brain activation in the right MFG/IFG during go/no-go task blocks in the healthy control subjects. This activation pattern is in accord with that found in previous fMRI studies, and this region is regarded as especially important for inhibitory control . This leIn ADHD conditions, ATX-induced normalization in the MFG/IFG, as identified using fNIRS, is consistent with former MPH-related studies . Also, tIn a different vein of studies using animals, both ATX and MPH led to increased NA and DA in the prefrontal cortex of mice  and ratsAccording to this evidence, we speculate that MPH has by far larger effects on the DA system between the prefrontal and striatal regions, while ATX has far larger effects on the locus coeruleus NA system between the prefrontal and coeruleus areas . Thus, w4.4In the present study, we selected a go/no-go task paradigm with alternating go blocks as baseline blocks and go/no-go blocks as target blocks without rest segments in between active (go and go/no-go) task blocks. Another merit of the block-design paradigm is that the baseline blocks serve as a motor control for the target blocks. Reminiscent of our study demonstrating the clinical utility of fNIRS-based assessment of the efficacy of an acute single dose of MPH to ADHD children, here ATX has been shown to be similarly effective: the current study demonstrates the utility of fNIRS-based assessment of the efficacy of an acute single dose of ATX administered to ADHD children. fNIRS-based assessment has a fundamental clinical importance as a diagnostic tool and for therapeutic encouragement. For the diagnostic aspect, we demonstrated that fNIRS-based measurement can reveal the effects of an acute single dose of ATX with higher sensitivity than can behavioral parameters. The moderately large effect size of the acute single dose of ATX as compared to that of the placebo (Cohen's d = 0.663) demonstrates that fNIRS-based assessment can serve as a comparably effective diagnostic tool for the effect of ATX in ADHD children, especially those at elementary-school ages.Moreover, fNIRS-based measurement could provide therapeutic encouragement to ADHD children and their families. One major problem of medication treatment, which is common with both AXT and MPH, is the high discontinuation rate estimated at between 36 and 85% . Since g4.5As discussed above, the current study has demonstrated the ATX-effect assessment on inhibitory control in ADHD children using fNIRS. However, for adequate understanding of current findings, several issues need to be addressed.First, IQs of control children  were significantly  higher than those of ADHD children . IQ has been reported as having a negative correlation with ADHD scores . Since IThe second limitation of this study is that controls were only tested once, while children with ADHD were tested a total of four times. The practice effect of multiple testing in ADHD children was controlled for by the counterbalanced design. Ethical limitations prevented us from testing healthy controls under stimulant medication, as well as from having them wait for 90 min to retest; however, we need to explore ways to eliminate potential training effects with appropriate experimental procedures. Since there are no studies on assessing order and learning effects of go/no-go tasks associated with fNIRS signals, this would be an interesting and essential area for future study.5The current study examining the effects of a single acute dose of ATX on inhibitory control in ADHD children using a double-blind, placebo-controlled, crossover design, revealed the following findings. First, the activation foci (right IFG/MFG), which are involved in inhibition control, were activated in control subjects performing a go/no-go task, but not in ADHD children. Second, the ATX-induced right IFG/MFG activation was significantly greater than placebo-induced activation during go/no-go task blocks. Third, the activation in the right IFG/MFG region was normalized after ATX administration. Taken together, these findings led us to conclude that the activation in the MFG/IFG could provide an objective neuro-functional biomarker that indicates the effects of ATX on inhibitory control in ADHD children. This fNIRS-based examination on the effect of ATX is applicable to ADHD children at elementary school ages including those as young as 6 years old. Thus, we believe that fNIRS-based examination is a promising clinical tool that could enable the early diagnosis and treatment of ADHD children.


Adult attention deficit hyperactivity disorder (ADHD) shows a robust association with alcohol and cannabis misuse, and these relationships are expressed differently in males and females. Manifestation of specific ADHD symptom profiles, even in the absence of the full disorder, may also be related to problems with alcohol and cannabis, although these relationships have not been investigated in epidemiological studies. To address this question, we studied the sex-specific associations of ADHD symptomatology with problematic alcohol and cannabis use in a representative sample of adults aged 18 years and older residing in Ontario, Canada.n = 5080) reported on current ADHD symptomatology, measured using the Adult ADHD Self-Report Version 1.1 Screener (ASRS-V1.1) and four additional items, and alcohol and cannabis use, which were measured using the Alcohol Use Disorders Identification Test (AUDIT) and the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST), respectively. Logistic regression analyses were conducted in men and women to test the association of each ADHD symptom cluster  with problematic alcohol and cannabis use.Data were obtained from the Centre for Addiction and Mental Health Monitor, an ongoing cross-sectional telephone survey, between January 2011 and December 2013. Respondents (After controlling for age, education, and comorbid internalizing and externalizing psychopathology, hyperactive symptoms were associated with problematic alcohol use in both men and women and with problematic cannabis use in men. Impulsive symptoms were independently associated with problematic cannabis use in men. By contrast, inattentive symptomatology predicted problems with alcohol and cannabis only in women. In all models, age was negatively associated with substance misuse and externalizing behavior was positively correlated and the strongest predictor of hazardous alcohol and cannabis use.ADHD symptom expression in adulthood is related to concurrent hazardous use of alcohol and cannabis. Distinctive ADHD symptom profiles may confer increased risk for substance misuse in a sex-specific manner. More individuals receive treatment for problematic alcohol and cannabis use than any other substance of abuse . Links bBy contrast, only a handful of studies have tested the association of ADHD symptom domains with substance use measures in non-clinical samples of adults. This research is a vital line of inquiry, since subthreshold ADHD phenotypes are likely more common than the clinical disorder and may also be associated with hazardous alcohol or cannabis use. Two studies that investigated samples of non-treatment seeking college students reported relationships between ADHD symptom clusters and substance use outcomes. One found a positive association of inattentive symptoms with alcohol use and cannabis misuse that was independent of comorbid internalizing and externalizing psychopathology , while tEpidemiologic study designs can improve upon these methodological limitations by providing estimates of key associations at a population level. To the best of our knowledge, only one cross-sectional, population-based study has analyzed ADHD symptom domains in relation to substance use outcomes . After cAnother important gap in the literature relates to the paucity of information on potential sex differences associated with ADHD symptom expression and substance misuse. Most population studies that examined ADHD diagnosis or symptomatology and substance use measures controlled for sex in the adjusted analyses and did not report on any sex-specific relationships –10. UndeTelephone interviews were conducted over 36 months between January 2011 and December 2013 in a similar manner as previously reported . InformeResults used in the analyses were based on “valid” responses to survey questions. That is, responses such as “don’t know” or refusals were treated as missing data and excluded from analyses. Overall, 994 individuals were excluded from the analyses due to missing data. The final sample included 5080 individuals who completed all study measures. Altogether, there were 2066 males (40.7 %) and 3014 females (59.3 %). Participant ages ranged from 18 to 97 years with a mean age of 54.4 ± 16.5 years. Regarding education, 31.8 % completed high school or less, 36.6 % completed some or all requirements for community college or a technical diploma, and 31.6 % completed some or all requirements for a Bachelor’s degree or higher.The ASRS-V1.1  is derivThe standardized Cronbach’s alpha for the full 10-item scale was 0.80, indicating good internal consistency . The CroThe AUDIT is an extensively validated 10-item, Likert-type screening instrument that was developed by the World Health Organization (WHO) and designed to identify individuals presenting less severe alcohol problems , 22. A sThe cannabis subscale of the ASSIST is a 6-item screening instrument that assesses risk of experiencing health, financial, legal, social, and relationship problems associated with cannabis use . A scoreThe GHQ12 is a 12-item screening instrument that captures current symptoms of depression, anxiety, and social functioning . Items aThe Antisocial Personality Disorder Scale from the Mini-International Neuropsychiatric Interview (MINI-APD) is a 12-item, dichotomous scale that assesses delinquent behavior and provided a measure of externalizing psychopathology . One iteSince increasing age relates to a decline in ADHD symptoms  and lowet-tests or the Mann-Whitney U test for those variables not following a normal distribution. Dichotomous variables were compared using chi-square tests. A series of logistic regressions were then applied to estimate the associations of problematic alcohol or cannabis use with ADHD symptom domains. Logistic regression was chosen, because we were interested in testing the relationship between ADHD symptom severity and alcohol and/or cannabis misuse as categorical outcomes. Forced entry logistic regression was employed, given that the models were theoretically-driven and there were relatively few predictor variables. For each dependent variable , three separate models were constructed, one for each ADHD symptom cluster  indexed by the ASRS-V1.1 screener and supplementary items. We considered entering inattention and hyperactivity/impulsivity symptom domains simultaneously in the regression analyses; however, we were interested in understanding the separate contributions of inattention, hyperactivity, and impulsivity symptom profiles in the current study. The specific inattention and hyperactivity/impulsivity factors, after the common variance was accounted for by a general factor model, have been interpreted as residual and unclear for interpretation [For each of the variables included in the analyses, comparisons were made between men and women in the sample. Continuous variables were compared using independent sample retation . Thus, wretation . All anaretation .Comparisons between men and women on demographic variables, measures of internalizing and externalizing psychopathology, substance misuse, and ADHD symptom cluster scores are presented in Table As depicted in Table Table As far as we are aware, this is the first population-based study of adults to examine the association of active hyperactive, impulsive, and inattentive symptomatology with problematic alcohol and cannabis use. Accumulating evidence from genetic studies suggests that conceptualization of ADHD symptomatology as a continuum of quantitative traits may be preferable to categorical approaches . AccordiOur results reveal that hyperactive, impulsive, and conduct disorder symptoms all predicted problematic alcohol and cannabis use in males, which agrees with previous research linking markers of behavioral disinhibition to risky alcohol and cannabis use in non-clinical samples composed mainly of men , 37. TakAmong the three ADHD symptom clusters, hyperactivity showed the strongest relationship with problematic alcohol use in females. This result is broadly consistent with results from a longitudinal design that detected a relationship between hyperactive symptoms assessed during childhood and indicators of alcohol misuse among adult females . AdditioIt is notable that externalizing psychopathology emerged as the strongest predictor of alcohol and cannabis misuse in every model tested, although relationships between ADHD symptomatology and substance misuse still persisted after controlling for conduct disorder symptoms. The associations between externalizing psychopathology and hazardous cannabis use were particularly robust. There is some debate in the literature as to whether associations between ADHD and substance misuse are mediated exclusively by conduct-disordered behaviors. For example, one longitudinal study of a non-clinical sample examined childhood behaviors in relation to adult substance use disorders and reported that oppositional but not ADHD symptom clusters predicted cannabis use disorders in adulthood . By contAn important clinical implication of our study is the potential for enhanced detection of problematic alcohol and/or cannabis use through identification of high ADHD symptom expression. Several reasons point to a growing awareness of adult ADHD in the general public , and froWe note several limitations of the present investigation common to most epidemiological surveys. First, given the cross-sectional study design, we are unable to make inferences about the direction of the relationship between ADHD symptom expression and problematic substance use. On the other hand, longitudinal studies have generally found that childhood ADHD predicts development of alcohol and cannabis use disorders in adulthood , suggestIn summary, our findings highlight a previously unreported nexus between active ADHD symptom cluster expression and problematic alcohol and/or cannabis use in a general adult population. These observations are of interest clinically, because they show that specific ADHD symptom profiles, even without evidence of the clinical disorder, are still associated with adverse health outcomes. Associations between ADHD symptom expression and hazardous substance use manifested differently in males and females, suggesting that sex effects are critical to understanding these relationships. Our results merit further study of subthreshold ADHD phenotypes to determine whether clinical intervention leads to improved health outcomes.


To assess the frequency of overweight and obesity in children and adolescents with autism spectrum disorder (ASD) and with attention deficit/hyperactivity disorder (ADHD) and their parents, in comparison with children and adolescents without developmental disorders.2 and obesity as a BMI higher than 30kg/m2.Anthropometric measures were obtained in 69 outpatients with ASD (8.4±4.2 years old), 23 with ADHD (8.5±2.4) and 19 controls without developmental disorders (8.6±2.9) between August and November 2014. Parents of patients with ASD and ADHD also had their anthropometric parameters taken. Overweight was defined as a percentile ≥85; obesity as a percentile ≥95; and underweight as a percentile ≤5. For adults, overweight was defined as a BMI between 25 and 30kg/mp<0.01) and z-score (p<0.01) than controls, and increased frequency of overweight and obesity (p=0.04). Patients with ASD and ADHD did not differ between them in these variables, nor regarding abdominal circumference. Parents of children with ASD and ADHD did not differ between themselves.Children and adolescents with ASD and ADHD had higher BMI percentile (Children and adolescents with ASD and ADHD are at a higher risk of overweight and obesity than children without developmental problems in the community. Nevertheless, whether this association is characteristic of ASD and ADHD or common to behavioral and developmental problems in general remains unclear. Furthermore, the association is likely to be bidirectional; that is, not only behavioral problems may lead to obesity, but obesity may be a risk factor for the development of behavioral and developmental problems.–Most studies of the nutritional status of young people and adults with ADHD reports a high frequency of overweight and obesity, as well as a mean body mass index (BMI) higher in patients with ADHD compared to controls without developmental disorders.–,Similarly, studies also reported that children and adolescents with ASD are more often overweight and obese.Despite these alarming data, there are no studies of the nutritional status of children with ASD and ADHD in Brazil. In addition, few studies have compared the BMI and/or the overweight frequency in different developmental disorders.In this context, the aim of this study was to evaluate the frequency of overweight and obesity in children and adolescents with ASD and ADHD and their parents.Children and adolescents seen in the outpatient clinics of ASD (n=69) and Attention Deficit (n=23) of the Psychiatry Service of the Hospital das Clinicas, Federal University of Minas Gerais (UFMG), Brazil, and their parents were invited to participate in this study. Data were collected between August and November 2014, and none of those invited declined to participate. All patients with ASD and ADHD met the diagnostic criteria of the DSM-5.Patients and controls were interviewed using a structured questionnaire to collect demographic (age and sex of child and guardians) and clinical data. Parents of children with ASD responded to the inventory Social and Communication Disorders Checklist (SCDC)2). Age and sex-specific BMI z-score and percentiles of patients and controls were calculated using CDC 2000 growth charts.2 and obesity as BMI over 30kg/m2.All subjects included in the study had their weight (kg) and height (m) measured at the time of interview. BMI was calculated using the formula: weight (expressed in kg) divided by height (expressed in meters) squared . Descriptive statistics were used to present the sociodemographic and clinical characteristics of the sample. Association between dichotomous variables was assessed with Pearson's chi-square or Fisher's exact test, as appropriate. Continuous variables were expressed as mean and standard deviation. All variables were tested for normal distribution using the Shapiro–Wilk test and no data had a normal distribution. Therefore, the differences between groups were compared using the Mann–Whitney test or Kruskal–Wallis test, as appropriate. Correlations were investigated using the Spearman coefficient. All p=0.66). Also, there was no difference in age between individuals with ASD , ADHD , and controls  (p=0.603).There was prevalence of male in the ASD (86.9%), ADHD (78.9%), and control (86.9%) groups. There was no statistically significant difference between groups (z-score and percentiles of controls were significantly lower than those of patients with ASD and ADHD (p=0.453).Age and sex-specific BMI and ADHD . Similarand ADHD . On the and ADHD . RegardiThe severity of ADS symptoms did not correlate with anthropometric measurements . In ADHDp=0.06) in participants taking risperidone. Of the 21 participants taking risperidone, 5 (23.8%) of guardians spontaneously reported seen a significant increase in appetite after drug initiation. Of the total 28 participants in use of methylphenidate, when faced with an open question on side effects, 13 (44.8%) guardians spontaneously reported that there was a significant decrease in appetite with the drug.Of ADHD patients, 20 (87%) were taking psychiatric drugs . Among Ap=0.34).Parents of participants with ASD and ADHD did not differ with respect to anthropometric measurements . There w–Overweight and obesity are public health problems in the general population. The incidence of many chronic diseases in adulthood is directly related to childhood obesity.Few Brazilian studies have investigated this issue. Domingues evaluated 30 children in a special school of Campo Grande and found that four (13.3%) were obese and seven (23.3%) were underweight.z-scores.Nascimento et al. found no difference in frequency of overweight among children and adolescents with “ADHD-indicative” and controls, or when comparing the BMI of both the groups.There are few published studies that compared BMI and frequency of overweight/obesity between developmental disorders. Curtin et al. performed a review of medical records of children and adolescents in care in a tertiary center for neuropsychiatric disorders and found a frequency of overweight and obesity of, respectively, 29% and 17.3% in ADHD patients and 35.7% and 19% in ASD patients.A common limitation of many studies of weight changes in people with ASD and ADHD is that the authors use only the BMI as base. Such an approach does not allow the direct measurement of body composition and/or distribution of body fat, there may be increased BMI because of increased muscle mass. Waist circumference measurement is easy to obtain and can indicate the presence of visceral adiposity in children.The severity of ASD and ADHD symptoms did not correlate with weight change. However, opposition and defiance symptoms negatively correlated with BMI percentile in ADHD participants. Korczak et al. noted that ADHD could predict obesity later in life, but according to the authors this association would be completely explained by the presence of behavior disorder in childhood.,Consistent with the medical literature, there was a trend towards the association of risperidone intake and higher BMI percentile in ASD patients. Increased appetite and metabolic alterations are common side effects of risperidone.,Finally, it was seen for the first time in the literature that parents of children with ASD and ADHD did not differ in BMI, waist circumference, and frequency of overweight/obesity. Although nearly half of parents are overweight/obese, unfortunately it was not possible to compare them with the control group because the children and adolescents of the control group were examined at school without the presence of their parents. Some studies suggest that obesity in parents is a risk factor for ASD and ADHD. However, more investigations are needed to assess factors underlying this possible association, such as genetic/epigenetic influence, family habits, inflammatory changes resulting from obesity during gametogenesis and pregnancy, among others.These results should be interpreted with caution. Due to its cross-cutting nature, one cannot infer causality between ASD, ADHD, and higher frequency of overweight and obesity. Furthermore, this study included a relatively small convenience sample of ADHD patients and controls. All patients were recruited from a single tertiary center where more complex cases with more pronounced symptoms of ADHD and ASD are usually treated, which could compromise the external validity of the study. Moreover, there were a significant proportion of underweight children in the control group, which highlighted a peculiarity of the sample involved in this work. The lack of waist circumference measurement in the controls and anthropometric measurement in their parents is also a limitation that should be mentioned. On the other hand, consecutive sampling, direct and careful measurement of anthropometric parameters of patients and community controls without developmental disorders, diagnosis and evaluation of patients by experienced clinicians, sample matched by gender and age, and the exclusion of comorbid cases of ADHD and ASD are strengths of the study that should be highlighted.In summary, this study showed that children and adolescents with ASD and ADHD followed-up in outpatient clinics are at increased risk of overweight and obesity than their typically developing peers. Drugs such as risperidone may have some causal role and patients taking these substances require close monitoring for metabolic changes. However, genetic and environmental factors  should also be considered. We emphasize that obesity and overweight are general risk factors for disorders and responsible for worsening the quality of life. Thus, it is very important that physicians routinely assess the weight of their patients with ASD and ADHD and give them advises on healthy living habits. ,A prevalência de sobrepeso e obesidade em países desenvolvidos é alarmante, atinge 31,8% das crianças e adolescentes.Estudos internacionais observam associação entre sobrepeso/obesidade infantil e transtornos psiquiátricos como o transtorno do espectro autista (TEA) e o transtorno do déficit de atenção/hiperatividade (TDAH). Apesar disso, não está claro se essa associação é própria do TEA e do TDAH ou comum a problemas comportamentais e desenvolvimentais de forma geral. Além disso, é possível que a associação seja bidirecional, ou seja, não apenas problemas comportamentais podem levar à obesidade, mas a obesidade pode ser um fator de risco para o desenvolvimento de problemas comportamentais e desenvolvimentais.-A maioria dos estudos sobre o estado nutricional de jovens e adultos com TDAH aponta para uma frequência elevada de sobrepeso e obesidade, bem como um índice de massa corporal (IMC) médio maior no grupo com TDAH em relação a controles sem transtornos desenvolvimentais.-,De modo similar, estudos também indicam que crianças e adolescentes com TEA têm sobrepeso e obesidade em maior frequência.Apesar desses dados alarmantes, não há estudos sobre o estado nutricional de crianças com TEA e TDAH no Brasil. Além disso, poucos estudos compararam o IMC e/ou a frequência de sobrepeso entre diferentes transtornos do desenvolvimento.Nesse contexto, o objetivo do presente trabalho foi avaliar a frequência de sobrepeso e obesidade em crianças e adolescentes com TEA e TDAH e seus pais.Crianças e adolescentes atendidos no Ambulatório de TEA (n=69) e no Ambulatório de Déficit de Atenção (n=23) do Serviço de Psiquiatria do Hospital das Clínicas da Universidade Federal de Minas Gerais (UFMG), Brasil, e seus responsáveis foram convidados a participar deste estudo. Os dados foram coletados entre agosto e novembro de 2014 e não houve recusa para participar de nenhuma das pessoas convidadas. Todos os pacientes com TEA e TDAH preencheram os critérios de diagnóstico do DSM-5Os pacientes e controles foram entrevistados por meio de questionário estruturado para a coleta de dados demográficos  e clínicos. Os pais das crianças com TEA responderam ao inventário Social and Communication Disorders Checklist (SCDC)2). Os percentis e escores-z do IMC específicos para a idade e gênero de pacientes e controles foram calculados a partir dos gráficos de crescimento do CDC 2000.2 e obesidade, IMC acima de 30 kg/m2.Todos os sujeitos incluídos na pesquisa tiveram seu peso (kg) e estatura (m) mensurados no momento da entrevista. O IMC foi calculado por meio da fórmula: peso (expresso em Kg) dividido pela estatura (expressa em m) elevada ao quadrado . Estatística descritiva foi usada para apresentar as características sociodemográficas e clínicas da amostra. Associação entre variáveis dicotômicas foi avaliada com o teste do qui-quadrado de Pearson ou o teste exato de Fisher, quando apropriado. Variáveis contínuas foram expressas como média e desvio padrão. Todas as variáveis foram testadas quanto à normalidade de distribuição por meio do teste de Shapiro-Wilk e nenhum dado apresentou distribuição normal. Portanto, as diferenças entre os grupos foram comparadas com o teste de Mann-Whitney ou Kruskal-Wallis, quando apropriado. Correlações foram averiguadas por meio do coeficiente de Spearman. Todos os valores de p foram bicaudais e o nível de significância de p<0,05 foi usado.As análises estatísticas foram feitas com o p=0,66). Também não ouve diferença de idade entre indivíduos com TEA , TDAH  e controles  .Gênero masculino foi a maioria no grupo com TEA , TDAH  e Controle . Não houve diferença estatisticamente significativa entre os grupos .O percentil do IMC e o escore-z específicos para sexo e idade dos controles foram significativamente mais baixos do que os dos pacientes com TEA e TDAH . AchadosA gravidade dos sintomas de TEA não se correlacionou com as medidas antropométricas . No grupp=0,06). Dos 21 participantes em uso de risperidona, 5  dos responsáveis relataram espontaneamente terem observado aumento significativo do apetite após início do fármaco. Do total de 28 participantes em uso de metilfenidato, frente a uma pergunta aberta sobre efeitos colaterais, 13  responsáveis relataram espontaneamente que houve diminuição significativa do apetite com o fármaco.Dos pacientes com TDAH, 20 (87%) estavam em uso de psicofármacos . Entre op=0,34).Os pais dos participantes com TEA e TDAH não diferiram estatisticamente com relação às medidas antropométricas . Também -O sobrepeso e a obesidade são problemas de saúde pública na população geral. A incidência de muitas doenças crônicas na vida adulta está diretamente ligada à obesidade na infância.et al. avaliaram 23 crianças e adolescentes autistas e observaram que três (13%) apresentavam baixo peso, cinco  tinham sobrepeso e seis  exibiam obesidade.Poucos trabalhos nacionais investigaram essa questão. Domingues avaliou 30 crianças de uma escola especial de Campo Grande e observou que quatro  estavam obesas e sete  com baixo peso.et al. não encontraram diferença na frequência de sobrepeso entre crianças e adolescentes com “indicativo de TDAH” e controles, nem ao comparar o IMC dos dois grupos.et al. relataram que todas as 70 crianças e adolescentes com TDAH avaliados no Hospital Universitário de Brasília eram eutróficos.Nascimento et al. fizeram revisão de prontuário de crianças e adolescentes em atendimento em centro terciário para transtornos neuropsiquiátricos e encontraram uma frequência de sobrepeso e de obesidade de, respectivamente, 29% e 17,3% em pacientes com TDAH e de 35,7% e 19% em pacientes com TEA.et al. tem a limitação de que as medidas antropométricas foram obtidas no prontuário, não houve padronização na forma de obtenção dos dados. Além disso, não havia grupo controle e não foram feitas comparações entre os grupos. Chen et al. avaliaram apenas a frequência de obesidade (percentil de IMC ≥95) em crianças e adolescentes com doenças crônicas  e encontraram frequência de 23,4% nos pacientes com TEA e 18,9% naqueles com TDAH.et al. também conta com uma série de limitações, como o uso de dados provenientes do National Survey of Children's Health (NSCH 2003), em que todas as informações foram coletadas por telefone; a possibilidade de o mesmo participante ter comorbidades, incluindo TEA e TDAH ao mesmo tempo; e não ter feito cálculo estatístico para comparar os grupos entre si. Mais recentemente, Philips et al. usaram dados do National Health Interview Survey (2008-2010) para comparar a frequência de baixo peso, sobrepeso e obesidade em adolescentes com vários transtornos do desenvolvimentoHá poucos estudos na literatura internacional que compararam transtornos do desenvolvimento entre si quanto ao IMC e à frequência de sobrepeso/obesidade. Curtin Uma limitação comum aos diversos estudos sobre alterações ponderais em pessoas com TEA e TDAH é que os autores tomam por base apenas o IMC. Tal abordagem não permite aferir diretamente a composição corporal e/ou a distribuição da gordura corporal, pode haver elevação do IMC em virtude de maior massa muscular. A aferição da circunferência abdominal é de fácil obtenção e capaz de indicar a presença de adiposidade visceral na população pediátrica.et al. haviam observado que TDAH poderia predizer obesidade na vida adulta, mas, segundo os autores, tal associação seria completamente explicada pela presença de transtorno de conduta na infância.A gravidade dos sintomas de TEA e TDAH não se correlacionou com as alterações ponderais. Porém, os sintomas de oposição e desafio se correlacionaram negativamente com o percentil do IMC nos participantes com TDAH. Korczak ,Condizente com a literatura médica, houve tendência de o uso de risperidona se associar com percentil mais alto do IMC nos pacientes com TEA. Aumento do apetite e alterações metabólicas são efeitos colaterais comuns da risperidona.,Por fim, observou-se, pela primeira vez na literatura, que pais das crianças com TEA e TDAH não diferem em relação ao IMC, circunferência abdominal e frequência de sobrepeso/obesidade. Apesar de quase metade dos pais estar com sobrepeso/obesidade, infelizmente não foi possível sua comparação com o grupo controle em virtude de as crianças e adolescentes do grupo controle terem sido examinados na escola, sem a presença de seus pais. Alguns estudos sugerem que a obesidade em pais e em mães são fatores de risco para TEA e TDAH. No entanto, são necessárias novas pesquisas para avaliar fatores subjacentes a essa possível associação, tais como influência genética/epigenética, hábitos familiares, alterações inflamatórias decorrentes da obesidade durante gametogênese e gestação, entre outros.Os resultados deste trabalho devem ser interpretados com cautela. Em razão de sua natureza transversal, não se pode inferir causalidade entre TEA, TDAH e a maior frequência de sobrepeso e obesidade. Além disso, este estudo incluiu uma amostra de conveniência relativamente pequena de portadores de TDAH e de controles. Todos os pacientes foram recrutados em um único centro terciário, onde casos mais complexos e com sintomas mais pronunciados de TDAH e TEA são normalmente atendidos, o que pode comprometer a validade externa do estudo. Além disso, houve, no grupo controle, uma proporção significativa de crianças com baixo peso, que ressaltou uma particularidade da amostra envolvida neste trabalho. A falta da medida de circunferência abdominal nos controles e das medidas antropométricas de seus pais também é uma limitação que devem ser mencionada. Por outro lado, a amostragem consecutiva, a aferição direta e criteriosa dos parâmetros antropométricos dos pacientes e controles da comunidade sem transtornos do desenvolvimento, o diagnóstico e avaliação dos pacientes por clínicos experientes, o pareamento da amostra por gênero e idade e a não inclusão de casos comórbidos de TDAH e TEA são pontos fortes do estudo que devem ser ressaltados.Em resumo, o presente estudo mostrou que crianças e adolescentes acompanhados em ambulatório com TEA e TDAH apresentam maior risco de sobrepeso e obesidade do que seus pares com desenvolvimento típico. Fármacos como a risperidona podem exercer algum papel causal e os pacientes em uso dessas substâncias necessitam de monitoramento próximo quanto a alterações metabólicas. No entanto, fatores genéticos e ambientais  também devem ser considerados. Ressalta-se que obesidade e sobrepeso são fatores de risco à saúde em geral e responsáveis por pioria da qualidade de vida. Dessa forma, torna-se de grande importância que clínicos façam rotineiramente avaliação ponderal e orientem seus pacientes com TEA e TDAH sobre hábitos saudáveis de vida.


The current model of ADHD suggests abnormal reward and punishment sensitivity, although differences in ADHD subgroups are unclear. This study aimed to investigate the effect of feedback valence (reward or punishment) and punishment magnitude  on Feedback-Related Negativity (FRN) and Late Positive Potential (LPP) in two subtypes of ADHD (ADHD-C and ADHD-I) compared to typically developing children (TD) during a children's gambling task.Children with ADHD-C (n = 16), children with ADHD-I (n = 15) and typically developing children (n = 15) performed a children's gambling task under three feedback conditions: large losses, small losses and gains. FRN and LPP components in brain potentials were recorded and analyzed.In TD children and children with ADHD-C, large loss feedback evoked more negative FRN amplitudes than small loss feedback, suggesting that brain sensitivity to the punishment and its magnitude is not impaired in children with ADHD-C. In contrast to these two groups, the FRN effect was absent in children with ADHD-I. The LPP amplitudes were larger in children with ADHD-C in comparison with those with ADHD-I, regardless of feedback valence and magnitude.Children with ADHD-C exhibit intact brain sensitivity to punishment similar to TD children. In contrast, children with ADHD-I are significantly impaired in neural sensitivity to the feedback stimuli and in particular, to punishment, compared to TD and ADHD-C children. Thus, FRN, rather than LPP, is a reliable index of the difference in reward and punishment sensitivity across different ADHD-subcategories. Attention deficit hyperactivity disorder (ADHD), which is the most prevalent childhood neuropsychiatric disorder, is defined in the current Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR) as developmentally inappropriate and impairing symptoms of inattention and/or hyperactivity-impulsivity Recent studies imply that ADHD is associated with an aberrant sensitivity to reinforcement Emotional-motivational dysfunctions are likely to contribute to ADHD, especially to hyperactive and impulsive symptoms. Regarding subgroup differences, ADHD-C and ADHD-HI in particular should show emotional-motivational dysfunction, while ADHD-I is less likely to show differences. A reduced responsiveness of the reward system was found to be associated with hyperactive-impulsive symptoms but not with inattentiveness The late positive potential (LPP) is a central-parietal positive slow ERP that reaches the largest amplitudes at 500–700 ms post-stimulus and lasts for several hundred milliseconds Numerous studies have reported that the human brain is especially sensitive to emotionally negative events, and that these events are preferentially processed relative to neutral and positive events Therefore, the present study investigated the monitoring of performance feedback coupled with score losses and gains in children with two subtypes of ADHD (ADHD-C and ADHD-I). In order to evaluate the effect of punishment on the monitoring of performance feedback, we manipulated the magnitude of punishment . Regarding the typically developing (TD) children, based on the outcomes of the study of van Meel and colleagues This study was approved by the Ethics Committee of Xiangya Second Hospital. Written informed consent was obtained from all the children and their parents. All participants were informed of their right to withdraw from the study at any time.The participants were 31 medication-free (stimulant-naive) children with ADHD (27 boys and 4 girls), aged 6–14 years, who were outpatients at the Clinic of Child Psychiatry of the Second Xiangya Hospital of Central South University. The inclusion criteria were as follows: meeting the DSM-IV-TR criteria and the Kiddie-Sads-Present and Lifetime Version (K-SADS-PL); no history of serious head injury, epilepsy, drug abuse or psychiatric disorders . The children with ADHD were classified into two subtypes: ADHD-I (n = 15), ADHD-C (n = 16). Fifteen TD children served as controls. The TD children were selected from local primary schools, and matched well with the ADHD group with respect to age and gender. The K-SADS-PL served to exclude TD children who displayed symptoms of ADHD. All participants reported normal or corrected-to-normal vision and were right-handed. Their full-scale IQ was above 80, according to the Wechsler Intelligence Scale for Children - Revised in China (C-WISC). The Child Behavior Checklist (CBCL) The symptoms at each ADHD cluster  were obtained from Swanson, Nolan, and Pelham Scale- version IV (SNAP-IV) We modified the gambling task according to the children's cognitive characteristics. The experiment was programmed and executed with E-prime . The task was administered under three reinforcement-contingency conditions: reward, small punishment and large punishment, which were operationalized as score gains and losses. In each trial, the participants were presented with two “doors” side by side (3000 ms) in the center of a black screen, following a 600–1000 ms central fixation cue. Participants were told that there was a happy face behind one door and a sad face behind the other door. Participants used a response box to make their choices. After an 800 ms interval, the feedback was displayed on the screen (1500 ms) by a number that indicated what the participants gained or lost. The happy face was always “+2” , while the sad face could be “−1”  or “-4” . The RD:LD:HD ratio was 6∶2∶2. All stimuli were randomly presented. If the participants did not respond within the required time (3000 ms), while the doors were on the screen, the computer would choose one door at random.The task took approximately 30 min and consisted of 10 blocks, with each block including 30 trials. The participants had a rest after each block. The children were told that they would be given the final reward according to the all rewards or punishments of the whole task. However, unknown to the children, happy faces and sad faces were randomly presented independent of their response. The children were simply told to “make as many scores as possible.” All subjects were provided with the same amount of compensation, 50 yuan RBM.F = 1.000, P = 0.371]. The averaged number of trials was 84.49 for TD group,78.98 for ADHD-I group, 70.85 for ADHD-C group. Additionally, there was no significant interaction effect between group and feedback . The average number of trials in the reward condition was 151.33 for TD group, 133.62 for ADHD-C group, 140.07 for ADHD-I group . In addition, the averaged number of trials in the small loss condition was 55.80 for TD group,51.53 for ADHD-I group, 48.81 for ADHD-C group . Lastly, the averaged number of trials during the large loss condition was 46.33 for TD group, 45.33 for ADHD-I group, 43.00 for ADHD-C group .The electroencephalography (EEG) measures were recorded continuously  from 36 scalp sites using Ag/AgC1 electrodes mounted on an elastic cap, according to the 10–20 international system. The array included 7 midline sites , 12 sites over each hemisphere , the left and right mastoids , and the horizontal electrooculogram  and the vertical EOG (FP2) electrodes to monitor the EOG bipolarly. All electrode impedances were kept below 5 kΩ. The EOG was recorded for the purpose of artifact correction; eye movement and blink artifacts were corrected using the Gratton et al. To assess the ERP waves elicited by feedback stimuli, we measured the average amplitude of FRN (250–350 ms) from Fz to Cz sites and the average amplitude of Lpp (400 ms–800 ms) from Pz site. A three-way ANOVA was conducted on the FRN component. ANOVA factors were feedback type , electrode site  and group . The same analysis was conducted for the LPP at Pz. The ERP data were analyzed using Brain Products Analyzer software. The degrees of freedom of the F-ratio were corrected according to the Greenhouse-Geisser method.F = 2.49, P = 0.049]. When controlled for age and IQ score, the feedback type by group interaction effect was still marginally significant . To further elucidate this interaction, we analyzed the feedback type effect in each group. In the TD group, the main effect of feedback type was significant , and large loss feedback elicited a larger negativity than did gain feedback  or small loss feedback , whereas no significant difference was observed between small loss and gain feedback . In the ADHD-C group, the main effect of feedback type was significant , large loss feedback elicited a larger negativity than did small loss feedback . However, no significant differences were observed between large loss and gain feedback , or between small loss and gain feedback . In the ADHD-I group, no significant main effect of feedback type was observed . In addition, we also broke down the feedback type by group interaction effect by analyzing the group effect during each feedback condition. No significant group effects observed during big loss feedback , small loss feedback , and gain feedback  conditions.The grand-average ERPs depicted in F = 6.17, P = 0.004]. To break down this interaction, we further analyzed the feedback type effect in each group, respectively. In the TD group, the main effect of feedback type was significant, and the large loss feedback effect is larger than small loss feedback effect . In the ADHD-C group, the main effect of feedback type was significant, and the large loss feedback effect is larger than small loss feedback effect . In the ADHD-I group, no significant main effect of feedback type was observed .In order to analyze the large loss and small loss feedback effect, we further subtracted the gain feedback from large loss and small loss feedback. The 2 ×2 ×3  ANOVA revealed a significant effect of feedback type by group interaction effect during 250–350 ms  and the feedback type by group interaction effect were not significant during 400–500 ms , but there was a significant main effect of group  during 400–500 ms. The LPP differences between the TD and ADHD-C , TD and ADHD-I  groups were not significant, but the LPP was larger in the ADHD-C group than in ADHD-I groups . However, the main effect of feedback type , group  and the feedback type by group interaction effect  were all non-significant during each 100 ms interval of the 500–800 ms intervals.In addition, the LPP component was also measured at 100 ms intervals during the 400–800 ms intervals at the Pz electrode site. When controlled for age and IQ score, the main effect of feedback type . This was consistent with a prior study by Carlson and colleague The present study observed an LPP component only in the early phase (400–500 ms) in children with ADHD-C, who showed an enhanced LPP amplitude to feedback indicating larger losses than TD children and children with ADHD-I. Furthermore, LPP has been reported to reach the largest amplitudes at 500–700 ms post-stimulus and to last for several hundred milliseconds There are some limitations to the interpretation of the current findings. First, of our study was the relatively small sample size, especially for female participants. There was only one girl in the ADHD-I group, three girls in the ADHD-C group and four girls in the TD group, which did not make it possible to examine the potential role of sex. Second, in our study we only recruited children with two subtypes of ADHD (ADHD-I and ADHD-C), and not the hyperactive/impulsive subtype (ADHD-H). Thus, we could assess only differences between the ADHD-I and ADHD-C subtypes. Finally, the children's gambling paradigm used in the present study was designed only for one reward condition (+2), and two different punishment conditions (−4 or −1). We probably should have designed two reward conditions. Future studies are needed to investigate whether the same results can be obtained when reward and punishment have an equal number of conditions.In conclusion, this is the first study to investigate to the effect of feedback valence and punishment magnitude on feedback negative and LPP in two subtypes of ADHD (ADHD-C and ADHD-I). In TD children and children with ADHD-C, large loss feedbacks evoked more negative FRN amplitudes than small loss feedbacks, suggesting that children with ADHD-C may keep intact brain sensitivity to the punishment and its magnitude. In contrast with the above two groups, the above FRN effect was absent in children with ADHD-I, suggesting that children with ADHD-I are significantly impaired in neural sensitivity to the feedback stimuli and in particular, to punishment. Secondly, the Late positive potential amplitudes were larger in children with ADHD-C in comparison with those with ADHD-I, regardless of feedback valence and magnitude. Therefore, we speculate that FRN, rather than LPP, is a reliable index to detect this difference across different ADHD-subcategories.


Although PI3Kγ has been extensively investigated in inflammatory and cardiovascular diseases, the exploration of its functions in the brain is just at dawning. It is known that PI3Kγ is present in neurons and that the lack of PI3Kγ in mice leads to impaired synaptic plasticity, suggestive of a role in behavioral flexibility. Several neuropsychiatric disorders, such as attention-deficit/hyperactivity disorder (ADHD), involve an impairment of behavioral flexibility. Here, we found a previously unreported expression of PI3Kγ throughout the noradrenergic neurons of the locus coeruleus (LC) in the brainstem, serving as a mechanism that regulates its activity of control on attention, locomotion and sociality. In particular, we show an unprecedented phenotype of PI3Kγ KO mice resembling ADHD symptoms. PI3Kγ KO mice exhibit deficits in the attentive and mnemonic domains, typical hyperactivity, as well as social dysfunctions. Moreover, we demonstrate that the ADHD phenotype depends on a dysregulation of CREB signaling exerted by a kinase-independent PI3Kγ-PDE4D interaction in the noradrenergic neurons of the locus coeruleus, thus uncovering new tools for mechanistic and therapeutic research in ADHD. E Darcq & BL Kieffer (July 2015)See also:


N = 494). Self-reported photophobia was prevalent in 69% of respondents with, and in 28% of respondents without, ADHD (symptoms). The ADHD (symptoms) group wore sunglasses longer during daytime in all seasons. Photophobia may be related to the functioning of the eyes, which mediate dopamine and melatonin production systems in the eye. In the brain, dopamine and melatonin are involved in both ADHD and circadian rhythm disturbances. Possibly, the regulation of the dopamine and melatonin systems in the eyes and in the brain are related. Despite the study’s limitations, the results are encouraging for further study on the pathophysiology of ADHD, eye functioning, and circadian rhythm disturbances.Many adult outpatients with attention-deficit/hyperactivity disorder (ADHD) report an oversensitivity to light. We explored the link between ADHD and photophobia in an online survey ( From clinical experience, we learned that a substantial number of adult patients with attention-deficit/hyperactivity disorder (ADHD) wear sunglasses throughout the year, even on overcast days. Many of these patients report a sensitivity or even oversensitivity of their eyes to bright light. Besides this clinical observation of photophobia, there are a number of studies indicating a link between ADHD and other optical dysfunctions. In children with ADHD, 76% have reduced visual acuity, caused by more strabismus (cross-eyedness), subnormal stereoacuity (depth detection), convergence insufficiency, and smaller optic disks . AnotherFrom chronobiology studies, we know that there is a link between retinal function and the circadian rhythm. The intensity of the light reaching the intrinsic photosensitive retinal ganglion cells (ipRGC) in the retina is signaled directly to the suprachiasmatic nuclei (SCN) of the brain, which is then translated into information about the time of the day , 6. The The combination of our clinical experience and the findings in the available literature suggest that there may be an increased prevalence of visual problems and photophobia in adults with ADHD. In order to study a possible link between photophobia and ADHD, we initiated a short-online survey in a large group of adults with and without ADHD (symptoms). We also explored if a delayed sleep phase (late chronotype) was related to photophobia. Results from this study can be used as a first exploration of the possible link between ADHD symptoms, chronotype, and eye functioning in general, in adults with and without ADHD (symptoms).We invited participants with and without ADHD (symptoms) from the Dutch general population to fill in our online survey, via websites of ADHD patient organizations and our social media accounts (Facebook© and Twitter©). Also, therapists from our outpatient Adult ADHD clinic invited their ADHD patients to participate in our study by emailing them the link to the survey.www.thesistools.nl (survey no longer available online). The survey consisted of the complete list of the following questions: a multiple choice question on having a diagnosed ADHD ; an item on having photophobia apart from any migraine episodes ; the effect of light on the eyes if one had photophobia ; if one had photophobia, the number of years one has had it; if one had photophobia, which measurements one takes ; the average number of hours per day in every season one wears sunglasses; and one’s chronotype (“Are you a morning or an evening person?”) that was scored on a five-point Likert scale (1 = definitely a morning type to 5 = definitely an evening type). We collected the following background information: age; gender; type; and dose of medication use ; and wearing glasses or contacts (yes or no). We also collected information on possible confounders for photophobia that are known from the literature: having an eye disease or disorder (yes or no); comorbidity ; and having had chemotherapy (yes or no) (The study was conducted in July 2013 and consisted of a very short (<5 min) self-composed and non-validated online survey in Dutch, using software by s or no) . The surWe used Chi-square analysis to compare categorical variables between the groups with and without ADHD (symptoms). In order to determine if any of the main and interaction factors significantly added to the odds of photophobia, we entered the relevant explanatory variables into a single binary logistic regression with photophobia as the dependent variable. The model included the following explanatory variables (reference categories between brackets): female gender ; age >40 years (≤40 years); ADHD group (controls); extreme evening chronotype (other chronotype); eye disease (no eye disease); contacts or glasses (no contacts or glasses); reporting migraine (no migraine); reporting SAD (no SAD); reporting chronic fatigue (no chronic fatigue); interaction effect of gender and age; interaction effect of ADHD and SAD; interaction effect of extreme evening chronotype and SAD. Because the SPSS Version 20.0 for Windows  was used for all statistical analyses, and α = 0.05 was used to indicate statistical significance.N = 494 participants eligible for analysis, see Table 2 = 3.9, df = 1, p = 0.048). The control group was on average slightly older, but not significantly . The groups did differed in their prevalence of use of glasses or contact lenses . Some possible confounders that were asked in the survey were very low prevalent , thus, these are reported as “Other confounding factors” in Table In total, 543 participants filled out the surveys, of which 49 were excluded from analysis due to incomplete surveys . This resulted in a total of 2 = 80.4; df = 1; p < 0.001), see Table 2 = 3.6; df = 1; p = 0.057). Photophobia was a life-long condition in 73% of the photophobia cases, and this was not significantly different between ADHD and non-ADHD groups. Bright light caused an unpleasant sensation in the eyes in 73% of the cases, headache or pain in the eyes in 46% of cases, and dryness of the eyes in 25% of cases. The ADHD group reported to wear sunglasses 2.3 h in spring ; 4.0 h in summer , 1.4 h in autumn , and 1.0 h in winter , see Table Self-reported photophobia was prevalent in 69% of participants in the ADHD group, vs. 28% in the control group  , and eye disease  were related to a higher odds of photophobia. There was a tendency for higher odds of photophobia for the use of contact lenses or glasses , and having  affective disorder . Contrary to our expectation, extreme evening chronotype had a tendency toward a lower odds of photophobia , and migraine was not related to higher odds of having photophobia . Other factors were also not significantly related to photophobia, and we did not find any interaction effects.We have entered all relevant explanatory variables into a single binary logistic regression model with photosensitivity as the dependent variable, see Table This preliminary study shows a strong relationship between photophobia and ADHD (symptoms). Also, the ADHD group more frequently reported the use of contacts and glasses, and wearing sunglasses longer during the day in every season than the non-ADHD group. The photosensitivity was not significantly related to seasonal affective disorder (SAD) in our study; however, there was a tendency. A recent study by Roecklein et al. showed that patients with SAD have a weaker pupil response to blue vs. red light as compared to healthy controls, allowing more light to reach the retina, which may be experienced as oversensitivity to light .These preliminary results should be interpreted in the light of the limitations of the study. The main limitation of our study is that we used an online survey, which has some methodological disadvantages with regards to selection of participants, in which the control group may not reflect the general population and the patient group may not reflect the general ADHD population, and also regarding unknown response quality and unverifiable self-report of diseases. Also, the survey may have lacked clarity in the formulation of photophobia, other than being oversensitive to light in general. We have hypothesized that the oversensitivity to light in ADHD may have been related to a behavioral adaptation such as avoiding daylight and wearing sunglasses, which in turn may prevent entrainment of the biological clock to daylight, leading to a further delay of the already delayed circadian rhythm. In the Van Veen study, there was a prevalence of 78% delayed sleep phase in a group of adults with ADHD , which are involved in the pupillary response to light and the sensitivity of the eye to light at the one hand, and in the synthesis of dopamine and melatonin in the retina at the other hand , 17. PosThe Review Editor, Eus J. W. Van Someren declares that, despite having collaborated with authors Denise Bijlenga and J. J. Sandra Kooij, the review process was handled objectively and no conflict of interest exists. Dr. J. J. Sandra Kooij reports having received lecture fees from Janssen B. V. and Lilly B. V. and unrestricted research grants from Janssen B. V. and Shire B. V.; all of these for other studies. Dr. Denise Bijlenga reports no financial interests or potential conflicts of interest.


These bacteria may cause paucisymptomatic bacteremia and endocarditis in humans. Bartonella species are known to cause afebrile bacteremia in humans and other mammals, including B. quintana, the agent of trench fever, and B. henselae, the agent of cat scratch disease. Reports have indicated that animal-associated Bartonella species may cause paucisymptomatic bacteremia and endocarditis in humans. We identified potentially zoonotic strains from 6 Bartonella species in samples from patients who had chronic, subjective symptoms and who reported tick bites. Three strains were B. henselae and 3 were from other animal-associated Bartonella spp. . Genomic analysis of the isolated strains revealed differences from previously sequenced Bartonella strains. Our investigation identifed 3 novel Bartonella spp. strains with human pathogenic potential and showed that Bartonella spp. may be the cause of undifferentiated chronic illness in humans who have been bitten by ticks.Certain  Bartonella spp. cause varied and multifaceted human diseases, including cat scratch disease (B. henselae), Carrion’s disease (B. bacilliformis), trench fever (B. quintana), endocarditis (B. quintana and B. henselae) (B. quintana and B. henselae), and hepatic peliosis (B. henselae). Bartonella spp. can also cause prolonged intra-erythrocytic bacteremia in both humans and animals .In this context, we screened for the presence of During January–June 2013, we conducted a study of a cohort of 66 French patients who had consulted their doctors for chronic symptoms appearing after a tick bite. The entire study protocol was approved by the ethics committee of the Institut Federatif de Recherche 48 under reference >3 months before the study. All patients associated symptom onset with tick bites that occurred during 2008–2012 . At sympWe collected blood samples from each patient in EDTA-containing sample tubes. For a control population, we used anticoagulated blood samples from 70 anonymous healthy blood donors from Paris (France). All samples (control and patients) were tested simultaneously. Bartonella spp., 100 μL of blood samples from patients or healthy donors were directly plated onto sheep blood agar plates and incubated at 35°C in a humidified atmosphere with 5% CO2 for 45 days. The plates were assessed daily from days 7–45 before the culture was deemed negative   default parameters.We extracted genomic DNA from each isolated strain by using the EZ1 automated extraction system , following the manufacturer’s recommendations. Bacterial genomic DNA was sequenced by using the Nextera XT DNA sample prep kit  and a 2×250 paired-end protocol with the MiSeq pyrosequencer (Illumina), according to the manufacturer’s instructions. We aligned each genome by using Mira version 3.2 software in the mapping mode (Bartonella strains by using GGDC software (Single-nucleotide polymorphisms (SNPs) among genomes were identified by using SNIT software , we had access to 2 blood samples that were taken at a 1-month interval. B. henselae was grown from the 2 samples, with similar bacteremia , suggesting chronic bacteremia.Bacteremia in the Bartonella  were classified within the B. henselae species on the basis of both their phylogenetic position and gltA and rpoB sequence similarities  DNA in 96 cases, including 2 co-infected with B. henselae (B. vinsonii berkhoffii (an agent of canine bacteremia and endocarditis) DNA in 24 cases (B. henselae and 2 cases of B. melophagi (http://www.mediterranee-infection.com/article.php?laref=14&titre=collection-de-souches) and are available upon request under references B546, B547, B548, B549, B550, and B551 for isolates MVT01, MVT02, MVT03, MVT04, MVT05, and MVT07, respectively.This work is similar to that of E.B. Breitschwerdt et al. . B. schoenbuchensis is normally found in deer, elk, and cattle  is particularly arduous and may require 6 weeks of doxycycline treatment together with 3 weeks of gentamicin, as these are the only antimicrobial drugs known to be effective in eradication of Bartonella (Bartonella spp. can also cause endocarditis, including B. quintana and B. henselae; therefore, reports of rare cases of endocarditis attributed to zoonotic Bartonella such as B. kohlerae, B. alsatica, Candidatus B. mayotimonensis, B. vinsonii, or B. elizabethae may actually be the final manifestation of asymptomatic bacteremia, similar to that reported by our infected patients (The significance of these Bartonella other than B. quintana in the blood of patients with poorly qualified syndromes. These results indicate that zoonotic Bartonella spp. infection may cause undifferentiated chronic illness in humans.In summary, our major finding is the isolation of zoonotic


Approximately, one-third of male adolescents in treatment for a substance use disorder (SUD) also have an Attention-Deficit Hyperactivity Disorder (ADHD). This strongly suggests that ADHD is a major risk factor for the development of SUD which practitioners must address if they are to provide adequate treatment for adolescents with SUD/ADHD. This paper supports a causal role for ADHD in the development of SUD and examines the developmental mechanisms whereby ADHD increases risk for SUD. These mechanisms include increased risk for conduct disorder, academic failure, deviant peer affiliation, engaging in risk behaviors, and self-medication. Assessment and treatment recommendations for those comorbid for SUD/ADHD are provided. Substance use, which includes smoking, drinking alcohol, or using other addictive substances, exists on a continuum ranging from no use on one end, to use that does not involve negative consequences, to risky use, to a substance use disorder (SUD) . SUD is n = 600), the Cannabis Youth Treatment Study (CYT), only 25% were in recovery at a 1-year followup, defined as no substance use or dependence problems and living in the community [Despite being the most important public health problem, only 15.4% of adolescents with SUD receive treatment . Indeed,ommunity . Similarommunity  and brieommunity . An impoommunity . As the ommunity –13. Despite this high rate of comorbidity, ADHD often goes untreated in adolescents with SUDs . Hence iADHD is the most common neurodevelopmental disorder in juveniles  with a pLastly, as van-Emmerik-van Oortmerssen and colleagues , as wellThe best evidence that sole reliance on self-report results in a substantial underestimate of ADHD comes from the follow-up study into young adulthood (age 21) of 147 males who had previously been diagnosed with ADHD in a childhood . Using aIn summary, ADHD prevalence rates for adolescents in treatment with an SUD range from 25% to 50%. Moreover, because assessment for ADHD in most studies failed to obtain information from parents and teachers, most studies probably underestimated the true prevalence rate of ADHD. Given this wide range and the high probability of underdiagnosis, Molina , one of Among the various conceptualizations that have been suggested to explain this comorbidity, two have the most research support: the secondary substance abuse disorder model and the common factor model . The secThere is a robust consensus, including two recent meta-analytic reviews, that ADHD is a major risk factor for the development of SUD , 26, 27.Four distinct risk mechanisms, discussed in order of importance, are operative in this model. The first is a cascading sequence in which ADHD increases risk for the development of the disruptive behavior disorders of oppositional defiant disorder (ODD) and conduct disorder (CD), thereby increasing the risk for the development of SUD, in part through association with deviant peers. The second is increased risk for school failure caused by ADHD leading to association with deviant peers. The third is that the behavioral and emotional impulsivity of ADHD, independent of comorbid CD, increases risk for SUD. The fourth is the use of legal and illegal substances to self-medicate ADHD symptoms. It is widely acknowledged that the deviance proneness of children with CD increases risk for the development of SUD . AlthougIt is widely acknowledged that behavioral impulsivity is a core impairment in ADHD . HoweverPerhaps the most persuasive evidence that, because ADHD is a disorder of impaired executive functioning, that is, impaired self-control/self-regulation , it incrThe role of ODD as a developmental precursor to CD has been well documented –48. Moreoften argues with adults, often actively defies or refuses to comply with adult's requests or rules, which index a “headstrong” dimension, predict CD [In addition, there is emerging evidence that there are subdimensions of ODD symptomatology that are not equally associated with the risk of developing CD . The symedict CD . The “heedict CD  and thusAs a consequence of this pathway, 22% of those with ADHD develop CD based upon combining data from community and clinical samples . FurtherSchool failure has long been recognized as a risk factor for SUD . Academi ADHD increases risk for academic failure in the following ways. First, the severe impairments in selective attention, working memory, and sustaining attention that characterize ADHD adversely affect academic performance . SecondlAlthough the increased risk that ADHD poses for the development of CD is the most important pathway that leads SUD, it is clear that ADHD can increase risk for SUD independent of increasing risk for CD , 62–65 tThe biological basis of this self-medication can be explained by the linkage of ADHD and substances to the neurotransmitter dopamine. There is consistent research support that links ADHD to a deficiency in dopamine , 68. AlsInterviewer: What is it like when you go to school high?Client: I can sit there and it helps me concentrate. It's like medicine.Interviewer: How does it help you concentrate?Client: I do not know, it just does. I can concentrate.Interviewer:  Do you have concentration problems otherwise?Client: Yeah.Interviewer: Can you explain those to me?Client: I do not know, like I get distracted easily but when on weed I focus more.Interviewer: Will you tell me more about being distracted?Client: I do not know. I do not, like…pay attention. I'm fidgety. I cannot, like, when I do not smoke weed all I do is like shake my leg or something. I cannot calm down. I use it more—I think I use it more as a medicine than I do to have fun.Lastly, perhaps the most impressive evidence that some SUD has it origins as self-medication comes from research on nicotine  and ADHD. Since cigarette smoking has been shown more to be more consistently associated with childhood ADHD than any other substance and less likely than other substances of abuse to have this association explained by CD or antisocial comorbidity, it suggests that the ADHD-tobacco association may be explained by a vulnerability specific to nicotine rather than access to drugs of abuse in deviant peer groups . The posThe common factor model posits that high rates of comorbidity are the result of shared risk factors . With reImpulsivity refers to the difficulty in withholding a prepotent response  . With reSensation-seeking can be defined as the seeking of varied, novel, complex, and intense sensations and experiences and the willingness to take physical, social, legal, and financial risks for the sake of such experience . As with Sensation-seeking is thought to result from an impairment in the dopamine reward system that characterizes ADHD and SUD , 77, 85.Unfortunately adolescents with comorbid disorders often fail to receive effective treatment, if any at all . If this Assessment for ADHD should be integrated into a comprehensive psychiatric, addictive, social, cognitive, educational, and family evaluation . FailureFirst, all of the adolescent's existing documentation should be examined for a prior diagnosis of ADHD in childhood. If it does contain a prior diagnosis, a referral for a more comprehensive confirmatory evaluation is warranted since most children diagnosed with ADHD continue to have the disorder into adolescence , 88.  Second, since acute intoxication or withdrawal symptoms may mimic ADHD symptoms, such as impulsive behaviors, concentration difficulties or restlessness , at leas Third, if the prior screening suggests the possibility of ADHD, the adolescent should be referred to an expert for a confirmatory evaluation. If a diagnosis of ADHD is made, it is essential to treat this disorder along with the SUD in an simultaneous, integrated approach, with SUD treated first , 11, 86.First, some concerns can be laid to rest. The concern of whether the widespread use of stimulant medications to treat children with ADHD increases risk for SUD later in life has been decisively answered. A substantial body of literature has found that stimulant treatment begun in childhood or early adolescence does not increase susceptibility to SUD , 86, 94.Second, legitimate concerns regarding safety and misuse should be addressed by a careful monitoring for signs of possible abuse or diversion such as missed appointments, repeated requests for higher doses and a pattern of “lost” prescriptions . Problemn = 42 subjects and five controlled, n = 557 subjects) [There have been only a few studies to date which have combined medication and psychological treatment  , 94 withubjects) , 98, 100ubjects) , 94. The literature provides robust support for the extensive agreement that ADHD is a major risk factor for the development of SUD. This risk results in approximately one-third of male adolescents in treatment for SUD being comorbid for ADHD. The developmental mechanisms whereby ADHD increases risk for SUD include increasing the risk for conduct disorder, academic failure, deviant peer affiliation, engaging in risky behaviors, and self-medication. This widespread comorbidity indicates that assessment for ADHD should be integrated into a comprehensive psychiatric, addictive, social, cognitive, educational, and family evaluation which should be provided for all males with SUD. If a diagnosis of ADHD is made, it is essential to treat this disorder along with the SUD in an simultaneous, integrated approach. Integrated treatment of SUD/ADHD has just begun, and much work needs to be done to develop and evaluate efficacious strategies.


Trachurus trachurus, Trachurus picturatus, and Trachurus mediterraneus, which are widely consumed in Spain. Principal component analysis suggested that the variable Cr was the main responsible variable for the identification of T. trachurus, the variables As and Sn for T. mediterraneus, and the rest of variables for T. picturatus. This well-defined discrimination between fish species provided by mineral element allows us to distinguish them on the basis of their metal content. Based on the samples collected, and recognizing the inferential limitation of the sample size of this study, the metal concentrations found are below the proposed limit values for human consumption. However, it should be taken into consideration that there are other dietary sources of these metals. In conclusion, metal contents in the fish species analyzed are acceptable for human consumption from a nutritional and toxicity point of view.The aim of this study was to measure selected metal concentrations in  Chromium (Chr), copper (Cu), iron (Fe), manganese (Mn), and zinc (Zn), among other metals, are essential micronutrients for humans  involvedApart from occupational exposure to heavy metals, the population is primarily exposed to these metals via the diet . For exaTrachurus trachurus), blue jack mackerel (Trachurus picturatus), and Mediterranean horse mackerel (Trachurus mediterraneus). All three belong to the family of Carangidae, which includes a variety of species with the anatomic characteristics typical of fish with high fat content [ Trachurus trachurus, Trachurus picturatus, and Trachurus mediterraneus, which are widely consumed in Spain. The final goal of this study was to determine the correlation between metal concentrations in these fish species and human nutrition and health.Horse mackerel is one of the most consumed commercial fish in Spain. Three species are marketed under the name of horse mackerel: Atlantic horse mackerel  were prepared from standard vials. Standard reference material  was used.All reagents were of analytical reagent grade. Double deionized water was used for all dilutions. Nitric acid (65%), hydrogen peroxide (33%), vanadium pentoxide, and sodium borohydride were of suprapure quality . All plasticware and glassware were cleaned by soaking in nitric acid (10%) and rinsed with double deionized water prior to use. Stock standard solutions, containing 1000 mgLA Thermo Fisher/Unicam Solaar M5  atomic absorption spectrometer was used, which was fitted with Termo Fisher Scientific Unicam Mseries-Solaar M5 with GF95 graphite furnace and a VP90 Vapour System. Atomic absorption spectroscopy and atomic emission spectroscopy were performed to determine the presence of metals. The metals identified by atomic absorption spectroscopy were Ca, Mg, Zn (flame technique), Cu, Fe, Mn, Cr, Sn, Al, Cd, Pb (graphite furnace technique), As (hydride generation technique), and Hg (cold vapor technique). Atomic emission spectroscopy revealed the presence of Na and K (flame technique). For flame measurements, air/acetylene flame was used. For graphite furnace measurements, argon was used as inert gas. A deuterium arc lamp background corrector was used for the elements analyzed by atomic absorption spectroscopy with the graphite furnace technique and the hydride generation technique. The operating parameters for working elements are given in Tables  Trachurus trachurus (n = 48), Trachurus mediterraneus (n = 45), and Trachurus picturatus (n = 49). All samples included a sufficient number of individuals to minimize errors due to individual variations. Samples were purchased in local markets and large supermarket chains in Granada (Spain) and had not been necessarily caught in Granada coastal waters. They were randomly purchased independent of their geographical origins. Fish samples were packed in polyethylene bags and stored below −20°C until analysis.Between June and July 2010, samples were obtained from the following fish species:3 , 1 mL of H2O2 at 33%, and 5 mL of double deionized water. Once in the microwave vessels, digestion was performed as follows: maximum power 1000 w and initial temperature 20°C. After 20 minutes, the sample reached a temperature of 200°C, which was maintained for 20 minutes. Subsequently, the sample was cooled for a further 20 minutes. A blank digest was carried out in the same way. The accuracy of the method was checked by analyzed certified reference material.A total of 200 g of edible tissue was filleted and dried in the microwave. Next, the samples were powdered using an agate mortar to prevent potential contamination of samples. Once the samples were powdered and homogenized, they were stored in polyethylene bottles at 5°C. Samples of 0.5 g were weighed in digestion vessels in triplicate adding 4 mL of HNOP < 0.05. Principal components analysis (PCA) was performed on data.Data analyses were performed using the statistical package SPSS . Metal concentrations were expressed as milligram and microgram per gram wet weight (ww). Values are given in means ± standards deviation (SD). Metal concentrations in different species were compared using one-way analysis of variance (ANOVA). Samples were considered significantly different at The accuracy and precision of analytical measurements were ensured using blank samples and fish protein certified reference material for trace metals. The results showed a high level of agreement between the certified and the analytical values  and conf Trachurus species. Although average concentrations of Al, Cr, and Ni did not differ significantly among species, there were statistically significant differences (P < 0.05) in metal concentrations among the species studied. Thus, the present study revealed that metal accumulation in fish is species specific. Toxic metal concentrations did not exceeded permissible limits in any of the samples. T. picturatus was found to have significantly higher values of these metals as compared to the remaining two species  and cadmium (0.321 ± 0.073) significantly higher than the other species studied.Lead is a ubiquitous toxic element, which is introduced into the environment by natural and anthropogenic processes. The natural contribution of lead comes from erosion of the Earth's crust and dust transport under varying climatic conditions, while anthropogenic sources of lead include emissions from industrial activities and the use of gasoline and phosphate fertilizers . Cadmium T. trachurus (1.5 ± 0.13) from the Black Sea [ T. mediterraneus (0.94 ± 0.76) from the Northeastern Mediterranean Sea in Turkey [ T. trachurus had the highest nickel content, while those of T. mediterraneus had the lowest one.Nickel concentrations are generally low in the aquatic environment . The niclack Sea  and for n Turkey . The mus T. trachurus [ T. mediterraneus species [ T. picturatus contained copper and zinc levels two orders of magnitude lower than the other two fish species studied.Copper and zinc are considered essential elements for the fish organism, and their concentrations are regulated mainly by vital metabolic processes . Copper rachurus , 22 and  species  in previArsenic is a widely distributed contaminant that occurs both naturally and as result of human activity . Arsenicμg/g, which is lower than the values reported for T. mediterraneus in the Iskenderun Bay (41.84 ± 18.41 μg/g) and for T. trachurus in Turkey (145 ± 12 μg/g). However, these results are in agreement with the values reported in Spanish and USDA food composition databases.Iron is found in organism compounds such as hemoglobin or myoglobin, as well as ferritin and hemosiderin in fish liver. The mean Fe contents found in this study ranged from 4.48 to 14.52 μg/g for T. mediterraneus and 0.126 μg/g for T. trachurus. The minimum and maximum manganese levels observed were 0.088 μg/g for T. trachurus and 0.168 μg/g for T. mediterraneus. Chromium and manganese concentration levels were lower than those reported by Mendil et al. [Chromium and manganese are recognized as essential trace elements for humans, of which several metabolic roles have been determined. These include manganese-containing enzymes and chromium involved in insulin function . The low T. mediterraneus with a concentration of 5.813 and 0.057 μg/g, respectively. These values, when compared with the provisional tolerable weekly intake (PTWI) of 1 mg/Kg of body weight (bw) for aluminium [Aluminum occurs naturally in the environment and is also released as a result of anthropogenic activities such as mining and industrial activity and in the production of aluminium metal and other aluminium compounds. The primary source of aluminium exposure for the general population is through food. Tin has not been proven to be nutritionally essential for humans and exposure to high levels of tin can cause gastrointestinal irritation and upset . The higluminium  and 14 mluminium , indicat T. trachurus to 0.286 ± 0.05 for T. picturatus, which is in agreement with the data reported by Roméo et al. [ T. trachurus from the Mauritanian Coast. Perelló et al. [Mercury is known to be a human toxicant. The primary source of contamination for humans is fish . Mercuryo et al.  for T. tó et al.  also fou T. trachurus, the variables As and Sn for T. mediterraneus, and the rest of variables for T. picturatus. This well-defined discrimination between fish species provided by mineral element allows us to distinguish them on the basis of their metal content.Principal component analysis was performed to explore data distribution patterns and visualize the potential relationship between the studied metals and fish species see . The firConcentrations of the toxic metals Pb, Cd, As, and Hg in human body due to fish intake were assessed and are displayed in  Trachurus trachurus, Trachurus picturatus, and Trachurus mediterraneus spp., all found in the Spanish market, and which, to the best of our knowledge, have not been previously studied. Based on the samples collected, and recognizing the inferential limitation of the sample size of this study, the metal concentrations found are below the proposed limit values for human consumption. Although mean Al, Cr, and Ni concentrations were similar among the species studied, the concentrations of other metals differed. Principal component analysis suggested that the variable Cr was the main responsible variable for the identification of T. trachurus, the variables As and Sn for T. mediterraneus, and the rest of variables for T. picturatus. This well-defined discrimination between fish species provided by mineral element allows us to distinguish them on the basis of their metal content. These results can be used to understand the nutritional quality of these fish species and evaluate the potential risks associated with their consumption. In conclusion, metal contents in the fish species analyzed are acceptable for human consumption from a nutritional and toxicity point of view. However, it should be taken into consideration that there are other dietary sources for these metals.In this study, we determined metal concentrations in muscle tissue of three popular commercial species in Spain and assessed if the intake of these species might represent a health risk. This is the first study to analyze metal concentrations in