To investigate the attention-deficit/hyperactivity disorder (ADHD) status among preschool-aged children in Guiyu, an electronic waste (e-waste) recycling town in Guangdong, China.Two hundred and forty-three parents were surveyed regarding ADHD behaviors in their children (aged 3–7 years) based solely on the DSM-IV criteria. The peripheral blood samples were taken from these children to measure blood lead levels (BLLs) and blood cadmium levels (BCLs).12.8% of children met the criteria for ADHD, of which the inattentive, hyperactive/impulsive and combined subtypes were 4.5%, 5.3% and 2.9% respectively. Of all children, 28.0% had BLLs ≥ 10 ug/dL and only 1.2% had BCLs ≥ 2 ug/L, levels conventionally considered high. Either modeled by univariate or multivariable analysis, the three ADHD scores  calculated from the Parent Rating Scale showed strong positive correlations with BLLs but not with BCLs. Furthermore, children with high BLLs had 2.4 times higher risk of ADHD than those with low BLLs (OR: 2.4 [95% CI: 1.1–5.2]). When each of the 18 categories on the Parent Rating Scale was separately analyzed, children with high BLLs had significant higher risks for positive ADHD symptoms than those with low BLLs in 12 of the 18 categories (ORs ranged from 2.1 [95% CI: 1.1–3.9] to 3.6 [95% CI: 1.7–7.5]).This study suggests that environmental lead contamination due to e-waste recycling has an impact on neurobehavioral development of preschool children in Guiyu.The online version of this article (doi:10.1186/s12887-015-0368-x) contains supplementary material, which is available to authorized users. Electronic waste (e-waste) is the most rapidly growing waste problem in the world. But to date, consumers, industry and government have only taken small steps to deal with this looming problem. Furthermore, some developed countries such as United States, Canada, Japan, and European countries that generate overwhelming majority of the hazardous waste have made use of exporting the e-waste crisis to the developing countries of Asia ,2.2 with a population of 133,000 (in 2008). Nearly 60–80% of families in the town are engaged in e-waste recycling operations. The hazardous recycling methods are mainly as follows: sorting, firing, incinerating, acidic/alkaline bathing, manual disassembling, open burning of wires and cables and strong acid leaching [Due to its geographical location, Guiyu, a seaside town situated in the southern coast of China, is one of the largest e-waste destinations in the world. It has a total area of 52 kmleaching -7 and th00 in 200. Nearly leaching . Thus, tADHD is the most common childhood neurobehavioral abnormalities, characterized by inattention, impulsivity and hyperactivity. Because of the lack of laboratory tests that can reliably predict ADHD, the diagnosis depends heavily on the interviews and questionnaires . In the The ADHD heritability, estimated at 60% to 80%, highlights the considerable role of environmental toxicants in the disorder susceptibility . It is lThis cross-sectional study carried out during January 2012 to May 2012 in Guiyu, China (a latitude and longitude of 23.29–23.41°N and 116.30–116.40°E). We chose 243 children aged 3–7 years from two public kindergartens as study participants. All children were born in Guiyu and were not diagnosed as ADHD before. Unhealthy children or those on medications were excluded. The study was approved by the Human Ethics Committee of Shantou University Medical College and all participating parents gave their written informed consents (about 25% parents refused to participate in the study). A self-designed questionnaire was used to conduct the survey among parents  were collected by well-trained nurses, transported to the laboratory, and stored at –20°C until analysis. One part of the blood sample (1 ml) was used to measure levels of Pb and Cd. The other part (2 ml) was used to measure serum ferritin by the chemiluminescence method  for the preliminary assessment of the nutritional status.For assessing ADHD, a Chinese-version of the Parent Rating Scale adapted from the DSM-IV criteria was used. On the ADHD Parent Rating Scale, there are 18 categories related to ADHD behavioral symptoms , vortexed, digested at room temperature for 10 min, and the digest was then used for Pb determination. The mixture was then used for the lead determination. The supernatant of the digest was obtained by centrifuging for 10 min at 2,000 rpm and used for Cd analysis.Pb and Cd were determined by the graphite furnace atomic absorption spectrophotometry , which consists of an autosampler (MPE60) with an injection volume set at 20 μL. The main parameters used for the lead determination were: a wave length of 283.3 nm, a lamp current of 4.0 mA, a slit width of 0.8 nm, drying at 90°C, 105°C and 120°C, ashing at 600°C, and atomization at 1,500°C. The standard calibration curve was plotted using the six working standard solutions which were prepared from the stock Pb standard solution diluted with nitric acid and added matrix modifier mixed with human blood. The linear correlation coefficient of the Pb standard calibration curve was 0.9920. Accuracy of the method was controlled by recoveries between 96% and 108%. The parameters for Cd analysis were: a wave length of 228.8 nm, a current of 2.0 mA, a slit width of 1.2 nm, drying at 90°C, 105°C and 120°C, ashing at 300°C, and atomization at 1,300°C. The linear correlation coefficient of the Cd standard calibration curve was 0.9990. The recoveries for this method were 100–103%, which were also from spiked blood samples.s) was used to assess any univariate associations. The Kormogorov-Smirnov test was used to determine the distribution of each set of data. Because the distribution of ADHD scores was skewed, log-transform of ADHD scores was used in linear regression analysis. A Chi-square test was used to compare categorical variables between different groups. Two-tailed p values < 0.05 were considered statistically significant.All database management and statistical analyses were conducted with SPSS 13.0 software . The central tendency of data was expressed as mean ± SD or median . The Spearman rank correlation   were associated with evaluated BLLs in the univariate analysis. This is consistent with numerous publications ,28. HoweWhen we put the above ADHD-related factors together by multiple linear regression analyses, we found that the high BLLs still played a major role in the development of ADHD. Furthermore, we found that the children with high BLLs had 2.4 times higher risk of ADHD than the children with low BLLs. The observation is supported by a recent analysis from the 2001–2004 National Health and Nutrition Examination Survey . It showCadmium is another heavy metal that has received considerable concern about the profound effect on children’s behavior and neurological development. It has been reported that cadmium levels in children are positively correlated with learning difficulties and dyslexia . Study c. Moreover, it appears that the local physicians rely on Parent Rating Scale to diagnose ADHD, because there are a large number of children in this area who do not attend kindergarten, which makes it difficult to establish the comprehensive evaluation package without the Teacher Rating Scale. Another drawback is the lack of control group to confirm the association between e-waste exposure and ADHD. However, our previous study [It should be noted that our data are based solely on the Parent Rating Scale of the DSM-IV criteria of ADHD. We suspected that the actual prevalence of ADHD in preschool children in Guiyu might be lower than 12.8%, as the relatively incomprehensive evaluation procedures were used. A complete and standard procedure should contain ratings from both Parent and Teacher Rating Scale and ensure that the ADHD symptoms are not associated with other mental disorders such as pervasive developmental disorders. But the goal of our study was not aimed for diagnostic purposes, but rather to estimate the prevalence of ADHD symptomatology in preschool childrenus study  and thisTo our knowledge, very few studies have been conducted in ADHD of children living in primitive e-waste recycling areas. We analyzed the prevalence rate of the ADHD based on the DSM-IV Parent Rating Scale and its three subtypes  in Guiyu, China. We showed that children with high BLLs had 2.4 times higher risk of ADHD than those with low BLLs. The study may have policy implications for the local government to regulate e-waste recycling such that children’s access is limited and that recycling methods are to be improved to reduce exposure . FurtherAdditional file 1:This file provides two questionnaires. One is the risk assessment for childhood ADHD under e-waste exposure and the other is the Parent Rating Scale of DSM-IV ADHD criteria.Below is the link to the electronic supplementary material.


The applicability of transcranial direct current stimulation (tDCS) in individuals with attention deficit hyperactivity disorder (ADHD) has not yet been investigated. This low-cost, non-invasive, and safe technique optimized to modulate the inhibitory response might be a useful treatment option for those affected by this condition.The aim of this single center, parallel, randomized, double-blinded, sham-controlled trial is to investigate the efficacy of transcranial direct current stimulation over the prefrontal cortex on the modulation of inhibitory control in adults with attention deficit hyperactivity disorder.A total of 60 individuals will be divided into 2 groups by block randomization to receive active or sham stimulation. Anodal stimulation over the left dorsolateral prefrontal cortex will be applied at 1 mA during a single 20-minute session. Before and after interventions, subjects will perform 2 go/no go tasks and the brain electrical activity will be recorded by electroencephalogram (EEG) with 32 channels, according to the 10-20 international EEG system.The trial began in May 2013 and we are currently performing the statistical analysis for the secondary outcomes.The findings from this study will provide preliminary results about the role of prefrontal cortex activation through tDCS on ADHD patients.Clinicaltrials.gov NCT01968512; http://clinicaltrials.gov/ct2/show/NCT01968512 (Archived by WebCite at www.webcitation.org/6YMSW2tkD). Attention deficit hyperactivity disorder (ADHD) presents prevalence rates in US studies of 5%-9% in childhood, especially in school age children. Of those affected, 67% continue to present symptoms in adulthood, which may compromise psychosocial, professional, and emotional development -5. In a The clinical presentation of ADHD may arise from disorders in the prefrontal cortex and its subcortical connections -11. ThisThere is evidence of a physiological association between the prefrontal cortex and inhibitory control ,14, wherTranscranial direct current stimulation (tDCS) is a simple and well-known neuromodulatory technique ,16 whichThe aim of this trial is to investigate the efficacy of tDCS over the prefrontal cortex on the modulation of inhibitory control in adults with ADHD by assessing behavioral and neurophysiological parameters. We expect that the application of this low-cost and safe technique will increase the inhibitory response in ADHD individuals what may result in a greater ability to inhibit inappropriate behaviors.This is a single-center, parallel, randomized, double-blinded, sham-controlled trial, conducted in the Laboratory of Functional Electrostimulation at the Federal University of Bahia . This study will include descriptive and analytical steps designed to investigate the neurobiological aspects of patients with ADHD, and the response of inhibitory control parameters to tDCS.Patients with ADHD will be recruited by sending letters and emails to neuropsychiatric societies and associations. Professional experts in ADHD, contacted by mail and telephone, will be invited to refer potential patients for the study. Advertisements will be published on the Internet and social networking sites, according to the inclusion criteria.The inclusion criteria for the study are (1) the ability to understand and sign the informed consent form, (2) a diagnosis of ADHD according to DSM-IV-TR and the Adult Self-Report Scale (ASRS), (3) resident of Bahia, and (4) ≥18 years old.Patients who meet the following criteria will be excluded (1) major psychiatric disorders such as schizophrenia and bipolar disorder, (2) inability to understand the questionnaires applied  or illiterate, and (3) abuse of psychoactive substances or alcohol, except nicotine and caffeine, during the last 12 months.A sample size of 50 subjects was calculated assuming a difference in proportion between the active tDCS and sham control groups of 40% on the go/no go performance, before and after interventions. This calculation was performed using the statistical program STATA 12.0, considering an alpha of .05 and a power of 0.80, resulting in a sample of 25 subjects in each group (intervention and control). To address unexpected factors, we applied a dropout rate of 20%, reaching a total sample size of 60 individuals.Individuals will be divided into two groups by block randomization aiming for a balanced distribution between the groups (30 subjects each), and considering gender and age as variables. Blocks will be composed of 10 subjects, totaling 6 blocks. Each intervention group will comprise 5 individuals from each block.An external researcher will perform the randomization and will generate a list to allocate patients and ensure a concealed allocation.Excluding the external researcher, investigators applying the go/no go tasks and registering the EEG, and the subjects will be blind to the intervention. Raters and researchers responsible for the statistical analysis will not be aware of the treatment group that the patient will be enrolled. For analysis purposes, the intervention groups will be identified as “0” and “1”. Blinding code will be known only by the principal investigator and by the person responsible for the stimulation.In accordance with the Declaration of Helsinki , this stThis trial was approved on October 2012  by the institutional review board of the Maternidade Climério de Oliveira-Federal University of Bahia.Signed consent will be obtained from each participant. Only subjects capable of understanding and agreeing to the consent will be enrolled. In addition to a signed consent form and prior to any intervention, participants will receive a detailed explanation about the trial aims and procedures that will be performed. Two experienced researchers will explain that participation is voluntary and they may withdraw at anytime without losses. The trial staff also will be available to clarify any question; at the same time they will assure that subjects understood all of the steps of the study. Participants will have an indefinite amount of time to make a decision, and those that agree, will be asked to sign two copies of the informed consent form.Following the consent procedures, subjects will undergo a cognitive screening using the MiniMental State Examination (MMSE) ,20, the Posterior electrical brain activity will be recorded by EEG with 32 channels placed on the scalp, according to the 10-20 international EEG system. Each recording will last 5 minutes and will be performed in a resting state, with the patient's eyes open and looking for a fixed point during the first minute, and with closed eyes for the remaining four. Participants will then be asked to perform tasks on the computer: 2 go/no go tasks adapted from the original version using a fruit and a letter as the first and second target, respectively. Following the cognitive tasks, subjects will undergo the active or sham stimulation, according to the previous randomization. At the end of the intervention, subjects will perform the 2 go/no go tasks again (randomly selected to avoid learning effect), and they will undergo another EEG recording.There will be no follow-up visits; participants will undergo a single visit of approximately two hours in duration. All subjects will be asked to abstain from caffeine, alcohol, and nicotine one day before the experiments.Participants of the intervention group will have the tDCS applied at 1 mA, with the anode electrode over the left dorsolateral prefrontal cortex and cathode electrode over the equivalent area on the right side. For the control group subjects, electrodes will be placed at identical positions and sham stimulation will be applied. The stimulation device will be turned on for 30 seconds so that the patient will feel the initial sensation, then will be shut down. The intervention and sham procedure will take place in one single 20-minute session to evaluate the immediate effect.The application of tDCS and the assessment of its effects will be performed by clinical observation using a reduction of symptomatology as evaluated by the neuropsychological task, go/no go, and by neurophysiological assessment, measured by quantitative electroencephalogram (qEEG) and thereconstruction of brain networks, as parameters.The primary outcome of this trial is the inhibitory response measured as behavioral performance by two go/no go tasks. These tests are adapted from a previous version , and wilThe secondary outcome variables are power analysis of frequency bands through qEEG and the brain networks. For the EEG, data will be recorded from the 32 channels and a reference electrode (Cz) placed according to the 10-20 international EEG system with additional electrodes . The EEG data will be filtered between 0.5-50 Hz, and analyzed through EEGLAB . Brain network reconstructions will be performed based on the EEG data.P<.05.A 5-step statistical analysis will be conducted see . These aStepsThe socio-demographic, clinical, and epidemiological description of the groups, using the usual procedures of descriptive statistics such as calculation of frequencies, measures of central tendency, and dispersion;Characteristics will be compared between groups at baseline, using a one-way analysis of variance (ANOVA) for continuous variables and a chi-square test for categorical variables;Shapiro-Wilk test will be performed to assess the normality assumption of the outcome variables;t test for comparisons within each group and between intervention groups, or applying equivalent non-parametric tests (according to Shapiro-Wilk test results) before and after intervention;Analysis of paired and independent samples using a Pearson chi-square test to evaluate blinding effectiveness, comparing between groups.This trial and enrollment began in May, 2013. The statistical analysis for the secondary outcomes is currently being performed.The findings from this trial will provide preliminary results about the role of prefrontal cortex activation through tDCS on ADHD patients. The results of this clinical trial will allow us to evaluate behavioral and neurobiological aspects of ADHD in addition to observing the socio-demographical and clinical-epidemiological parameters of this population.We will examine the tDCS contribution in modulating inhibitory control and neurophysiological parameters measured by neurocognitive tasks (go/no go), qEEG, and brain reconstruction network models. We also expect that the present trial will contribute scientifically to the development of neurophysiological assessment methods of ADHD, and to the evaluation of the feasibility of this low cost, non-invasive, and safe technique for optimization of inhibitory responses in ADHD patients.One possible limitation is that we will only apply a single session of tDCS. However, since, to the present moment, there are no previous studies regarding tDCS in ADHD subjects, we opted for a conservative protocol with only one session of tDCS delivered at 1 mA to ensure safe parameters.To the best of our knowledge, this trial will be the first study to assess the cognitive and neurophysiological effects of tDCS on ADHD patients. In the long term, we expect that our results might reinforce comprehensive programs of intervention and multidisciplinary approaches in patients with ADHD.


Cirsium arvense (L.) Scop. , an economically damaging pastoral weed in temperate regions of the world, but its optimization has remained obscure. We developed a matrix model for the population dynamics of C. arvense in sheep‐grazed pasture in New Zealand that accounts for the effects of aerial shoot defoliation on a population's photosynthetic opportunity and consequential overwintered root biomass, enabling mowing regimes varying in the seasonal timing and frequency of defoliation to be compared. The model showed that the long‐term population dynamics of the weed is influenced by both the timing and frequency of mowing; a single‐yearly mowing, regardless of time of year, resulted in stasis or population growth, while in contrast, 14 of 21 possible twice‐yearly monthly mowing regimes, mainly those with mowing in late spring, summer, and early autumn, resulted in population decline. Population decline was greatest  with twice‐yearly mowing either in late spring and late summer, early summer and late summer, or early summer and early autumn. Our results indicate that mowing can be effective in reducing populations of C. arvense in pasture in the long term if conducted twice each year when the initial mowing is conducted in mid spring followed by a subsequent mowing from mid summer to early autumn. These mowing regimes reduce the photosynthetic opportunity of the C. arvense population and hence its ability to form the overwintering creeping roots upon which population growth depends.Defoliation has frequently been proposed as a means of controlling  Cirsium arvense (L.) Scop.   Fig.  has longle) Fig. . During C. arvense in pastures in Australia  can result in a negative rate of growth in the aerial shoot population and hence population decline. But, due to the practical limitations of field experiments, none encompassed all possible combinations of frequency and timing of mowing and so their optimal combination for a desired rate of population decline remains unknown.The mowing treatments in these experiments were widely distributed across almost all months of the growing season from early spring  through until late autumn . In addition to this variation in the number and timing of mowing treatments, the experiments have varied greatly in the number of consecutive years during which the mowing treatments were applied; from two years  starting on Sept 21st (mid‐spring) (t = 0).In our single‐year model of a rt: Old root dry mass (g m−2). At Sept 21st (t = 0), this comprises all underground overwintered plant material . This root mass formed over the previous year and has survived the winter. Over the subsequent 12 months (1 year) from Sept 21st–Sept 21st (t = 0 to t = 12), it decays. Any roots formed during this year join the “new root dry mass” compartment (see 3 below).nt: Aerial shoot density (m−2). This comprises vegetative shoots (rosettes and bolting shoots) and reproductive shoots .Rt: New root dry mass (g m−2). This is the root mass that is newly formed during the current year Sept 21st–Sept 21st (t = 0 to t = 12). As with old roots, it includes all subterranean tissues.t (months). The time‐dependent mortality rate for each compartment is μt month−1, and the recruitment rates of aerial shoots  are crt and cRt, respectively. The “creeping root” parameter, cBt, is the transition rate from aerial shoots to the new root dry mass per month. The units of cBt are “grams of new root dry mass per unit of aerial shoot dry mass per month”. The total average dry mass of nt aerial shoots at time t is Bt = btnt where bt is the average dry mass (g) of one typical aerial shoot at time t.Model equations eqs  show theA schematic of the matrix model is given in Figure t + 1 is Sept 21st.Despite 7.6% of old root mass surviving 12 months , can be written: t to month t + 1 and A0 is the transition matrix from Sept 21st to Oct 21st, A1 is the transition matrix from Oct 21st to Nov 21st, etc.The projection matrix At stays constant for the same month over subsequent years and so the projection matrix P does not change from year to year and, for example, X12 = P X0 and X24 = P X12 etc. The dominant eigenvalue, λ, of the projection matrix P describes the long‐term dynamics of the population over time, with λ > 1, 1, and <1 corresponding to long‐term population increase, stasis, and decrease, respectively  as at May 21st (t = 8)  which was the closest date (in the model) to the experimental sampling (first week of June). The model's estimate of the aerial shoot biomass duration (g days) was defined, in accordance with the experimental data, as the area  under the total aerial biomass versus time curve  between t = 2 (Nov 21st) and t = 7 (Apr 21st).A number of mowing regimes were simulated. First, for model validation, combinations of early (Nov 21st), mid (Jan 21st) and late (Feb 21st) season mowing events were considered. For each combination, model outputs “autumnal root biomass” and “aerial shoot biomass duration” were compared with experimental data from Bourdôt et al. . Here, wC. arvense shoots are below mower height in early spring. Similarly, May–August were excluded as C. arvense dies off over these late autumn/winter months. The mowing combinations were given identification acronyms according to the first letter of the mowing month that is mowing on January 21st and March 21st was encoded “JM” etc.Secondly, to consider more effective mowing, the mowing regimes “mow once a year” (7 possibilities) and “mow twice a year” (21 possibilities) were considered. It was assumed that mowing could take place on the 21st of any month from October to April inclusive. September was excluded because Et for each monthly transition matrix At, was calculated using methods described in Lesnoff et al.  and then a subsequent rapid winter decline. New root dry mass began to form from December and increased steadily until the end of May (~400 g m−2), subsequently senescing over the winter months. What was left of the new root mass at the end of the year became the old root mass.In the first year, with default parameter inputs, the model population density of P for default model parameters was λ = 2.03, implying that, in the long term, shoot population density doubles each year.The eigenvalue of the projection matrix The trajectory for aerial shoot density is similar in shape to that calculated for percentage ground cover in Bourdôt et al. . Both thThe relationship between the autumnal root biomass and aerial shoot biomass duration was found to be linear in the field experiments by Bourdôt et al. , and our−2) and for aerial shoot biomass duration  when the mowing event was imposed in mid‐summer (January) as compared to both earlier (spring) of later (autumn) in the growing season  and January (λ = 1.02)  Fig. .λ = 0.41, autumnal root biomass = 99 g m−2, aerial shoot biomass duration = 5,133 g days)  Fig. . Seven oλ by an average of approximately 8% in all one and two‐yearly mowing regimes that included the month of March. This reduction did not cause any of the λ values to fall below unity. Autumnal root dormancy did not affect λ values for April mowing.Incorporating autumnal root bud dormancy reduced λ) came from the overwintered root compartment through old root survival and recruitment of new aerial shoots from the overwintered root mass , the biggest contribution to population growth . Also Donald (λ = 0.4). However, both of these experimental estimates of λ were derived from shoot density data collected within patches of C. arvense. Because creeping roots move off plots over time, the shoot density data collected most likely underestimate the actual changes in shoot population size and density that were occurring at the larger scale.Model input parameters were chosen to be seasonal, so output population trajectories also showed seasonal behaviors as expected Fig. . In the lly Fig. . By complly Fig.  estimatelly Fig.  where 4 o Donald  estimateλ) at this time of year . Adults and larvae of the beetle feed on the leaf mesophyll tissue, stripping the plant of its photosynthetic capacity thus restricting the plants ability to produce new overwintering root mass. In a C. arvense population in New Zealand, the beetle was observed to occasionally kill aerial shoots, and on average caused 63% defoliation (Cripps Similarly, the biocontrol agent, n Cripps . An exteC. arvense in permanent grassland, where the size of an ephemeral overwintering root bud population is a linear function of the photosynthetic opportunity attributable to the aerial shoots during the preceding growing season, two conclusions may be drawn concerning the influence of mowing. First, an annually repeated single mowing, regardless of the time when this is imposed on the shoots during each growing season, is unlikely to cause long‐term population decline. Second, mowing can be effective in reducing populations of C. arvense in pasture in the long term if conducted twice each year. According to the model, the optimal combination is when the initial mowing is conducted in mid spring followed by a subsequent mowing from mid summer to early autumn. These mowing regimes reduce the photosynthetic opportunity of the C. arvense population and hence its ability to form the overwintering creeping roots upon which population growth depends.From the population model that we have developed for C. arvense populations in native and introduced regions have similar dynamics (Cripps et al. C. arvense is also a problematic weed (Tiley Over a typical growing season, ed Tiley .None declared.Appendix S1. Parameter value estimation for the matrix model.Click here for additional data file.


M = 67.33 months, SD = 10.10; 65 % boys). Results showed that these regulatory processes were all significantly related to ADHD symptoms and that most of these relations remained after controlling for comorbid conduct problems. Most previous preschool studies have only included cognitive regulation, and to some extent motivation-based regulation. By also including affective regulation, we were able to explain a larger proportion of the variance in ADHD symptoms. However, it should be noted that the amount of variance explained was still small in comparison with what has been found in previous studies of school-aged children. This finding could be taken as an indication that further studies examining the nature of preschool ADHD are needed, and that it may be necessary to look beyond the neuropsychological factors that have been linked to the disorder in older children and adults.There is a trend toward diagnosing ADHD prior to school entry. Despite this, there is a lack of studies investigating ADHD in the preschool years, at least studies including a large range of different neuropsychological functions. Our knowledge of the independent effects of different neuropsychological functions in relation to preschool ADHD is therefore limited. In order to address this issue, the present study investigated cognitive, affective, and motivation-based regulation in relation to ADHD symptoms in 104 preschool children (age  Attention deficit/hyperactivity disorder (ADHD) is often diagnosed in middle childhood, but there is a trend toward diagnosing children prior to school entry  and effects were significant mainly due to the large sample size . To our knowledge, only two previous studies examining independent effects have included motivation-based regulation. In one study, independent effects of cognitive and motivation-based regulation were found in relation to ADHD symptoms . Separating these two constructs is difficult. However, a child with infrequent and flat emotional reactions may display poor regulation and an emotional child may be a relatively good regulator. It has therefore been argued that it is important to distinguish emotion regulation from emotional functioning in general in order to better understand which aspect of emotional functioning that is related to different behavior problems in children  include items that overlap with symptoms of Oppositional Defiant Disorder (ODD) and/or Conduct Disorder (CD). As ADHD and ODD/CD often co-occur  between 4-6 years of age . The first task was based on the go/no-go paradigm. The particular version used here was originally developed by Berlin and Bohlin  and consThe second measure of inhibition was a Navon task . A third session was performed in which participants were asked to shift between responding to local or global stimuli. A total of 40 trials were presented, and a square and a circle in the lower corners of the computer screen indicated what stimulus to respond to . Number of errors during this last session was used to measure shifting.Reaction time variability was measured using the standard deviation of participants’ reaction times for correct answers on the non-shifting trials in the Navon task and correct answers on the go/no-go task (see descriptions above).Sustained attention was measured using the go/no-go task described above under the heading “inhibition”. As a measure of sustained attention, we used number of omissions  on the go/no-go task.Delay aversion was measured using the Choice Delay Task  and has been widely used in epidemiological, developmental and clinical research, as well as in routine clinical and educational practice. The conduct problem subscale used in the present study includes questions about temper tantrums, lying, stealing, aggression, bullying, and disobedience. As described in the introduction, it has been argued that the role of symptoms of ODD/CD needs to be taken into account when examining the relation between affective regulation and ADHD  and all outliers  were replaced with the value at three SD. To further establish data integrity, we analyzed the detailed computer files generated by the cognitive tasks to make sure that there were no systematic errors in the data . However, no such systematic errors were identified.In line with the reasoning that ADHD is better captured as a continuous trait rather than as two discrete categories , medium (r = 0.30) or large (r = 0.50).To investigate independent effects of the three forms of regulation in relation to symptoms of inattention and hyperactivity/impulsivity, we performed hierarchical regression analyses. This way, we were able to study to what extent affective regulation can explain additional variance in preschool ADHD symptoms, beyond the more established cognitive and motivation-based pathways presented in current ADHD theories  in Step 1, and all variables that were significantly correlated with the two ADHD dimensions (except emotion regulation) in Step 2. In Step 3, all significant emotion regulation variables were included. As shown in Table p < 0.05). This significant interaction indicated that the combination of high levels of affective regulation of happiness/exuberance and low reaction time variability was associated with especially low levels of inattention. However, it should be noted that this could have been a chance finding due to the very large number of interactions investigated .Fourth, we investigated whether there were any significant interactions between cognitive, affective and motivation-based regulation. A significant interaction effect would indicate that the different neuropsychological deficits combine synergistically . Of all possible interactions, only the effect of reaction time variability and regulation of happiness/exuberance in relation to inattention reached significance , but well within the range of the studies included in these analyses  than that reported in the meta-analysis by Pauli-Pott and Becker . HoweverWith regard to independent effects, both cognitive and motivation-based regulation were shown to have independent effects in relation to symptoms of inattention, which is in line with a previous preschool study  and hyperactivity/impulsivity (14 %) was explained, even though a wide range of cognitive and motivation-based deficits were included. By adding emotion regulation, we could explain additional variance in both inattention (37 %) and hyperactivity/impulsivity (25 %), but still a large amount of variance remains unexplained. The importance of this finding can be discussed both in relation to previous ADHD studies of school-aged children and in relation to current models of heterogeneity.If we compare our findings with those of older children, we see that effects for both cognitive and affective regulation have generally been larger in school-aged samples (e.g., Berlin et al. Based on the discussion above, we would like to suggest that an important avenue for future research could be to examine to what extent neuropsychological functioning in preschool can help in identifying children who will show stability in ADHD symptoms over time or develop ADHD later on in life. We would also like to suggest that a comprehensive theoretical model of ADHD needs to not only account for the link between neuropsychological deficits and ADHD symptom levels, but also for the extent to which such deficits can explain the functional impairments associated with the disorder. The link between poor executive functioning and academic achievement has been well established in previous ADHD research on school-aged children (e.g., Biederman et al. Regarding the practical implications of our findings, it should be acknowledged that measures of executive functioning, delay aversion, as well as regulation of emotion may be useful as screeners for ADHD in the preschool age and should be further investigated. Also, these aspects should be considered when developing early intervention and prevention programs for ADHD. In previous research, computerized programs have been shown to strengthen working memory in preschool children (e.g., Thorell et al. In conclusion, the present study has shown that cognitive, affective and motivation-based forms of regulation are all related to ADHD symptoms in preschool and that it is important to study affective regulation in terms of both positive and negative emotions. In relation to current theoretical models of ADHD, these findings clearly provide support for the notion that ADHD is a neuropsychologically heterogeneous disorder involving multiple pathways (cf. Nigg et al.


Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) frequently co-occur. Besides shared genetic factors, pre- and perinatal risk factors (PPFs) may determine if ASD, ADHD, or the combination of both disorders becomes manifest. This study aimed to test shared and unique involvement of PPFs for ASD and ADHD, using an approach that stratifies the sample into affected/unaffected offspring and single-incidence (SPX) versus multi-incidence (MPX) families. Pre- perinatal data based on retrospective parent-report were collected in 288 children  from 31 SPX and 59 MPX ASD families, 476 children  from 31 SPX and 171 MPX ADHD families, and 408 control children . Except for large family size and more firstborns amongst affected offspring, no shared PFFs were identified for ASD and ADHD. PPFs predominantly related to ASD  were more often reported in affected than unaffected siblings. PPFs associated with ADHD  were shared between affected and unaffected siblings. Firstborn-ship was more frequent in SPX than MPX ASD probands. Our results suggest that the co-morbidity of ASD and ADHD is not likely explained by shared PPFs. Instead, PPFs might play a crucial role in the developmental pathways leading up to either disorder. PPFs in ADHD appear to index an increased shared risk, whereas in ASD PPFs possibly have a more determining role in the disorder. SPX-MPX stratification detected possible etiological differences in ASD families, but provided no deeper insight in the role of PPFs in ADHD.The online version of this article (doi:10.1007/s10802-015-0081-0) contains supplementary material, which is available to authorized users. Autism spectrum disorder (ASD) and attention deficit/hyperactivity disorder (ADHD) are both highly heritable, impairing neurodevelopmental disorders that manifest early in development and frequently co-occur  were more frequently observed in individuals with ASD than in controls  risk factors  or multiplex (MPX) affected ones. Families with only one affected individual are defined as SPX and families in which two or more individuals are affected, are defined as MPX. The hypothesis is that the constellation of etiological factors differs between SPX versus MPX families. It is expected that individuals from SPX families are more likely than individuals from MPX families to develop the disorder as a result of sporadic genetic  or non-genetic causes  strictly personal to the patient. These factors may (at least partly) explain why that child developed ASD or ADHD, yet his/her siblings did not. In families with multiple cases of the disorder (MPX families) risk factors may be shared between affected individuals. Previous molecular genetic studies confirmed the assumption of different etiologies for SPX and MPX cases, demonstrating that a more than threefold rate of de novo mutations was identified in ASD SPX families (~7–10 %), compared to ASD MPX families (~2–3 %) or control families (~1 %)  instead of increasing the overall liability for the disorder only slightly (trait factors). Third, we examined whether offspring from MPX families shares a large proportion of PPFs, whereas in SPX families PPFs were mostly non-shared between affected and unaffected siblings.ASD and ADHD families were recruited as part of two large family-genetic studies: the Biological Origins of Autism (BOA) study and the Dutch part of the International Multicenter ADHD Genetics (IMAGE) study , 476 children from ADHD families , and 408 control children were included in this study, see Table Pre- and perinatal information was retrospectively obtained through a questionnaire filled out by the parents before diagnostic assessments. The questionnaire is derived from the Prechtl optimality scales used by Gillberg and Gillberg , with adQuestionnaires were filled in separately for each child at home, mostly by the mother of the child. Additional data collection included demographic information, blood samples of all family members and neuropsychological data of the children. The study was approved by the local medical ethics board, and parents and children (12 years and older) signed for informed consent.χ2 (69) = 59.40, p = 0.789. The full pre-and perinatal risk factor questionnaire was only administered to about 50 % of the participating ADHD families (IMAGE study), since it was added to the test protocol at a later stage. A shorter version of the questionnaire  was later sent to the remaining participating families. In the IMAGE cohort, data was not missing completely at random, Little’s (χ2 (144) = 176.76, p = 0.033. A series of ANOVAs and Chi-Squared tests revealed that children whose families did and did not complete the long version of the questionnaire did not differ on age, sex, estimated TIQ, parent-rated ASD symptoms, teacher-rated ADHD symptoms, and proportion SPX vs. MPX, p-values > 0.10. Children who filled in the short version of the PPF questionnaire had slightly lower parent-rated ADHD symptoms , than children who did complete the long version , F  = 6.19, p = 0.009. However, this is likely explained by the larger proportion of control families within this short version group (40 %), compared to the long version group (31 %), χ2  = 5.95, p = 0.015. Missing data were not imputed to prevent spurious associations.In the BOA (ASD) study, the pre-and perinatal risk factor questionnaire was part of the standard test protocol and administered to all participating families. Missing data for the ASD study was less than 5 % and was missing at random, Little’s  MCAR tesLittle’s  MCAR tesFirst, to examine which PPFs were associated with ASD, ADHD or both, Wald chi-square values were calculated using generalized estimated equations (GEE) with a binary logistic model, robust estimators, and exchangeable structure for working correlation matrices. To correct for familial dependency within the data set, family number was used a repeated measure. Independent variables were type of disorder (ASD vs. ADHD vs. control) and sex and the two-way interaction type of disorder*sex. The two-way interaction was dropped from the model when non-significant. Sex was added to the model because previous studies reported that pre-/perinatal complications are more prevalent in boys  whether the effect was specific to affected children or shared between affected and unaffected siblings and b) whether the effect was selectively found in either SPX or MPX families. Similar GEE analyses were run with independent variables a) diagnosis (affected vs. unaffected siblings) and sex or b) type of family (SPX vs. MPX families) and sex. For the factor firstborn, mean family size was included as covariate to account for the number of children per family. The post hoc analyses were run separately for ASD and ADHD cohorts. A False Discovery Rate (FDR) correction with a χ2 tests and ORs for the PPFs for ASD and ADHD families. Multivariate significant and trend-level multivariate effects were found on six PPFs, namely family size, low parental age, tobacco use during pregnancy, stress during pregnancy, maternal diseases and maternal infections, p-values < 0.10. Only one of these PPFs was significantly associated with both disorders, namely the factor family size, ASD families vs. controls: χ2  = 28.54, p < 0.001, OR = 1.64, 95 % CI 1.37–1.97; ADHD families vs. controls χ2  = 27.98, p < 0.001, OR = 1.41, 95 % CI 1.24–1.61; ASD vs. ADHD families: p = 0.084. Case parents had significantly more children than control families and this did not differ between ASD and ADHD.Table χ2  = 3.83, p = 0.050, OR = 3.97, 95 % CI 1.00–15.82, and χ2  = 3.88, p = 0.049, OR = 1.52, 95 % CI 1.00–2.31, respectively. Children from ASD families were almost four times more likely to have suffered from a severe infection during pregnancy and were one and a half times more likely to have experienced at least one suboptimal condition at birth than controls. These factors were not significantly associated with ADHD. Further, a trend level effect of high birth weight was found in ASD, χ2 = 2.74, p = 0.098, OR = 2.38, 95 % CI 0.85–6.63. Although non-significant, high birth weight appeared to be more frequent in ASD than controls, OR = 2.38.Predominantly associated with ASD were the factors maternal infections and suboptimal condition at birth, χ2  = 21.20, p < 0.001, OR = 2.26, 95 % CI 1.60–3.21, tobacco use during pregnancy, χ2  = 7.87, p = 0.005, OR = 2.12, 95 % CI 1.52–4.48, and stress during pregnancy, χ2  = 12.17, p < 0.001, OR = 2.61, 95 % CI 1.52–4.48. A nominally significant association was found between ADHD and maternal diseases, χ2  = 5.67, p = 0.017, OR = 1.84, 95 % CI 1.11–3.04. A reverse effect was found for high parental age, χ2  = 11.51, p = 0.003, with parents of ADHD cases being less likely to have an advanced parental age than control parents, χ2 = 10.85 p = 0.001, OR = 0.45, 95 % CI 0.28–0.72. These results indicate that children from ADHD families were over two times more likely to have young parents than control children. Furthermore, case mothers were almost twice as likely to have suffered from at least one disease and were over twice as likely to have smoked or experienced stress during pregnancy as control mothers, see Table p-values < 0.006.Predominantly associated with ADHD were the PPFs low parental age, χ2 , N = 878p-values < 0.10.No differences in occurrence between ASD and ADHD cases and controls were found for miscarriages/bleeding, alcohol use during pregnancy, labor/parturition, prematurity, birth weight, and fertility treatment, all χ2  = 8.77, p = 0.003, OR = 6.48, 95 % CI 1.88–22.33. A trend-level effect of being firstborn was found for ADHD as well, χ2  = 3.23, p = 0.072, OR = 1.16, 95 % CI 0.99–1.35. A suboptimal condition at birth was nominally significantly more frequently reported in ASD-affected compared to ASD-unaffected siblings, χ2  = 4.47, p = 0.034, OR = 1.70, 95 % CI 1.04–2.79. ASD affected and unaffected offspring did not significantly differ from each other with regard to the prevalence of maternal infections, p = 0.114. Within ADHD families, no significant differences were found between ADHD-affected and unaffected siblings for any of the identified PPFs, p-values > 0.10. However, despite suboptimal condition at birth not being significantly associated with ADHD, this perinatal complication was nominally significantly more often reported in ADHD-affected compared to ADHD-unaffected offspring, χ2  = 4.39, p = 0.036, OR = 2.13, 95 % CI 1.05–4.33. Similarly, stress during pregnancy was more frequent in ASD-affected vs. ASD-unaffected children, χ2  = 5.91, p = 0.015, OR = 2.19, 95 % CI 1.16–4.13, see Fig. As a next step, we compared affected vs. unaffected siblings for their exposure to PPFs. We found that after controlling for family size, ASD affected children were more likely to be firstborn than their unaffected siblings, χ2  = 3.44, p = 0.064, OR = 0.51, 95 % CI 0.24–1.04, with SPX ASD families having proportionally more firstborns than MPX ASD families. Further, trend-level effects were found for SPX versus MPX ASD unaffected siblings on suboptimal condition, χ2  = 5.91, p = 0.052, OR = 0.44, 95 % CI 0.19–1.01, and for SPX versus MPX ADHD siblings on being firstborn, χ2  = 3.35, p = 0.067, OR = 0.51, 95 % CI 0.24–1.05. Siblings from MPX families were more likely to be firstborn (ADHD) or to have experienced a suboptimal condition at birth (ASD) than unaffected siblings from SPX families, see Fig. A final step in the data analyses was the stratification into SPX vs. MPX families. This revealed a trend-level significant difference between SPX and MPX ASD families in the factor being firstborn, This is the first study to test sharing and uniqueness of the involvement of PPFs for ASD and ADHD, using an approach that stratifies the sample into affected versus unaffected offspring and SPX versus MPX affected families. In accordance with other studies, our findings indicate that pre- and perinatal complications are more frequent in children with ASD and ADHD compared to control children. Novel findings are that we showed that, except for large family size and more firstborns amongst affected offspring, no shared PFFs were identified for ASD and ADHD. PPFs predominantly related to ASD  were more often reported in affected offspring. PPFs associated with ADHD  were shared between affected and unaffected siblings. Furthermore, by using the SPX-MPX stratification, we showed that PPFs in ADHD appear to index an increased shared familial risk, whereas in ASD PPFs possibly have a more determining role in the disorder.This study adds importantly to the literature by demonstrating that there are limited shared pre- and perinatal risk factors across ADHD and ASD. This is surprising given that cross-disorder traits were present in both ASD and ADHD affected and unaffected siblings, mainly in MPX families (see sample characteristics). This may suggest that the comorbid presence of ASD and ADHD symptoms is not likely explained by shared pre-and perinatal risk factors. The finding that affected siblings were more often firstborns than unaffected siblings concurs with previous literature  or ADHD . Higher frequencies of maternal infections and suboptimal conditions at birth in ASD cases are consistent with previous findings  did not differ among affected and unaffected siblings . Strategic oversampling of SPX ADHD families might be necessary to increase the power of studies using the SPX-MPX stratification. A second important limitation is that our study design was not suited to test causal inference, thus caution is required in assuming that PPFs have causal effects on ASD and ADHD. As Thapar and Rutter  pointed In conclusion, the findings reported here indicate that pre- and perinatal complications are more frequent in children with ASD and ADHD compared to control children. Most of the PPFs were uniquely related to either ASD or ADHD, suggesting that the high co-morbidity is not likely to be explained by shared pre-and perinatal risk factors. Instead, PPFs might play a crucial role in the developmental pathways discriminating the disorders on a background of shared genetic factors. Further stratification into affected versus unaffected siblings suggests that PPFs in ASD may have a unique, highly penetrant contribution to the disorder and are more likely to be true determinants , whereas in the case of ADHD, PPFs are weak risk factors that only slightly increase the overall liability for the disorder in a family (trait factors). In agreement with our hypothesis, some PPFs appeared to be more frequently shared by affected and unaffected siblings from MPX than SPX families, particularly in ASD. This may pinpoint to potential pre-perinatal etiological differences between SPX and MPX forms of the disorder. These results can stimulate further research on the complex etiologies of ASD and ADHD and the role of PPFs herein.ESM 1(PDF 152 kb)Below is the link to the electronic supplementary material.


Evolocumab has been shown to consistently reduce low-density lipoprotein cholesterol (LDL-C) across populations. The phase 3 studies included administration in the home-use and in-clinic settings but did not specifically evaluate the feasibility of home-use administration. Two clinical studies enrolled patients with hypercholesterolemia or mixed dyslipidemia on statin therapy and with/without ezetimibe received evolocumab in the home-use setting. Patients were randomized to self-administer evolocumab using one of two injection devices biweekly over 6 weeks  or monthly over 12 weeks . The first self-administration occurred in the in-clinic setting, and two more were performed in the at-home setting. Patients were successful in self-administering evolocumab in the home-use setting in approximately 95 % of attempts and experienced LDL-C reductions from baseline to week 6 or the mean of weeks 10 and 12 of approximately 65 %. Rates of successful self-administration and LDL-C reduction were similar across dosing schedules and study devices. Adverse events were similar between randomized groups and generally mild in severity. In two clinical studies, therefore, patients were able to successfully self-administer evolocumab in both the in-clinic and at-home settings regardless of which dosing schedule or device they used.The online version of this article (doi:10.1186/s40064-016-1892-3) contains supplementary material, which is available to authorized users. This program is composed of several completed studies that demonstrated safety and efficacy in hyperlipidemia and mixed dyslipidemia patients, as well as several ongoing studies that are evaluating safety and efficacy in the setting of atherosclerosis and secondary prevention . In the PROFICIO phase 2 studies  with similar designs that specifically evaluated injection success of evolocumab in the home-use setting with three different devices. In this article, we report the primary results of the THOMAS studies.® autoinjector vs a prefilled syringe (PFS) (THOMAS-1) or the prefilled SureClick® autoinjector vs an AMD (THOMAS-2).THOMAS-1 (NCT01849497) and THOMAS-2 (NCT01879319) were multicenter, open label, parallel-arm, randomized studies that enrolled patients at 22 and 23 sites (respectively) in the United States and Canada from April to December 2013. Patients with hypercholesterolemia or mixed dyslipidemia on statin therapy with or without ezetimibe were eligible. Enrolled patients were randomized to receive evolocumab administered at home with the prefilled SureClickBoth studies required written informed consent, adherence to Good Clinical Practices and local regulations, and approval of the protocol by institutional review boards/ethics committees.Patients were eligible for enrollment in the THOMAS studies if they were 18–80 years of age, taking an approved statin (with or without ezetimibe) at a stable dose for at least 4 weeks before LDL-C screening, and had a fasting LDL-C ≥85 mg/dL and fasting triglycerides ≤400 mg/dL. Exclusion criteria included the following conditions or procedures: family or personal history of hereditary muscular disorders, moderate to severe heart failure, moderate to severe renal dysfunction, recent cardiovascular event or deep vein thrombosis/pulmonary embolism, recent or planned revascularization/cardiac surgery, type 1 diabetes, uncontrolled or recently-diagnosed type 2 diabetes, infection, recent malignancy, and major cardiac, endocrine, major hematologic, renal, metabolic, and gastrointestinal disorders. Patients were excluded for current or recent use of the following drugs: lipid-lowering drugs or supplements other than statins or ezetimibe, drugs or supplements that potentially alter lipid metabolism or inhibit cytochrome p450 family 3 subfamily A (CYP3A), and evolocumab or other PCSK9 inhibitor. Female patients were excluded if they were pregnant, breast-feeding, intended to become pregnant, or were of childbearing potential and not using effective birth control. Finally, patients were excluded if they were enrolled in another investigational device or drug study.During screening prospective enrollees received 1 (THOMAS-1) or 3 (THOMAS-2) 1 mL placebo injections delivered via the PFS (THOMAS-1) or autoinjector (THOMAS-2) to confirm tolerance of subcutaneous injection; this period also included laboratory testing to confirm study eligibility. Patients who tolerated the screening and met eligibility criteria were randomized. Enrolled patients were randomized 1:1 by interactive voice/web-based response system to the autoinjector or PFS in THOMAS-1 and autoinjector or AMD in THOMAS-2. Randomization was stratified by baseline LDL-C <130 mg/dL vs ≥130 mg/dL.Three total doses were administered over 6 weeks in THOMAS-1 (140 mg biweekly) and 12 weeks in THOMAS-2 (420 mg monthly). At the time of the first dose of evolocumab, the clinic healthcare practitioner trained the patient on how to use the device to safely deliver a full dose and reviewed the device’s instructions for use  the patient was randomized to. At the first visit (day 1) and during telephone contacts , clinic staff documented whether the patient was able to administer a full dose of evolocumab. Patients returned to the site for LDL-C measurement at week 6 in THOMAS-1 and weeks 10 and 12 in THOMAS-2. The end of study visit was a telephone contact at week 8 for documenting AEs in THOMAS-1 and an in-clinic visit at week 12 in THOMAS-2.Evolocumab is a sterile, preservative-free solution. Investigators could prescribe any concomitant medications or treatments except for prohibited drugs or supplements that potentially lower lipids, affect lipid metabolism, or inhibit CYP3A.The autoinjector used in the phase 3 evolocumab studies contained 140 mg of evolocumab in 1 mL total solution. The PFS, similarly, contained 140 mg of evolocumab. Each autoinjector or PFS injection was administered in up to three anatomical locations: abdomen, thigh, or outer arm (arm injections required caregiver assistance).The AMD is a single-use, disposable, on-body electromechanical injection device. It was packaged with a prefilled cartridge assembly containing 420 mg of evolocumab in a 3.5 mL solution. All AMD injections were administered to the patient’s abdomen, thigh, or outer arm with arm injections requiring caregiver assistance.Diagrams of the devices are displayed in the Appendix of Additional file Successful administration of a full evolocumab dose in the at-home setting was assessed in telephone contacts at weeks 2 and 4 of THOMAS-1 and 4 and 8 of THOMAS-2.Fasting lipid assessments were taken at screening and day 1 in both THOMAS studies, week 6 in THOMAS-1, and weeks 10 and week 12 in THOMAS-2. LDL-C was determined in a reflexive manner by using the Friedewald equation  and PCSK9 levels (pharmacodynamics [PD]), as well as anti-evolocumab antibodies. PK and PD analyses were conducted and presented descriptively by study device. If samples tested positive for binding anti-evolocumab antibodies, they were also tested for neutralizing antibodies.AEs and serious AEs were documented at all visits. Treatment-emergent AEs were defined as those occurring with an onset after the first administration of study drug and before the end of study visit, and investigators were asked to assess whether there was a reasonable possibility that the events were related to evolocumab or device. Adverse device effects were treatment-emergent AEs that the investigator deemed possibly related to the device. Investigators were trained about intentional use before enrolling patients.Deaths and cardiovascular events were adjudicated by an independent clinical endpoint committee  composed of independent members blinded to patient identity, treatment assignment, and LDL-C concentrations.The primary endpoint of both THOMAS studies was the patient-reported successful outcome of attempted self-administered full-dose of evolocumab in the home-use setting with the study device . The secondary endpoint was the mean change in LDL-C from baseline to 6 weeks in THOMAS-1 and the mean of weeks 10 and 12 in THOMAS-2.The THOMAS studies did not test a formal hypothesis. For the analysis of the primary endpoint in both studies, the proportion of patients who successfully self-administered a full dose of evolocumab at each of the two home visits was reported. The 95 % confidence intervals (CIs) for the proportions were calculated using the Wilson score interval. The secondary endpoint was estimated percent change from baseline in LDL-C to week 6 in THOMAS-1 and the mean of weeks 10 and 12 in THOMAS-2. In THOMAS-1, this outcome was estimated using an analysis of covariance model that included study device and LDL-C stratum . In THOMAS-2, the outcome was estimated using a repeated-measures mixed-effects model that included the screening LDL-C stratum, study device, visit, and study device by visit. Prespecified subgroup analyses included age (<65 years and ≥65 years) and sex. AEs, deaths, and adjudicated cardiovascular events were summarized and are presented descriptively. Analyses were conducted using SAS version 9.2 or later .In the THOMAS-1 study, 271 patients were screened, 149 were randomized , and 144 completed the study (97 %). In the THOMAS-2 study, 243 patients were screened, 164 were randomized , and 157 completed the study (96 %). Patient disposition is displayed in the Appendix of Additional file The patient profiles of THOMAS-1 and THOMAS-2 were similar and balanced between study device groups  or the mean of weeks 10 and 12 (THOMAS-2) similarly regardless of the patients’ device or dosing schedule  and PCSK9 levels (PD) were similar between devices in the THOMAS studies  and no preferred term was reported more than once for these events. In THOMAS-1, one patient (autoinjector group) experienced cerebrovascular accident (serious AE), one subject (PFS group) experienced cholecystitis (serious AE) and cholelithiasis, and one subject (PFS group) experienced renal impairment. These events were not considered related to the study drug or device. In THOMAS-2, one patient (autoinjector group) experienced injection-site hematoma that was not considered related to the study drug but was considered related to the study procedures and device.There were four adverse device effects total, all of which occurred in THOMAS-2 and were low severity (grade 1). One patient experienced two instances of injection-site reaction (AMD group); one patient, pain in extremity (autoinjector group); and one patient, injection-site hematoma (autoinjector group). There were no deaths in either study. There was one positively adjudicated cardiovascular event; one patient  experienced an adjudicated, nonfatal ischemic stroke. No binding anti-evolocumab antibodies developed during evolocumab treatment.The results of the THOMAS studies indicate patients can successfully administer evolocumab in the home-use setting without healthcare provider–supervision. The study devices were all comparable with respect to the primary endpoint of successful home-use self-administration as well as their safety profiles, with comparable rates of injection-site reactions and adverse device effects. Reduction in LDL-C following home-use administration was comparable across dosing regimens and devices. The devices tested were safe and well tolerated. AEs in the THOMAS studies were similar to AEs of the overall PROFICIO population (Koren et al. Despite the availability of injectable biologics in the home-use setting for multiple other conditions (AbbVie Inc The THOMAS studies were open label because blinded allocation to injection devices is not possible. Possible limitations include inaccuracy or bias in self-reporting for the primary endpoint, but the profound LDL-C reduction seen at follow-up in both studies indicates that the proportion of successful self-administrations is reliable.The THOMAS-1 and THOMAS-2 studies demonstrate that after appropriate training, patients can safely and effectively self-administer evolocumab in the home-use setting. LDL-C reductions were robust and consistent with expectations from the other PROFICIO studies. AEs, including injection-site reactions, were infrequent and similar between treatment groups. The biweekly and monthly dosing regimens were clinically equivalent.


Attention-deficit/hyperactivity disorder (ADHD) is a highly heritable neurodevelopmental disorder, yet the search for genes with a definitive role in its etiology has been elusive. Deconstructing the disorder in its endophenotypic traits, where the variance is thought to be associated with a fewer number of genes, should boost the statistical power of molecular genetic studies and clarify the pathophysiology of ADHD. In this study, we tested for neuroanatomical and cognitive endophenotypes in a group of adults with ADHD, their unaffected first-degree relatives, and typically developing control subjects.Sixty participants, comprising 20 adults with ADHD, 20 unaffected first-degree relatives, and 20 typically developing control subjects matched for age and gender undertook structural magnetic resonance imaging scans. Voxel-based morphometry with DARTEL was performed to obtain regional gray and white matter volumes. General linear analyses of the volumes of brain regions, adjusting for age and total intracranial volume, were used to compare groups. Sustained attention and response inhibition were also investigated as cognitive endophenotypes.Neuroanatomical abnormalities in gray matter volume in the right inferior frontal gyrus and white matter volume in the caudal portion of the right inferior fronto-occipital fasciculus were shared between ADHD probands and their unaffected first-degree relatives. In addition, impairments in sustained attention were also found to be shared between ADHD patients and their relatives.Cognitive impairments in sustained attention and neuroanatomical abnormalities in the right inferior frontal gyrus and the posterior part of right inferior fronto-occipital fasciculus are putative neurocognitive endophenotypes in adult ADHD. Given the CFP network mainly includes cortical areas and that previous data showed the cortex as the primary source of volumetric abnormalities, particularly in adult ADHD Twenty ADHD patients, 20 unaffected first-degree relatives of ADHD patients, and 20 typically developing participants matched for age and gender were included. Written consent was obtained and the study was approved by the Cambridgeshire 3 Research Ethics Committee (REC: 09/H0306/38). Attention-deficit/hyperactivity disorder proband-relative pairs were recruited from the Adult ADHD Research Clinic, Addenbrooke’s Hospital, Department of Psychiatry, University of Cambridge. Patients received a diagnosis of ADHD according to DSM-IV Text Revision On the testing day, all participants were interviewed using the Mini International Neuropsychiatric Inventory All participants completed the Cambridge Neuropsychological Test Automated Battery stop signal task of response inhibition Images were acquired at Wolfson Brain Imaging Centre, University of Cambridge, using a Siemens TIM Trio 3T system   or false discovery rate Within these ROIs, conjunction analyses testing for global differences at the cluster level was conducted with the conjoined contrasts as  to identify decreased gray matter volume in the ADHD group and their unaffected relatives compared with control subjects. To identify increased gray matter volume in the ADHD group and their unaffected relatives compared with control subjects, the conjoined contrasts were  [a similar approach is used in For white matter analysis, to explore both cortical and subcortical abnormalities in a nonbiased manner, a whole-brain approach was used. The same conjunction analysis used for gray matter analysis testing for global differences at the cluster level was carried out with the conjoined contrasts as  to detect decreased white matter volume in the ADHD group and their unaffected relatives compared with control subjects. To identify increased white matter volume in the ADHD group and their unaffected relatives compared with control subjects, the conjoined contrasts were .To characterize differences between the three groups, cluster regional volume estimates surviving the conjunction analyses were extracted using MarsBaR The three groups did not differ in age and gender. Attention-deficit/hyperactivity disorder group scored four points lower than typically developing control subjects on NART full IQ. Attention-deficit/hyperactivity disorder differed from relatives and control subjects in self-reported current and childhood symptoms. Unaffected first-degree relatives were significantly different from ADHD and control groups on self-reported current hyperactive/impulsive symptoms, childhood total symptoms, childhood hyperactive/impulsive, and childhood inattentive symptoms .Table 1SF2,55 = 2.637, p = .081). Post hoc analysis showed a trend toward significance when comparing the ADHD group versus control subjects (p = .064). First-degree relatives were not different from the ADHD and control groups . Given the trend, we reran the analysis with a less stringent correction for multiple comparisons (Sidak), yet the significance remained unchanged.F2,55 = 6.058, p = .004). Post hoc analysis showed that the ADHD group performed worse than the control group (p = .025). First-degree relatives were not different from ADHD (p = 1.000) but performed significantly worse than the control group (p = .005)  ( = .005) .Figure 1F2,56 = 1.536, p = .224; total brain volume: F2,56 = 1.827, p = .170).Multivariate analysis of covariance assessing for TIV and total brain volume with group as a fixed factor and age as a covariate showed no differences between the three groups   (cluster surviving at FWE  z = 30) . To charF2,57 = 10.259, p = .0002). Post hoc comparisons revealed that the ADHD group had significantly decreased gray matter volume in the rIFG compared with control subjects (p = .035); first-degree relatives were not different from the ADHD probands (p = .184) but differed from the control group (p < .001), suggesting that abnormal decrease in gray matter volume in the rIFG was shared by both ADHD probands and their first-degree relatives. Region of interest conjunction analysis on the putamen and caudate nucleus did not show significant decrease in gray matter volume in these regions.Results showed a main effect of group . Post hoc comparisons revealed that the ADHD group had significantly increased gray matter volume in the L-MoG compared with control subjects (p = .001); first-degree relatives were not different from the ADHD probands (p = .110) or from the control group (p = .259). Analysis of variance on volume estimates extracted from R-SoG showed a main effect of group , and post hoc comparisons revealed that the ADHD group had significantly increased gray matter volume in the R-SoG compared with control subjects (p = .002); first-degree relatives were not different from the ADHD probands (p = .137) or from the control group (p = .334). Similar results were found in the L-dmCC showing a main effect of group , and post hoc comparisons revealed that the ADHD group had significantly increased gray matter volume in the L-dmCC compared with control subjects (p = .010); first-degree relatives were not different from the ADHD probands (p = .121) or from the control group (p = 1.000). Region of interest conjunction analysis on the putamen and caudate nucleus did not reveal significant increase in gray matter volume.Analysis of variance on the regional volume estimates extracted from the L-MoG showed a main effect of group  at the posterior portion of the right inferior fronto-occipital fasciculus (r-iFoF) (cluster-level FWE correction p < .05) . Post hoc analysis confirmed that the ADHD group had an abnormal increase in white matter volume compared with control subjects (p < .001) and that there were no differences between the ADHD group and their first- degree relatives (p = .343); first-degree relatives were statistically different from control subjects (p = .011). The results suggest that white matter abnormalities in the posterior portion of the r-iFoF were shared between ADHD probands and their unaffected first-degree relatives.Whole-brain conjunction analysis showed a cluster of 288 voxels with peak local maxima  . AnalysiBivariate Pearson correlation was calculated between gray and white matter volume estimates (extracted from the rIFG and r-iFoF) and sustained attention and response inhibition scores  across groups. Gray matter volume estimates in the rIFG correlated with RVP-total hits, but not with SSRT, while white matter volume estimates in the r-iFoF correlated with SSRT but not with sustained attention score .Table 3PThe aim of this study was to test for putative neuroanatomical and cognitive endophenotypes in adult ADHD in the CFP cognitive/attention network, which is thought to have a role in the pathophysiology of ADHD. Results could not be explained by nonspecific confounds such as age or variation in total intracranial or brain volume, since these were not statistically different between groups. Moreover, the effects of age and TIV were controlled for in the analyses. Although the ADHD group had a lower full IQ compared with control subjects, the first-degree relatives of ADHD participants had an IQ comparable with the control and the ADHD groups. Therefore, shared impairments between relatives and ADHD probands are less likely to be explained in full by variability in intellectual abilities. Finally, despite not being statistically significant, there were trend-level gender differences across groups. However, previous research in adult ADHD has shown no evidence that gender moderates the phenotypic expression of the disorder or the patterns of cognitive and psychosocial functioning Here, we identified both neuroanatomical and cognitive putative endophenotypes. Neuroanatomically, the ADHD group had gray matter volume decrease in the rIFG and white matter volume increase in the posterior part of the r-iFoF, and these abnormalities were shared by both ADHD probands and their unaffected first-degree relatives. Moreover, sustained attention impairments were also shared among ADHD probands and their unaffected first-degree relatives. This suggests that these abnormalities are at least partly mediated by factors common to both groups and might indicate vulnerability markers for adult ADHD. We did not test for heritability of sustained attention, which is another criteria to be met for a putative endophenotype; however, others have shown that sustained attention is substantially genetically determined, with heritability estimates of about 60% et al. Decrease in gray matter density in the rIFG in ADHD has been observed in other studies A trend toward significant impairments in response inhibition in the ADHD group was present, and therefore we cannot exclude that with an increase in sample size results would become significant. However, the absence of clear impairments, even when using a less stringent correction for multiple comparisons, and the lack of correlation between response inhibition measure and rIFG volume are consistent with previous research showing that in individuals with ADHD impulsivity improves with age, while attentional impairments remain NTRK1 and NTRK2, that encode a high-affinity receptor for nerve growth factor, a neurotrophin involved in neural development and myelination. A variant in the neurotrophin gene, BDNF, has previously been associated with white matter integrity in the iFoF in young adults It is known that white matter continues to develop until the late 20s et al.Attention-deficit/hyperactivity disorder individuals had abnormal increase in gray matter volume compared with control subjects in the L-MoG, R-SoC, and L-dmCC. Recently, Seidman In summary, we have demonstrated for the first time that neuroanatomical and cognitive impairments implicated in ADHD in adulthood are shared between individuals with ADHD and their unaffected first-degree relatives, highlighting neurocognitive vulnerability markers for adult ADHD. These findings correspond with the recent development of the Research Domain Criteria approach


Attention-Deficit/Hiperactivity Disorder (ADHD) is a prevalent disorder, but its neuroanatomical circuitry is still relatively understudied, especially in the adult population. The few morphometric magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) studies available to date have found heterogeneous results. This may be at least partly attributable to some well-known technical limitations of the conventional voxel-based methods usually employed to analyze such neuroimaging data. Moreover, there is a great paucity of imaging studies of adult ADHD to date that have excluded patients with history of use of stimulant medication.A newly validated method named optimally-discriminative voxel-based analysis (ODVBA) was applied to multimodal  MRI data acquired from 22 treatment-naïve ADHD adults and 19 age- and gender-matched healthy controls (HC).Regarding DTI data, we found higher fractional anisotropy in ADHD relative to HC encompassing the white matter (WM) of the bilateral superior frontal gyrus, right middle frontal left gyrus, left postcentral gyrus, bilateral cingulate gyrus, bilateral middle temporal gyrus and right superior temporal gyrus; reductions in trace (a measure of diffusivity) in ADHD relative to HC were also found in fronto-striatal-parieto-occipital circuits, including the right superior frontal gyrus and bilateral middle frontal gyrus, right precentral gyrus, left middle occipital gyrus and bilateral cingulate gyrus, as well as the left body and right splenium of the corpus callosum, right superior corona radiata, and right superior longitudinal and fronto-occipital fasciculi. Volumetric abnormalities in ADHD subjects were found only at a trend level of significance, including reduced gray matter (GM) in the right angular gyrus, and increased GM in the right supplementary motor area and superior frontal gyrus.Our results suggest that adult ADHD is associated with neuroanatomical abnormalities mainly affecting the WM microstructure in fronto-parieto-temporal circuits that have been implicated in cognitive, emotional and visuomotor processes. Attention-deficit and hyperactivity disorder (ADHD) is a frequent and underdiagnosed mental disorder in the general adult population, with a reported prevalence of up to 5.8% in this age range The neuroanatomical circuitry underlying adult ADHD is still relatively understudied. Only a few brain morphometric investigations using magnetic resonance imaging (MRI) have evaluated adult ADHD subjects to date, most of which enrolling patients under pharmacological treatment with stimulant agents. These MRI studies have suggested the presence of gray matter (GM) volume abnormalities in prefrontal-striatal-parietal networks Thus although not yet numerous, the above MRI studies have provided preliminary evidence that the neuropathology underlying ADHD in adults may involve abnormalities both of GM and WM tracts. However, there has been a great paucity of studies evaluating treatment-naïve adult ADHD subjects to date ad hoc way, even though it significantly affects the detected group differences. Finally, and most importantly, conventional VBM methods employ a “mass univariate” statistical approach, considering each voxel individually in its separate brain compartment without weighting possible inter-relationships with neighboring voxels and voxels from other brain tissues Because widely distributed brain networks may be implicated in ADHD, voxel-based methods that systematically search for abnormalities across the entire brain may be more suitable for analyzing data in MRI studies of ADHD, rather than region of interest (ROI)-based methods that are unavoidably restricted to a few selected portions of the brain. However, significant findings have varied considerably across the few MRI studies of ADHD to date that used voxelwise methods, particularly in regard to their specific brain location A recently developed voxelwise image analysis methodology, known as optimally-discriminative voxel-based analysis (ODVBA), attempts to minimize the above technical limitations. The ODVBA approach employs a spatially adaptive smoothing filtering and a high-dimensional multivariate local discriminative analysis technique in order to achieve improved sensitivity and accuracy to detect regional brain abnormalities In the present MRI study, we employed the ODBVA approach to compare treatment-naïve adults with ADHD and age and gender-matched healthy controls (HC). Given the relevance of assessing both localized morphological abnormalities and microstructural changes in large-scale brain networks associated with ADHD Twenty-two treatment-naive patients with ADHD aged 18–50 years were consecutively evaluated at the outpatient ADHD clinic of the Institute of Psychiatry, University of São Paulo, Brazil. Subjects were interviewed with the Structured Clinical Interview (SCID) for the DSM-IV Healthy volunteers matched for age and gender with ADHD patients were recruited through advertisement in the local community and constituted our HC group. All subjects in the HC group also underwent clinical interviewing, including the SCID and the K-SADS-PL screening, in order to exclude psychiatric disorders and previous use of psychopharmacological agents.In addition to the clinical instruments mentioned above, both patients and HC were screened for substance use with the Alcohol Use Disorders Identification Test (AUDIT) Exclusion criteria for both groups were: substance abuse or dependence (current and lifetime); the presence of medical conditions or neurological disorders which could affect the central nervous system; history of mental retardation as assessed by clinical interviews with the patients and a close relative if necessary; past history of head trauma with loss of consciousness; and contraindications for MRI scanning.Comissão de Ética para Análise de Projetos de Pesquisa” – CAPPesq from the board of the University o Sao Paulo Medical School, and “Comissão Nacional de Ética em Pesquisa – Conep”. After complete description of the study to the subjects, written informed consent was obtained.This study was approved by our local ethics committee: “All subjects (ADHD patients and HC) underwent MRI scanning using a 1.5T Siemens Espree system .Morphological data was acquired using a T1-weighted magnetization-prepared rapid gradient echo sequence (MPRAGE) using the following parameters: TR = 2,400 ms, TE = 3.65 ms, NEX = 1, field of view (FOV) = 240 mm, flip angle = 8o, matrix = 192×192 pixels, slice thickness = 1.2 mm (no gap between slices), voxel size = 1.3×1.3×12 mm, resulting in 160 slices covering the whole brain.2) plus diffusion-weighted images (DWI) acquired along 64 non-colinear directions  using the following parameters: TR = 8,000 ms, TE = 110 ms, NEX = 2, FOV = 240 mm, matrix = 120×120 pixels, slice thickness = 2.7 mm (no gap between slices), voxel size = 2.0×2.0×2.7 mm, resulting in 50 slices covering the whole brain.The DTI sequence was acquired using cardiac gating, a 12-channel head coil and parallel imaging. DTI was based on an echo-planar image (EPI) acquisition and consisted of one image without diffusion gradient  and a fluid attenuated inversion recovery (FLAIR) transaxial sequence . Individual image inspection of the datasets of each subject was performed visually by an expert neuroradiologist aiming to identify silent gross brain lesions and artifacts that could interfere with image processing and analysis.http://www.bic.mni.mcgill.ca/software/N3/, was used for correcting for signal inhomogeneities. Then, the skull-stripping and cerebellum removal were performed using a novel automated method known as Multi-Atlas Skull-Stripping (MASS version 1.0) http://www.mccauslandcenter.sc.edu/mricro/mricron/index.html. As the segmentation algorithms used to extract the GM and WM have been shown to be inaccurate in the cerebellum, due to reduced contrast, our group routinely performs the cerebellum removal. Moreover, the removal of the cerebellum improves our ability to accurately segment GM/WM throughout the brain.The T1-weighted images were pre-processed by correcting for signal inhomogeneities followed by skull-stripping and cerebellum removal. The MNI_N3 Software Package http://www.rad.upenn.edu/sbia/software/request.php?software=mico. The skull-stripped and cerebellum-removed images were then spatially registered to the single-subject brain template of Montreal Neurological Institute (MNI) through a robust method for elastic registration called Deformable Registration via Attribute Matching and Mutual-Saliency weighting (DRAMMS version 1.1.0) http://www.rad.upenn.edu/sbia/software/dramms/download.html. The deformation field resulting from this spatial registration was then applied to the segmented images in order to generate mass-preserved volumetric maps, named Regional Analysis of Volumes Examined in Normalized Space (RAVENS) maps of the GM, WM, and cerebrospinal fluid compartments The images were subsequently segmented into their 3 principal brain tissues  through an automated, iterative algorithm for energy minimization called Multiplicative Intrinsic Component Optimization (MICO) http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FslInstallation. Following the spatial normalization, Fractional Anisotropy (FA) and Trace (TR) images were derived for each subject. While FA provides a measure of diffusion directional anisotropy, TR affords indices of diffusivity, similarly to other commonly employed DTI measures such as mean diffusivity (MD) micro-structural brain abnormalities, the relatively large voxel size of the DTI acquisition (2.0*2.0*2.7 mm) implies that FA differences between groups may not always indicate a micro-structural change.The diffusion tensor images were reconstructed from the DWI data using multivariate linear fitting p values) are obtained by using permutation tests Statistical analyses were performed voxel-by-voxel using the Optimally-Discriminative Voxel-Based Analysis (ODVBA 2.0) Software Package For the detection of differences in morphometry, anisotropy and diffusivity measures between adult ADHD and HC, we used a strict statistical threshold of p<0.05 with false-discovering rate (FDR) correction for multiple comparisons. Findings that were significant only at an uncorrected threshold of p<0.001 are reported as trends. The significance maps are partitioned and analyzed according to 1) the automated anatomical labeling (AAL) atlas In addition to the above described between-group comparisons, we conducted a voxel-based search for significant linear correlations between the severity of symptoms as assessed by the ASRS-18 within the ADHD group and each of the four maps , in a regression analysis using the general linear model (GLM) As mentioned above, both groups were matched for age and gender, and all participants had no current of past history of substance use disorders. ADHD patients and HC did not differ with regard to years of education and handedness.From the 22 patients with ADHD, 10 had the combined subtype whereas 12 presented the inattentive subtype of the disorder. Also, 7 out of the 22 ADHD patients fulfilled criteria for comorbid axis I disorders: 4 for bipolar disorder, 2 for major depressive disorder and 1 for anxiety disorder NOS.Significant group differences (at the corrected p<0.05 level) and/or trends (p<0.001 uncorrected) were detected in four comparisons between ADHD patients and HC: 1) GM of ADHD < GM of HC; 2) GM of ADHD > GM of HC; 3) FA of ADHD > FA of HC; 4) TR of ADHD < TR of HC. These differences are detailed in the sub-items below.p<0.001, uncorrected for multiple comparisons. These foci were located mainly in the parietal cortex (right angular gyrus), as presented in There were foci of lower GM values in ADHD patients compared to HC, but these were significant only at the trend level of p<0.001, uncorrected). These foci of increased GM values in the ADHD group were detected mainly in the right supplementary motor area right superior frontal gyrus. , in WM underlying the bilateral superior frontal gyrus, right middle frontal gyrus, bilateral cingulate gyrus, bilateral middle temporal gyrus and left postcentral gyrus  between groups when we compared: 1) WM of ADHD < WM of HC; 2) WM of ADHD > WM of HC; 3) FA of ADHD < FA of HC; and 4) TR of ADHD > TR of HC.None of the findings reported in the above comparisons retained statistical significance after correction for multiple comparisons (p<0.05). However, the following results remained as trends  see , 3 and 4The investigation of correlations between ASRS-18 scores within the ADHD group and brain imaging measures revealed no significant results at p<0.05 (corrected for multiple comparisons).micro-structural changes in a whole-brain fashion, thus potentially affording a more thorough understanding of the network of anatomical abnormalities underlying the clinical manifestations of ADHD This MRI study investigated brain morphometric and DTI differences between adults with ADHD and age- and gender-matched healthy subjects. In contrast with the vast majority of imaging studies of adult ADHD patients conducted to date, we were able to investigate a group of adult ADHD subjects who had never been exposed to treatment. Samples of treatment-naïve adults with ADHD provide information of critical relevance on brain abnormalities which are genuine to the disease and cannot be attributed to medication effects The present results suggest that adult ADHD is associated with subtle GM volume abnormalities affecting fronto-parietal networks, since there was a statistical trend towards GM reductions in the right angular gyri in our ADHD sample compared to controls, as well as GM volume increases in the right superior frontal gyrus, and right supplementary motor area. These cortical areas are interconnected and participate critically in a number of cognitive processes of relevance to ADHD such as attention, executive functioning and visuomotor coordination Regions of GM reduction affecting the parietal cortex in adults with ADHD were also found by Makris et al. (2007), who observed a decrease in thickness in the inferior parietal lobule of the right hemisphere ADHD in children is known to be linked to a retarded cortical maturation relative to normal development Despite the improved sensitivity of the ODBVA methodology employed herein No significant focus of WM volume abnormality was observed in the ADHD group relative to controls, even when a flexible statistical threshold of uncorrected p<0.001 was used. Few MRI studies investigated the presence of WM morphological changes in ADHD to date. Studies evaluating children and adolescents with ADHD reported an overall reduction of total cerebral WM as well as mostly bilateral reductions in all four lobes compared to healthy subjects Conversely, our analyses of DTI data revealed a widespread pattern of microstructural WM differences between the ADHD and HC groups, as measured, respectively, by FA and TR indices, with findings retaining statistical significance after correction for multiple comparisons. These changes in DTI indices in our sample of adults with ADHD relative to HC were located in fronto-striatal-parieto-temporo-occipital circuits, involving WM regions underlying the frontal, parietal, temporal and occipital lobes, as well as the superior corona radiata, caudate nucleus, superior longitudinal and superior fronto-occipital fasciculi, besides portions of the corpus callosum responsible for the inter-hemispheric connection of frontal, parietal and occipital regions  and 4. TIt is interesting to note that some of the WM tracts implicated in the present study  are among the tracts that mature most tardive in normal life, with the age of peak FA and minimum TR varying from 30 to 40 years in healthy aging. Conversely, other WM tracts also implicated herein  show an early developing pattern of maturation in normal life, with the age of peak FA and minimum TR varying from 20 to 30 years in healthy aging Although findings of increased FA Higher values of FA are typically interpreted as reflecting more highly organized fibers oriented in the same direction In regard to the decrement in TR, this measure reflects the rate of water diffusion through the WM, which was reduced in our adult ADHD patients. Besides the hypothesis of abnormally increased fiber density raised above, findings of decreased TR in brain diseases have been previously suggested to reflect processes of atypical myelination Part of the WM tracts in which we found the greater degree of FA and/or TR differences between ADHD patients and HC are known to interconnect the brain regions where we also detected trend GM volume changes in the ADHD group, namely the fronto-striatal-parieto-temporo-occipital networks. Therefore, taking together the different GM and WM measurements evaluated in the present study, the findings obtained suggest that the persistence of ADHD symptoms into adulthood relates to: circumscribed GM volume abnormalities, subtler than those detected in children and adolescent with ADHD and which are thought to reflect delayed maturation processes We used exactly the same image processing pipelines and statistical inference approach to the analysis of both morphometric and DTI data obtained from the same individuals in a single MRI scanning session. This allowed us to demonstrate that microstructural WM differences from HC are more widespread and significant than macroscopic GM or WM volumetric changes in never-medicated adult ADHD patients. To the best of our knowledge, such prominence of WM microstructural changes in treatment-naïve ADHD adults has not been reported previously in studies combining DTI and brain volumetric measurements. This pattern of results is consistent with the notion that ADHD-related impairments in cortico-subcortical circuits may originate from alterations in microstructural connectivity We did not find any significant results in our correlation analysis between brain imaging measures and the severity of ADHD symptoms. This may relate to an increased risk of type II statistical errors, due to the relatively small size of the ADHD sample. Also, the inclusion of ADHD patients with comorbidities may have increased the clinical heterogeneity of our ADHD sample. However, comorbid psychiatric disorders are very frequent in ADHD Finally, two additional methodological limitations should be acknowledged. First, regarding to the protocol used for the acquisition of DTI data, we acquired only one reference “B0” (non-diffusion) image. Although this is a standard strategy In conclusion, the use of the newly-validated ODVBA image analysis methodology in the present multimodal MRI study revealed the presence of widespread microstructural WM changes in tracts connecting distributed cortical regions in treatment-naïve ADHD adults, as well as subtle regional brain volume abnormalities confined to the GM compartment. Further application of such study design in larger samples is warranted to confirm these preliminary findings and to further investigate how they relate to specific ADHD symptom dimensions, associated neuropsychological deficits, treatment response patterns and other aspects of clinical outcome.