As two common mental disorders during the period of adolescence that extend to early adulthood, attention-deficit/hyperactivity disorder (ADHD) and substance use disorders (SUDs) have considerable diagnostic co-occurrence and shared neuropsychological impairments. Our study aimed to identify overlapping and distinct brain structural abnormalities associated with ADHD and SUDs among adolescents and young adults. A systematic literature search on voxel-based morphometry (VBM) studies of ADHD and SUDs was conducted in PubMed and Web of Science. Data were extracted and analyzed to identify brain abnormalities using Seed-based d-Mapping software. Data-driven functional decoding was conducted to identify the psychophysiological functioning associated with brain alterations. 13 and 14 VBM studies for ADHD (619 patients and 483 controls) and SUDs (516 patients and 413 controls), respectively, were included. Patterns of decreased gray matter volume (GMV) were found in the left precentral gyrus, bilateral superior frontal gyri, and left inferior frontal gyrus in the ADHD group compared to the control group. In contrast, individuals with SUDs, relative to controls, were characterized by increased GMV in the left putamen and insula. Comparative analysis indicated larger regional GMV in the right inferior parietal lobule and smaller volumes in the left putamen and left precentral gyrus in the ADHD group than in the SUDs group. Dissociable brain structural abnormalities in adolescents and young adults with ADHD and SUDs potentially implicate different pathogeneses and provide a reference for differential diagnosis and early detection for shared symptomology and comorbidity. Attention-deficit/hyperactivity disorder (ADHD) and substance use disorders (SUDs) are distinct psychiatric conditions in the current categorical and hierarchical diagnostic system . ADHD isImpulsivity caused by deficits in inhibitory control and reward processing is the most striking behavioral trait common to ADHD and SUDs , 10. On Neuroimaging studies on ADHD have identified the delayed maturation of brain structure and function, particularly the prefrontal cortex and subcortical regions engaged in cognitive, attentional, and emotional processes –20. SpecSimilarly, individuals with SUDs present neuroadaptations in the frontal-striatal circuitry with reduced GMV in the prefrontal cortex, ACC, bilateral insula, and thalamus –34. ImpaIdentifying their common neural phenotypes may help to detect those who have high vulnerability to comorbidity, which would allow early intervention, and exploring disjunctive neural properties may facilitate differential diagnosis. Nevertheless, due to the lack of research directly comparing brain structural alterations between those with ADHD and SUDs, it remains unclear whether there are common or disorder-specific structural brain abnormalities. Therefore, we conducted a voxel-based neuroimaging meta-analysis to explore the overlapping and distinct brain regional volumetric changes between individuals with ADHD and SUDs. Given the high prevalence of co-occurrence during the period of adolescence and early adulthood, we selected adolescents and young adults for this analysis and defined this population as 12–24 years old . To provhttps://osf.io/r5xz2). Since the first method paper about VBM was published in 2000 [The study protocol was preregistered on the Open Science Framework . If two researchers had inconsistent opinions on the inclusion or exclusion of one study, they would discuss with the third author (N. P.) to reach a consensus. We recorded sample size, mean age, number of female subjects, comorbidity and medication status, scanner and preprocessing protocols, statistical approach as well as peak coordinates for brain structural abnormalities and corresponding statistical values of each study to construct the database.d-Mapping (AES-SDM) software (https://www.sdmproject.com/old/) respectively. AES-SDM is a statistical technique that uses the altered cluster information reported in individual studies to recreate the statistical effect-size maps when considering their variances with the approach of anisotropic Gaussian kernel [d values and a map of their variances were created and combined to obtain the meta-analytic maps in the preprocessing. Then statistical maps were generated in the main analysis utilizing standard random-effects general linear model, with a p < 0.001 threshold for this step [Prior to meta-analyses, age and sex were compared across patient and control groups in SPSS Statistics, version 24. Separate meta-analysis of regional differences of brain gray matter in populations with ADHD and SUDs was conducted using Anisotropic Effect Size Seed-based n kernel , 42. Texhis step . We set his step . Notablyp < 0.001 and cluster size > 10 voxels) [Following the separate disorder-specific analysis, we further conducted the overlapping and comparative analyses by applying the multimodal and linear models to assess whether there were any common or distinct structural alterations across two groups by comparing ADHD and SUDs groups directly (threshold  voxels) . To acco voxels) . Subsequ voxels) , 46. Jac voxels) .https://neurosynth.org/decode/) [https://www.brainmap.org/taxonomy/behaviors.html) [To explore the psychological process relevant to each identified brain region, we performed a functional decoding analysis by retrieving related psychophysiological terms to brain alterations in NeuroSynth decoder (decode/) , 48. Bradecode/) . We clasrs.html) , 50. Allrs.html) . Therefop < 0.001) and consisted of a larger proportion of females (p < 0.001) than those with ADHD. In the SUDs group, a total of 8 substances of interest were investigated, including stimulants (31.98%), cannabis (23.84%), alcohol (17.05%), tobacco (15.12%), inhalants (2.91%), and poly-substance use (9.11%). Demographic characteristics and other details of included sample in Supplementary Tables In total, 13 studies for ADHD and 14 studies for SUDs were included after a systematic literature search , bilateral superior frontal gyri , orbital part of the left inferior frontal gyrus   compared with control group  , and reduced GMV in the left putamen (extending to left insula)  and left preCG  relative to those with SUDs , left IFG (p < 0.001), and the right SFG (p < 0.001), yet funnel plots were found to be symmetric across all clusters. Publication bias was not significant with respect to GMV differences found in left putamen in SUDs studies. Jack-knife analyses confirmed the robustness of our main findings without apparent fluctuation, in which identified clusters could be replicated in 12 out of 13 primary ADHD studies and 13 out of 14 SUDs studies (Table For ADHD, Egger’s tests revealed publication bias in several clusters encompassing the left preCG (es Table .To the best of our knowledge, this is the first whole-brain neuroimaging meta-analysis that aimed to disentangle the neural structural correlates and differences associated with ADHD and SUDs among adolescents and young adults. The initial meta-analysis for each disorder found that ADHD and SUDs had substantial disorder-specific GMV alteration patterns relative to healthy controls, with decreased GMV in the left preCG, bilateral SFG, and left IFG in those with ADHD but increased GMV in the left putamen in those with SUDs. Comparative analysis revealed that individuals with ADHD presented larger GMV in the IPL and smaller GMV in the putamen and preCG than those with SUDs. Functional decoding indicated that these abnormalities mainly corresponded to perception and action. Overall, our findings showed that altered patterns of brain gray matter structure associated with ADHD and SUDs are spatially discordant during the period of puberty and young adulthood, which may facilitate differential diagnosis in clinical settings.In the disorder-specific meta-analysis, we found that decreased GMV in the left preCG differentiated ADHD. The preCG is a key region engaged in fine motor control and direct sensorimotor mappings  and is oPatterns of GMV reduction were also found in the bilateral SFG and orbital part of the IFG, showing good convergence across prior studies , 58. TheIncreased GMV in the left putamen extending to the insula in the SUDs group was identified. As part of the frontal-striatal circuitry, the putamen receives glutamatergic and dopaminergic inputs and coordinates various aspects of motion and cognition, serving as a crucial component of the motor and reward systems in addictive behaviors , 71, 72.Notably, partial enlargement of the insula was also observed in the SUDs group compared with the control group. From a psychological perspective, the insula is recognized as an integrator between emotional, cognitive, and sensory-motor systems . AnalogoComparative patterns were detected in the right IPL, where the ADHD group showed an enlarged GMV compared to the SUDs group, and in the left putamen and left preCG, where the reverse pattern was observed. Given the GMV reduction in the preCG in those with ADHD and the increased GMV in the putamen in those with SUDs were reported when compared with controls, differences in the above two clusters naturally met our expectation. Thus, the right IPL stood out as a region that distinguished the disorders. From the perspective of local neuropsychological functions, the IPL mediates the superior processing of motor and sensory information and attention . When coWe initially speculated that the alterations in inhibitory control and reward processing-related neural structures might be the overlapping mechanisms underlying ADHD and SUDs. However, discrepant structural abnormalities in the early life stages of the two disorders were found, indicating distinct differentiating neural signatures. We inferred from the results that, although two disorders ended up affecting similar circuits, abnormalities in ADHD may initially originate from immature frontal cortices and progress into regions governing motor control and the reward system, which is a form of top-down regulation . In contThe meta-regression analyses showed sources of the heterogeneity among demographic variables associated with brain abnormalities contributing to these disorders of interest. Age exhibited a modulatory effect on the regional GMV alterations in the bilateral SFG in individuals with ADHD. Children with ADHD presented with decreased GMV in frontal areas triggered by a developmental delay of neural maturation . The strOur study had several limitations for further consideration. First, given that all the included studies were cross-sectional, causal interpretations of these findings may not be sensible . It is sAlthough ADHD and SUDs share neuropsychological features and a high level of co-occurrence among adolescents and young adults, they exhibited distinct patterns of GMV alterations. Decreased GMV was observed in the motor cortex and frontal lobes in ADHD patients compared with healthy controls, while an increased volumetric pattern in the left putamen was observed in those with SUDs. The ADHD group showed larger regional GMV in the right IPL and smaller volumes in the left putamen and left preCG than the SUDs group. These patterns of alterations may correspond to various types of psychopathological processing in the action and perception domains in two disorders of interest. From an objective view, the current findings elucidate distinct brain structural abnormalities between ADHD and SUDs, which may pave the way for a better understanding of the differentiation in clinical settings. In addition, our study may contribute to the development of psychoradiology , which iSupplemental Material


The study aimed to analyze the target of the policy to decrease low birth weight (LBW) in Indonesia. This cross-sectional study used a sample of live births in last five years preceding the survey of birth weight. Data collection took place from July to September 2017. The weighted sample size was 17,848 participants. The variables analyzed included residence, age, marital status, education, employment, parity, and wealth. The study employed binary logistic regression in the final stage to determine the target of policy regarding LBW. The results showed that women in urban areas were 1.200 times more likely to deliver babies with LBW than women in rural areas. All age groups were less likely to deliver babies with LBW than those aged 45–49. The study also found all marital statuses had a lower likelihood of providing babies with LBW than those who had never been in a marriage. Women of all education levels had a greater risk of giving birth to babies with LBW than women with higher education levels. Unemployed women had 1.033 times more chances of delivering babies with LBW than employed women. Primiparous women were 1.132 times more likely to give birth to babies with LBW than multiparous women. Overall, the women in all wealth status categories had a higher probability of delivering babies with LBW than the wealthiest groups. The study concluded that policymakers should target women who live in urban areas, are old, have never been married, have low education, and are unemployed, primiparous, and poor to decrease LBW cases in Indonesia. A newborn should have an average body weight of ≥2500 kg. The baby is categorized as having a low birth weight if its weight is <2500 g 1500–2499 g). Birth weight is crucial for infant development because it is associated with infant mortality ,4. Anoth99 g. BirThe incidence of LBW babies is more than 20 million births each year globally. Overall, the global prevalence shows that the LBW rate in developed regions was 27.2%, compared to 17.3% in Asia, 5.6% in Central Asia, and 27.2% in Southern Asia . LBW is A previous study showed that other factors that influence the incidence of LBW, including cultural practices, are crucial to be addressed by health workers in providing maternal and child health care services. Indonesia is rich in artistic methods for treating diseases and caring for mothers and newborns, which can cause maternal and infant mortality . The tre‘Desa Siaga’ or Alert Village program since 1994. It is a community engagement program that seeks to help pregnant women by maximizing the resources available, such as access to transportation, costs, and social support in their living areas [Based on the factors related to LBW, the Indonesian government strives and is committed to accelerating nutrition levels through the ‘Scaling Up Nutrition (SUN)’ program. The government includes long-term, medium-term, and short-term development plans regulated by the law. In the long-term development plan (2005–2025), the Indonesian government focuses on the first 1000 days of life through the fulfilment of nutrition for the womb until the baby is two. The government carries out cross-sectoral synergies in concrete steps to improve food production, processing, and consumption that meet nutritional needs. Such actions increase nutrition awareness, promotion, education regarding physical and health activities, and access to quality science- and technology-based nutrition services ,14. Furtng areas .The most critical part of implementing the policy for LBW prevention is educating pregnant women and young women (adolescents) who will prepare for pregnancy. Health workers can attempt to minimize beliefs in cultural behavior that can endanger pregnant women’s and babies’ health and safety and improve the quality of baby feeding, especially exclusive breastfeeding ,17. AdvoThis cross-sectional study analyzed secondary data from the 2017 Indonesia Demographic and Health Survey (IDHS). It used a sample of live births in the last five years preceding the survey, comprising birth weight, written records, and maternal memories. The author used the ‘IDIR71FL_Individual Recode’ files.The stratified two-stage sampling design used in the 2017 IDHS was as follows: Stage 1: selecting several census blocks systematically proportional to size probability with the number of households resulting from the 2010 population census listing. In this example, an implicit stratification procedure based on urban and rural regions was used for sorting census blocks based on the wealth index category of the 2010 population census data. Stage 2 picks 25 ordinary households in each census block based on updating the households in each census block . The 201The study used LBW as a dependent variable. It defined LBW as a birth weight of fewer than 2500 g regardless of gestational age . Apart fFollowing the Indonesian Central Bureau of Statistics, the study divided residences into urban and rural categories. The study split ages into seven groups: 15–19, 20–24, 25–29, 30–34, 35–39, 40–44, and 45–49 years. Education level, the last certificate owned, was categorized into four categories: no education, primary, secondary, and higher. Marital status had three categories: never in marriage, married/living with a partner, and divorced/widowed.Meanwhile, this study divided employment status into two categories: unemployed and employed. Parity, the acknowledgment of the number of live babies ever born, was studied in three categories, namely primiparous (<2), multiparous (2–4), and grand multiparous (>4).The 2017 IDHS described wealth status as the socioeconomic quintile in a household. It was related to household income as seen from the styles and prices of furniture, such as televisions, bicycles, motorcycles, and household products, including drinking water supplies, bathroom amenities, and flooring materials. The 2017 IDHS determined the value of this variable by using the principal component analysis in the report. Every household’s score for the national wealth quintiles was then grouped into the same five classes, accounting for 20% of the population . They weThe study employed the bivariate test to analyze all data investigated at the first stage. In the bivariate analysis, the researchers used the chi-square test. Before conducting a binary logistic regression test, the study performed a co-linearity test to ensure no multicollinearity symptoms existed between the independent variables. The study used binary logistic regression to determine the policy’s target at the final stage. The author processed all statistical analyses in SPSS 26 software.The study used ArcGIS 10.3 to map the percentage distribution of LBW cases by provinces in Indonesia . The study collected the shapefile of administrative boundary polygons from the Indonesian Bureau of Statistics.https://dhsprogram.com (accessed on 1 November 2020).The study used secondary data from the 2017 IDHS for a materials analysis. The survey removed the identities of all respondents from the 2017 IDHS dataset. Participants in this study signed written consent forms, and the children’s parents or guardians gave their consent (under 16 years). The author has obtained permission to use data for this study through the website The 2017 IDHS adheres to the Standard D.H.S. survey protocol under the Demographic and Health Surveys Program (DHS-7), which has been approved by ICF International’s Institutional Review Board and was previously reviewed and approved by the ORC Macro IRB in 2002. DHS surveys that adhere to the Standard are classified as DHS-7 program-approved, and the approval document is attached. ICF International’s Institutional Review Board followed the US Department of Health and Human Services requirements for the “Protection of Human Subjects” (45 CFR 46).The national average percentage of LBW was 6.981% (95% CI 6.607–7.355%). At least 18 out of the 34 provinces in Indonesia have LBW rates above the national average. In terms of education, women with secondary education were more likely to deliver LBW babies. Unemployed women and multiparous women tended to give birth to LBW babies. Moreover, wealthier women were more likely to have LBW babies.The collinearity test result indicated no symptoms of multicollinearity between the independent variables tested. The tolerance value of all variables was greater than 0.10. Simultaneously, the variance inflation factor (VIF) value for all independent variables was less than 10.00. Then, referring to the basis of decision-making in the multicollinearity test, the study concluded that there was no indication of a strong relationship between the independent variables in the regression model.According to maternal education level, mothers with only primary school education and less ruled in both nutritional status categories. Based on maternal age, stunted children under the age of five have mothers with an average age slightly older than normal children under five years.While women in all age group categories, except the 45–49 age group, are less likely to give birth to LBW babies. Moreover, pregnant women in all marital status categories, except those who have never been married, are less likely to give birth to LBW babies.Women in all education level categories showed a higher probability of giving birth to LBW babies than women with higher education levels. Concerning education level, unemployed women are 1.033 times more likely to deliver LBW babies than those employed . This analysis showed that unemployment is a risk factor for women giving birth to LBW babies in Indonesia.Regarding parity, primiparous women are 1.132 times more likely to labor LBW babies than women with many children . The information indicated that being primiparous is a risk factor for pregnant women giving birth to LBW babies in Indonesia.Finally, Nationally, the average percentage of LBW cases, at 6.981% in 2017, was below the target of the National Medium-Term Development Plan in 2015–2019. However, at least 10 out of 34 provinces in Indonesia did not experience a lower percentage of LBW cases below this target. Besides, the Indonesian government recorded 18 regions with a prevalence of LBW cases above the national average . This coThis finding contradicts several previous studies. Studies in Ethiopia and Iran provided different conclusions. Mothers in rural Ethiopia and Iran were 1.39 and 1.4 times more likely to give birth to LBW babies than those in urban areas . AnotherBased on the age group, the result showed women in all age group categories except the 45–49 age group had a lower likelihood of giving birth to LBW babies. Previous studies in Jordan and Ethiopia also indicated that age influenced LBW incidence ,27. A stp = 0.004) [Women in all marital status categories, except those who had never married, had a lower chance of giving birth to LBW babies. An earlier study in Sub-Saharan Africa also reported marital status was associated with LBW babies. Divorced or widowed mothers were more likely to deliver LBW babies than married mothers . Having = 0.004) . Because= 0.004) . Higher-= 0.004) ,32. A be= 0.004) ,33,34. M= 0.004) ,36,37,38= 0.004) . Unemplo= 0.004) . Another= 0.004) . This co= 0.004) .Primiparous women had a higher probability of giving birth to LBW babies than women with many children. A study in Brazil also reported that primiparous mothers had up to 1.62 times the chance of delivering LBW babies than mothers with many children . MoreoveMoreover, this study revealed that women in all wealth status categories, compared to the wealthiest, had a higher probability of giving birth to LBW babies. An earlier study analyzing secondary data from the 2016 Ethiopia Demographic and Health Survey in Ethiopia also reported similar results with the incidence of LBW being dominant among the poor . Poor hoThe 2017 IDHS derived the data from a stratified multi-stage sampling procedure. The sampling method allows for an unequal probability of selection.This current study analyzed secondary data limited to variables reported in the IDHS. It excluded several variables known as determinants of LBW incidence in previous studies. Some were antenatal care during pregnancy ,45, smokAdditionally, this study employed a quantitative approach and thus did not uncover the social and cultural phenomena related to LBW regarding family and children value ,52,53, pBased on the results, policymakers should target pregnant women who live in urban areas, are old, have never been in a marriage, have low education, and are unemployed, primiparous, and poor to decrease LBW cases in Indonesia. The policymaker should target prospective mothers with a higher risk of having LBW babies.


Literature shows overlapping alterations in brain structure in Attention-deficit/Hyperactivity Disorder (ADHD) and substance use disorder (SUD), suggesting shared pathophysiological mechanisms. It is unclear to what extent family history (trait) effects and/or substance misuse (state) effects explain the observed overlap.Our aim was to examine the effects of (i) SUD family history (FH) and (ii) substance misuse on brain structure in ADHD.We compared structural MRI data  between (i) ADHD subjects and controls with or without FH , and (ii) FH-matched ADHD groups with and without substance misuse and controls . Furthermore, we explored whether FH effects were more pronounced in subjects with SUD in both parents (n=63) compared to subjects with one SUD parent (n=105) and without FH (n=160).There was no main FH effect on brain structure. ADHD+SM showed decreased CT in inferior frontal gyrus (IFG) compared to controls, while no difference was found between ADHD-only and ADHD+SM or controls. Subjects with SUD in both parents showed decreased thickness of IFG and volume of nucleus accumbens (NAcc), compared to those with one SUD parent.Substance misuse in ADHD might result in smaller IFG, which is in line with findings in SUD-literature. A contribution of premorbid alterations, due to FH, could not be ruled out, particularly for IFG thickness. Future studies should further investigate the potential role of these regions in treatment and prevention strategies.No significant relationships.


Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder characterized by symptoms of inattention, hyperactivity, and/or impulsivity. It is one of the most common disabilities in college populations and comorbidity with depression is frequently reported.The aim of the study is to shed light on depression as comorbidity and other intrapersonal correlates of ADHD in young adults.Participants were Hungarian university students . Criteria of the ADHD group were based on the Adult ADHD Self Report Scale V1.1 (ASRS-V.1.1) screening tool. The participants filled in the Beck’s Depression Inventory, the Hyperfocus Scale, Flow State Scale, Academic Persistence Scale, Satisfaction With Life Scale, General Self-Efficacy Scale, and the Connor-Davidson Resilience Scale.We found that in the group of students who had ADHD symptoms, depression score was significantly (p<.001) higher  than the control group’s scores . Frequency of severe depression was 13.4% (moderate: 33.5%) while in the control group: 1.6% and 17.6% respectively. Participants reporting ADHD symptoms  also reported lower levels of resilience , relative to their non-ADHD peers . Significant differences were found in the areas of self-efficacy, depression, flow and hyperfocus as well, and ADHD symptoms contributed to lower level of life satisfaction .Our findings suggest that university students reporting symptoms of ADHD may be assisted with strategies that are focused on increasing protective factors  to prevent depression and improve their life satisfaction and quality of life.No significant relationships.


ADHD is a common behavioral syndrome with a heritability of 70–80%. Genome wide sequencing and association studies indicate that ADHD risk variants are distributed across a wide range of allele frequencies and relative risks. Several common single nucleotide variants (SNPs) have been identified that increase the risk of ADHD with a few percent. Many of the reported risk genes and copy number variants are shared with other neuropsychiatric disorders. Moreover, ADHD often coexists with common or rare somatic diseases, including rare Mendelian neurometabolic diseases that can affect normal brain development and function. Some genetic/metabolic syndromes masquerading as common ADHD may lead to irreversible brain damage if not properly identified and treated during early childhood. As ADHD is such a heterogeneous condition in terms of severity, clinical features and most probably also underlying biology, it is crucial to offer individualized treatments. Recent progress in ADHD genetics is reviewed, prospects of using this information for targeted pharmacotherapy are discussed and critical knowledge gaps are identified. It is suggested that genome guided therapies could be introduced gradually, starting with rare ADHD syndromes with highly penetrant risk genes. Routine diagnostic application of whole exome or whole genome sequencing combined with metabolomic screening, and brain imaging may be needed in cases with suspected neurometabolic disorders. Identification and treatment of ADHD patients with defined neurometabolic aberrations could be a first step toward genome guided personalized treatment of ADHD. Possibly, screening for relevant biomarkers may gradually be implemented to guide treatment choices in larger patient groups. Attention-deficit/hyperactivity disorder (ADHD) is defined a childhood onset disorder with behavioral symptoms and problems that interfere with normal development and functions . It is cADHD genetics has been intensively investigated and subject to multiple reviews , 3, 4. EADHD management includes pharmacologic and non-pharmacologic treatments. The most widely used drugs in ADHD are amphetamine (used for ADHD since 1937) . DiagnosEarly linkage studies in affected families with ADHD produced diverging results. Likewise, candidate studies on genes believed to be implicated in stimulant drug therapy or ADHD symptoms failed to identify major gene effects. Early genome wide association (GWA) studies with modest sample sizes were also inconclusive. Together, these findings indicated that many risk variants and genes may be involved in ADHD etiology . The firBased on the results from GWA studies, a polygenic model of ADHD has emerged, where the genetic risk of ADHD is considered to result from the additive effects many small (or possibly larger) genetic risk variants interacting with each other and with multiple environmental factors. Many of the genetic markers are shared between ADHD and other common psychiatric disorders, such as major depressive disorder (MDD), autism spectrum disorder (ASD) and anxiety disorders , 14. ThiAPOE) confers a strong risk. In persons of European ancestry, a 3–4-fold increased risk in heterozygotes and 10–12-fold increased likelihood of AD in homozygotes has been reported  involved in lipoprotein homeostasis constitutes a large fraction of the total genetic risk  are usually termed single nucleotide polymorphisms (SNPs). Genetic variants may have detrimental effects on health and fitness or appear to be functionally silent. The conservation of such SNPs in the population has been partially explained by their low effect on fitness, being relatively protected from the forces of evolution. Typically, such variants are found in non-coding DNA and may be genetically linked to other functional elements or affect gene expression through subtle modification of enhancer region functions. In contrast, the classical Mendelian diseases are typically caused by coding variants with strong effects on fitness and reproduction. However, a closer examination of Mendelian disorders has shown that many have a variable penetrance that is partially dependent on genetic background and presence of other common variants. Indeed, there is no sharp boundary between textbook “genetic” diseases following Mendelian patterns of inheritance and complex conditions. Thus, many common multifactorial, complex human diseases have also been shown to have a combination of genetic risk factors, with some major risk loci in combination multiple other loci of small effects. For example, in Alzheimer's disease (AD), a few common genetic factors, such as the ε4 allele of apolipoprotein E   , X-linkeL2HGDH)  and HUWEutations . These eIn addition to genomics, many other types of neurophysiological, brain imaging or biochemical biomarkers have been examined in ADHD . ComparePartially inspired from recent progress in cancer treatment, most fields of medicine have experienced an expectation to use individual genetic or other biomarker information for the purpose of patient classification and “individualized,” “precision” or “personalized” medicine. In molecular oncology tumor targeted therapies are based on biomarker results from patient derived cells and tumor tissue. Such stratified treatments have dramatically improved life expectancy for selected groups of patients . In compAt first glance, ADHD may seem like an ideal candidate for personalized treatments. It is a very heterogenous condition. ADHD symptoms appear with a wide range of severities, clinical manifestations, and patterns of comorbidities. As summarized above, many different rare and common genetic variants and probably also a range of biological mechanisms may produce symptoms of inattention, impulsivity, and hyperactivity. The ideal treatment should be biologically informed and target individual underlying mechanisms and risk factors. However, in clinical practice, pharmacotherapy of ADHD is still largely based on trial and error with titration of broadly acting stimulant drugs affecting common neuromodulating monoamine transmitters. Although the majority of patients show some symptom reduction from stimulant drug therapy, many experience side effects or have no clear benefit from these drugs. Although several pharmacogenetic tests have been suggested, mainly targeting polymorphisms in dopamine and noradrenaline transporters or receptors, as well as stimulant metabolizing enzymes such carboxylesterase 1, there are currently no generally accepted reliable genetic or other biomarkers tests that can predict treatment outcome in this patient group .Different scenarios may be imagined for the introduction of genome guided personalized therapies for ADHD. It is theoretically possible that pharmacogenomics might reveal common, converging biological pathways, including new druggable targets for large patient groups. However, as mentioned above, ADHD appears to be a highly heterogenous condition, involving many additive and interacting genetic and environmental risk factors. Thus, a more realistic option is that personalized ADHD therapies will only be introduced gradually for small patient groups where ADHD symptoms might be secondary e.g., to defined neurometabolic aberrations. This expectation is based on experiences from oncology and other therapeutic areas, where personalized treatments have been introduced very slowly in based on the identification of particular biological signatures that are present only in a small minority of patients.Genetic research has clearly shown that each person with ADHD is unique. However, before personalized ADHD therapies can become a clinical reality, there are many challenges and knowledge gaps that need to be addressed. First, the whole spectrum of risk factors and biological mechanisms of ADHD needs to be systematically explored. This will require much larger sample sizes than currently available, defined clinical subgroups and the merging of data from studies on common and rare genetic variants. Biologically meaningful subgroups may need to include patients across traditional diagnostic categories. In addition to genomics data, information from multiple data sources, including epigenetics, transcriptomics, metabolomics and proteomics need to be integrated and jointly analyzed to describe biological profiles in these subgroups. Such -omics and systems medicine approaches are essential for identifying the relevant patients, whether they are suffering from a potentially treatable cancer or a progressive brain damaging neurometabolic disease.Given that sufficient research progress can be made, the practical implementation of genome guided therapies may be equally challenging. Clinicians need to be aware of new therapeutic possibilities, to be trained to recognize relevant symptoms and to have access to adequate laboratory resources, including a medical genetics/ systems biology service. As detailed above, in cases with atypical or progressive clinical features and co-occurring somatic manifestations it is vital to properly explore possible underlying conditions and to examine for coexisting problems beyond classical ADHD symptoms. In conclusion, as research on ADHD genetics is coming of age, personalized (drug) therapy could become a reality also for ADHD patients. This could start with the most obvious genetic perturbations affecting known targets of currently used drugs, as well as new druggable targets identified using pharmacogenetic pipelines of discovery.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.The author confirms being the sole contributor of this work and has approved it for publication.This study has received funding from the Research Council of Norway (Project No. 331725), Stiftelsen Kristian Gerhard Jebsen (SKJ-MED-02), the Regional Health Authority of Western Norway (25048), and the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No. 728018.This article reflects only the author's views and the European Union is not liable for any use that may be made of the information contained therein.JH has received lecture honoraria as part of continuing medical education programs sponsored by Shire, Takeda, Medice, and Biocodex.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Despite widespread use of stimulants to treat ADHD, individual responses vary considerably and few predictors of response have been identified. The identification of reliable and clinically feasible biomarkers would facilitate a precision medicine approach to pharmacological treatment of ADHD. We test the hypothesis that two electroencephalography (EEG) based neural signatures of ADHD, resting aperiodic slope exponent and novelty P3 amplitude, are markers of methylphenidate response in children. We hypothesize that positive response to methylphenidate treatment will be associated with greater abnormality of both neural markers.n = 16) or non-responders (n = 13) using the clinical global improvement (CGI-I) scale during blinded retrospective interview. All participants abstained from prescribed medications for at least 48 hours prior to the EEG.Twenty-nine 7-11 year-old children with ADHD and a history of methylphenidate treatment, and 30 controls completed resting EEG and visual oddball event related potential (ERP) paradigms. ADHD participants were characterized as methylphenidate responders  demonstrated attenuated P3 amplitude relative to controls. Unexpectedly, methylphenidate non-responders showed atypically flat aperiodic spectral slope relative to controls, while responders did not differ on this measure.ADHD symptoms associated with atypical patterns of intrinsic neural activity may be less responsive to methylphenidate. In contrast, ADHD symptoms associated with abnormal frontal-striatal neural network excitation may be correctable with methylphenidate. Altogether, EEG is a feasible and promising candidate methodology for identifying biomarkers of stimulant response. ADHD is the most common neurodevelopmental disorder diagnosed in children. The number of and use of approved medications for ADHD has increased over the past four decades . The mosf distribution , neural pink noise, and scale-free dynamics (X in 1/xf). Greater aperiodic exponent reflects increased excitatory signal and engagement of global neural populations, while flatter slope reflects a shift toward inhibitory currents and local neural networks  with age across the lifespan . Adolescvia reduced integrity of the fronto-striatal cortical networks, and/or reduced excitatory synaptic capacity.In contrast to the aperiodic slope, there is a large literature documenting attenuated amplitude of the P300 event related potential (ERP) component among children and adults with ADHD . In partA small body of literature has reported associations among methylphenidate treatment, behavioral improvement, and increased amplitude of the novelty P3a or related components, among children and adolescents with ADHD. For example, The current study tests the hypothesis that two electrophysiological indices of neurocognitive functioning will be associated with methylphenidate response in children with ADHD. First, we hypothesize that the aperiodic exponent and novelty P3a amplitude are potential biomarkers of individual response to methylphenidate among school age children with ADHD. Secondly, we hypothesize that children with evidence of both bottom-up and top-down cognitive dysregulation  will show greater response to methylphenidate, relative to children with normal neurocognitive functioning in one or both measures.n = 100; control n = 30) who had completed a study of neurocognitive correlates of ADHD at the University of Washington . Parent study procedures included a single laboratory visit during which the child completed a one-hour EEG and neuropsychological testing. Caregivers reported on their child’s medical, behavioral, psychiatric, and temperament histories through a combination of in-person and remote data collection procedures. All children abstained from stimulant medications for at least 48 h prior to the visit.All ADHD participants from the parent study were emailed within two years of parent study participation with an invitation to participate in a remote follow-up if their child had ever been treated with methylphenidate. As part of the follow-up, caregivers completed two retrospective reports in which they were instructed to rate their child’s ADHD symptoms (1) before methylphenidate treatment and (2) at the time the child was taking an optimal dose of methylphenidate, using the Strengths and Weaknesses of ADHD and Normative Behavior (SWAN) scale . OptimalContinuous EEG was acquired with a 128-channel Magstim-EGI Hydrocel geodesic sensor net and Netstation Acquisition software version 4.5.6, integrated with a 400-series high impedance amplifier . Electrode impedances were reduced to below 50 kOhms at the start of the session and monitored throughout. EEG signals were referenced to the vertex electrode, analog filtered , amplified and digitized with a sampling rate of 1,000 Hz. Timing of the presentation of the visual stimuli was recorded using a Cedrus Stimtracker . Continuous EEG data were subsequently processed offline in MATLAB R2018b using EEGLAB 15 and ERP Lab v8.0 functions. Eye electrodes and 14 rim channels were excluded from analyses. Data were downsampled to 250 hz and bandpass filtered at 0.3-80 hz. Electrical line noise from 55 to 65 hz was removed using the Cleanline plugin for EEGLAB. Following methods outlined in the Harvard Automated Processing Pipeline for Electroencephalography HAPPE; , channeln = 11) of the responders were currently taking a methylphenidate medication at the time of the interview, as opposed to 31% (n = 4) of the non-responders, further supporting our characterization approach.CGI-I ratings were used to characterize ADHD participants as methylphenidate responders or non-responders. Consistent with previous literature indicating that CGI-I ratings of “much improved” or “very much improved” correspond to a 30% reduction in symptoms , CGI-I sAperiodic slope exponents were acquired from a lights-off resting EEG paradigm. During the resting EEG, participants were seated in a comfortable chair in a dark room and instructed to sit quietly with their eyes open for two minutes. The lights off condition was selected over an “eyes-closed” resting condition to minimize muscle artifact and potential cognitive effort that is often introduced by asking young children to keep their eyes closed. After processing, the amount of usable data ranged from 85 to 120 s.peak_width_limits = , max_n_peaks = 8, min_peak_height = 0.5, peak_threshold = 2.0. For each individual, a mean aperiodic exponent was calculated as the average exponent across electrodes in five midline scalp regions: anterior frontal , frontal , central , parietal  and occipital .Aperiodic exponents were computed in MATLAB. Welch’s method was used to perform fast Fourier transformation (FFT) on resting EEG data with a 50% overlap and 1-second Hamming window. Next, the Fitting Oscillations and One-Over-f (FOOOF) MATLAB toolbox  was usedvia camera and “bad trials” in which the child was not attending to the task or moving excessively were coded for exclusion from the analyses. Task accuracy did not differ between ADHD and control groups .The ERP task was completed following the resting EEG. One-hundred-forty target (task-related) visual stimuli were presented alternately with 140 oddball (non-task-related) visual stimuli, using a design adapted from t[54.15] = −0.37, p = 0.714; ADHD range = 22-28; control range = 16-28).Event related potential task data were segmented to 300 milliseconds prior and 900 milliseconds following presentation of novel stimuli on the participant screen. Epochs were further lowpass filtered at 40 Hz and baseline corrected using the full 300 ms. Based on visual inspection of ERP waveforms, average amplitude of the novelty P3a component was extracted from the Pz electrode during the 280-450 ms window . After pData were prepared and analyzed in R Studio version 2021.09.1. Continuous variables  were normally distributed. To address our main hypothesis, we tested a multinomial logistic regression with methylphenidate response group as the unordered categorical dependent variable, and controls specified as the reference group. Independent variables were race, aperiodic exponent, and novelty P3a amplitude. Next, we examined the ability of our model to distinguish between responders and non-responders using receiver operating characteristic (ROC) analysis (R package pROC). The ADHD sample was randomly split into 200 test (70%) and train (30%) datasets. Area under the curve (AUC) and 95% confidence intervals (CI) were calculated for each set, along with sensitivity and specificity estimates at five thresholds. CI estimates were bootstrapped over 2,000 stratifications for each calculation.2[2] = 6.51, p = 0.039). Response groups did not differ on age  or proportion of females . Responders and non-responders did not differ on IQ (p = 0.967). Thus, only the binomial self-identified race variable (white versus non-white) was included in subsequent analyses.Sample demographics are described in Results of the multinomial logistic regression model are reported in Contrary to our predictions, the opposite pattern emerged for aperiodic slope . MethylpFinally, we examined the ability for the combined P3a and aperiodic slope indices to predict responder group membership. The average AUC was 0.79 (95% CI: 0.50 – 0.99), with an optimized sensitivity/specificity of 0.71 and 0.70, respectively.Aperiodic spectral slope and novelty P3a amplitude measure distinct neural processes, with the former reflecting global patterns of intrinsic activity at rest and the latter representing time-locked activation of fronto-striatal neuronal populations. In the current study, the combination of these measures achieved moderate to high accuracy for predicting retrospective report of response to methylphenidate in a small sample of children with ADHD. More specifically, methylphenidate responders and non-responders showed opposing patterns of neural atypicality, wherein responders were characterized by attenuated ERP amplitude and non-responders characterized by reduced aperiodic exponent.These preliminary results indicate that methylphenidate, which increases catecholamine availability in the synapse, may be more effective for children whose blunted P3a amplitudes suggest reduced excitation of neuronal populations in the frontal-striatal cortices. This is consistent with a substantial body of research demonstrating that methylphenidate enhances  P3a amplitude among children with ADHD . The impIn contrast, our results suggest that methylphenidate may be less effective for children with intact P3a amplitudes and flatter aperiodic slope. The aperiodic slope is a measure of the balance of slower versus faster background neural oscillations. While slower oscillations are generated by larger, coordinated global neuronal populations, faster oscillations generally reflect activity in smaller, local neural networks. Thus, the balance of slow and fast aperiodic oscillations represents an intrinsic “self-tuning” by the brain that supports flexible and efficient neuronal activation in response to periodic environmental elements. In a dark room at rest, as in the current study, the brain is expected to show a greater emphasis toward engagement of long-range, global networks , while in an environment with more visual or auditory input, the emphasis shifts toward involvement of smaller, more segregated networks . Dynamic shifts of this balance in response to environmental conditions, which have previously been demonstrated to be atypical in ADHD populations , facilitIf flatter aperiodic slope is a mechanism contributing to ADHD symptoms among non-responders, then our study may indicate that increased availability of catecholamines is not as effective at normalizing intrinsic activity patterns in the brain. However, results of a prior study were inconsistent with this theory, in that they found methylphenidate treatment did indeed increase the aperiodic exponent in children with ADHD . MethodoOur findings are consistent with prior studies reporting that faster frontal alpha peak frequency in male children and adolescents with ADHD is associated with a history of improved behavioral response to MPH . The alpThe current results must be interpreted with caution, however, given the small sample size and retrospective nature of our methylphenidate responder categorization. Prospective studies involving treatment naïve children and consistent optimization of methylphenidate dosing will be necessary to validate our findings. Moreover, while we hypothesize that behavioral effects of methylphenidate are correlated with change in our neurobiological markers, we were not able to re-test these children while on medications as part of the current study. Thus, we cannot confirm that these neural markers of treatment response represent a neurobiological mechanism for the individual child’s ADHD symptoms. Moreover, although all children abstained from prescribed ADHD medications for 48 hours  prior to the EEG, we cannot rule out the possibility that prior stimulant use moderated these neural signatures, a finding that has been suggested in previous work . FinallyMeasurement of brain activity using electroencephalography is feasible and thus presents as a strong candidate technique for measuring individual indicators of treatment response. The results of our preliminary work indicate at least two distinct electrophysiological markers of ADHD symptoms were associated with divergent responses to methylphenidate. These findings have potential to improve delivery of precision medicine care for children with ADHD, as well as inform our understanding of the neurobiological mechanisms contributing to the broader ADHD phenotype.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by University of Washington Institutional Review Board. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.AA wrote the first draft of the manuscript, contributed to study design, conceptualization and data collection, and ran statistical analyses. TR contributed to conceptualization and data collection and reviewed the final manuscript. MS contributed to study design and conceptualization, contributed to manuscript drafts, and reviewed the final manuscript. All authors contributed to the article and approved the submitted version.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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Attention-Deficit/Hyperactivity Disorder (ADHD) runs in families; however, there are mixed results on the interaction effects of parent’s and child’s psychopathology on parenting qualities. Cognitive/schema therapy is a promising treatment approach for adult ADHD; we know little about the effect of cognitive factors on parenting, however.We aimed to fill this gap by exploring the role of dysfunctional schema modes in the associations between adult ADHD symptoms, child’s externalizing symptoms, and perceived parental competence in a dimensional approach.A community sample of parents  filled out online questionnaires assessing ADHD symptoms , dysfunctional schema modes (Schema Mode Inventory), perceived parental competence , and child’s psychopathology (Strength and Difficulties Questionnaire).In a multivariate model, higher levels of parental ADHD symptoms were related to higher levels of dysfunctional schema modes. However, neither the child’s externalizing symptoms nor the interaction term of parent’s symptoms by the child’s symptoms had any effect on dysfunctional schema modes. Furthermore, the child’s externalizing symptoms had a direct negative association with parental self-efficacy beliefs, whereas the relationship between adult ADHD symptoms and parental self-efficacy was mediated by the detached and overcompensating dysfunctional schema modes.Our results suggest that the activation of dysfunctional schema modes is related to the parent’s but not the child’s psychopathology. The activation of dysfunctional schema modes may play an important role in the self-efficacy beliefs of parents with ADHD. Targeting that cognitive factors may enhance the effect of behavioral parent training programs.This research was supported by National Research, Development, and Innovation Office (NKFIH) OTKA-PD-134849 grant.


Gastrointestinal symptoms, as well as stool microbiome, were assessed in both groups. Stool samples were serially collected from all participants during both the school term and summer vacation. The stool samples were subjected to total genomic extraction, 16S rRNA amplicon sequencing, and bioinformatics analysis. The gut microbiome was compared at school and during vacation. Other metrics, alpha diversity, and beta diversity, were also compared between the two school terms in every group. Results: In the healthy group, there were differences in microbiome composition between school terms and summer vacation. Conversely, we found no differences in the FAPDs group between the two terms. The healthy control group revealed differences  in 55 bacterial species between the school term and vacation. Several of the differentially abundant identified bacteria were involved in short-chain fatty acids production (SCFAs), inflammation reduction, and gut homeostasis. Alpha diversity metrics, such as the Shannon index, were different in the control group and remained unchanged in the FAPDs group. Conclusion: Although preliminary, our findings suggest that the gut microbiome is static in FAPDs. This compares with a more dynamic healthy gut microbiome. Further studies are warranted to corroborate this and understand the interplay between stress, symptoms, and a less diverse and static microbiome. Future studies will also account for different variables such as diet and other patient demographic criteria that were missing in the current study.Background: Functional Abdominal Pain disorders (FAPDs) are a group of heterogeneous gastrointestinal disorders with unclear pathophysiology. In children, FAPDs are more common in the winter months than summer months. The possible influence of school stressors has been proposed. Previously, our group showed differences in bacterial relative abundances and alpha diversity in the gut microbiome and its relationship with stressors in a cross-sectional evaluation of children suffering from FAPDs compared to a healthy control group. We present longitudinal data to assess whether the gut microbiome changes over school terms in the control and FAPDs groups. Methods: The longitudinal study included children with FAPDs ( Functional Abdominal Pain disorders (FAPDs), a group of heterogeneous gastrointestinal disorders, are common among schoolchildren. Children with FAPDs frequently report comorbid extraintestinal symptoms and limitations in social and physical activities . FAPDs, This was a longitudinal study. Children with and without FAPDs  who met the inclusion/exclusion criteria participated in the study. Children with FAPDs (cases) were recruited from a large pediatric gastroenterology clinic in Central Florida. The healthy controls were recruited from five local pediatric practices in the greater Orlando area. The control group included healthy children seen for routine exams or well-check appointments who met the inclusion/exclusion criteria. The participants consented via child and/or parental consent based on age. The patients and caregivers were instructed to collect three stool samples at home and send them via US mail. The hemoccult ICT collection kit was used to collect all of the stool samples . The kit included a toilet hat, application stick, collection card, collection pouch, specimen biohazard bag, pre-addressed mailing envelope, and detailed paper instructions about the collection procedures. The procedure has been validated as a cost-effective method of stool collection with no significant microbiome differences from other stool collection methods . The stoThe follow-up comparative analysis such as Alpha and beta diversity metrics were assessed using R with the packages such as phyloseq, tidyverse, ggplot2 ,22,23,24p < 0.05 was used for statistical significance. (MaASLin) statistical pipelines from Huttenhower lab Galaxy  (Access date 15 June 2022) were used in the analysis of the data. Multivariate analysis by linear models (MaASLin) was used to assess the differences in the relative abundance of the bacterial phyla between the groups (FAPDs vs. controls) and for the academic year (school vs. vacation). GraphPad Prism V.8  was also used for the analyses of the bacterial relative abundances between groups; two-tailed, and a p-value > 0.05). Sixty-five percent of the enrolled participants did not take antibiotics in the year before the study, and none of them received antibiotics two weeks prior. Briefly, both groups were similar in age (p = 0.287), sex (p = 0.64), and race/ethnicity (p = 0.400). Forty-five children with FAPDs and 86 healthy were enrolled in the study . Twenty-Enterobacter was the only identified bacteria to be statistically and significantly different  (data not shown). In contrast, the healthy group gut microbiome showed that at least 55 bacterial species revealed statistically significant differences   . Holdemania, Bacteroides, Collinsella, Lachnospiraceae, Fusicatenibacter, Enterococcus, and Alistipes , but not Faecalibacterium, was lower in the vacation term compared to the school. In addition, Alistipes levels  were also lower during vacation, while Prevotella levels were higher . In addition, genera such as Rothia, Lactobacillus, and Streptococcus were higher in vacation terms compared to the school term  in controls but not in the FAPDS group , while no significant changes were observed in the FAPDs group. Lactobacillus showed a similar pattern as well, while the Bifidobacterium and Ruminococcus levels were unaltered in both groups. These findings suggest a static nature of the microbiome in the FAPDs compared to a dynamic, healthy control microbiome  in school and one on vacation, excluding repetitive samples of the same subject in each school term. This selection reduced the sample size to 19 paired samples for the control group and 11 paired samples for the FAPDs group. Using paired testing, we found that the FAPDs group did not reveal differences in any bacterial taxa, while the healthy control group had approximately 52 bacterial taxa that were significantly different. The two most abundant bacterial species in the gut, crobiome .p-value > 0.05), while a difference was observed in the control group  . PCA of Bray–Curtis distances discriminated by school term in the control group with statistical significance .We measured and compared α-diversity (Shannon diversity) between the school terms in the FAPDs and control groups. Shannon diversity did not reveal any statistically significant differences in the FAPDs group between the two school terms ( < 0.05) A,B. Addi < 0.05) . PERMANOFaecalibacterium and Dorea showed altered abundances in the gut of IBS patients [Bacteroides may be involved in the development of the disease [Recent studies have suggested a possible role of gut microbiota in the pathophysiology of multiple gastrointestinal (GI) diseases such as IBS, inflammatory bowel disease (IBD) ,26,27,28patients . Similar disease . Our gro disease ,33. We pRuminococcus, which were previously implicated in adult IBS.Studies in adults with irritable bowel syndrome  showed sIndeed, the human gut is likely to be affected by environmental factors, including xenobiotics, stress, diet, and lifestyle throughout the individual’s lifespan, and is an important key player in IBS pathogenesis . GeneralEnterobacter was the only genera that showed a significant increase during a vacation in both control and FAPDs fecal samples. Interestingly, in the control group, some bacteria species involved in short-chain fatty acids (SCFAs) were among the 55 identified bacterial species that changed during a vacation in the control group. Lactobacillus and Prevotella were among the acetate-producing bacteria, while others such as Bifidobacteria, Akkermansia, and Ruminococcus [Bacteroides and Veillonella [Bacteroides levels were significantly higher during school terms. When we further studied the smaller groups with paired samples, only the control samples showed changes in the two most abundant species, Bacteroides (increase) and Faecalibacterium (decrease), during the school term  both produce propionic and acetic acids. In a cross-sectional study, higher levels of organic acid-producing flora, especially acetic and propionic acid, were found to be associated with IBS, including Veillonella and Lactobacillus [nococcus  did not nococcus . Acetatellonella . Bacteroool term A. Interebacillus . The relbacillus ,41. Othebacillus ,43,44. TFaecalibacterium and Bacteroides. A potential and accurate tool such as Droplet Digital PCR (ddPCR) can be used to estimate the absolute load of such bacterial species. Additional diagnostics can also be used at the fecal metabolites, especially bacterial metabolites, to confirm the concomitant differences at the metabolomic levels as well. As a futuristic approach for diagnosis and treatment, we can target the gut microbiome with a research-based probiotics cocktail tailored to every FAPDs patient. We can use the differential bacterial abundances to diagnose and monitor the disease progression in children.The FAPDs gut microbiome is static compared to the healthy age-matched group. This finding needs to be confirmed in a multicenter and a larger sample size study. Noteworthy, the selected population represents an understudied segment of the population, and 25% of the children with FAPDs evolve into IBS in adulthood. The static nature of the gut microbiome of FAPDs patients can offer clues about the symptoms, such as the stress associated with the symptoms. Based on these findings, we can explore options to measure the bacterial differences or metabolites in the stools of FAPDs patients. We just launched a larger study in our hospital to explore the variations in the gut microbiome and stool metabolites levels. If the gut microbiome showed the same pattern in lack of diversification at the level of bacterial abundances, diversity, and fecal metabolites, we could devise targeted measurements of certain bacterial species, such as


The differential diagnosis between Autism Spectrum Disorder (ASD) and Attention Deficit/Hyperactivity Disorder (ADHD) is often challenging and detrimental to early and timely treatment. Co-current and overlapping symptoms contribute to erode differential diagnostic accuracy, based mainly on clinical assessment supported by standardized instruments and reports from parents and teachers. The microbiota was recently considered a valuable resource in the search for biological markers in neurodevelopmental disorders.Our objective was to examine the published literature in order to clarify the role of the microbiome as a possible differential biomarker between ASD and ADHD.Five hundred and sixteen articles were reviewed in order to contextualize the role of Gut- Brain Axis in neurodevelopment and neurodevelopmental disorders, the microbiome as a biomarker and ultimately to unravel microbiome abnormalities reported in patients diagnosed with ASD and/or ADHD.Although gut microbiome appears to be involved in the pathogenesis of ASD with several reports identifying changes in gut populations and functions, a “microbial signature” is still not reached. In ADHD patients, research confirms that the composition and predicted functions of gut microbiome are also altered, but identically controversial results were found.Future studies are needed to confirm the relationship between the composition and function of the microbiome and the occurrence or presentation of each of the disorders. A specific signature of the microbiota could then constitute itself as a differential biomarker in ASD and ADHD.


Their parents completed the CBCL twice—first during the summer medication-free period, that is, at least one month after drug interruption; and again after three months of treatment restart. Results demonstrate that MPH is associated with a statistically significant reduction in ED in ADHD and ASD, without substantial adverse events, supporting the use of psychostimulants for the treatment of ED in these neurodevelopmental disorders.Emotional dysregulation (ED) is common in attention-deficit/hyperactivity disorder (ADHD). Nonetheless, research on ADHD in children with autism spectrum disorder (ASD) and ADHD is still ongoing. Several studies suggest that methylphenidate (MPH) may be effective for ED in ADHD, while there is not enough evidence about its use in ASD with comorbid ADHD. This naturalistic study aims to investigate the effectiveness of immediate- and extended-release MPH in the treatment of ED in 70 children and adolescents (6–18 years), with a diagnosis of ADHD ( Emotional dysregulation (ED) is characterized by an inability to modulate emotional responses, resulting in extreme reactions of an internalizing or externalizing nature, inappropriate for developmental age . It has As for therapy, to date, no data are available regarding a specific pharmacological treatment for ED. To date, in most cases, treatment choice was guided by the main psychiatric condition behind ED. In ADHD individuals, preliminary evidence suggests that psychostimulants improve emotional recognition and reduce emotional lability and irritability . NeverthThe aim of this study was to evaluate the effectiveness and tolerability of immediate- and extended-release MPH treatment on ED in children and adolescents with ADHD, with or without ASD.This was a naturalistic study based on a clinical database of Caucasian young people, aged between 6 and 18 years, consecutively referred to the Child Neuropsychiatric Unit of the University of Bari during a two-year period (September 2019–September 2021). The inclusion criteria were a diagnosis of moderate to severe ADHD, according to DSM-5 , pharmacThe starting dose of MPH was 0.3–0.5 mg/kg/day. The dosage could be increased up to 1 mg/kg/day depending upon the subject’s clinical response and tolerability, up to a maximum of 60 mg/day. The total dose could be administered in two or three doses/day. After one month of titration, the IR-MPH was generally replaced with ER-MPH. The therapeutic management of ADHD children in our unit comprises short breaks in summer, in agreement with parents and patients about the best pattern of use, with the aim of investigating the ongoing benefit of medication, helping to verify need and the possibility of a reduction in side effects relating to sleep and appetite, albeit considering its reintroduction whenever needed. The median MPH dose and therapy duration are described in For the specific purpose of this study, ED was studied through the evaluation of CBCL scores.The CBCL is a self-reported scale developed by Achenbach and Edelbrock to evaluate existing competencies and behavioral, emotional, and social problems in children and adolescents aged between 6 and 18 years, through information derived from parents. The behavioral problems scales include 118 items, divided in internalizing and externalizing subscales. The internalizing subscale contains items concerning withdrawn behavior, somatic complaints, and anxious/depressed behavior. The externalizing subscale includes items concerning delinquent and aggressive behavior. Furthermore, there are subscales that contain social, thought, and attention problems. The higher score represents a higher level of problems. A computer program calculates the t scores  for each scale. Raw scores are converted to gender- and age-standardized scores.According to Biederman ,49,50,51Data obtained from the ADHD group and the ADHD and ASD group were compared to each other, henceforth analyzed.The Ethic Committee of the Azienda Ospedaliera-Universitaria Consorziale Policlinico di Bari approved the study. Informed consent from parents and assent from children and adolescents were obtained prior to enrollment. Among 75 patients who were prescribed MPH, 5 were excluded because their caregiver did not sign the informed consent. The enrolled sample consisted of 70 patients of which 41 had a diagnosis of ADHD (henceforth named the ADHD group) and 29 had a diagnosis of ASD with comorbid ADHD (henceforth named the ADHD and ASD group).es) and the pooled standard deviation: D = es × Sp.Comparisons between the two groups were analyzed by t-test or Wilcoxon test for independent samples, appropriately selected according to the evaluation of normality of quantitative variables. Comparisons of proportions between independent groups have been performed by the chi-square test or the Fisher exact test, according to appropriateness. Comparisons between proportions in paired samples were compared by the McNemar test. A general linear model was also applied to evaluate the difference between the two groups at the two timepoints. The main aim was to evaluate whether there was a difference between the two groups (ADHD vs. ADHD and ASD) in terms of effectiveness and tolerability of MPH on ED; therefore, a test of equivalence was performed: the Two One Side Test (TOST) was applied comparing the limits of the 90% confidence interval of the difference between the two means with the of equivalence (D). They were determined as the product between the effect size (ES) .All the analyses were performed using SAS 9.4 for personal computer. The significance level was set at Demographic and clinical characteristics of the two groups, comorbidities and pharmacological treatments in addition to MPH are described in p = 0.08 and p = 0.18, respectively). Conversely, comparing CBCL-AAA profiles in T0 and T1 in each group and in the total sample, the difference was statistically significant (p < 0.01)  at T0 and at T1 was not statistically significant ( < 0.01) .p = 0.32, attention: p = 0.42, aggressive: p = 0.27; T1 anxious: p = 0.31, attention: p = 0.04, aggressive: p = 0.29). Conversely, comparing the scores of CBCL-AAA subscales in T0 and T1 in each group and in the total sample, the difference was statistically significant (p < 0.01).Comparing the ADHD group with the ADHD and ASD group, the difference between each subscale of CBCL-AAA both at T0 and at T1 was not statistically significant . Conversely, comparing the CBCL-AAA total score in T0 and T1 in each group and in the total sample, the difference was statistically significant (p = 0.01)  .Evaluating the equivalence between the difference T0–T1 of the CBCL-AAA total scores, the two groups were equivalent to each other.Conversely, evaluating the equivalence between the CBCL-AAA scores in the two group at T0 and at T1, the two groups were not equivalent to each other.No severe adverse events were reported; indeed, among these, no cardiovascular events neither suicidal ideation or behaviors were seen .The most frequent side effects in the ADHD group were loss of appetite, abdominal discomfort, and headache , each only temporary, in the first days or weeks of treatment; the same side effects were seen in the ADHD and ASD group . The difference between each side effect in the two groups was not statistically significant. Two ASD patients with comorbid ADHD, both with intellectual disability, of which one was affected by level 3 ASD and the other by level 2 ASD, presented worsening of behavior, with restlessness and increased stereotypes that caused the interruption of treatment and completely resolved after treatment discontinuation.This study analyzes MPH effectiveness and tolerability on emotional dysregulation (ED) in a naturalistic setting of 70 ADHD patients, of which 29 also had ASD. To the best of our knowledge, this is the first study focusing on the effect of MPH on ED in ASD children and adolescents.Several studies analyzed the prevalence of ED both in ADHD, finding percentages between 24 and 55% in children and adolescents and 34 to 70% in adults , and in ED is a challenging pharmacological target, and the scientific literature to date does not provide tailored guidelines for its management, probably because most of the available pharmacological trials did not focus on ED per se. Given the transnosographic quality of ED, pharmacological approaches aimed at it are largely guided by the presence of comorbid illnesses: risperidone and aripiprazole in the context of ASD and/or intellectual disability, serotonin reuptake inhibitors in the context of depression or generalized anxiety disorders, and mood stabilizers  in the context of bipolar spectrum disorders ,53,54,55Previous research and clinical experience clearly demonstrated that MPH has a beneficial effect on ADHD core symptoms ,57,58. RConcerning the use of MPH in ASD patients, efficacy and safety data are controversial: some early studies reported that stimulant medication resulted in increased stereotypical movements in children with ASD or in additional adverse events that may impact negatively on social interaction. However, these results are based on small samples of patients (frequently case report), often comorbid with intellectual disability ,60,61. Tp< 0.0001) reduction in CBCL-AAA score was found both in the ADHD group and in the ADHD and ASD group. Within these findings, it is remarkable to note that the median of intellectual quotient was 97.2 in the ADHD group and 96.3 in the ADHD and ASD group. As for tolerability, treatment with MPH was well tolerated; there were no serious adverse events, with the main adverse events being temporary loss of appetite, abdominal discomfort, and headache, without significant differences in the two groups.The present study suggests that MPH is associated with a significant improvement in ED in ADHD children and adolescents with or without ASD. Actually, after MPH use, a statistically significant , with a specific focus on ED, assessed through a standardized measure. Being a naturalistic study, medication titration and dose adjustment were possible as necessary, almost like in a real-life setting.Study limitations include the lack of randomization or blinding and control of other pharmacological/behavioral treatments and the small sample size. The suitability of our study design used to measure ED administering the CBCL during the summer medication-free period and after three months of treatment restart (employing each patient as his/her own control) could be discussed. Future research in this field should involve proper administration of the CBCL before the beginning of treatment and the extension of ED assessment through other measures, as objective as possible and preferably not only parent mediated.In conclusion, our study shows that MPH treatment is well tolerated and effective in reducing ED in children and adolescents with ADHD who may also have high-functioning ASD. Thus, the routine use of MPH in this group of children and adolescents is recommended.


Crystal House is a specialist CAMHS ID inpatient 5-bedded unit based in the Kingswood Centre, North West London - for children aged between 13 and 18 years with primary diagnosis of Intellectual Disabilities with or without additional concerns that warrant admission to hospital for purpose of assessment and management. Reporting this case, we wanted to highlight complexities of management of children presenting with neurodevelopmental conditions and history of trauma.This is a case of a fourteen-year-old girl with established diagnoses of Moderate Intellectual Disability, Childhood Autism, Foetal Alcohol Syndrome and childhood trauma. She was admitted to our CAMHS ID Assessment and Treatment Unit with a nine- year history of self-injurious behaviour, suicidal ideation and voice-hearing experiences – after failed treatment in the community and in-patient treatment (including under restrictions of long-term segregation) on generic CAMHS unit. Her current treatment includes a person-centred Trauma- Informed Positive Behaviour Support Plan; individual and family therapy psychology sessions based on the principles of trauma-informed care and consultation with staff on trauma-informed care. She also undertook ADHD assessment, and we are in the process of optimising ADHD medication.Trauma-Informed Positive Behaviour Support Plan was a new concept for the team. Therefore, this was supported by training and consultations with staff. The latter was introduced to create a psychologically oriented environment using trauma-informed care principals and helping the team understand what trauma means and how it affects the individual. ADHD assessment confirmed the diagnosis of ADHD which was followed by optimising ADHD medication.Systemic and a person-centred approach is used for this child with concerning presentation and history of neurodevelopmental disorder and childhood trauma.


Attention-deficit/hyperactivity disorder (ADHD) is associated with a wide array of neural and cognitive features, and other psychiatric disorders, identified mainly through cross-sectional associations studies. However, it is unclear if the disorder is causally associated with these neurocognitive features. Here, we applied a two-sample bidirectional Mendelian randomization (MR) study to summary GWAS data to explore the presence and direction of a causal effect between ADHD and a range of neurocognitive features and other psychiatric disorders. The inverse variance weighted method was used in the main analysis, and two MR methods  were used for robustness checks. We found that genetic risk for ADHD was causally associated with a decreased area of lateral orbitofrontal cortex. Conversely, we found that brain volume and some features of intrinsic functional connectivity had causal effects on ADHD risk. Bidirectional causal links were found between ADHD and adult general intelligence, as well as depression and autistic spectrum disorders. Such work highlights the important ties between ADHD and general cognitive ability, and suggest some neural features, previously merely associated with the disorder, may play a causal role in its pathogenesis. Attention deficit hyperactivity disorder (ADHD) is a highly heritable neuropsychiatric disorder, with family and twin studies suggesting a heritability of around 70–80% . A landmComplimenting the genetic associations studies of ADHD, a wide range of associations have been reported between ADHD and cognitive and neural features. The disorder is strongly associated with other psychiatric disorders, particularly other neurodevelopmental disorders, such as autistic spectrum disorders (ASD) , 5 and TTo overcome this limitation, an epidemiological approach has been proposed, Mendelian Randomization (MR), that uses genetic variants as instrumental variables to assess potential causal relationships between an exposure (such as liability to ADHD) and an outcome  . Two-samTo conduct MR, genetic data, usually in the form of genome wide association study, is needed on both the “exposure”  and the “outcome” . Such GWAS data exists for ADHD, stemming from Psychiatric Genomics Consortium ADHD working group, as does publicly accessible GWAS summary results for many traits and disorders associated with ADHD. The application of MR to such summary GWAS data has already allowed the exploration of possible causal pathways between ADHD and other mental and physical disorders. For example, the MR approach has demonstrated a possible causal effect of liability to ADHD on major depression , smokingHere we extend this work by examining possible causal links between ADHD and an array of neural and cognitive features. In focusing on neural features, we leverage recent mega-analyses from the ENIGMA consortium, which report on the anatomic features that are most robustly associated with ADHD. The ENIGMA-ADHD consortium has reported modest associations between ADHD and total brain volume, and at the subcortical level, with striatal and amygdala volume reduction . At the ADHD has also been hypothesized to be a disorder of neural dysconnectivity –18. ThisWhile no single cognitive feature characterizes ADHD, small changes have been reported in more general measures of cognition, such as “g” (the first component extracted from a swathe of cognitive tests) or measures such as the intelligence quotient . AdditioP < 5 × 10−8). Summary GWAS data for each the neurocognitive traits and for other psychiatric disorders were obtained from publicly available datasets, as shown in Table We obtained summary GWAS data on ADHD from PGC on participants of European ancestry (the 11 PGC samples and the 23 genotyping batches within iPSYCH) . The metDetails on trait definitions and the origin of the summary GWAS data are given in Supplementary Table We selected neuroanatomic features that have been associated with ADHD through recent mega and meta-analytic studies. This included brain volume, and the closely correlated measures of intracranial volume and head circumference. We also considered the subcortical features most robustly associated by mega-analyses with ADHD, namely the volume of the left amygdala (ADHD related change d = −0.19), right caudate (d = −0.11), and right putamen (d = −0.14) . At a coWhite matter tract microstructural measures of the tight sagittal stratum, splenium of the corpus callosum and left tapetum were chosen based on the voxel wise meta-analysis of fractional anisotropic changes associated with ADHD .N = 34, 691) [For intrinsic functional connectivity, we leveraged a large GWAS of resting state connectivity data  . This stCognitive traits were selected based both on associations with ADHD, and publicly available GWAS summary-level data on underlying SNP associations. These include childhood and adult general intelligence. The childhood study reported GWAS on both the intelligence quotient (IQ) and “g” .We also considered measures derived from the Attention Network Test (which had GWAS data on 1665 youth): namely attention alerting, orienting, executive attention, reaction time and standard error of reaction time. Reaction time was also considered, using GWAS data from the UK BioBank. Finally, we considered measures stemming a GWAS into intra-individual response time variability (IIRTV), as a putative measure that is tied to attentional brain network activity. The GWAS into IIRTV extracted these measures from two tasks, and derived principal components: the first component was taken to reflect response selection, as it loaded on response time in tasks that required participants to select one response from competing choices. The second component was taken to reflect selective attention as it comprised of response time tasks that necessitated participants to choose task-relevant from task-irrelevant stimuli.https://www.med.unc.edu/pgc/).We included seven mental disorders: Schizophrenia, Bipolar Disorder, Major Depression, Anxiety Disorders, ASD, Tourette’s Syndrome and Obsessive Compulsive Disorder. All summery level GWAS data sets for mental health were from PGC . Linkage disequilibrium among SNPs was calculated based on 1000 genomes LD reference panel (European population). We then extracted SNPs associated with each exposure at a genome-wide level of significance (P < 5 × 10–8). Finally, we harmonized exposure and outcome data so that the effect estimates of both exposure and outcome variants were expressed per effect allele increase. Palindromic SNPs, in which the alleles on the forward strand are the same as on the reverse strand  were excluded. For traits that had 3 or fewer IVs at this level of significance level, we relaxed the P-value threshold to P < 1 × 10−5. This relaxed threshold was used for childhood cognitive ability, attention function (reaction time) in children, the component reflecting selective attention derived from intra-individual response time variability measures, anxiety disorders, ASD, and Obsessive Compulsive Disorder. Traits with three or fewer independent SNPs (associated at the P < 1 × 10−5) were excluded for the further analysis. Dropped traits due to the lack of IVs are listed in Supplementary Table P-value threshold and number of IVs for each MR analysis are included in Supplementary Table Prior to extracting genetic instruments for each exposure (trait), linkage disequilibrium (LD) clumping was applied to the summary GWAS data to select independent SNPs (rP < 0.05) is an indication of directional pleiotropy . Secondly, we used pleiotropy residual sum and outlier (MR-PRESSO) test [We conducted bidirectional two-sample MR analyses to test for the causal relationship between risk ADHD and related traits. We used the inverse the variance–weighted (IVW) method  as the pSO) test  to identhttps://shiny.cnsgenomics.com/mRnd/) [We calculated the power of our MR analyses using the online calculator mRnd (m/mRnd/) . The equAll statistical analyses were performed using the TwoSampleMR  and MR-PWe applied two sample bidirectional MR to parse causal relationships between genetic risk for ADHD and 27 ADHD associated traits. Statistical power is given Supplementary Table ßIVW = −0.096; 95% CI: −0.144 to −0.048; FDR-adjusted PIVW = 0.001). . .Bidirectional casual associations were detected between ADHD and intelligence. Firstly, genetic variants associated with ADHD were causally associated with “g”, the measure of adult intelligence (5). Fig.  The relaPIVW = 0.016) and liability to major depression increased the risk of ADHD by ~87% . Liability to ADHD was also associated with an increased risk of ASD . The converse directional link of liability to ASD increasing risk for ADHD emerged only at the threshold of P < 1 × 10−5, (encompassing 50 SNPs), .A bidirectional causal association was also detected between major depression and ADHD: liability to ADHD increased the risk of MDD by ~9%  . No white matter microstructural measures showed possible casual effects.A causal effect also emerged for one of the global resting-state connectivity components and ADHD, namely the component with an anterior dorsolateral prefrontal cortical node that connected to a range of posterior regions in the default mode, central executive and salience networks. Thirty SNPs associated with this connectivity component were causally associated with the risk of ADHD. The IVW results showed that greater expression of this component during rest was associated with a lower risk of ADHD . ADHD was not linked casually to any other anatomic, white matter microstructural and intrinsic functional connectivity.A unidirectional link between liability to ADHD and one neuroanatomic trait: area of the right lateral orbitofrontal cortex. Specifically, ADHD was casually linked to a decrease in the area of the right lateral orbitofrontal cortex .As mentioned above, we also found an unidirectional link between liability to ADHD risk and childhood cognitive ability  intelligence, depression, and autistic spectrum disorder.The most novel findings pertain to the possible causal relationship between neural features and ADHD. We found that decreased expression of a global functional connectivity component, centered on dorsolateral prefrontal cortex and encompassing connections between regions of the executive control, default mode and salience network, had a causal association with increased risk for ADHD. The executive control, default mode and salience network are closely implicated in ADHD and previous work has pointed to cross-sectional associations between ADHD symptoms or diagnosis and abnormal intra- and inter-network connectivity involving these network –26. Whild = 0.1 to d = 0.21), including reduced overall intracranial volume  in children with ADHD relative to controls. Previous work has indicated relationships between reduced total brain volume and genetic risk for ADHD, both as assessed using polygenic risk scores [N = 196), while their unaffected siblings (N = 169) showed total brain and total gray matter volumes that were intermediate to participants with ADHD and control individuals [Structurally, we found that total brain volume had a causal relationship with risk for ADHD, such that smaller brain volumes were positively associated with ADHD risk. Smaller brain volumes, involving smaller gray matter and white matter volumes, have been reported often in pediatric ADHD samples. Specifically, patients with the disorder have been reported to show approximately 1–5% decreases in total cerebral volume, including total white and grey matter volume, compared to matched controls –50. Of nk scores , and in k scores . Specifiividuals . Our finividuals . Importarg, −0.41, −0.36, respectively) [Both epidemiological and genetic studies suggesting that ADHD is associated with cognitive differences, and vice versa. For example, measures of childhood cognitive ability and verbal numeric reasoning show an inverse genetic correlation with ADHD (ctively) . A recenctively) . We furtg = 0.42) [We confirm prior findings of bidirectional causal effects between ADHD and major depression, using the same summary GWAS data, but slightly different clumping methods . It migh = 0.42) , 55. Our = 0.42) .There are limitations to the study. Firstly, we had limited power to detect causal effects for some traits. MR methods depend on the source GWAS samples sizes and heritability of the trait. These factors may have had a particular impact on the GWAS summary data sets for attention, and intra-individual response time variability, as all GWAS were based on modestly sized samples. Many cognitive traits associated with ADHD, such as reward processing, visuospatial working memory and sustained attention performance still lack the publicly available GWAS data needed for MR. Thirdly, despite applying a number of methods to test for pleiotropy and finding limited evidence for any directional pleiotropy, we cannot fully rule out possible bias due to residual horizontal pleiotropy.In conclusion, we provide further evidence for a causal link between cognition and ADHD. We also point to ADHD as a possible driver of observed changes in the lateral orbitofrontal cortex, and to alterations in features of functional connectivity as a possible driver of the disorder.Trait definitions and the origin of the summary GWAS dataP-value threshold and number of IVs for each MR analysisStatistical power for MR analysisTest of Outliers by MR-PRESSOLeave one out AnalysisSensitivity analyses