Lastly, we examined the impact of the prenatal environment by association analysis of maternal pre-pregnancy BMI and offspring ADHD symptoms, adjusted for PRS of both traits, in NFBC1986 dataset. Through MR analyses, we found evidence for bidirectional causality between ADHD liability and obesity-related traits. PRS association analyses showed evidence for genetic overlap between ADHD symptoms and BMI. We found no evidence for a difference between inattention and hyperactivity symptoms, suggesting that neither symptom subtype is driving the association. We found evidence for association between maternal pre-pregnancy BMI and offspring ADHD symptoms after adjusting for both BMI and ADHD PRS . These results are consistent with the hypothesis that the co-occurrence between ADHD and obesity has both genetic and prenatal environmental origins.Attention-deficit/hyperactivity disorder (ADHD) often co-occurs with obesity, however, the potential causality between the traits remains unclear. We examined both genetic and prenatal evidence for causality using Mendelian Randomisation (MR) and polygenic risk scores (PRS). We conducted bi-directional MR on ADHD liability and six obesity-related traits using summary statistics from the largest available meta-analyses of genome-wide association studies. We also examined the shared genetic aetiology between ADHD symptoms (inattention and hyperactivity) and body mass index (BMI) by PRS association analysis using longitudinal data from Northern Finland Birth Cohort 1986 (NFBC1986,  Attention-deficit/hyperactivity disorder (ADHD) often co-occurs with obesity. There has been a surge of studies investigating this association in recent years, despite some variability in findings, the consensus is that the association is well replicated, yet puzzling –4. TogetExposure to maternal obesity at the start of pregnancy was first reported as a risk factor for ADHD symptoms in the child in 2008 . ExperimMR, a method that uses genetic variants as surrogates for the exposure variable, has the benefit of circumventing issues in observational studies relating to confounding or reverse causation . A few sTo address this issue, we investigated the potential causal association between ADHD liability and multiple obesity-related traits in a bidirectional two-sample MR. We undertook various sensitivity analyses relaxing the standard assumptions of MR and used negative control exposure and outcome to validate the specificity of our findings.To further probe genetic mechanisms, we took advantage of genome-wide association studies (GWAS) on both ADHD liability and BMI. These studies have shown considerable polygenicity , 27. TheWe used individual-level and longitudinal data from Northern Finland Birth Cohort 1986 (NFBC1986). The use of this pregnancy-offspring cohort provided us with distinctive advantages—we were able to study the shared genetic aetiology of ADHD and adiposity traits at two ages, eight and 16 years, use mother and teacher reports, and had intergenerational data to test the effect of intrauterine exposure to adiposity on offspring ADHD symptoms. In sum, to clarify the causal association between ADHD and obesity, we performed (1) bidirectional MR on ADHD liability and a variety of obesity-related traits, (2) association analysis of both BMI and ADHD PRS with ADHD symptom subtypes, BMI and WHR, and (3) association analysis of maternal pre-pregnancy BMI and offspring ADHD symptoms while adjusting for the inherited genetic susceptibility to the phenotypes.Summary statistics were obtained from the largest and most recent GWAS available for ADHD liability and six obesity-related traits: BMI, waist circumference (WC), waist-hip-ratio (WHR), BMI-adjusted WHR, body fat percentage (BFP) and basal metabolic rate (BMR). Summary statistics for ADHD liability are based on 55 374 individuals  from 12 cohorts  and UKBiNFBC1986 included all pregnant women with expected date of delivery between July 1985 and June 1986 in the two northernmost provinces of Finland . Women wFollow-ups have been conducted when children were seven, eight and 16 years old. The Ethical Committee of Northern Ostrobothnia Hospital District approved the study. A written informed consent was provided by parents and adolescents at the 16-year follow-up. Supplementary Fig. Mothers and teachers rated children’s inattention and hyperactivity symptoms at seven and eight years, respectively. Parents used the Rutter A scale to evaluate the children’s behaviour , while tWhen adolescents were 16 years old, parents used the Strengths and Weaknesses of ADHD symptoms and normal behaviour (SWAN) scale . SWAN meWe also created three global scores to summarise the data by aggregating ADHD symptom scores  across all raters and ages: global inattention, global hyperactivity, and combined global inattention-hyperactivity symptom scores.During the clinical examination at the 16-year follow-up, trained staff measured height, weight, and hip and WCs, from which BMI and WHR were computed. Maternal BMI was extracted from the pregnancy medical record after delivery as previously described .Adolescents’ blood samples were obtained during the clinical examination at 16 years. A total of 3834 samples were genotyped using Illumina HumanOmniExpressExome-8v1.2 platform and Beadstudio calling algorithm. After excluding individuals with low call rate (<95%), low mean heterozygosity (<0.305), related individuals (identity-by-descent pairwise sharing <0.2), gender mismatch or duplicate samples, genotype data were available for 3743 adolescents. This includes a selected set of 372 individuals exposed to gestational diabetes, gestational hypertensive disorders and preterm birth, and the rest is a random sample. Adjusting for the sampling stratum in the analyses did not affect the results.p < 1 × 10−4), 889,119 SNPs remained in the genotyped dataset. The genetic data were imputed using Haplotype Refererence Consortium (HRC) imputation reference panel. Finally, the imputed dataset was filtered based on imputation quality (excluded SNPs with imputation R2 < 0.5), minor allele frequency  and HWE p-value (excluded if p < 1 × 10−12), and the final genetic data comprised of 11 009 294 SNPs.For quality control of the single nucleotide polymorphisms (SNPs), after exclusions based on call rate (<99%) and Hardy-Weinberg equilibrium  were generated using the genotyped SNPs with MAF > 0.05. Prior to the PC calculation, the data were pruned excluding SNPs with We conducted two-sample MR to investigate the potential causality of ADHD liability on obesity-related traits and vice versa. In MR, genetic variants that are robustly associated with the exposure are used as surrogates for the exposure. These variants are then tested for association with the outcome. Both variant-exposure and variant-outcome associations can be extracted from their corresponding GWAS summary statistics . MR analp-value [p-values while controlling for family-wise error rate [Hypothesis testing for the effect of ADHD on multiple obesity-related outcomes requires an appropriate multiple testing correction. We combined the evidence from the IVW MR results by combining the p-values using the harmonic mean p-value , 40. Thiror rate .The IVW method provides an efficient estimate when all of the following instrumental variable assumptions hold: (i) the genetic variants are associated with the exposure, (ii) the genetic variants are independent of all confounders of the exposure-outcome association, and (iii) the genetic variants are independent of the outcome, given the exposure and all confounders. Violations to these assumptions can distort the MR estimates, resulting in inaccurate causal estimates, loss of statistical power or false-positive results . As a seWeighted median method provides consistent estimates if at least half of the weight for the analysis comes from valid instrumental variables. MR-PRESSO detects outliers (MR-PRESSO outlier test) in the IVW method and provides outlier-corrected IVW estimates by excluding these outliers from the analysis. MR-PRESSO gives consistent estimates when the assumption for weighted median method and the InSIDE (Instrument Strength Independent of Direct Effect) assumption both hold . We alsoFor the MR analyses with ADHD liability as the exposure, we used blonde hair colour as a negative control outcome. This was done to examine the validity of the genetic variants used as instrumental variables for ADHD liability . We woulIn addition, to examine the specificity of our findings, we used autism spectrum disorder (ASD), representing a neurodevelopmental disorder, and rheumatoid arthritis (RA), representing an autoimmune disease, as negative control exposures for MR analysis of the effect of ADHD liability to obesity-related traits. These phenotypes were selected as they are based on GWAS of similar size as for ADHD , 46.p < 1 × 10−8 for BMI as suggested in [p < 5 × 10−8 for other obesity-related traits and ADHD liability) were selected as surrogates for the exposure. The effect estimates of these SNPs were extracted from the GWAS summary statistics of both the exposure and the outcome and aligned to have the same effect allele. The SNPs were clumped [r2 threshold of 0.01. For those SNPs not available in the outcome summary statistics, proxies were sought using an r2 cut-off of 0.8. We tested alternative values for p-value threshold (p < 1 × 10−7 for ADHD liability), clumping window (500 kb), clumping r2  and proxy r2 cut-off (1.0).SNPs that were strongly associated with the exposure  and then calculating the PRS with p-value thresholds of 1 × 10−8, 5 × 10−8, 1 × 10−5, 1 × 10−4, 0.001, 0.01, 0.1, 0.2, 0.3, 0.4, and 0.5 using PRSice software [R2 with the target phenotype was selected as the final PRS for the corresponding trait.We generated PRS for BMI and ADHD. The effect size estimates for each SNP were obtained from the corresponding GWAS summary statistics Table  as the wclumping  the summsoftware . ClinicaWe conducted association analysis using both ADHD and BMI PRS in NFBC1986 to study the shared genetic aetiology between BMI and ADHD symptom subtypes. Multiple outcomes ordinal regression with logit link function was used to estimate the effect of BMI PRS on the different ADHD symptom outcomes. Ordinal regression is a semiparametric regression approach that requires the outcome to be ordinal or continuous. This method has less restrictive assumptions than the ordinary least squares regression and is invariant to the choice of transformation of the outcome . Using aR2 [We studied our previously reported association between maternal pre-pregnancy BMI and offspring ADHD symptoms as reported by teachers , adjusteR2 .p-value = 0.04), WC , WHR  and BMI-adjusted WHR . The point estimates for the other adiposity traits were also positive .Depending on the trait, the number of independent SNPs available for MR with ADHD liability as the exposure was between nine and 12 . For negative control exposure analyses, we did not find evidence for genetically determined ASD or RA being associated with obesity-related traits . Analysing each rater and time point separately yielded similar effect size estimates  and their CIs for increasing number of symptoms per 1-standard-deviation (SD) increase in BMI PRS were identical for both inattention and hyperactivity , thus the precision for ADHD MR and PRS contrasts with the GWAS data for the adiposity traits; our BMI PRS was based on summary statistics of almost 700,000 people. Despite this difference, our negative control analyses showed that the genetic instruments functioned as we aimed. As of writing, no summary statistics from substantially large GWAS are available for inattention and hyperactivity, and thus, sufficiently powered MR analysis or PRS for the separate ADHD symptom sub-types are not yet feasible. Nonetheless, we are first in examining inattention and hyperactivity symptom sub-types, which are the core of ADHD, using different raters and in childhood and adolescence.We had data available on all 18 symptoms of ADHD only at the 16-year report via the SWAN. Consequently, the global ADHD symptom score we used includes impulsivity symptoms at 16 years but not in childhood, thus somewhat limiting conclusions in regard to impulsivity. A recent study also using PRS for ADHD and BMI, based on <900 participants, proposed neural substrates related to impulsivity could be the link between the two conditions, i.e., via unmeasured impulsive eating . HoweverFor the association between maternal pre-pregnancy BMI and offspring ADHD symptoms, we were only able to use the genotype of the offspring for the adjustment. As the offspring genotype is also influenced by father’s genotype, adjusting for the offspring genotype might cause bias in the results due to the fact that father’s genotype may affect offspring ADHD symptoms via other pathways than through offspring PRS only. In addition, information on parents’ ADHD symptoms was not available to use as covariates. While the use of offspring PRS partially captures the genetic effects, parental ADHD symptoms may exacerbate child ADHD via alternative pathways, such as parenting style . A more In the individual participant data analysis using NFBC1986, our approach was to study symptoms of ADHD rather than diagnosis. We do not view this necessarily as a limitation, but rather as a strength. ADHD is the extreme of a continuous trait, which, even at sub-threshold level, is linked to impairments , 35. LikAnother common source of variability is self-reported BMI. However, here we used clinically measured offspring height, weight as well as waist and hip circumferences and maternal BMI abstracted from medical prenatal records, thus increasing the accuracy of measurement. Importantly, we examine the impact of the prenatal environment while adjusting for the genetic risk.Within the bounds of these strengths and limitations, given that our data sources are based on observational studies, the implication of the present work is that there are genetic and prenatal components explaining the ADHD-obesity association repeatedly reported in observational studies. Therefore, these results create opportunities for treatment and prevention. The risk of obesity needs to be considered when treating ADHD symptoms and ADHD screening is advisable for children and adolescents seeking care for obesity, due to the shared genetic liability. It is likely that in humans there is continuity between the obesogenic environment during prenatal development and childhood/adolescence, thus genetic and environmental factors are likely to have an additive effect. In turn, obese adolescents, bearing genetic risk for ADHD, are likely to enter pregnancy overweight/obese thus compounding the risk of ADHD symptoms in their child and contributing to a vicious cycle. Our results reinforce the importance of maternal overweight/obesity prior to pregnancy as a time for the promotion of health not only for an immediate, but for a trans-generational benefit.The link between Attention Deficit Hyperactivity Disorder (ADHD) symptoms and obesity-related traits: Genetic and prenatal explanations Supplementary information


Objective: The objective of the study was to evaluate the relationship between frequency of exposure to general anesthesia before the age of 3 and subsequent risk of diagnosis for attention-deficit hyperactivity disorder (ADHD).Method: We searched PubMed, Embase, Web of Science, and Cochrane Library database for eligible inclusion in the meta-analysis. The indicated outcomes were extracted from the included studies, and the combined effects were calculated using the RevMan software 5.3.Results: Compared with no exposure to general anesthesia, single exposure to general anesthesia did not increase the risk of ADHD for children before the age of 3 , while multiple exposures to general anesthesia did increase the risk of ADHD .Conclusion: Multiple, but not single, exposures to general anesthesia in children before age of 3 increased the risk of ADHD. Attention-deficit hyperactivity disorder (ADHD) is a neuropsychological disorder, which is characterized by hyperactivity, impulsivity, inattention, lack of vigilance, and inability to adapt to the rapid changes . ChildreAnesthesia is a state of unconsciousness and painlessness required for unpleasant invasive therapeutic or diagnostic procedures, and general anesthesia is a common anesthesia method for inhibiting the function of the central nervous system. Exposure to a neurotoxic agent, such as anesthetics, could be one of the environmental factors of ADHD. Currently, many studies have reported a relationship between anesthetic exposure and neurodevelopmental outcomes  in children , 7, whicTo our knowledge, there is no consensus on whether single or multiple exposures to general anesthesia increases subsequent risk of ADHD for young children before the age of 3. Therefore, we performed this meta-analysis to elucidate the effect of single or multiple exposure(s) to general anesthesia on subsequent diagnosis of ADHD for children before the age of 3, and then provide guidance for pediatric practitioners taking care of young children undergoing surgical procedures with general anesthesia at an early age.We conducted the meta-analysis according to MOOSE  guidelines. We have searched the following databases (inception to April 2021): PubMed, Embase, Web of Science, and the Cochrane Register of Controlled Trials. The search strategy was specific for each database by using the following search terms: [ and (including keyword “pediatric” or “child” or “children” or “newborns” or “neonate” or “young”) and (including a MeSH search “attention-deficit/hyperactivity disorder”)]. A manual search was also performed for relevant references from the selected articles and published reviews.Related studies were included on the basis of the following criteria: (1) focused on the relationship between frequency of exposure to procedures requiring general anesthesia for children before the age of 3 and the subsequent risk of ADHD; (2) with sufficient available data to estimate the hazard ratio (HR) with 95% confidence intervals (CI). Only those studies published in the English language were included; we did not define the minimum number of cases in studies to be included for meta-analysis.We obtained data about the general characteristics  and patient characteristics  from studies. Times of exposure to general anesthesia and the risk of ADHD for children was also extracted as a major outcome . All artI2-test (I2 > 50%), the random effects model was applied. On the contrary, the fixed effects model was used when homogeneous outcomes were obtained (I2 < 50%). Results were considered as statistically significant for p < 0.05.We performed statistical analyses with Review Manager . For each study, HR was retrieved to estimate the association between the times of anesthesia exposure and the risk of ADHD. The combined HRs and their 95% CI were considered as the effect sizes for calculating the merged results. Using Cochrane-based I2-test , heterogThe flow diagram of study selection is shown in A total of 26,510 children were included, among which, 3,506 children had experienced single anesthesia, and 1,775 children had experienced multiple exposure to anesthesia due to surgery procedures before the age of 3. Of the four included studies, one was conducted in Olmsted County, Minnesota, USA , two in All articles reported the adjusted HR for the association between the times of exposure to general anesthesia and the risk of ADHD. Data in the study of Hu were adjusted for sex, birth weight, gestational age, mother's education, and socioeconomic status . Data inI2 = 0.0%), a fixed-effects model was used to combine adjusted HRs of single exposure vs. no exposure. As shown in p = 0.11].Because there was no significant heterogeneity (I2 = 81%), a random-effects model was used to combine adjusted HRs of multiple exposures vs. no exposure. As shown in P = 0.05].Because there was significant heterogeneity , Henan Provincial Education Department (No. 19A320021), and National Natural Science Foundation of China (Nos. 81800395 and 81600940).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) is a neuropsychological disorder that causes inattentiveness, hyperactivity, and impulsiveness in patients. Ventral striatal hypo-responsiveness, orbitofrontal cortex, and dopaminergic status in the brain are related to the pathogenesis of ADHD. Reinforcement tasks by monetary incentive delay (MID) was shown to produce more responsiveness in patients. In this study, we reviewed how reinforcement interventions and compensatory mechanisms affect the behavior of ADHD patients. This systematic review was undertaken as per the Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines, and PubMed database was used for literature search.The quality appraisal was completed using the Newcastle-Ottawa scale, and nine case-control studies were included in this systematic review. A total of 976 participants were included, with 493 cases and 330 controls. The studies included discuss reinforcement, attention networks, and compensatory mechanisms. Our review concludes that reinforcement improves responsiveness to gain and loss of rewards in ADHD patients. Reward processing is selectively associated with the salience network. While ADHD, predominantly the inattentive type, is insensitive to stimuli, ADHD combined type and controls showed similar responsiveness. The right visual cortex may also be related to compensatory mechanisms in ADHD. As we only included case-control studies from the last eight years, in the English language, we might have missed some relevant studies related to this research. Because the included studies have a relatively small sample size, we recommend future studies to explore larger cohorts of patients to improve the reliability of findings pertinent to this field. Attention-deficit hyperactivity disorder (ADHD) is a neurological and behavioral disorder that affects not only the person but the entire family, including parents and extended family of parental siblings and grandparents. It tests the limits of the family’s ability to be supportive, understanding, and loving .ADHD is a heterogeneous group of neurodevelopmental disorders, defined and diagnosed with the help of the Diagnostic and Statistical Manual of Mental Disorders (DSM-MD). It is the most prevalent psychiatric disorder in adolescents, affecting 5.29% of adolescent children worldwide and 9.4% of children in the United States -8.The hypothesis underlying the pathogenesis of ADHD revolves around the reward processing areas of the brain, which are the ventral striatum and orbitofrontal cortex (OFC), as well as the hypo-dopaminergic status of an individual. The dysfunctional interaction between these results in disarranged sensitivity toward reinforcement, such as rewards, which can be either decreased or increased in reward centers ,9-11. ThDiscounting is a part of an individual’s nature and causes them to devalue rewards that are either delayed, uncertain, or require more effort. This phenomenon is assumed to be strongly linked to dopamine function . SeveralADHD has three subtypes: ADHD-I, predominantly inattentive type ; ADHD-HI, predominantly hyperactive-impulsive type ; and ADHD-CT, combined type  . ReinforThis review focuses on exploring the mechanisms by which ADHD patients respond to applied reinforcement in the form of monetary incentive tasks across the different subtypes of ADHD, compensatory mechanisms involved, and how attention and execution networks function in ADHD patients that make them perform in a different way than normally developing individuals.MethodsProtocolThis systematic review was conducted and reported in the accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) .Inclusion/Exclusion CriteriaThe literature search was done to identify studies that defined ADHD, reward processing, and reinforcement in adolescent children. The criteria used to search for eligible studies included the following: (1) reinforcement in male adolescents with ADHD, and (2) reward processing in male patients with ADHD. The studies that reported other illnesses and those that included female patients along with male patients or only female patients were excluded as they were outside the scope of the extant study. The case-control studies discussing reward processing and reinforcement in adolescent males with ADHD and subtypes of ADHD were considered for inclusion, while other types of clinical studies were excluded.Search StrategyA methodical search of the database, PubMed , was conData ExtractionAll titles, abstracts, and full-text articles were screened by two reviewers independently, MV and PF. The items extracted from each study included year of publication, sample size, age range, response rate, study design, and study outcome. The studies gathered by one reviewer were also scrutinized by other reviewers for accuracy and eligibility. In case of dissidence, conflicts were resolved by a mutual discussion on the study in question.Bias Evaluation and Data ExplicationThe quality appraisal was done using the Newcastle-Ottawa scale for the included case-control studies. Only moderate-to-high quality studies were included in the final analysis. Table ResultsSearch OutcomeA total of 5,145 papers were identified through field search of the database and controlled vocabulary, that is, MeSH; 488 duplicates were removed using EndNote Basic and 4,657 articles were screened for eligibility regarding inclusion/exclusion criteria, and 730 studies were identified (383 full-text articles) which were screened through title and abstract for compatibility in the ongoing analysis. A total of 21 relevant studies were assessed for quality appraisal and nine moderate-to-high quality case-control studies were included in this systematic review. Figure The nine articles included here were published in peer-reviewed journals from 2012 to 2020 and discussed reinforcement and reward processing in patients with ADHD and the subtypes of ADHD. One article also discussed possible compensatory mechanisms in ADHD patients. The sample size of the studies included was small ranging approximately 14-32 cases, and the sample size was the same for the control group. Only two studies had larger sample sizes of 150 cases and 48 controls in one and 169 cases and 122 controls in another. ADHD was explored in all the articles and patients were diagnosed using the Diagnostic and Statistical Manual of Mental Disorder (DSM-5).A total of 976 participants were included, of which 493 participants were ADHD patients and 330 were controls. The rest of the participants were subthreshold cases and unaffected siblings of the cases from one study. The study findings of the included studies are summarized in Table DiscussionADHD is a disorder of childhood and adolescence, but some symptoms persist through adulthood. Several mechanisms and areas of the brain are speculated to be involved in the development of signs and symptoms of ADHD. In this review, we aimed to bring them to light and improve the understanding of the various aspects of this disorder.Reward Processing NetworksFrom previous studies, we know that reward processing is related to four networks: (1) the default mode network (DMN), (2) the frontoparietal network, (3) the lateral visual network, and (4) the salience network.However, Oldehinkel et al.  showed nvon Rhein et al.  also ideAttention-Deficit Hyperactivity Disorder Subtypes and ControlsADHD patients are divided into three types: (1) ADHD-I, predominantly inattentive; (2) ADHD-HI, predominantly hyperactive-impulsive; and (3) ADHD-CT, combined type.Paloyelis et al.  studied Gong et al.  showed sKappel et al.  demonstrReinforcement and Orbitofrontal CortexUsing the e-MID task, a study by Chronaki et al.  tested tThe electrophysiological brain response showed that the amplitudes were convincingly high in monetary gain than neutral conditions for cases but not for controls during the awaiting and targeting stage of reinforced tasks. This was somewhat true for negative reinforcement as well. This confirmed the sensitivity to anticipatory incentives in ADHD cases, their attention to both, gain and loss, was enhanced and led to better management of motivational task-related stimuli. This study provided no evidence of ADHD-related hyposensitivity to tasks predicting gain or loss. Instead, cases showed a greater neural response in gain conditions. They found that there was greater neural activity in the ventral striatum and ACC in the adolescent with ADHD compared to controls, that is, cases appeared to be hypersensitive rather than hyposensitive to expected rewards.This is in contradiction to another study by Tegelbackers et al.  that conA study by Chevrier et al.  analyzedReinforced learning impacts in the striatum and between neurotransmitter nuclei throughout an expected error are vital in relation to basic and overturned development as the unified function of the system sharply controls how all functional networks work rooted in previous experiences. ADHD cases and controls displayed a highly noticeable pattern of activity and intersubject association on error detection and more median post-error reaction time. Reinforced learning drives basic development, and diverted reinforced learning most likely drives the flourishing of ADHD patient’s brains. Figure Compensatory MechanismsAbramov et al.  studied LimitationsThere are some limitations of this study. The study only includes case-control studies in the English language from the last eight years; hence, we might have missed different types of studies in other languages and those published prior to 2012 related to this analysis. In the studies included, the sample size was relatively small, which could affect the results, limit their reliability, and deter the applicability of the results for the entire population with certainty.DMN and frontoparietal network are complementary in the execution of more natural tasks and salience network is selectively associated with reward processing, while others are unrelated. ADHD patients are more responsive to reinforcement related to monetary gain and loss and are more sensitive to larger rewards than smaller ones. ADHD-CT and typically developed controls were found to have similar responsiveness, while ADHD-I appeared to be insensitive to stimulus. The compensatory system might be located in the right visual cortex that reimburses for lower attention in patients. Future studies should focus more on these compensatory systems and their mechanism of action and how to make them more efficient. This study can help in implementing reinforcement learning in patients as an alternative to medication and the use of rewards for improving symptoms and increasing positive behavior in patients with ADHD.


Ixodes ricinus is the most important vector for arthropod-borne pathogens in Europe. However, its vector competence for Bartonella spp. is still unclear. This study aimed to experimentally compare its vector competence for three Bartonella species: B. henselae, B. grahamii, and B. schoenbuchensis. A total of 1333 ticks (1021 nymphs and 312 adults) were separated into four groups, one for each pathogen and a negative control group. Ticks were fed artificially with bovine blood spiked with the respective Bartonella species. DNA was extracted from selected ticks to verify Bartonella-infection by PCR. DNA of Bartonella spp. was detected in 34% of nymphs and females after feeding. The best engorgement results were obtained by ticks fed with B. henselae-spiked blood (65.3%) and B. schoenbuchensis (61.6%). Significantly more nymphs fed on infected blood (37.3%) molted into adults compared to the control group (11.4%). Bartonella DNA was found in 22% of eggs laid by previously infected females and in 8.6% of adults molted from infected nymphs. The transovarial and transstadial transmission of bartonellae suggest that I. ricinus could be a potential vector for three bacteria.Bartonellae are facultative intracellular alpha-proteobacteria often transmitted by arthropods.  Bartonella species .Bartonella tamiae, which was described as the causative agent for febrile symptoms in patients from Thailand, is the only zoonotic Bartonella species that is thought to be mainly transmitted by ticks  [Bartonella DNA in ticks collected from the field, the vector role of ticks has not been elucidated for many different Bartonella species [Bartonella spp. in ticks are scarce and mainly focused on B. henselae [Bartonella henselae is ubiquitous and the zoonotic causative agent for the cat-scratch disease primarily evoking regional lymphadenopathy in humans [Ctenocephalides felis), this pathogen was also detected in questing ticks collected in nature [B. henselae was detected in ticks collected from cows, dogs, and humans, which was associated with clinical symptoms such as asthenia and headache [B. henselae in I. ricinus was previously experimentally shown, our study included this pathogen as a confirmatory reference group [B. henselae-DNA can be transmitted transstadially from nymphs to adults [B. henselae-positive females laid eggs in which Bartonella DNA was also detected, suggesting that transovarial transmission in I. ricinus may occur. Contrarily, a study by Cotté et al. suggested a lack of transovarial transmission for B. henselae in I. ricinus ticks, but the eggs from only nine females were tested [B. henselae-infected blood were very similar and also similar compared to another study examining nymphs (62.3%) after B. henselae-infection [B. henselae compared to the negative control and B. grahamii-infected blood. Nonetheless the ratio of developed males and females was almost alike compared to B. grahamii and the control group. The engorgement rate and the mean weight of females after feeding were significantly lower compared to females fed on non-infected blood in the current study. Liu et al. showed similar tendencies for I. ricinus comparing engorgement rates and mean weight after feeding on non-infected and B. henselae-infected blood [I. ricinus serine proteinase inhibitor protein associated with B. henselae infection using a transcriptomic approach. Silencing the expression of this protein by RNA interference led to a lighter mean engorgement weight and a lower bacterial load in ticks [is spp.) ,33. Even species ,35,36. Fhenselae ,30,37,38n humans . While bn nature . Moreoveheadache ,42,43. Ace group . In the o adults . Furthere tested . Contaminfection . A recennfection . Lighterin ticks .B. schoenbuchensis, which is usually transmitted by deer keds (Lipoptena cervi) [B. schoenbuchensis may lead to deer ked dermatitis in humans. There is even a report of clinical symptoms in a human with B. schoenbuchensis infection that might be associated to previous tick exposure [B. schoenbuchensis has never been conducted before. Ticks feeding on B. schoenbuchensis-infected blood performed similarly to ticks fed on B. henselae-infected blood concerning the engorgement rate and their detachment weight. The ratio of nymphs developing into females was however higher compared to both of the other Bartonella spp. and the control group. Furthermore, it was remarkable that the rate of oviposition was higher for ticks fed on B. schoenbuchensis-blood (91.7%) compared to B. henselae- (74%) and B. grahamii-infected blood (50%). Further, the prevalence of transstadial transmission (18.2%) was significantly higher in ticks previously fed on B. schoenbuchensis compared to B. grahamii and B. henselae . Epidemiological studies showed also higher prevalence rates for B. schoenbuchensis in I. ricinus ticks compared to other Bartonella species [Domesticated and wild ruminants are known to be reservoirs for a cervi) . Infectiexposure . To the  species ,34.Bartonella grahamii is mostly associated with small mammals such as bank voles (Clethrionomys glareolus) and field voles (Microtus agrestis) being the main reservoirs [B. grahamii can also be transmitted to humans by cat scratches [B. henselae. Ixodes ricinus ticks collected from nature or from small mammals tested positive for this pathogen in earlier investigations [B. grahamii-infected blood performed the worst concerning the engorgement rate and the detachment weight after feeding compared to the other two pathogens. Further, we observed that some ticks fed on B. grahamii-infected blood died during tick feeding. However, the prevalence for B. grahamii in eggs laid by infected females was comparable to rates for B. henselae and B. schoenbuchensis, and in molted adults it was higher than B. henselae and lower than B. schoenbuchensis. A former study showed that the feeding time or engorgement status of I. ricinus is not influenced by the species of the blood donor [B. henselae and B. schoenbuchensis, B. grahamii has never been naturally detected in bovine blood [B. grahamii to bovine blood may be a reason for the differing results concerning tick development in comparison to both other Bartonella spp. Moreover, all selected Bartonella spp. in this study have a different combination of pathogenicity factors, which may also be a reason for differing results in ticks [B. henselae and B. grahamii belong phylogenetically to the same clade (lineage 4), B. schoenbuchensis is more distinct (lineage 2) in regard to phylogeny, main vectors, and reservoir hosts [Bartonella spp. [Bartonella species.servoirs . Fleas acratches  causing igations ,48. In tod donor . Unlike ne blood ,49. The in ticks . Howeverir hosts . A previlla spp. . Yet, a Bartonella spp. from infected I. ricinus failed due to a fast proliferation of accompanying flora on the agar plates. This is why the described transovarial and transstadial transmission in ticks can only be reliably described for Bartonella-DNA and not necessarily for the viable bacteria. Nonetheless, the current study points out that I. ricinus should be regarded as a potential vector for the examined Bartonella species.The recultivation of Bartonella spp. in blood and ticks.Future studies by our group will focus on the bacterial transmission to mammal models to identify the onset of symptoms/disease and to verify the viability of the detected B. grahamii, B. henselae, and B. schoenbuchensis may occur in I. ricinus ticks. Even though transstadial and transovarial prevalence rates were low to moderate (1.3–26.1%) these results suggest that I. ricinus is a possible vector for these Bartonella species. The success of tick engorgement, development, and Bartonella prevalence in I. ricinus might depend on the respective Bartonella sp. Further research is needed to unveil the mechanisms leading to the described differing results.Our study showed that transstadial and transovarial transmission for


Background: The neuropsychological features of older adults with ADHD are largely unknown. This retrospective chart review aims to elucidate their cognitive trajectories using a case series of six older adults with ADHD presenting with memory complaints to a cognitive neurology clinic, whom we argue are a particularly relevant group to study due to their potential to mimic neurodegenerative syndromes.Methods: Participants were included if they were age 40 or older at intake, had ADHD based on DSM-5 criteria, and had cognitive data collected prior to 2014 with follow-up at least 5 years later.Results: Five men and one woman were included (M = 53.8 years at intake) and had an average of 135.0 months of follow-up data available. Despite notable between- and within-subject variability, cognition generally improved or remained stable across visits. Two participants experienced notable memory decline, but a global consideration of their performance in other domains suggests these deficits may be frontally-mediated.Conclusion: In this small sample, cognition remained generally unchanged across 5–21 years. Isolated impairments likely reflect substantial intra-individual variability across time and measures. Attention-deficit/hyperactivity disorder (ADHD) is conceptualized as a childhood disorder, but what happens to these children as they grow up, and grow old? Although ADHD is now known to persist into later life in 40–60% of cases , it is rThe cognitive features of younger adults with clinical ADHD  have been comprehensively documented. Meta-analytic and review studies generally find mild to moderate impairments spanning a broad range of cognitive domains, including attention , workingThis lack of evidence has detrimental outcomes for patients and society. Most clinicians admit being uneasy diagnosing ADHD in older patients , potentiThe objective of this study is to expand upon this limited previous literature by characterizing the cognitive profile of later-life ADHD over a longer longitudinal period (up to 21 years) in a retrospective case series of six older adults followed in an academic cognitive neurology clinic. Case studies and case series are well-established research designs that, similar to grand rounds used routinely in medical settings, allow for consideration of multiple facets of a complex phenomenon in a naturalistic context by providing a very detailed report on a small number of selected patients . AlthougWe recognize that older adults presenting to a cognitive neurology clinic are not likely representative of the broader ADHD community. We argue that these are a particularly relevant group to study, because they comprise a group whose clinical presentation is difficult to distinguish from prodromal dementia . CharacWe also acknowledge that a retrospective design biases the sample toward the inclusion of persistent ADHD cases whose cognitive performance is relatively stable . However, we propose these cases are ideal to study because they arguably represent a relatively “pure” ADHD group, with low likelihood of comorbid neurodegenerative pathology, and in this sense will provide compelling evidence for the expected cognitive trajectories associated with ADHD in later life, in the absence of comorbid pathology.Participants for this study were identified through a chart review of patients followed at the Cognitive Neurology Clinic at Sunnybrook Health Sciences Centre in Toronto, Canada. An experienced clinician (SEB) identified individuals suspected of having ADHD based on clinical history and when available, collateral information collected by a knowledgeable third party, usually a spouse. They were considered for potential enrollment in this study if they were at least 40 years old at the time of their first visit, had undergone neuropsychological assessment (described below) prior to 2014 and again at least 5 years later, and were free from neurological injury (including stroke) or significant white matter disease on clinical neuroimaging.Individuals who met the above criteria were invited to partake in the present study and agreed to grant access to all previous cognitive assessments for this purpose. All procedures were approved by the Sunnybrook Institutional Review Board (#238-2013). A trained research assistant (RT) administered the ADHD module of the Structured Clinical Interview for DSM-5 SCID-5;  to all pOf 19 participants initially identified as potentially eligible, 10 were excluded because they did not fulfill current inattentive or hyperactive/impulsive symptom criteria for ADHD upon completing the SCID-5. An additional three participants were excluded because we could not confidently ascertain an early-life onset of their ADHD symptoms. The remaining six participants endorsed at least five inattentive and/or hyperactive symptoms that had been longstanding since early life, and they were included in this retrospective chart review. Four of the six also had obstructive sleep apnea (treated in three), and two had comorbid restless legs syndrome.Participants were asked about the presence and severity of ADHD symptoms in childhood using the Barkley Adult ADHD Rating Scale-IV (BAARS-IV) Self-Report Childhood Symptoms Scale , which qCurrent ADHD symptom severity was assessed using the Adult ADHD Self-Report Scale (ASRS-v1.1)  and the All participants had completed a comprehensive neuropsychological assessment prior to 2014 through the Cognitive Neurology Clinics at Sunnybrook, and had at least one follow-up visit ≥ 5 years later. Cognitive data were extracted from participants’ clinic charts and compiled into a single data file.As this study constitutes a retrospective chart review, the cognitive data available in the charts was acquired in clinical visits and sometimes differed from person to person. Across the different visits, cognition was assessed using some or all of the following tasks. The California Verbal Learning Test (CVLT) served to evaluate short- and long-term free and cued memory and recognition of a word list. Immediate and delayed recall of a short story were assessed using the Logical Memory Story A. The Rey-Osterrieth Complex Figure Task assessed visuoconstruction abilities  as well as short- and long-term free recall of a complex figure . Verbal fluency evaluated individuals’ ability to retrieve specific information based on a criterion, and provided measures of selective attention and inhibition, mental set shifting and self-monitoring. Both phonemic and semantic fluency were assessed by asking the participants to name words beginning with the letters F, A, and S, or different animals, in 1 min. The Boston Naming Test, in which participants are asked to name a series of line drawings, assessed semantic retrieval capacities. The Wisconsin Card Sorting Test (WCST), in which subjects must match stimulus cards to reference cards based on “correct” or “incorrect” feedback provided after each trial, measured strategic planning, the ability to implement feedback to shift cognitive sets, controlling impulsive responding and problem solving. The Trail Making Test requires participants to quickly connect sequential numbers (part A) or alternating letters and numbers (part B), and provided measures of speeded attention and task switching, respectively. Digit span forward and backward assessed simple attention and working memory, respectively. Depressive symptoms were assessed at each clinic visit using the Beck Depression Inventory II BDI-II:  or the GZ = 0 provides a benchmark for expected performance in healthy older adults (with an associated standard deviation of 1) and can be used to interpret performance in the absence of a healthy control group. Our prior work has established that this method of evaluating cognitive performance using published normative data produces essentially the same results as standardizing raw scores using a demographically-similar locally-recruited healthy control sample  or standardized regression based formulas (SRBs) ], these SD = 4.9). The sample had between 12 and 20 years of formal education  and between 56 and 252 months of available follow-up data . Participants 4, 3, and 2 were trialed on methylphenidate one, 8 and 9 years after their initial evaluations, respectively. Five of the six participants were taking antidepressant medications.A detailed description of the sample is presented in M = 18.0, SD = 4.1), and the mean CAARS ADHD Index was 62.7 . On the BAARS, participants’ self-reported childhood symptoms were above average, ranging from the 76th to the 99th percentile .On self-reported ADHD scales, participants’ scores ranged from 12 to 24 on the ASRS Part A  was born.” He had held various trade jobs in the past but was on disability when he first presented to the clinic. His self-reported behavior as a child fell within the 96th and 99th percentiles on the BAARS inattentive and hyperactive/impulsive subscales, respectively . He met Participant 3, a 48-year-old Caucasian man with 20 years of education followed for 7 years, recalled first noticing his ADHD symptoms in early adulthood. Whereas he had “been bored” throughout high school, he apparently began experiencing significantly more organizational difficulties in university. He was employed in a professional job. His self-reported behavior as a child (prior to age 12) fell within the 96th percentiles on both the BAARS inattentive and hyperactive/impulsive subscales , and he Participant 4 was a 61-year-old Caucasian man with 20 years of education followed for 5 years. He first sought help for symptoms of inattention around age 45, but reported that his issues with attention and memory “go way back, from early on,” that he had always avoided tasks or activities that required extended periods of sustained attention , and that he was often in trouble in elementary school. He was formerly employed in a professional job and subsequently transitioned to a management position. On the BAARS, his self-reported difficulties with inattention in childhood fell within the 97th percentile . He met Participant 5, a 57-year-old Caucasian man with 12 years of education followed for 12 years and employed in a trade job, first sought help for distractibility and difficulty focusing in his mid-forties. When asked about his childhood, he described difficulties socializing and being “the biggest troublemaker in the class.” He obtained such poor academic performance that he was held back a grade in high school. His self-reported behavior as a child fell within the 90th percentile on the BAARS inattentive subscale , and he Participant 6, a 54-year-old Caucasian man with 19 years of education followed for 21 years, reported lifelong issues with fidgeting, trouble concentrating and remembering things, and distractibility. He had held technical and intermediate jobs but retired during his the course of his follow-up at clinic. He was reportedly a very poor student who disliked school greatly. He emphasized that his son had also been extremely inattentive and hyperactive as a child. The participant’s self-reported childhood behavior fell within the 98th and 99th percentiles on the BAARS inattentive and hyperactive/impulsive subscales, respectively . He met This study is the first to describe cognitive trajectories across 5 to 21 years in a sample of older adults with ADHD presenting with cognitive complaints to a cognitive neurology clinic. Results from this small retrospective case series tentatively point toward three main findings: (1) significant within-subject variability, (2) significant between-subject variability, and (3) relatively stable cognitive trajectories overall. These findings will be discussed in detail presently.visit, some participants evidenced performance differences upward of 3 SD on different tests (even within a single cognitive domain), suggesting inconsistent cognitive processing efficiency. Response variability and inconsistent responding are well-documented features of ADHD in both children and adults , notable variability was observed between individual participants in this small sample. There was often a difference upward of 3 SD between the highest- and lowest-performing participants on any given measure, and these patterns varied from test to test. Like the within-subject variability described above, between-subject variability is a recognized feature of ADHD that has been described extensively . In esseWe are not aware of any prior work that has explicitly aimed to characterize cognitive heterogeneity in later-life ADHD. Individual scores of participants in the case study by improvement on other memory measures in both participants over the course of follow-up  suggests this is unlikely. Participant 2 exhibited additional persistent Alzheimer-like cognitive deficits  experienced 1.5 SD declines or more on several memory measures over periods of 12 and 11 years, respectively. It is possible that these memory declines reflect very early signs of Alzheimer’s disease, as verbal memory is among the first affected cognitive domains in this disease . HoweverOur sample was very small and heterogeneous . Part of the reason for this heterogeneity is that ADHD in older adults has only been recently recognized e.g.,  and thervia a Cognitive Neurology Clinic implies that participants were not likely representative of the broader ADHD community. This is reflected in the sample’s high educational and occupational attainment, which is atypical of adult ADHD  symptoms of ADHD, and did not include adults with earlier-life ADHD whose symptoms had resolved (“remitted”). This implies that the cognitive trajectories observed in our sample may reflect those of relatively more severe cases of ADHD, and extending this work to remitted cohorts will be important to clarify the effects of aging on ADHD more fulsomely. Here, we did not include remitted cases to avoid further heterogeneity in the sample, and because the population of interest consisted of older adults currently experiencing symptoms of ADHD. Previous research comparing persistent vs. remittent ADHD in younger adults indicates that cognitive performance is relatively independent of ADHD symptom course . This teThe 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 Sunnybrook Institutional Review Board (#238-2013). The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.BLC conceptualized the research idea, analyzed and interpreted the data, drafted the manuscript, and approved the final version for submission. PS collected and interpreted the data, contributed to the manuscript draft, and approved the final version for submission. RT and NR compiled the data, contributed to the manuscript draft, and approved the final version for submission. SB interpreted the data, contributed to the manuscript draft, and approved the final version for submission. 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.


In addition, Verrucomicrobiota was higher in the control group than the FAPDs (p < 0.05). At the genus level the relative abundance of 72 bacterial taxa showed statistically significant differences between the two groups and at the school term levels. In the control group, Shannon diversity, Observed_species, and Simpson were higher than the FAPDs (p < 0.05), and beta diversity showed differences between the two groups  as well. Using linear discriminant analysis effect size (LEfSe), Enterobacteriaceae family and Megaspherae showed increased abundances in vacation term . In the FAPDs group, the severity of symptoms (T-scores) correlated with 11 different taxa bacterial relative abundances using Pearson′s correlation and linear regression analyses. Our data showed that gut microbiome is altered in FAPDs compared to the control. Differences in other metrics such as alpha- and beta diversity were also reported between the two groups. Correlation of the severity of the disease (T-scores) correlated with gut microbiome. Finally, our findings support the use of Faecalibacterium/Bacteroides ratio as a potential diagnostic biomarker for FAPDs.In this prospective longitudinal study, we enrolled 54 healthy pediatric controls and 28 functional abdominal pain disorders (FAPDs) pediatric patients (mean age was 11 ± 2.58 years old). Fecal samples and symptom questionnaires were obtained from all participants over the course of the year. Clinical data assessment showed that FAPDs patients were more symptomatic than the control group. Microbiome analysis revealed that Phylum Bacteroidetes was higher in FAPDs compared to the control group ( Approximately 32% of schoolchildren experience weekly abdominal pain with 20% of them reporting functional disability including school absenteeism, and limitation with social and physical activities . In 1958Faecalibacterium and Dorea showed altered abundances in the gut of IBS patients [Bacteroides may be involved in the development of disease [Despite the high prevalence and impact of FAPDs in children, their etiology and pathogenesis remain poorly understood. In search of risk factors that could worsen or trigger these disorders, investigators have found that in children, abdominal pain was more common and severe during winter months, and this seasonal pattern is not found in adults ,6,7,8. Mpatients . Similar disease . Microbi disease .We conducted a study to characterize the microbiota and their changes in children with and without FAPDs throughout the year in a subtropical region devoid of four seasons. We hypothesized that the microbiota composition of children with and without FAPDs will differ, and there will be variations in microbiota when comparing school term versus vacation.This study was a prospective longitudinal study of children ages between 7 and 16 years of age with and without FAPDs. Cases (FAPDs patients) were recruited at a large pediatric gastroenterology clinic in Central Florida , while the controls (no FAPDs) were enrolled from five local pediatric practices. Enrollment was conducted by clinic staff. Participants were consented via child and/or parental consent. Research forms were managed using REDCap electronic data capture tools hosted at Florida State University  . The proAn experienced gastroenterologist from Orlando Health performed Rome IV classification. The Rome IV Diagnostic Questionnaire on Pediatric Functional Gastrointestinal Disorders (for parents and children) was used to ensure FAPD patients satisfied Rome IV criteria for inclusion . Patient® Stress Score. The PROMIS® is standardized to generate T-scores [Throughout the year, FAPD patient′s clinical data, use of antibiotics or probiotics as well as stress data was collected through well-defined and validated stress and symptoms scales. Initial clinical assessments were completed at enrollment and additional data were submitted to the investigators via US mail. The stress score was evaluated using PROMIST-scores . The symPatients and caregivers were instructed to collect three stool samples at home and send them via US mail. Every FAPDs patient and healthy control gave three stool samples throughout the year. The hemoccult ICT collection kit was used to collect all 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 . Stool sFor analyses, data was grouped into academic terms as school term (August–May) and vacation term (June–August). Changes in sample size are related to missing data issues  or from the decisions on data management as described above.I) Clinical outcomes. Patient characteristics are reported as mean ± SD or count (%). The independent sample t-test, and the Fisher′s exact test were used to test group equivalence on baseline characteristics. Symptoms were grouped into two groups: symptomatic (1–10) and asymptomatic (0) and reported as frequency with percentages. Fisher′s exact test was used to assess the association of symptoms and study group (FAPDs and controls). Among FAPDs patients, gut symptom intensity by academic term (school vs. vacation) was assessed with the Friedman′s test and the Wilcoxon signed-rank test, respectively. Tests were two-tailed and α = 0.05 was used for statistical significance. IBM SPSS Statistics for Windows v. 26.0 was used for univariate analyses. Psychological stress was collected only for the FAPDs group using validated assessment forms. The Patient-Reported Outcomes Measurement Information System PROMISR was used for self-assessment (if the child was >7 years old) or the parent form (if the child age was <7 years old). The raw scores were transformed into T-scores where the increase of T-scores means increase of disease severity. A score of 50 represents the average psychological stress level for normal children [(children .(II) Bacterial relative abundance. Multivariate analysis by linear models (MaASLin) was used to assess differences in relative abundance of bacterial phyla between groups (FAPDs vs. controls), and for academic year (school vs. vacation). GraphPad Prism V.8 was also used for the analyses; two-tailed, and a p < 0.05 was used for statistical significance. Associations of specific bacterial taxa with other variables such as school or vacation terms were assessed using the linear discriminant analysis effect size (LEfSe). (MaAsLin) and LEfSe statistical pipelines from Huttenhower lab Galaxy  were used in the analysis of the data.(III) Correlation of the severity of the disease with the relative abundances of bacteria in FAPDs patients. IBM SPSS Statistics for Windows v. 26.0 was used to conduct Pearson correlation of the T-scores with the relative abundances of bacteria taxa in FAPDs patients. Linear regression was then used to measure the correlation between the identified taxa. Only FAPDs patients with a T-score were included in this analysis. Any patient with a missing T-score was excluded when conducting Pearson′s correlation. Outliers for each bacterial taxa were identified in SPSS by using a boxplot. Values denoted by the * symbol are called extreme values within SPSS and were removed for each bacterial taxa before conducting the correlation. Additionally, bacterial taxa that had zeroes for more than 70% of the patients were also excluded when conducting the Pearson′s correlation. The receiver operating characteristics curve (ROC) was performed using SPSS as well.Total genomic DNA was extracted from the collected stool samples using QIAGEN kits . The DNA was analyzed for purity and integrity using Agilent Bioanalyzer , and quantified by labeling and detection kits . DNA was used to amplify the V3–V4 region of the bacterial 16S rRNA gene. Microbiome analysis was performed by the UW biotechnology center using Quantitative Insights Into Microbial Ecology (QIIME2) version 2 . Illuminn = 54, and FAPDs n = 28). Overall, mean age was 11 ± 2.58 years old. Just over half of the children were female  and non-Hispanic . The groups were similar in age (p = 0.287), sex (p = 0.64), and race/ethnicity (p = 0.400). During enrollment, there were no statistically significant differences in antibiotic course among FAPDs and control groups (p = 0.086). More specifically, 53 (65%) children had not taken antibiotics in the past year. Among the 28 (35%) children that had taken antibiotics over the past year, 57% (16 patients) had received one course and 43% (12 patients) had received two or more courses. FAPD children were significantly more likely to be on probiotics  and among children taking probiotics (6 participants (7%) reported taking daily dosages). During the duration of the study, FAPDs patients reported significantly higher symptom intensity than healthy controls  n = 1, functional nausea n = 1, functional vomiting n = 1, and cyclic vomiting syndrome n = 1. No patient belonged to non-retentive fecal incontinence or Aerophagia groups. In addition, the 13 patients with functional dyspepsia were classified as either post-prandial distress syndrome n = 10 (77%) or epigastric pain syndrome n = 3 (33%).Eighty-two patients were included in the analyses (controls controls . Brieflyp < 0.05), Firmicutes were higher in the FAPDs group than the control group (p < 0.05). Similarly, Verrucomicrobiota were higher in the control group compared to the FAPDs group (p < 0.05). On the other hand, the Actinobacteria and Proteobacteria did not show statistically significant differences between the two groups .In total, 213 stool samples were sequenced including 142 control samples and 71 FAPDs. A total of 4,156,326 sequences were generated and 7214 ASVs were identified in our analysis. MaASLin analysis revealed differences between the two groups at the phyla levels . BrieflyBacteroides relative abundances were affected in FAPDs and in school vacation. With the exception of Bacteroides, Eubacterium, Candidatus-stoquefishus, Clostridium-innocuum group, Anaerofustis, Eisenbergiella, Acetanaerobacterium, and Eggerthella all the remaining 30 species were depleted in the FAPDs group compared to the control group . Faecalibacterium species and Ruminococcus species were depleted in the FAPDs group compared to the controls (p < 0.001). Other bacterial taxa such as Sutterella, Akkermansia, Dialister, and Veillonella were depleted from the FAPDs groups (p < 0.05) as well. Bacteroides and Holdemania were depleted in the vacation term compared to the school term, while the other 32 were enriched in the vacation term. All the identified taxa are included in the file   .p < 0.05). Beta diversity analysis using Bray–Curtis dissimilarity index confirmed the structure differences of fecal microbiota between the FAPDs and the control groups  = 2.38; p = 0.002)  .p < 0.05). Two bacterial taxa were found to be positively correlating with the T-score, while the remaining nine taxa were found to be negatively correlating with the T-score. Blautia and Colidexbacter correlated positively with the T-scores. We conducted linear regression to measure the correlation , the mean was 0.20 (±0.12), while the mean for the FAPDs group (n = 63) was 0.13 (±0.10). We conducted ROC analysis and the area under the curve (AUC) was 0.712. When we performed the analysis for the school term to exclude vacation impact, the AUC increased to 0.797. The ROC data for both analyses are in the Post hoc analysis was performed based on observations of the inverse relationship between p < 0.001).FAPDs are a heterogenous group that includes IBS, functional dyspepsia, abdominal migraine, and functional abdominal pain—not otherwise specified. Previously, in a retrospective cohort study collected from six US tertiary care institutions, the rates of abdominal pain consultations were consistently higher in winter in all the six locations ,7. This p < 0.05), while the Firmicutes were higher in the control group . Our findings are consistent with some broader trends reported in a metanalysis of IBS in adults, suggesting that the abundance of Firmicutes is beneficial and Bacteriodetes can be detrimental [Enterobacteriaceae, and Megaspherae showed school and vacation term variations . This finding implies a minor role of school stress in microbiome alterations on the FAPDs patients. Our study controlled for the recent antibiotics consumption as an exclusion criteria from the study, but other factors such as diet and pre- and probiotics consumption were not controlled due to the nature of recruitment of pediatric population. These factors represent a limitation of our study. Unpublished data suggested a minor role of the probiotics consumption on the FAPDs gut microbiome in our study (data not shown).At the microbiome level, our findings confirmed that the two groups (control and FAPDs) exhibited differences at the phyla and genus levels, as well as α-diversity and β-diversity. Approximately, 12% of the identified bacterial taxa  showed significant differences between the two groups which is a clear indication of microbiome signature differences between FAPDs and the healthy controls. Bacteroidetes and Firmicutes were significantly different between groups: Bacteroidetes was lower in the control group compared to the FAPDs  (butyrate and acetate) as well as lactic acid production [Faecalibacterium, Clostridium, and Roseburia are the main producers of butyrate, and they belong to the phylum Firmicutes, thought to be protective. Veillonella and Akkermansia (Verrucomicrobia) both produce propionic and acetic acids. Higher levels of organic acid producing flora, and especially acetic and propionic acid, were found to be associated with IBS with Veillonella and Lactobacillus specifically implicated [Interestingly, oduction . Faecaliplicated . The relplicated ,31,32. Tplicated .Faecalibacterium/Bacteroides ratio alterations in the FAPDs group compared to the control group. Previous data of gut microbial dysbiosis focused on the ratio of Bacteroidetes and Firmicutes as a potential IBS biomarker [Faecalibacterium/Bacteroides ratio at the genus level.Our post hoc analysis showed iomarker ,35, but Our findings revealed the gut microbiome differences at the phylum and genus levels between FAPDs pediatric patients and healthy controls. The F/B ratio suggests the potential use for FAPDs diagnosis. If confirmed in a larger study, this finding could be used as a future biomarker for FAPDs, disease progression, and intervention evaluation. The analysis of fecal metabolites and functional genomics will allow deeper insights into other cellular and molecular pathways for FAPDs diagnosis. To the best of our knowledge, our study is the first to report significant variation in FAPDs microbiome. Though limited by the sample size, our findings support larger studies assessing factors affecting microbiome changes the role of school in FAPDs.