Attention-deficit/hyperactivity disorder (ADHD) is the most commonly diagnosed neurodevelopmental disorder in childhood, which affects more than 5% of the population worldwide. ADHD is characterized by developmentally inappropriate behaviors of inattention, and/or impulsivity and hyperactivity. These behavioral manifestations contribute to diminished academic, occupational and social functioning, and have neurobiological bases. Neuronal deficits, especially in the attention and executive function processing networks, have been implicated in both children and adults with ADHD by using sophisticated structural and functional neuroimaging approaches. These structural and functional abnormalities in the brain networks have been associated with the impaired cognitive, affective, and motor behaviors seen in the disorder. The goal of this review is to summarize and integrate emerging themes from the existing neuroimaging connectivity studies based on advanced imaging techniques, applied in data of structural magnetic resonance imaging (MRI), functional MRI (fMRI), diffusion tensor imaging, electroencephalography and event related potential; and to discuss the results of these studies when considering future directions for understanding pathophysiological mechanisms and developmental trajectories of the behavioral manifestations in ADHD. We conclude this review by suggesting that future research should put more effort on understanding the roles of the subcortical structures and their structural/functional pathways in ADHD. Attention deficit/hyperactivity disorder (ADHD) is the most commonly diagnosed neurodevelopmental disorder in childhood. Diagnoses of ADHD are made based on developmentally inappropriate behavioral symptoms, which have been categorized into three subtypes: inattentive, impulsive and hyperactive, and combined type. These core behavioral symptoms must be pervasive across situations, persistent for more than 6 months and observed before the age of 7 years, defined by the diagnostic and statistical manual of mental disorders (DSM-IV-TR) issued by the Attention deficit/hyperactivity disorder is considered one of the most hereditable disorders with an estimated mean heritability of 75% . BesidesIn this study, we will review and summarize these existing studies, which have assessed the regional features and systems-level patterns of the structural and functional brain networks in ADHD, based on advanced computational techniques applied to data of structural MRI, diffusion tensor imaging (DTI), fMRI, electroencephalography (EEG), and event related potential (ERP). We will also discuss the results of these studies when considering future directions for understanding pathophysiological mechanisms and developmental trajectories of the behavioral manifestations in ADHD.Structural MRI is the primary imaging tool used for studying brain anatomy and identifying changes in brain structures. Commonly used structural MRI measures include volume and density of the gray (GM) or white matter (WM) of the whole brain or sub-regions, as well as the regional and whole brain cortical GM thickness . TechniqThe early estimations showed approximately 4–5% overall cerebral and cerebellar volumetric reductions in children and adolescents with ADHD, compared to that of typically developing controls TDC; . Other sBasal ganglia regions, such as the globus pallidus, putamen, and caudate have been reported to have structural abnormalities in children with ADHD. Structural MRI studies have detected reduced globus pallidus, putamen, and caudate volumes in voxel-based studies , and in By now, most replicated findings from the voxel-based and ROI-based structural MRI studies have suggested significant decrease of the whole brain GM and WM volumes and significant regional underdevelopment in the prefrontal cortex (PFC), including the OFC, DLPFC, and SFC, basal ganglia substructures , and cerebellum, in patients with ADHD . StructuFrom literature, structural MRI-based techniques for constructing the anatomical brain networks, such as in , have noFunctional MRI techniques provide a way to understand normal brain functions and to test for regional brain dysfunctions associated with disorders . Both taStructures of the cingulo-fronto-pariental (CFP) cognitive/attention network, including the fronto-striatal and fronto-parietal pathways, are thought to be the primary substrate for most attention and executive functions . The maiThe dACC is an important component of the fronto-striatal circuitry of the CFP network, which has been consistently reported to have abnormal activation in ADHD . The dACThe thalamus is a key subcortical structure of the cortico-striato-thalamo-cortical (CSTC) loops that serve attentional and cognitive processing. Significantly reduced regional activations in bilateral thalami , significantly decreased functional connectivity between bilateral pulvinar and right prefrontal regions, and significantly increased connectivity between the right pulvinar and bilateral occipital regions have been reported in children with ADHD, during a visual sustained attention task-based fMRI study . AnotherAltered topological features and inter-regional functional connectivity in large-scale brain networks encompassing cortical and subcortical regions have been increasingly reported, indicating systematic and more widespread brain alterations in ADHD. Resting-state fMRI has been used across laboratories to identify neural networks such as the DMN, dorsal, and ventral attentional networks, as well as motor, visual, and executive control systems . The DMNAltered topological features and inter-regional functional connectivity in large-scale brain networks in ADHD, which have been reviewed in the fMRI section, are convinced in EEG/ERP studies as well. A GTT-based study in resting-state EEG data reported abnormal cluster coefficients and path lengths of the nodes in the left hemisphere, which were recognizable in the delta band, in patients with ADHD when compared to controls . An NBS in vivo information about the WM microstructure through water diffusion, which can reveal microscopic details about tissue architecture  that allows for a complete overview of the WM integrity in the brain, and ROI-based analysis for more specific exploration of the WM abnormalities in certain brain regions. A recent meta-analysis reviewed the ROI-based studies assessing the WM integrity, and provided evidence of several disturbed WM regions in children with ADHD, including the inferior and superior longitudinal fasciculus, anterior corona radiate, cortico-spinal tract, cingulum, CC, internal capsule, caudate nucleus, and cerebellum . Review Development of WM determinative and probabilistic tractography techniques has made it possible to estimate and visualize the structural connectivity of the WM pathways in human brain. Using tractography-based analyses, DTI studies have demonstrated increased FA in WM structures connecting parietal-occipital regions , and traThe neural pathways that are associated with the areas of abnormal WM reviewed above are the pathways connecting the cortical regions, cortical-striatum and cortical-cerebellum. The prevailing theory regarding the neurobiological basis of ADHD identified the fronto-striatal network as a probable substrate of cognitive and behavioral impairments seen in ADHD . StudiesThe CC, the largest band of WM fibers in the brain that connects the left and right hemispheres, plays an important role in inter-hemispheric communication. Thus, abnormal microstructure of CC may affect cognitive functions that depend on bilateral collaboration . Across Attention-deficit/hyperactivity disorder is the most common neurodevelopmental disorder in childhood. Neuroimaging studies have attempted to identify the pathophysiology of the disorder by searching for abnormalities in brain regions and their connections that are involved in attention, executive function, motor control, response inhibition, working memory, and even during rest. We reviewed and summarized the important findings from the structural MRI, fMRI, EEG/ERP, and DTI studies, which have provided the abundant evidence of structural and functional alterations in widespread brain regions and their connections, in this severe and heritable brain disorder.The majority of the existing neuroimaging studies, which have attempted to find the neurobiological underpinnings of ADHD, have focused on cortical regions and their connections, and has demonstrated global cortical maturation delay based on reduced cortical thickness and reduced GM and WM volumes, specifically in frontal lobe , regionaSubcortical regions may also significantly contribute to the pathophysiology of ADHD. For example, the basal ganglia has been associated with the execution of appropriate goal-directed behaviors and may play a role in the behavioral impairments for response control seen in many children with ADHD . NeuroimHowever, the role of the thalamus and its mediating role in cortico-striatal and cortico-cortical pathways in ADHD have been relatively ignored. Very recently, investigation of high resolution structural MRI data revealed reduced bilateral thalamic volumes, as well as regional surface atrophy in the pulvinar nucleus of the left side thalamus in children with ADHD . In the As a summary, brain network associated dysfunctions have been found to be central in ADHD pathophysiology. It is important to gain a better understanding of how subcortical-cortical and cortical-cortical networks development is altered during the onset of the disorder. Thus, future studies should allocate greater resources on subcortical regions and relationships between subcortical and cortical regions in order to provide a better understanding of the etiology of the disorder.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


F, 0.004) that contains a 66Gln-Tyr-Gly chromophore tripeptide sequence. We investigated the optical properties and structure of two variants, Rtms5Y67F and Rtms5Y67F/H146S in which the tyrosine at position 67 was substituted by a phenylalanine. Compared to the parent proteins the optical spectra for these new variants were significantly blue-shifted. Rtms5Y67F spectra were characterised by two absorbing species , whilst Rtms5Y67F/H146S spectra were characterised by a single absorbing species (F, 0.75; trans conformation. The results of chemical quantum calculations together with the structural data suggested that the 513 nm absorbing species in Rtms5Y67F results from an unusual form of the chromophore protonated at the acylimine oxygen. These are the first X-ray crystal structures for fluorescent proteins with a functional chromophore containing a phenylalanine at position 67.Rtms5 is an deep blue weakly fluorescent GFP-like protein ( Aequorea victoria GFP (avGFP) Discosoma species Heteractis crispa have served as a valuable source of far-red fluorescent proteins that include HcRed GFP-like proteins are valuable tools for use in molecular cell biology applications avGFP with tryptophan or histidine resulted in blue-shifted fluorescent proteins (FPs) with cyan and blue fluorescence emissions, respectively avGFPY66F , and no X-ray crystal structures are available, other than those for proteins that do not have a correctly formed GFP-like chromophore H146S each containing a Tyr67Phe substitution. The resulting proteins, Rtms5Y67F and Rtms5Y67F/H146S, have green fluorescence emission  the fluorescence quantum yield for Rtms5Y67F/H146S  was somewhat higher. No significant florescence emission was observed when the 513 nm species of Rtms5Y67F was excited. By comparison the tyrosine-containing chromophores of Rtms5 and Rtms5H146S show a single red-shifted absorbing species . The optical characteristics determined for proteins in this study are summarised and compared to those of other selected proteins in F.In order to investigate the effects of a tyrosine to phenyalanine substitution in Rtms5 and Rtms5 ∼589 nm . The flu 508 nm) , but comavGFP, the chromophores of Rtms5Y67F and Rtms5Y67F/H146S are red-shifted by ∼ 86 nm. Since the Rtms5 and Rtms5H146S chromophores are reported to contain an acylimine linkage  promotes protein unfolding thereby exposing the chromophore acylimine linkage to the bulk solvent, and subsequent nucleophilic attack and hydration. We incubated Rtms5 species . For Rtmectively . CollectY67F and Rtms5Y67F/H146S. The absorbance and fluorescence emission for both Rtms5Y67F and Rtms5Y67F/H146S remained remarkably stable over the range pH 3–11 (pKa <3.0 absorbance and emission)   . Changesmission) . In compctively)  [17]. ThH values . CollectY67F and Rtms5Y67F/H146S. The crystallography and structural statistics are reported in Y67F and Rtms5Y67F/H146S consist of the same 11-stranded β-can motif  and the protein matrix are similar to those observed for Rtms5  interactions  H-bond with Thr179 and an H-bond with Asn161 . Howeverf His146 . Since tY67F/H146S, contribute to differences in hydrogen bonding around the chromophore of Rtms5Y67F (Y67F compared to that of Rtms5Y67F/H146S (Two waters (W292 and W1092) not observed in Rtms5 or Rtms5tms5Y67F . The Nε2tms5Y67F . It is p7F/H146S ; Table 1Y67F is rotated around Cβ towards the benzylidine ring and contributes to a significant increase in the non-coplanarity of the Rtms5Y67F chromophore compared to the Rtms5 chromophore , the imidazolinone oxygen site (ImOH+), and the acylimine oxygen site (AcOH+). The excitation energies and dipole observables associated with the S0–S1 transition of the Rtms5Y67F chromophore model are listed in In order to guide the assignment of the absorbance bands of the Rtms5The computational results were obtained for the truncated model in gas phase and any effects of the protein environment, both steric and electronic, are neglected. For this reason, the confidence that one can place on assignments based on these data is determined by the relative separation of the distinct absorbance bands in the proteins and the separation of excitation energies for different states of the model. Fortunately, the excitation energies of most of the states used in the calculations are quite distinguishable. However, we note that in all cases the optimized geometries of the models are planar. Non-planar distortions of the methine bridge are expected to provide a modest red-shift (on the order of 0.1 eV) Y67F but not Rtms5Y67F/H146S has an absorbance band at 513 nm (+) is significantly redder than the neutral chromophore (368nm)  . This sue oxygen . RotatioY67F and Rtms5Y67F/H146S. mBlueberry 2 was derived from the acylimine-containing red fluorescent mCherry by introduction of number of amino acid substitutions including a Tyr to Phe substitution at position 67. In the absence of a an X-ray crystal structure for mBlueberry 2 the reasons for the marked difference in emission maxima (∼ 40 nm) between mBlueberry 2 and the Rtms5Y67F variants  has been attributed previously to their trans non-coplanar chromophores F, 0.16) observed for Rtms5H146S at alkaline pH  compared to their Rtms5 parents, we were surprised by the lack of evidence for a cis-coplanar chromophore in their structures. The poor electron density corresponding to the chromophore in Rtms5Y67F/H146S suggests it is mobile, and may adopt alternate conformations. However, the difference maps for trans and cis Rtms5Y67F/H146S chromophore conformations under different occupancies indicated that the trans conformation is favoured . This idea is given additional support by the structural data that suggests a change in the position of the side-chain of Ser 69 in Rtms5Y67F compared to Rtms5Y67F/H146S  or oxygen site (ImOH+) on the imidazolinone ring. Although the excitation energy calculated for the ImOH+ model is closer to the experimentally measured energy gap, the weight of precedent favors assignment to a nitrogen-protonated ImNH+ species. Protonation at either of these two positions might be expected be reflected in altered chromophore/protein matrix contacts. Although differences exist in the H-bond network around the chromophore in the RtmsY67F variants compared to their tyrosyl-containing counterparts (Rtms5 and Rtms5H146S) (The data in s5H146S)  in each s5H146S) . We havetrans chromophore conformation. Rtms5Y67F and Rtms5Y67F/H146S have the most pH-stable  green emissions of any FPs (500–520 nm) reported to date. The green emissions of Sapphire FPs having been reported previously to be the most stable to pH (pKa 4.9) Y67F and Rtms5Y67F H146S can be attributed to the benzylidine moiety which lacks a titratable group. The chromophore of the pH-stable blue-emitting Sirius contains the same benzylidine moiety, and has a pKa <3.0 Y67F and Rtms5Y67F/H146S to fluoresce with little attenuation down to ∼ pH 3.5, may prove useful for engineering new improved biosensors for monitoring autophagy in live cells There are few reports in the literature of FPs containing a phenylalanine in position 67 of the chromophore. The phenylalanine substituted variants reported here represent an alternative platform on which to develop fluorescent proteins with green emissions (500–520 nm) and superior pH stability. These proteins may also have a fluorescent Y67F and Rtms5Y67F/H146S are obligate tetramers. However, we recently described a monomer of Rtms5 called Ultramarine Rtms5Y67F or Rtms5Y67F/H146S were constructed by site-directed mutagenesis  using the primer pair 5′-caccacagtgtcagttcggaagcataccattc-3′ and 5′-gaatggtatgcttccgaactgacactgtggtg-3′ and expression vectors pQE10:Rtms5 or pQE10:Rtms5H146S as templates.Expression vectors encoding Rtms5Y67F and Rtms5Y67F/H146S proteins were expressed in the NovaBlue (λDE3) strain of E. coli (Novagen) and purified by Ni-NTA chromatography as described Y67F or Rtms5Y67F/H146S tetramer were pooled and concentrated to 15 mg.ml−1 ready for crystallization trials by the hanging drop vapour diffusion technique.Rtms5F values were determined for proteins (in 20 mM Tris–HCl (pH 8.0), 300 mM NaCl) at 25°C as described F, 1.0) in buffer as standard. Absorbance spectra were determined using a Varian Cary 50 spectrophotometer. For pH titrations, proteins in 20 mM Tris-HCl (pH 8.0) were diluted (∼100-fold) as required into selected 0.1 M buffers Fluorescence spectra were determined using a Varian Eclipse fluorescence spectrophotometer . ΦY67F and Rtms5Y67F/H146S that appeared brown or pale green, respectively were obtained at 20°C via the hanging drop method. Protein (15 mg.ml−1) in 20 mM Tris, 300 mM NaCl, pH 8.0 was mixed 1∶1 or 1∶2 with crystallization solutions, respectively. Numerous small crystals were obtained using conditions reported for Rtms5 Y67F crystals (0.1–0.2 mm in length) were obtained using a crystallization solution composed of 22% PEG 3350 and 0.34 M KI buffered with 0.2 M Tris-HCl pH 8.5 in 3 µl hanging drops . Rtms5Y67H/H146S crystals 0.1–0.2 mm in length were obtained using a crystallization solution with 21% PEG 3350, 0.36 M KI, and 25% glycerol buffered with 0.2 M Tris pH 8.5 in 3 µl hanging drops . Rtms5Y67F crystals were flash frozen prior to data collection using 30% (v/v) glycerol in the precipitant as cryoprotectant. Crystals were transferred stepwise (5% increments) into increasing amounts of glycerol over a time period of 2 h. Rtms5Y67F/H146S crystals were dipped in perfluoropolyether oil  for 1 min before vitrification in a nitrogen-gas stream maintained at 100 K.Crystals of Rtms5Y67F and Rtms5Y67H/H146S were collected at the APS IMCA-CAT beamline in Chicago (USA), and at the MX-1 beamline of the Australian Synchrotron, respectively.Diffraction images for Rtms5http://www.hkl-xray.com) Y67F and with XDS (http://xds.mpimf-heidelberg.mpg.de) Y67F/H146S. Molecular replacement for both Rtms5Y67F and Rtms5Y67F/H146S was carried out with Phaser http://www.ccp4.ac.uk/ccp4i_main.php) Y67F consists of 8 protomers arranged into a pair of 222 tetramers in its asymmetric unit while the top-scoring solution for Rtms5Y67F/H146S had a single protomer in the asymmetric unit.Data integration was carried out with the HKL software package (Y67F and Rtms5Y67F/H146S models was carried out in Refmac5 http://www.ysbl.york.ac.uk/~lohkamp/coot/wincoot.html) http://molprobity.biochem.duke.edu) Y67F which was relaxed in later rounds of refinement. Rounds of simulated annealing refinement in Phenix (http://www.phenix-online.org) O-FCF map and kept in the model if they were located within hydrogen-bonding distance of chemically reasonable groups, visible at 3.0σ map contour level, and possessed a B-factor <80 Å2. Strong peaks observed in the O-FCF map too large to be waters were modelled as chloride ions while even stronger peaks were modelled as iodide ions .Restrained refinement of Rtms5Y67F/H146S chromophore proximal to Ser146 in a position shown to be accessible to halides in Rtms5H146SThe monomer library definitions and PDB coordinates of the QFG chromophore were created using the CCP4 Monomer Library Sketcher Y67F and Rtms5Y67F/H146S models prior to deposition through PDBj ADIT was carried out using Molprobity along with SFcheck Y67F model was refined to Rfactor 15.42% and Rfree 19.77% with 98.6% and 1.4% of residues in the favored and allowed regions of the Ramachandran plot, respectively, with none in the generously or disallowed regions. The final Rtms5Y67F/H146S model was refined to Rfactor 19.68% and Rfree 23.99% with 98.1% and 1.4% of residues in the favored and allowed regions of the Ramachandran plot, respectively, with none in the generously or disallowed regions. The coordinates and structure factors for Rtms5Y67F and Rtms5Y67F/H146S have been deposited in the Protein Data Bank . Biological assemblies for Rtms5Y67F and Rtms5Y67F/H146S were predicted using PISA included in the CCP4 program suite Validation of the final Rtms5nd order perturbation theory nd order perturbation theory http://www.molpro.net) For each protonation state examined, we optimized the geometry of the model using Møller-Plessett 2Figure S1Y67F and Rtms5Y67F/H146S.The chromophore cavities of Rtms5 Orthogonal cutaway views are shown for Rtms5Y67F (A and B) and Rtms5Y67F/H146S (C and D). The side-chain of His146 stabilises the trans conformation of the Rtms5Y67F chromophore. The His146Ser substitution (C) creates a pocket with the potential to accommodate an Rtms5Y67F/H146S chromophore with a cis conformation. The non-coplanar conformation of the chromophores in both Rtms5Y67F and Rtms5Y67F/H146S is stabilised by the side-chains of Arg96 and Arg197 (C and D). Waters are shown as red spheres.(TIF)Click here for additional data file.Figure S2Difference maps showing the trans and cisY67F/H146S chromophore conformations under different occupancies. Rtms5 Occupancy ratios (trans/cis) are 0.0/1.0, (A); 0.25/0.75, (B); 0.5/0.5, (C); 0.75/0.25, (D) and 1.0/0.0 (E). The positive (green mesh) and negative (red mesh) difference maps are contoured to +2.5σ and −2.5σ, respectively. The trans chromophore conformation is favoured in Rtms5Y67F/H146S. A nearby chloride ion (green sphere) was omitted from the map calculation.(TIF)Click here for additional data file.Figure S3Y67F/H146S with a hypothetical A model showing the chromophore cavity of Rtms5trans-coplanar chromophore. Orthogonal views of the trans Rtms5Y67F/H146S chromophore in a trans non-coplanar as suggested by the X-ray structure (A and B), and modelled in a trans coplanar conformation (C and D) are shown. The conformation of the Arg197 residue, which contacts the benzylidene moiety of the chromophore  restricts the possibility of a trans coplanar chromophore (A). The conformation of Arg197 is stabilised by H-bonds  to two nearby water molecules  and to Glu148 (B). Repositioning of the Arg197 side chain (C) creates a space in which a trans coplanar chromophore could be accomodated. The side-chain of Arg197 in is stabilised by different contacts (D). A nearby chloride is shown (green sphere). The hypothetical model was created in WinCoot, avoiding major clashes with nearby atoms, and only the rearrangment of the Arg197 side chain has been considered.(TIF)Click here for additional data file.Figure S4Hypothetical resonance structures for the chromophore model.(TIF)Click here for additional data file.Text S1(DOCX)Click here for additional data file.Scheme S1(TIF)Click here for additional data file.Scheme S2(TIF)Click here for additional data file.


N = 559) and their unaffected peers (N = 365), aged 6–11, in four parameters of MOXO-CPT performance: Attention, Timing, Hyperactivity and Impulsivity. Results have shown that despite improvement in CPT performance with age, ADHD children continued to demonstrate impaired performance as compared to controls. In most parameters, CPT performance of ADHD children matched that of 1–3 years younger normal controls, with a delay most prominent in older children. However, in the Hyperactivity parameter, ADHD children's performance resembled that of much younger healthy children, with almost no evidence for a developmental catch up. This study suggests that while some cognitive functions develop slower but normally, other functions  show a different trajectory.While data from behavioral, neuropsychological, and brain studies suggested that Attention-Deficit/Hyperactivity Disorder (ADHD) is related to a developmental lag that reduces with age, other studies have proposed that ADHD represents a deviant brain function. The present study used a cross-sectional approach to examine whether ADHD children show a developmental delay in cognitive performance measured by continuous performance test (CPT). We thus, compared six age groups of ADHD children ( Attention-deficit hyperactivity disorder (ADHD) is the most common neurobehavioral disorders of childhood, characterized by inattention, impulsivity and hyperactivity. Using the DSM-IV criteria [American Psychiatric Association (APA), Many children with ADHD have been described as having co-morbid developmental problems in motor coordination, language, behavior, sleep, and mood   in four parameters of CPT performance to determine whether the disorder is characterized by a delay in cognitive development.Participants in this study were 924 children aged 6–11 years, of them 539 boys and 385 girls. The ADHD group included 559 children diagnosed with ADHD and the control group included 365 children without ADHD. The children were divided into six age categories (6–11 years). For example, the category of “8 years” included children who were equal or older than 8 years old, but younger than 9 years old. Background variables are presented in Table Participants in the ADHD group were recruited from children referred to the out-patient paediatric clinics of a Neuro-Cognitive Center, based in a tertiary care university hospital. The children were referred through their paediatrician, general practitioner, teacher, psychologist, or directly by the parents.Each child met the criteria for ADHD according to DSM-IV-TR criteria APA, , as asseEach child scored above the standard clinical cut off values for ADHD symptoms on ADHD/DSM-IV Scales APA, .All children were drug naïve.Inclusion criteria for participants in the ADHD group were:Each child scored below the clinical cut off point for ADHD symptoms on ADHD/DSM-IV Scales APA, .Absence of academic or behavioral problems, as reported by parents and teachers.Participants in the control group were randomly recruited from pupils in regular classes at primary schools. Inclusion criteria for participants in the control group were:Exclusion criteria were intellectual disability, other chronic condition, chronic use of medications, and other primary psychiatric diagnosis . All participants agreed to participate in the study and their parents gave written informed consent to the study, approved by the Helsinki committee (IRB) of Hadassah-Hebrew University Medical Center .The parent and teacher forms of the Conner's ADHD/DSM-IV Scales were used to assess the level of children's ADHD behaviors Conners, .This study employed the MOXO-CPT versionThe total duration of the test was 15.2 min, and it is composed of eight levels . In each trial a stimulus (target/non-target) was presented for 500, 1000, or 3000 ms and then followed by a “void” period of the same duration  that may be confound with CPT performance  visual distractors ; (b) auditory distractors ; and (c) combination of both visual and auditory distractors .Overall, six different distractors were included, each of them could appear as pure visual, pure auditory or as a combination of them. Each distractor was presented for a different duration ranging from 3.5–14.8 s, with a fixed interval of 0.5 s between two distractors. Distractors' onset was not synchronized with target/non-target's onset and could be generated during target/non-target stimulus or during the void period. Visual distractors appeared at one of four spatial locations on the sides of the screen: down, up, left or right. Different levels of the MOXO-CPT were characterized by a different set of distractors: levels 1 and 8 did not include any distractors but only target and non-target stimuli, levels 2 and 3 contained pure visual stimuli, levels 4 and 5 contained pure auditory stimuli, and levels 6 and 7 contained a combination of visual and auditory stimuli. The sequence of distracters and their exact position on the display were constant for each level. The burden of the distracting stimuli increased at the odd number levels; in the 2nd, 4th, and 6th level only one distractor was presented at a time, while in the 3rd, 5th, and 7th level two distractors were presented simultaneously.Performance indices. The MOXO-CPT included four performance indices: attention, Timing, Impulsivity, and Hyperactivity. For detailed description of performance indices see Supplementary A.Attention. This index corresponded to the number of correct responses (a space bar keystroke in response to a target stimulus) performed during the stimulus presentation or the void period that followed it. This index was considered as a pure measure of sustained attention because it measured correct responses independently of the response time.Timing. The timing index was the number of correct responses given only during the time in which the target stimulus was present on the screen.Impulsivity. The impulsivity index was the number of commission responses performed only during the time in which a non-target stimulus was present on the screen.Hyperactivity. The hyperactivity index was the total number of commission responses that were not coded as impulsive responses .T-tests for independent samples and chi-square tests were used for examining group differences across demographic variables. Second, T-tests for independent samples were used to measure the effect of group on CPT indices. Then, each age category of ADHD children was matched to a group of typically developing children which had the closest mean value in the same parameter, by using Cohen's d measure  between ADHD children and their age-matched healthy peers were examined by two tailed p = 0.07 and p = 0.08, respectively) and at age 9 for impulsivity responses (p = 0.06). The rest of the comparisons did not yield significant group differences.As can be seen in Table In order to evaluate the developmental trajectories of the attention performance, each age category of ADHD children was matched to a group of typically developing children which had the closest mean value in the same parameter. The matched group was chosen by using Cohen's d measure   and many of them included only boys . Although CPT performance is often affected by gender  do not show a clear developmental trajectory. The cross-sectional approach chosen for this study allowed frequent evaluations of typically ADHD-related behavior, which is independent upon definition of remission and persistence. Thus, it was possible to trace small and non-linear changes in performance. One of the major difficulties in early diagnosis of ADHD is that decisions about the inappropriateness of behavior in young children are based on subjective judgments of the observers (Rousseau et al., Future research is needed to investigate the course of ADHD symptoms in wider spectrum of age, in specific sub-types of ADHD, and in response to psychostimulants. Moreover, it is important to examine the clinical and behavioral implications of improvement in CPT performance.Itai Berger suggested the study. Itai Berger, Merav Aboud, Julia Melamed, and Hanoch Cassuto collected the data. Itai Berger, Ortal Slobodin, and Hanoch Cassuto designed the study with assistance from Merav Aboud and Julia Melamed. Ortal Slobodin, Itai Berger, and Hanoch Cassuto performed the statistical analysis. Itai Berger, Ortal Slobodin, and Hanoch Cassuto wrote the manuscript. All of the authors contributed to interpret the findings and writing the manuscript, and read and approved the final manuscript.Itai Berger serves on the scientific advisory board of Neuro-Tech Solutions Ltd. All other authors declare no conflicts of interests.


The association between exposure to perfluorinated compounds (PFCs) and attention deficit hyperactivity disorder (ADHD) diagnosis has been sparsely investigated in humans and the findings are inconsistent.A matched case-control study was conducted to investigate the association between fetal exposure to PFCs and ADHD diagnosis in childhood.The study base comprised children born in Malmö, Sweden, between 1978 and 2000 that were followed up until 2005. Children with ADHD (n = 206) were identified at the Department of Child and Adolescent Psychiatry. Controls (n = 206) were selected from the study base and were matched for year of birth and maternal country of birth. PFC concentrations were measured in umbilical cord serum samples. The differences of the PFC concentrations between cases and controls were investigated using Wilcoxon's paired test. Possible threshold effects (above the upper quartile for perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) and above limit of detection [LOD] for perfluorononanoic acid (PFNA)) were evaluated by conditional logistic regression.The median umbilical cord serum concentrations of PFOS were 6.92 ng/ml in the cases and 6.77 ng/ml in the controls. The corresponding concentrations of PFOA were 1.80 and 1.83 ng/ml. No associations between PFCs and ADHD were observed. Odds ratios adjusted for smoking status, parity, and gestational age were 0.81  for PFOS, 1.07 (95% CI 0.67 to 1.7) for PFOA, and 1.1 (95% CI 0.75 to 1.7) for PFNA.The current study revealed no support for an association between fetal exposure to PFOS, PFOA, or PFNA and ADHD. Emission of pollutants from densely populated areas and industries is a growing environmental problem. Contaminants present in the environment can have a negative impact on both human health and environment. Perfluorinated compounds (PFCs) are extremely stable and persistent man-made organic chemicals that have been identified as environmental pollutants. The unique properties of PFCs have made them highly useful in numerous industrial and consumer applications such as lubricants, firefighting foams, cleaning agents, and in surface coating for paper, food packaging, textiles, furniture, carpets and cookware PFCs, particularly perfluorooctane sulfonate (PFOS) and perfluorooctanic acid (PFOA) have been widely detected in the environment, wildlife, and humans Animal studies have shown that neonatal exposure to low doses of PFCs induced irreversible neurotoxic effects in adult mice and caused changes in behavior and habituation by altering the dopaminergic and cholinergic system ADHD is a neurodevelopmental disorder defined by inattention, hyperactivity and impulsivity Two cross-sectional studies based on parent-reported ADHD diagnosis have investigated the potential association between PFC levels in school-age children and ADHD The frequency of children receiving an ADHD diagnosis has increased in recent years The objective of this study is to investigate the association between fetal exposure to PFCs and ADHD diagnosis in childhood. Unlike previous studies, this case-control study is based on clinical ADHD diagnosis and PFCs are measured in umbilical cord serum samples which reflect the PFC concentrations in the fetus. The study is a part of the Fetal Environment and Neurodevelopment Disorders in Epidemiological Research project (the FENDER project).11 and DSM-IV12 were used before 1994 and from 1994 and onwards, respectively. Age at the time of diagnosis varied between 5 and 17 years, with most children being diagnosed between the ages of 8 and 12 years.The selection procedure of the children with ADHD diagnosis has been previously described by Gustafsson and Kallen Using the personal identification numbers, children with ADHD were linked to the Swedish Medical Birth Register (SMBR) which contains demographic and obstetric information on nearly all (99%) the mothers and the infants in Sweden. Umbilical cord serum samples for children with ADHD were collected from the Malmö Maternity Unit Serum Biobank (MMUSB) using the personal identification numbers. Nearly all deliveries in Malmö take place at the Malmö University Hospital Maternity Unit, where blood samples from the mother and from the umbilical cord of the newborn have been collected at the time of delivery and stored at −20°C at the MMUSB since 1969. Controls were selected into two phases. In the first phase, for each ADHD case with an available umbilical blood sample in the biobank, the next-baby-born with serum sample of the same sex was selected as a control. However, a new publication by Gustafsson and Kallen At the Maternity Unit, the women were informed that the umbilical cord serum sample collected could be used for research purposes in the future and those who accepted gave their verbal informed consent that was documented in the medical records. During the study period only verbal informed consent was obtained. The written informed consent has been implemented in 2005 and therefore could not be considered for the current study. The data were analysed anonymously. The study protocol followed the requirements of the Declaration of Helsinki and the study, together with the consent procedure, was approved by the Research Ethics Committee at Lund University, Sweden.The analyses of PFHxS, PFOS, PFOA, PFNA, perfluorodecanoic acid (PFDA), perfluoroundecanoic acid (PFUnDA), perfluorododecanoic acid (PFDoDA), and cotinine were performed as previously described th percentile for the control group. For PFNA the concentrations above the limit of detection (LOD) were compared to those below LOD (0.2 ng/ml).The Wilcoxon's paired test was used to compare the PFC concentrations between ADHD cases and controls. Conditional logistic regression analysis was used to assess the association between fetal exposure to PFCs and ADHD. The odds ratio was calculated for both 1 unit increase (nanogram per milliliter) in the concentrations of PFOS and PFOA and for comparisons between concentrations above and below the 75The potential confounding variables that were considered in the present study were smoking during pregnancy, parity, and gestational age at birth, since they have been found to be associated with both PFC exposure and ADHD Smoking during pregnancy was determined by cotinine levels in umbilical cord serum. Cotinine levels below the LOD (0.2 ng/ml) were related to nonsmoking pregnant women, cotinine levels higher than 15 ng/ml were related to active smokers and levels between 0.2 and 15 ng/ml were related to second-hand smokers The odds ratios were calculated in paired samples (n = 202) using Egret for Windows 2.0 (Cytel Software Corporation). The rest of the analyses were performed in IBM SPSS Statistics version 20 .The power calculation was based on 206 cases and matched controls. With the current setting, we had an 80% chance of detecting a difference in the levels of 0.20 standard deviations, with α value of 0.05, between cases and controls. For the analysis of the threshold effect, with α value of 0.05 and β value of 0.80, the lowest detectable odds ratio was 1.8.PFOS and PFOA concentrations were above the LOD in 98% of the samples, whereas for PFNA about 12% were above the LOD. PFOS and PFOA concentrations below the LOD in individual samples (n = 2 for each) were replaced with 0.2 ng/ml.The demographic characteristics and the umbilical cord PFC concentrations of the study population are presented in p = 0.72, 0.44, and 0.48 for PFOS, PFOA, and PFNA respectively).Conditional logistic regression analyses revealed no significant associations between umbilical cord concentrations of PFCs and ADHD . The resThe present study found no statistically significant associations between exposure to PFCs during pregnancy and ADHD diagnosis during childhood, although the measured umbilical cord concentrations of PFOS were among the highest in Europe Animal data revealed that neonatal mice that were exposed to high doses of PFOS and PFOA showed behavioral defects which ranged from slight effects at the anxiety level Our study is primarily comparable to the study by Fei and Olsen The present study has some limitations. Unfortunately, while 419 children with ADHD diagnosis were identified at the Department of Child and Adolescent Psychiatry, there were significant losses to get to the final study sample. The study was restricted to children born in Malmö with available obstetric and demographic information from the SMBR and stored cord blood samples in the biobank. About 50% of the identified children met these two inclusion criteria and were included in the study. The second limitation of the current study is the small number of ADHD cases. Although we would be able to detect an odd ratio of 1.8 and a difference in PFC levels of at least 0.20 standard deviations between cases and controls, it should be emphasized that the statistical power was not high enough to detect some minor associations and we could not accordingly rule out small effects. In addition, we lack information about other exposures that are significant for ADHD, such as exposure to mercury and lead. The PFC levels measured here might also be too low to trigger undesirable effects on the brain development.During our study period, the clinical diagnostic criteria for ADHD were changed from the definition in DSM-III-R to the definition in DSM-IV, where DSM-IV is regarded as more inclusive. Thus, DSM-IV criteria yield a higher prevalence of ADHD The study has also several important strengths. First, unlike most of the previous studies on the associations between PFC levels and ADHD, our prospective study design is more reliable in the sense that it is based on clinical diagnosis of ADHD made at the Department of Child and Adolescent Psychiatry. Children were diagnosed at the same psychiatric clinic through the whole study period.Second, the present study is based on analyzed blood samples from the fetal period, which we believe is the most susceptible exposure window, whereas in other studies, which were of a cross-sectional nature, blood samples were collected from school-age children Third, we were able to account for important covariates; smoking during pregnancy, parity, and gestational age at birth that have been found to be associated with both PFC levels in pregnant women or infants In a previous study, we found that fetuses of mothers originating from a country other than Sweden, especially those from Middle East and sub-Saharan Africa, had lower PFC levels in the cord blood than fetuses of native Swedish mothers Human serum PFC levels showed an increasing pattern from the early 1970s through the late 1990s, followed by leveling out and a decreasing trend right after the phase-out of the production of PFOS and PFOS related compounds in 2002 According to our findings, fetal exposure to PFOS, PFOA and PFNA was not associated with ADHD diagnosis in childhood.


ZNF804A) is associated with psychotic disorders including bipolar disorder and schizophrenia. One study also found significant association between rs1344706 and the executive control network of attention. In this study we examine the role of the rs1344706 polymorphism that previously showed association with BD and is known to alter expression of the gene in two clinical family-based ADHD samples from the UK and Taiwan.Genome-wide association studies (GWAS) have been conducted on many psychiatric disorders. Evidence from large GWAS indicates that the single nucleotide polymorphism (SNP) rs1344706 in the zinc-finger protein 804A gene (P = 0.91) and UK (P = 0.41). Even combining the two datasets together the A allele of rs1344706 SNP was still not significantly over-transmitted to affected probands (P = 0.50). Furthermore, there was no evidence of association with the specific symptoms subgroups of inattention or hyperactivity-impulsivity.To investigate the association between rs1344706 and ADHD, two family samples of ADHD probands from the United Kingdom (n = 180) and Taiwan (n = 212) were genotyped using TaqMan SNP genotyping assays and analysed using within-family transmission disequilibrium test. No significant associations were found between rs1344706 polymorphism and ADHD in either of the samples from Taiwan (ZNF804A gene and ADHD. Results showed no significant association of rs1344706 with ADHD in UK and Taiwanese samples.In this study we used family-based ADHD data in the UK and Taiwanese population to test for an association between rs1344706 SNP in the  Attention deficit hyperactivity disorder (ADHD) is one of the most frequent and heritable neurodevelopmental disorders of childhood characterised by developmentally inappropriate and impairing levels of inattention, hyperactivity and impulsivity. Current estimates show that 3%–5% of school age children have a diagnosis of ADHD . The disA wide variety of candidate genes have been investigated in ADHD and other psychiatric disorders including BD, with some genes reported to be associated with both ADHD and BD -16. For ZNF804A) gene (located on the long arm of chromosome 2 at the 2q32.1) with psychiatric disorders including both BD and SZ [ZNF804A and schizophrenia (P = 1.61 × 10-7), and found strong evidence when the affected phenotype included patients with bipolar disorder (P = 9.96 × 10-9) [P = 2.54 × 10-11) and a combined schizophrenia/bipolar phenotype (P = 4.1 × 10-13) [ZNF804A and attention in 200 healthy volunteers and found a significant association with a measure of the executive control attention network. One recent study examined six SNPs in five genes in adult ADHD, and concluded that the six SNPs including rs1344706 in ZNF804A, which showed strong evidence of association with bipolar disorder, did not appear to be associated with ADHD [GWAS studies on ADHD have yet to identify SNPs associations with genome-wide significance . HoweverD and SZ ,23. One  × 10-9) . Several × 10-9) -27. Meta× 10-13)  investigith ADHD .ZNF804A in two clinical ADHD samples from the UK and Taiwan.As ADHD and BD are both highly heritable, show comorbidity with each other and an increased cross-disorder familial risk ,31, the DNA was collected from 180 ADHD combined subtype probands. Both parents were available for 116 families, and only the mother was available for 64 families. Ninety-six percent of the sample was male. Cases were recruited from child behaviour clinics and referred for assessment if they were thought by experienced clinicians to have a diagnosis of combined subtype ADHD under DSM-IV criteria, with no significant Axis I co-morbidity apart from oppositional defiant disorder  and conduct disorder . Intelligence quotient (IQ) was assessed using the Wechsler Intelligence Scale for Children-Third Edition (WISC-III). Exclusion criteria included IQ less than 70, neurological disorders, brain damage or autism. Only those individuals fulfilling the recruitment criteria after completion of research assessments were included in the study. All probands were of European-Caucasian origin. The age range was 5–15 years at the time of assessment . Parents were interviewed with a modified version of the Child and Adolescent Psychiatric Assessment (CAPA) . InformaSamples were collected from 212 children with ADHD diagnosed between the ages of 5–15 years , from both parents for 114 families of the ADHD probands and from only the mother for 59 families or only the father for 39 families. ADHD cases were ascertained from Child Psychiatric Clinics in the Chang Gung Memorial Hospital in Taipei area, Taiwan. The diagnosis of ADHD was made under DSM-IV criteria following completion of a standard maternal interview  and compP >0.05).The rs1344706 polymorphism was genotyped using a TaqMan® SNP genotyping assay (Assay ID: C_2834835_10) on a 7900HT sequence detection system (Applied Biosystems). The distribution of the genotypes did not deviate from Hardy-Weinberg equilibrium  implemented in the UNPHASED program (TDTPHASE) . http://χ2 = 0.390, df =1, P = 0.474); and genotype frequencies did not deviate from Hardy–Weinberg equilibrium in either population.Population frequencies for SNP rs1344706 (an A/C polymorphism) were estimated from parental genotypes. For the UK and the Taiwanese sample the A-allele frequency was 61% and 55%, respectively. There was no significant difference in allele frequencies between the two populations . When the two datasets were combined, the A allele was still not significantly over-transmitted to affected probands .TDT analysis Table  showed nχ2 =0.604, P = 0.437). We were not able to investigate the hyperactive-impulsive subtype separately because neither samples included any such cases. To investigate whether there were any associations with the specific symptom domains of ADHD, we therefore completed an additional analysis using quantitative ratings of parent rated inattentive and hyperactive-impulsive symptoms using quantitative pedigree disequilibrium test (QPDT) from the UNPHASED program. The results from QPDT analysis showed that the A allele of rs1344706 was not associated with either symptom domain in samples from UK  or Taiwan . When the two datasets were combined, the A allele was still not significantly associated with either symptom domain .We further explored the subtypes of ADHD. We found that there was no association between rs1344706 and ADHD in the subgroup of the Taiwanese sample with the inattentive subtype (ZNF804A gene, which was previously found to be associated with BD, and ADHD in two independent ADHD samples from the UK and Taiwan. No association was observed between this polymorphism and ADHD in either sample or when the two samples were pooled together. We further investigated the association on specific symptom subgroups of ADHD. We found no association with the subgroup of the Taiwanese samples with DSM-IV inattentive subtype. Furthermore, using a quantitative trait approach there was no evidence of association with quantitative ratings of either inattentive or hyperactive-impulsive symptoms in either sample.In this study we set out to investigate association between SNP rs1344706 in the ZNF804A gene is located on the long arm of chromosome 2 at the 2q32.1 and ZNF804A encodes the transcription factor zinc-finger protein 804A. SNP rs1344706 lies in intron 2 of ZNF804A and the A allele is predicted to enhance the maintenance of binding sites for brain-expressed transcription factors [ZNF804A gene shows strong evidence of association with both BD and SZ from GWAS [The human  factors . ZNF804Arom GWAS ,23. The rom GWAS . Data frrom GWAS .In our study we used family-based ADHD data from the UK and Taiwan to investigate the role between rs1344706 and ADHD. The study presents several limitations that need to be considered. The sample was relatively small and might therefore be underpowered to exclude very small genetic effects. Furthermore, the subgroup with inattentive subtype ADHD was only 22% of the Taiwanese sample and none of the UK sample. Only one polymorphism was genotyped in this gene, therefore we cannot exclude the possibility of association between multiple SNP haplotypes and ADHD.ZNF804A and ADHD in UK and Taiwanese samples. Due to the limitation of sample size in our study and the fact that, to our knowledge, there is only one published study examining association between rs1344706 and ADHD in adult samples, further association studies are required to investigate the role of the high-risk ZNF804A SNPs in ADHD. ZNF804A is a protein currently of unknown function. However, the risk allele of rs1344706 associated with other major mental illnesses has been shown to be associated with higher ZNF804A expression [This study found no evidence of an association between SNP rs1344706 in pression . FurtherThe authors declare that they have no competing interests.XX selected the SNP, performed genotyping and drafted the manuscript. GB supervised the study and revised the manuscript. LL and BS analysed genetic data. UMP helped to do genotyping. CKC, YSH and YYW provided the Taiwanese DNA samples and clinical data. CKC also revised the manuscript. PA supervised the study and revised the paper. All authors contributed to the final critical revision of the manuscript.


Low birth weight (LBW) is associated with an increased risk of mortality, adverse metabolic conditions, and long-term chronic morbidities. The relationship between LWB and short maternal stature coupled with nutritional status was investigated in poor communities.st quartile of stature ≤ 152cm) showed a tendency of increased risk of LBW children compared to mothers in the 4th quartile of stature (>160.4cm) . Children from short-statured mothers weighed an average of 125g less than those from taller mothers . Multivariate analyses showed that short stature, age < 20y  or were underweight  increased the risk of LBW, while overweight  and obesity  had lower risk for LBW. In taller mothers, lower income and underweight were associated with LBW , and obese mothers showed a trend of increased risk of LBW .A cross-sectional population-based study involving 2226 mother-child pairs was conducted during the period 2009-2010 in shantytowns of Maceió, Alagoas, Brazil. Associations between LBW and maternal sociodemographics, stature and nutritional status were investigated. The outcome variable was birth weight (< 2500g and ≥ 2500g). The independent variables were the age, income, educational background, stature and nutritional status  of the mother. The frequency of LBW was 10%. Short-statured mothers (1Overweight was found to have a protective effect in short-statured mothers, indicating that a surplus of energy may diminish the risk of LBW. Short-statured younger mothers, but not taller ones, showed higher risk of LBW. The mother being underweight, regardless of stature, was associated with LBW. Globally, approximately 20 million infants are born with low birth weight (LBW < 2500 g) annually. Approxi< 37 weeks) and intrauterine growth restriction (IUGR). Low birth weight is considered to be one of the most significant factors associated with neonatal, post-natal and infant mortality as well as the increased risk of diseases in adulthood[2]. Determinants of LBW may differ between populations depending on whether LBW is due to growth restriction or prematurity. Sixty-four percent of the worldwide deaths of children under the age of five in 2010 were attributable to infectious causes, and preterm birth complications were the second-leading cause of death[3]. Preterm birth complications (14.1%), intrapartum-related complications (9.4%), and sepsis or meningitis (5.2%) were the leading causes of neonatal death. In older children, pneumonia (14.1%), diarrhea (9.9%), and malaria (7.4%) claimed the most lives[3]. Brazil is among the 10 countries with the highest number of preterm births[4]. One of the most important determinants of fetal growth and birth weight is maternal nutritional status-7. Studi2] plays a critical role in the determination of gestational outcome, as maternal overweight and underweight are both strong predictors of birth weight[In addition, body mass index [BMI = weight (kg)/height (m)th weight,12. A meth weight. On the th weight, althougThe Brazilian state of Alagoas has the lowest human development index (0.677) in the country. The popThe aim of the present study was to examine the hypothesis that obese mothers of short stature are at increased risk of bearing children with LBW, as has been described previously for undernourished mothers of short stature. For this purpose, the association between LBW and short maternal stature, coupled with maternal current nutritional status, has been investigated in a sample population drawn from poor communities in Maceió-AL, Brazil. The study was approved by the Ethics Committees in Research of the Federal University of Alagoas  and of the Federal University of São Paulo . The aims and objectives of the study were explained to all potential participants, and it was emphasized that participation was voluntary. Written informed consent was obtained from the mothers for themselves and on behalf of the children participants prior to the commencement of the study. None of the invited participants refused to participate in the study.The cross-sectional, population-based study was conducted during a one-year period (2009-2010) in shantytowns located on the periphery of Maceió. The necessary sample size was estimated using the StatCalc module in Epi Info™ (version 3.5.1.), assuming a LBW prevalence of 8%, a study power of 80% and a type one error of 5%. The minimum sample population required to comply with these criteria was estimated at 2972 children, i.e., 129 children per visited shantytown.Data were collected in the homes of participants using a pre-tested structured questionnaire. In each shantytown, visits commenced at a previously selected corner starting point and continued in a clockwise direction. At each home, residents were asked if there was at least one child under 5 years of age living in the home. If there was no such child in the home, the researcher moved to the next dwelling until a sufficient number of households were sampled. Children with unconfirmed birth weight; children with genetic, endocrine or anatomical abnormalities that could compromise evaluation; pregnant or lactating women; mothers less than 18 or more than 49 years old; and non-biological mothers were excluded from the analysis. 2; eutrophic, BMI 18.5 to <25 kg/m2; overweight, BMI 25 to < 30 kg/m2; and obese, BMI ≥ 30 kg/m2 [st quartile  were considered to be the reference group for analyzing the variables of interest. Previous studies from our research group[th percentile of the WHO reference. In addition, our previous studies found significant relationships between adults with short stature (1st quartile), the comorbidities and the nutritional status of children. Maternal nutritional status was based on BMI using the cutoff points recommended by the World Health Organization (WHO) as follows: underweight, BMI < 18.5 kg/m30 kg/m2 . Anthropng to WHO), considrch group,23 have The nutritional status of children was assessed from the weight and height/length measurements, which were standardized according to technical recommendations. ChildreThe associations between LBW and maternal sociodemographics, stature and nutritional status were investigated. The mean differences in birth weight values were distributed according to the maternal stature quartiles and evaluated using one-way analysis of variance (ANOVA) and the Tukey post-hoc tests.The dependent variable was birth weight, which was dichotomized as < 2500 g and ≥ 2500 g. The independent (explanatory) variables were the mother’s age at birth (< 20 and ≥ 20 years), family income , length of schooling (< 4 and ≥ 4 years), stature and nutritional status , according to the above-mentioned cutoffs). 2-test and on the crude odds ratios with 95% confidence intervals (95% CI). In multivariate analyses using logistic regression, the criterion for inclusion of independent variables in the model was whether they were associated with the dependent variable in the univariate analyses at the p ≤ 0.20 level. Only those independent variables with p < 0.05 remained in the final regression models. Adjusted odds ratios (95% CI) were calculated. As we detected a modification of the effect of maternal BMI by stature in relation to LBW, the analyses were stratified by maternal stature. We used the first and the fourth stature quartiles in these analyses to maximize the chance of detecting an effect due to differences in stature and to obtain a clear separation between the groups of low and normal stature. The associations between LBW and the independent variables were tested. Univariate analyses were based on the Pearson xP < 0.05). The differences were considered statistically significant when the probability of alpha error was less than 5% , and 49% were boys (1349). The population was very homogeneous with respect to socioeconomic and educational levels . The ave2-test, P = 0.003, OR: 1.460 CI 95%:1.13 - 1.88).< ½ minimum salary). Fifty percent of the mothers had attended school for less than 4 years. Forty-six percent of the children were overweight or obese, and 5% were underweight. The mean birth weight of the children was 3230 ± 575 g (Table 1). Short stature was observed in 25% of the women. Slightly under half (47.5%) of the short-statured mothers were either overweight or obese. Ten percent of the children surveyed had LBW. The frequencies of LBW were 11.6% in girls and 8.1% in boys (Pearson xP<0.0001), while a 32% lower chance was observed for overweight mothers compared to mothers with a normal body mass index. The analysis of the sociodemographic characteristics of the mothers associated with LBW is shown in th stature quartile (p=0.078).To maximize the possibility of detecting the influence of maternal stature in LBW, we contrasted the first  and fourth (above 160.4 cm) height quartiles . Mothersst quartile of stature weighed an average of 125 g less than those of mothers in the 4th quartile (p= 0.002)  . The meath quartiles of maternal stature, respectively. Because we detected a modification of the effect of maternal BMI by stature in relation to LBW children, we stratified the analysis of factors influencing birth weight by maternal stature. st quartile), univariate analysis showed that younger age at childbirth and underweight were significantly associated with LBW , but overweight decreased the risk of giving birth to a child with LBW compared with normal BMI  (In mothers of short stature (115-0.87) . MultivaThe results for the mothers in the 4th stature quartile are presented in The causes of LBW are different in developing and developed countries. In deveth quartile , although other factors were more relevant as determinants of LBW in short-statured mothers. In addition to being an extremely poor population, the average height of all mothers was low, 156 cm, which corresponds to the 15th percentile of the WHO reference for 19-year-old girls [Various studies have shown that poor families in different parts of the world have a greater risk for children with LBW than their more affluent counterparts-34. A reld girls . For thiNo association between length of schooling and LBW could be established in the present study, most likely because the sample population was very homogeneous with respect to this variable. The mean length of schooling was 2.9 years, and more than 40% of the mothers had less than 4 years of education. However, the association between poor maternal education and LBW has been observed in developed and developing countries and is well described in the literature,36. A stAlong with the factors mentioned above, gender can also influence the fetal weight,39. The The results of the present study confirmed that young mothers (< 20 years old) were 2.2 times more likely to give birth to children with LBW than their older counterparts when the entire sample was considered. This association became insignificant when mothers in the fourth quartile of stature were assessed, while younger short-statured mothers were 3.1 times more likely to give birth to LBW infants. This finding demonstrates a stronger likelihood of giving birth at an early age among short-statured mothers.Maternal BMI is known to be a determining factor for fetal development in that both excess weight and weight deficiency can lead to adverse gestational outcomes,13,42. Ast (short) and 4th  stature quartiles. In short-statured mothers, age and underweight were associated with LBW; overweight mothers were protected  against having LBW children, and this tendency was also observed among obese mothers. Among mothers in the 4th stature quartile, income and underweight were the factors associated with LBW in the multivariate analysis; however, in this subgroup, being overweight or obese was not significantly associated with protection against LBW. Obese mothers showed a trend towards increased risk of LBW . These results show that, in addition to the association between LBW, maternal short stature and undernutrition that has been described in the literature, mothers who were overweight at the time of the study were less likely to have babies with LBW. We can speculate that in extreme poverty, overweight acts as a protective factor and ensures better health for the children of mothers with short stature. This finding is the opposite of those described for developed countries such as England and the United States, where overweight (BMI > 25 kg/m2) non-short mothers were observed to have a higher risk of adverse fetal and perinatal complications and infant death [The present study confirmed a strong association between LBW and maternal underweight, regardless of stature, as underweight mothers were 2.43-fold more likely to have LBW offspring than the group as a whole. On the other hand, a marginal protective effect of overweight in mothers was found . As the effect of BMI appeared to be different in mothers of short and normal stature, we carried out an analysis stratified according to the 1nt death ,45. Amonnt death ,45 .It is well known that adult short stature reflects health processes throughout life and is associated with nutritional stress during the early stages of life,9,46. ThThe present study reports the effects of combined maternal short stature and overweight or obesity on the birth weight of children for the first time . The coexistence of stature deficit and excess weight is being observed at an increasingly early age in developing countries. A study conducted in 2001 established that the prevalence of overweight and obese women of short stature in poor communities of Alagoas was 30%. In the Our study has several limitations: the lack of an assessment of other risk factors for low birth weight, such as smoking status and alcohol intake, parity, and other maternal and obstetric conditions; the inability to discriminate between at-term and premature children; and the cross-sectional study design that prevented us from establishing a clearer causal relationship between the mothers’ BMI and LBW. Mothers’ BMI was determined an average of 30 months following childbirth. We believe that it is unlikely that maternal BMI changed dramatically after childbirth, as the establishment of obesity, overweight or even undernutrition in adult, low-income women usually requires several years and is directly related to their long-term living conditions. th quartile) gave birth to significantly heavier babies compared those in the first and second quartile. Because this is a cross-sectional study, prospective studies are necessary to confirm the present findings. In conclusion, the most important finding of this study was that overweight short-statured mothers showed a significantly lower risk of LBW. Thus, overweight seemed to be a protective factor against LBW in extreme poverty conditions. In addition, younger mothers had a higher risk of LBW and the effect was stronger among those with short stature, as the effect was not significant among normal-stature mothers when analyzed alone. Income had a negative impact on birth weight only in the normal-statured mothers, while in short-statured mothers, the negative effects of low age and the protective effects of overweight remained the most important factors in the multivariate analysis. Our other results are agree with the literature, as maternal underweight, regardless of stature, was associated with LBW, and taller women (4


Studies based on functional magnetic resonance imaging (fMRI) during the resting state have shown decreased functional connectivity between the dorsal anterior cingulate cortex (dACC) and regions of the Default Mode Network (DMN) in adult patients with Attention-Deficit/Hyperactivity Disorder (ADHD) relative to subjects with typical development (TD). Most studies used Pearson correlation coefficients among the BOLD signals from different brain regions to quantify functional connectivity. Since the Pearson correlation analysis only provides a limited description of functional connectivity, we investigated functional connectivity between the dACC and the posterior cingulate cortex (PCC) in three groups  using a more comprehensive analytical approach – unsupervised machine learning using a one-class support vector machine (OC-SVM) that quantifies an abnormality index for each individual. The median abnormality index for patients with ADHD was greater than for TD age-matched subjects (p = 0.014); the ADHD and young TD indices did not differ significantly (p = 0.480); the median abnormality index of young TD was greater than that of TD age-matched subjects (p = 0.016). Low frequencies below 0.05 Hz and around 0.20 Hz were the most relevant for discriminating between ADHD patients and TD age-matched controls and between the older and younger TD subjects. In addition, we validated our approach using the fMRI data of children publicly released by the ADHD-200 Competition, obtaining similar results. Our findings suggest that the abnormal coherence patterns observed in patients with ADHD in this study resemble the patterns observed in young typically developing subjects, which reinforces the hypothesis that ADHD is associated with brain maturation deficits. Attention Deficit/Hyperactivity Disorder (ADHD) is a highly prevalent disorder in childhood and adolescence Based on the observations of executive dysfunctions in ADHD Specifically, functional connectivity magnetic resonance imaging (fcMRI) has been used to investigate Alzheimer disease, depression, autism, epilepsy in comparison to subjects with typical development Most neuroimaging studies exploring functional connectivity are based on extracting Pearson or Spearman correlation coefficients between the signals from different brain regions. Correlation coefficients can be useful as an index of synchronous BOLD signal fluctuations measured in distinct areas. On the other hand, they may be strongly influenced by artifacts and do not take into account the temporal-scale of the dependence, i.e., short/long term or frequency features. Spectral coherence analysis (SCA) Pattern recognition methods based on machine learning algorithms have been successfully applied to fMRI datasets In this paper, considering that SCA provides a multivariate characterization (at different frequencies) of functional connectivity, we introduce a combination of SCA and OC-SVM to demonstrate that the functional connectivity between the posterior cingulate cortex (PCC) and dorsal anterior cingulate cortex (dACC) is not only different but abnormal in ADHD patients compared to subjects with typical development (TD). Moreover, we show that the functional connectivity patterns of patients with ADHD are more similar to those of young TD subjects, which reinforces the hypothesis that ADHD is related to abnormalities in brain maturation.Data from 21 patients with ADHD , 21 age-matched TD subjects  and 21 young TD subjects  were used in this study. Patients were recruited from the New York University (NYU) School of Medicine Adult ADHD Program and controls were recruited through local media advertisements . Data from 20 ADHD patients and six TD age-matched subjects were included in the sample described by Castellanos et al. The data used in this study are publically available via the 1000 Functional Connectomes Project database . A high resolution anatomical MRI was also acquired.www.fmrib.ox.ac.uk/fsl/). The images were processed for motion correction , spatial normalization , spatial smoothing , temporal filtering . Further analyses were carried out using R platform (www.r-project.org). VAR modeling for coherence estimation was carried out using the “ar” routines of the “base” package and OC-SVM training was done using the “svm” routines in the “e1071” package.The data was preprocessed using routines of FSL toolbox . The PCC ROI was defined using a spherical ROI of radius 7.5 mm centered at MNI coordinates , based on Biswal et al. Functional connectivity between ROIs was quantified using spectral coherence analysis (SCA) For each subject, SCA was calculated at each ROI  over the whole resting state session, estimating the parameters of a vector autoregressive model (parametric SCA estimation), given by:Consider the following matrix:I is the identity matrix andThe coherence matrix is given by,The foundations of the one-class support vector machine were developed by Schölkopf et al. Anna Karenina). In the univariate case, the implementation of general normative rules is intuitive, since it can be based on building confidence intervals . The confidence interval can be obtained parametrically by assuming a probability distribution  or non-parametrically by using empirical quantiles. On the other hand, in cases where the number of variables is large (even greater than the sample size), the definition of these “multivariate quantiles” is not simple, and must be founded on mathematical and probability theory. Since the application of OC-SVM is not based on assuming two-classes a priori  but uses only the target group as the training data, it is considered an unsupervised classifier. Basically, the main idea of OC-SVM is to find a partition or subset based on the training data, such that the probability that a new observation (test data) is not contained by this subset is p. This parameter is defined a priori within the interval from 0 to 1. Note that p is the rejection rate for observations from the same population of the training data, and thus, from a clinical normative definition perspective, it is the expected false positive rate.In the current study, we applied one-class SVM (OC-SVM), developed for the main purpose of defining normative classification rules in cases where the number of variables is large. By normative rules, we mean defining a target population and then predicting whether a new observation belongs to the population or not. The intuition behind OC-SVM is that “all positive examples are alike and each negative example is negative in its own way”  kernel, which projects the data into a hypersphere, and OC-SVM works by classifying the data from the origin. In addition, one of the key features of OC-SVM is that it can provide a score, given by.The OC-SVM approach has been relatively well described in the machine learning literature and applications to neuroimaging databases can be found in Hardoon et al. Finally, it is important to mention that although two-class and multi-class SVM Vapnik The main idea in this study was to use OC-SVM to obtain an abnormality index of each subject to compare the dACC-PCC coherence measures between adult patients with ADHD, TD age-matched controls and young TD. Basically, the subjects of two groups  were assumed to be from the same single population. OC-SVM was trained using this mixed sample, the abnormality index was obtained for each subject from this sample and the distribution of this index was compared between the two original groups. These procedures guarantee that there is no systematic bias in the analysis, in favor of a specific group. Since OC-SVM was applied in a sample which is the mixture of two groups of the same size (21 subjects in each), the quantile parameter The following steps were conducted:Step 1) Preprocessing of the EPI images of all subjects;Step 2) Extraction of the mean BOLD signal of each ROI, as representative time-series;Step 3) Calculation of coherence between the ROI signals;Step 4:4A) Train an OC-SVM classifier using the coherence of ADHD patients and TD age-matched controls as a single group. Obtain the abnormality index for all subjects;4B) Train an OC-SVM classifier using the coherence of TD age-matched controls and young TD subjects as a single group. Obtain the abnormality index for all subjects;4C) Train an OC-SVM classifier using the coherence of ADHD patients and young TD controls as a single group. Obtain the abnormality index for all subjects;Step 5) For each of the three classifiers in step 4, apply a Mann-Whitney test to assess the statistical significance of the difference of index values between groups. Since the hypothesis is that patients with ADHD will be abnormal (compared to TD subjects), which implies higher values of the abnormality index, the test is one-tailed (median of ADHD indices < median of TD indices). For comparison purposes, the evaluation between TD age-matched controls and young TD was also one-tailed.As described previously, the proposed abnormality index could be used to evaluate the coherence values of any given subject. Still, it does not provide any information as to why some subjects were identified as more abnormal than others. Thus, further analyses were carried out focusing on identifying frequencies which were more influential (regarding discrimination) in the analyses comparing ADHD patients vs TD age-matched controls and TD age-matched controls vs young TD subjects. All OC-SVM procedures of step 4 described in the previous section were repeated in a complementary analysis, in which the subjects’ abnormality indexes were recalculated, assuming a training set excluding each frequency at a time. We define the relevance coefficient of each frequency as.http://fcon_1000.projects.nitrc.org/indi/adhd200/). The preprocessed data was released by The NeuroBureau (http://neurobureau.projects.nitrc.org/ADHD200/) and is available at the referred website. The preprocessing of fMRI data was performed using routines from the packages AFNI (afni.nimh.nih.gov/afni), FSL (www.fmrib.ox.ac.uk/fsl/) and processed at the Athena computational cluster at Virginia Tech’s ARC (www.arc.vt.edu). Data processing was based on: exclusion of the first four EPI volumes (in order to achieve MR steady-state), slice timing correction, deoblique dataset, reorientation of the volumes to RPI, correction for head motion (first volume as reference), masking the volumes to exclude voxels at non-brain regions, averaging the EPI volumes to obtain a mean functional image, co-registration of mean image to corresponding anatomic image of the subject, spatial normalization to standard space, removing effects of WM, CSF, motion and trend using linear multiple regression, temporal band-pass filter (0.009<f<0.08 Hz), spatial smoothing using a Gaussian kernel (FWHM = 6 mm). BOLD time series from dACC and PCC were extracted from ROIs at the same coordinates of the adult experiment as described in subsection 2.4. The ROIs were defined using the CC400 parcellation provided by the NeuroBureau.Although the main focus of the current study is the investigation of connectivity patterns and abnormality index in adults, we also performed the proposed analysis using the data of publicly released at the ADHD-200 Sample , age-matched typical developing children , and young typical developing children . The abnormality index of the subjects were calculated independently for each pairwise combination between the three groups, by following the approach described in subsection 2.7. All research carried out by ADHD-200 contributing sites was conducted under local IRB approval. The data was fully anonymized in compliance with HIPAA Privacy Rules.The relevance of each frequency in group discrimination is shown in This is the first study using OC-SVM and spectral coherence measures to demonstrate that resting state functional connectivity between PCC and dACC is abnormal (and not only different) in patients with ADHD when compared to TD age-matched controls and that these abnormal coherence patterns of ADHD patients are more similar to the patterns observed in young subjects with typical development. To address these questions, we introduced a multivariate approach to define an abnormality index for any subject.We note that this was not an exploratory study using massive-multivariate classifiers with the objective of obtaining maximum accuracy in discriminating groups. The aims of this study were threefold: i) to demonstrate that ADHD patients have abnormal dACC-PCC coherence patterns (in a multivariate sense); ii) to identify the abnormal frequencies; and iii) to obtain evidence addressing the brain maturation hypothesis of ADHD.Our finding of abnormal PCC/dACC coherence between ADHD patients and TD age-matched controls provides supports the use of this approach as a potential tool for investigating ADHD. Until recently, most neurobiological studies of ADHD investigated brain regions encompassing the prefrontal–striatal and mesolimbic circuits involved in executive functions and inhibitory control Interestingly, we did not observe any statistically significant difference in the coherence index of ADHD patients compared to young TD subjects. Whether ADHD is a disorder related to a delay in brain maturation or whether it represents a frank derangement of typical development has remained an unsettled question since its earliest descriptions A limitation of the proposed approach is that it was developed to deal only with two regions of interest, in this case, dACC and PCC. Technically, the method could be extended to the case of three or more brain regions by considering the coherence between all pairwise combinations of ROIs as features in OC-SVM. However, in practice, this would lead to a massive increase in the number of variables. Since the samples for most fMRI studies are relatively small (less than 100), the inclusion of too many variables would decrease the performance of OC-SVM, due to the “curse” of dimensionality and the presence of irrelevant variables. In addition, the successful application of OC-SVM is strongly dependent on the signal-to-noise ratio of the observations. This was the main reason for using the ROI average signal as regional representative, before calculating coherence values. Actually, this is a limitation of using an unsupervised classifier, since all variables are assumed to have the same relevance in the calculation of the abnormality index. However, it is the unsupervised nature of the classifier which ensures that the analysis of the abnormality index would not be biased by the selection of the target population (ex: if only the control group was chosen as the target), since both ADHD and TD groups are mixed in a single group, before extracting the indexes of each subject.The results of this study suggest that low frequencies below 0.05 and around 0.20 Hz are most relevant to ADHD. This frequency characterization was relevant to show that the features that led ADHD patients to be classified as abnormal compared to TD age-matched controls, were the same features that were abnormal in young TD. However, the neurophysiological meaning of this finding is still an unanswered question. Although there are some studies investigating changes in the amplitude of low frequency fluctuations Future studies should explore and describe the frequency properties of functional connectivity in ADHD and also evaluate the proposed approach in other samples of ADHD patients. The inclusion of patients with different psychiatry disorders would also be important to investigate whether these findings would be specific for ADHD.


ADHD is a common childhood onset mental health disorder that persists into adulthood in two-thirds of cases. One of the most prevalent and impairing comorbidities of ADHD in adults are substance use disorders. We estimate rates of ADHD in patients with substance abuse disorders and delineate impairment in the co-morbid group.Screening for ADHD followed by a research diagnostic interview in people attending in-patient drug and alcohol detoxification units.We estimated prevalence of undiagnosed ADHD within substance use disorder in-patients in South London around 12%. Those individuals with substance use disorders and ADHD had significantly higher self-rated impairments across several domains of daily life; and higher rates of substance abuse and alcohol consumption, suicide attempts, and depression recorded in their case records.This study demonstrates the high rates of untreated ADHD within substance use disorder populations and the association of ADHD in such patients with greater levels of impairment. These are likely to be a source of additional impairment to patients and represent an increased burden on clinical services. ADHD is a common childhood onset mental health disorder defined by the presence of impairing levels of hyperactive, impulsive and inattentive symptoms. The disorder has an estimated prevalence during childhood in the United Kingdom of 3.6%. LongituThis study addresses some of these concerns by implementing a systematic screening protocol for ADHD in London (UK) SUD clinics, with the aim of estimating the rate of undiagnosed and untreated ADHD within SUD patients; and evaluating whether those with comorbid ADHD and SUD experience greater impairment, in terms of co-morbid diagnoses, previous convictions or suicide attempts than those with SUD alone. We also carried out an investigation of autistic traits in this population to determine if this confounded our results.Sample characteristics are listed in Table The study of people undergoing inpatient detoxification included two screening stages using ADHD rating scale data, followed by formal evaluation of the diagnosis of ADHD using a semi-structured interview for DSM-IV ADHD. By including two screening steps (T1 and T2) we were able to evaluate the difference between the level of ADHD symptoms on admission (T1) and one week later (T2), when they had been detoxified or stabilised on treatments such as methadone. Screening assessment session one (T1) took place soon after admission . The second screening assessment session (T2) was completed as close as possible to seven days after the T1 assessment . During the T1 session, patients completed current and childhood symptom checklists for DSM-IV ADHD; and during the T2 session current symptoms only, since it was assumed that only the report of current levels of symptoms would be affected by state of detoxification and current drug use and needed to be measured at both time points. In addition whenever possible we obtained contact details from informants for childhood and current ADHD symptoms who were asked to complete an informant version of the screening questionnaire. Current informant ratings were obtained for 72 participants, and childhood ratings for 48 participants. The self-rated screening data were used to allocate participants into screen positive and negative groups for ADHD. Participants screening positive for ADHD were invited to complete a research diagnostic interview assessment. Participants who failed to attend the diagnostic interview were offered up to three further appointments. Following three missed appointments, a final letter invited participants to contact the research team to reschedule an appointment before the assessment was recorded as “missing”.often) or 3 (very often). The Barkley rating scales offer a total symptom count for the inattentive domain and the hyperactive/impulsive domain (0–9 for each). We also asked participants to provide contact details for an informant to provide similar ratings for both current and childhood behaviour. Impairment questions from the Barkley scales[Participants completed DSM-IV 18-item self-report ADHD screening questionnaires for both current and childhood behaviour, using the 4-point  rating scales from Barkley. A sympty scales were incy scales which scy scales. The ADOhttp://www.divacenter.eu)[Research diagnosis of ADHD was established using the Diagnostic Interview for ADHD in Adults ), conducThe diagnostic algorithm for ADHD used the following criteria: (i) 6 or more ADHD symptoms in either domain from retrospective childhood rating scales; (ii) 4 or more ADHD symptoms from either domain from current ADHD symptom rating scales; (iii) Research diagnosis of DSM-IV ADHD following application of diagnostic interview for DSM-IV ADHD. This study was approved by the South London and Maudsley Research Ethics Committee and all participants gave informed consent before taking part.Recruitment and screening stages are summarised in Figure Mean total childhood ADHD symptom scores were highest in the group treated for drug dependency  followed by the combined drug and alcohol group  and the alcohol dependency group . A one way ANOVA showed significant effects of primary diagnosis  on childhood screener total score (p<0.001). Planned contrasts showed significantly higher ratings of ADHD symptoms for drug compared to alcohol participants (p<0.001), but not between drug and combined drug and alcohol groups (p=0.12).These data are summarised in Table A 2x3 Mixed Model Factorial ANOVA on the time (T1 vs. T2) and primary diagnosis  found a significant main effect of time (p<0.001), indicating that self-rated ADHD symptom scores are influenced by the detoxification treatment process and/or withdrawal states following admission. A significant effect of primary diagnosis was also found (p<0.001) but no significant interaction between time and primary diagnosis (p=0.34). Between subjects contrasts showed significant differences for ADHD ratings between the alcohol and combined drug & alcohol groups (p<0.001), but not between drug and combined (p=0.28) or alcohol and drug (p=0.11), indicating higher levels of ADHD symptoms at T1 and T2 among those with drug abuse compared to those with alcohol abuse alone.There was an estimated prevalence rate for ADHD of 12.2% , only had a small impact on the prevalence estimate. For example reducing the threshold for diagnosing ADHD from ≥6 symptoms in childhood to ≥4 only increased the overall prevalence estimate to 14.4%; and no additional cases were identified by decreasing the threshold for current symptoms to ≥4.64% of participants provided contact details for informants of their current behaviour and 43% for childhood behaviour; and 50% of both sets of contacts returned screening questionnaires. The correlations between self and informant reported symptoms are listed in Table As expected the SUD sample rated themselves as significantly more impaired than controls p<0.05). Among the individuals with SUD there was a significant positive relationship between self-rated impairment and the severity of ADHD symptoms in childhood and at both T1 and T2 . Furthermore, greater impairment was significantly negatively correlated with change scores between T1 and T2 ; indicating that participants with greater impairment at T1 showed a smaller drop in ADHD symptoms between T1 and T2. Lastly, within the SUD population we compared the diagnosed ADHD cases to the non ADHD cases. Those with ADHD had significantly higher rates of self-reported impairments  measures. Appropriate assessment and management of ADHD in SUD patients would therefore seem to be potentially important to improve the general level of functional impairments and, particularly, given our finding that ADHD is associated with increased frequency of suicide attempts and depression. Whether treating ADHD in the context of SUD improves depression has yet to be adequately studied; yet we know that in people with ADHD symptoms such as mood instability and low self-esteem respond well to treatments for ADHD-28. AnotOur work attempted to address, as best we could, the inevitable methodological difficulties that might impact on accurate estimation of prevalence rates for ADHD within people with SUD. These include the potential for unreliable information from self-report questionnaires, difficulties with retrospective recall of childhood symptoms and the direct impact of drug and alcohol intoxication and withdrawal states on ADHD-like symptoms. We therefore attempted to measure ADHD symptoms before and after detoxification, included independent informant ratings whenever possible, compared these to population control data, and completed research diagnostic interviews. One additional confounder might arise if the study participants considered a positive diagnosis of ADHD as a way to obtain stimulant medication. However the study was not linked directly to the treatment of ADHD and expectations for treatment with stimulants are currently low in the UK, because in most cases ADHD in adults goes unrecognised and untreated. Based oWe investigated the impact of drug intoxication and/or the detoxification process by evaluating self-rated ADHD symptom scores a few days after admission to the detoxification unit and one week later, when they were detoxified or stabilized on long term medication and no longer in a withdrawal state. We found significant decreases in ADHD symptoms of around 8-points , which is a clinically significant reduction in ADHD symptoms and comparable to a one-level drop of the Clinical Global Impression Scale. In termOur findings suggest that clinical evaluations for ADHD are probably best completed once detoxification or stabilization for drug or alcohol dependency has been completed. However this suggestion may be difficult to implement in community patients. Furthermore, once diagnosis of ADHD has been established it will be important to offer treatment. Use of some pharmacological treatments (such as use of stimulants) is complex, however, in those with a current SUD. Nevertheless therapeutic nihilism is not an option as treatment of underlying ADHD may be important to the success of drug treatment programs for some individuals. It might be advisable to use the more stringent screening criteria of 6+ symptoms in either domain to identify those that need full clinical evaluation for ADHD, or to recognise the need for detailed ADHD assessment in a higher proportion of cases. Moreover it may be more appropriate to use non stimulant medications such as atomoxetine, as a first line treatment. Further work is required to address this issue, and the potential for using CBT based therapies for ADHD in this complex population. Obtaining informant data on ADHD symptoms for childhood and for current symptoms proved difficult in this population. The reasons for this were not investigated here, but likely reflect the often poor relationships that many SUD patients have with their family and friends. Therefore in clinical practice it will also often be the case that the diagnostic assessment of ADHD will depend on self-report alone. We were able to investigate the validity of these self-reported data by comparison of self-report with informant reported data in a subset of our sample and a comparison control sample. These showed moderate correlations between raters which were similar to that seen in non-SUD control populations. For the most impaired sub-group however, who were screening positive for ADHD based on their self-report, there was a far higher correlation with informant report for current ADHD ratings of around 0.62–0.65. We therefore suggest that while discrepancies between raters exist for ADHD rating scales, this does not appear to be different for SUD compared to control populations. Furthermore ratings showed moderately high levels of agreement for the group of patients with ADHD. Previous research has shown that in general people with ADHD tend to rate their symptoms lower than informants perhaps This study applied stringent ADHD diagnostic criteria, necessary to avoid mistaking withdrawal states and other mental health problems for ADHD. This resulted in identification of a relatively small ADHD group compared to other studies relying only on self-report screening questionnaires. Despite this, our findings confirm high rates of ADHD within SUD populations that are approximately 5-fold higher than general population rates. Furthermore SUD patients with high levels of ADHD were functionally more impaired (including higher rates of suicide attempts). This study highlights the importance of identifying the sub-group of people with both SUD and ADHD. Further studies are required to evaluate the effectiveness of targeted treatments for ADHD within SUD patient populations. The following co-authors have no conflicts of interest: Karen Glaser, Patrick Bolton, Francis Keaney, Alun Morinan, Lotte Williams, Stefanos Maltezos, Zoe Huntley, Amy Brinsford, David Ball, Raoul Howe-Forbes, Kiriakos Xentidis and Jane Marshall. The following co-authors have the following conflict of interest: Philip Asherson has received funds on behalf of Kings College London for advisory board and/or consultancy for Janssen-Cilag, Shire, Flynn Pharma and Eli-Lilly. He received educational and research grants from Janssen, Vifor, Shire and QbTech. Declan Murphy is currently funded by MRC, Wellcome trust and the Thomas Bailey Foundation. Jonna Kuntsi has received a speaker’s fee from Eli Lilly that has been used for educational and research activities and is funed by Action Medical Research. Susan Young has been a consultant for Janssen-Cilag, Eli-Lilly and Shire. She has given educational talks at meetings sponsored by Janssen-Cilag, Shire, Novartis, Eli-Lilly and Flynn-Pharma and has received research grants from Janssen-Cilag, Eli-Lilly and Shire.PA, DM, PB and KG obtained funding and conceived of the project and study design with SY. Other co-authors were involved in coordination and collection of data at the clinical sites. Analyses completed by ZH. PA and ZH wrote the first and final drafts with review and comments from all authors listed. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-244X/12/223/prepub