Attention deficit hyperactivity disorder [ADHD] is one of the most common psychiatric disorders of childhood with poor prognosis if not treated effectively. Recommended psychosocial evidence-based treatment for preschool and school-aged children is behavioral parent and teacher training [BPT]. The core elements of BPT are instrumental learning principles, i.e., reinforcement of adaptive and the ignoring or punishment of non-adaptive behaviors together with stimulus control techniques. BPT is moderately effective in reducing oppositional behavior and improving parenting practices; however, it does not reduce blinded ratings of ADHD symptoms. Also after training effects dissipate. This practitioner review proposes steps that can be taken to improve BPT outcomes for ADHD, based on purported causal processes underlying ADHD. The focus is on altered motivational processes (reward and punishment sensitivity), as they closely link to the instrumental processes used in BPT. Following a critical analysis of current behavioral treatments for ADHD, we selectively review motivational reinforcement-based theories of ADHD, including the empirical evidence for the behavioral predictions arising from these theories. This includes consideration of children’s emotional reactions to expected and unexpected outcomes. Next we translate this evidence into potential ADHD-specific adjustments designed to enhance the immediate and long-term effectiveness of BPT programs in addressing the needs of children with ADHD. This includes the use of remediation strategies for proposed deficits in learning not commonly used in BPT programs and cautions regarding the use of punishment. Finally, we address how these recommendations can be effectively transferred to clinical practice. Attention deficit/hyperactivity disorder [ADHD]  and to increase the discriminative value of the stimuli predicting adaptive behavior (antecedent or stimulus control techniques) , cognition, timing, and emotional lability proposed as distinct but partly overlapping pathways toward the behaviors that define ADHD  is potentially relevant not only for how non-adaptive behavior can be extinguished  but also potentially for how to improve long-term effectiveness of behavioral treatment for ADHD. Behavioral treatment for ADHD is largely based on teaching adaptive behavior through, as much as possible, continuously rewarding such behavior; however, in daily life such high rates of reinforcement cannot be maintained. Some behavioral treatment programs explicitly include fading procedures following initial high frequencies of reinforcement, others don’t  learning theory and behavior management principles (see next paragraph). The primary aim of psycho-education for ADHD is to increase parents’ knowledge about the nature of ADHD, it’s possible causes, and the potential treatment options  is intertwined with the expression of problem behavior and it’s management by behavioral treatment. In classical conditioning an originally neutral stimulus becomes a predictor of another event, sometimes developing an emotional connotation. For example, the instruction of a teacher to start math can, due to previous negative reactions of the teacher to the child during the math class, become a conditioned stimulus that triggers feelings of worthlessness  and subsequent behavioral problems  in an attempt to escape such feelings/situations. This clowning can then be reinforced by its consequences . In designing specific  interventions for a child, these Pavlovian learning processes are important. At the same time parents and teachers implementing behavioral treatment have their own learning histories that shape their willingness to use techniques recommended by behavior therapists. Without addressing their attitudes toward specific techniques a parent or a teacher will not be able to convincingly implement instrumental interventions for a child. Thus the basis for effective behavior therapy is comprehensively assessing or addressing the instrumental and classical components of the child’s problem behavior and the learning history of parents/teachers. Individual case conceptualizations and functional analysis take into account these processes and are the basis for effective BPT training of non-adaptive behavior and behavioral persistence of learned adaptive behavior), but none, with the exception of Amsel, make predictions about responses to positive punishment  in ADHD. Together these theories and their predictions may have implications for the techniques used in PBT with children with ADHD. These theories and their predictions are briefly reviewed below, with the predictions and the strength of the empirical evidence for them summarized in Table The DTD hypothesis . As a result, when behavioral reinforcement is delayed or discontinuous dopamine signaling is also delayed or discontinuous resulting in ineffective reinforcement at the cellular level. Such impaired anticipatory dopamine firing is believed to negatively impact learning from reward and to disrupt control of behavior by its consequences in children with ADHD. The following predictions are made by the DTD. Children with ADHD are expected to demonstrate:Prefer immediate over delayed rewardsLearn more efficiently when rewards are immediate and frequentShow more variable responding, with only short sequences of behavior reinforcedDemonstrate slower extinction Demonstrate slower establishment of conditioned reinforcers .Dopamine neurons normally fire at low tonic rates, showing phasic burst activity following a reward. The DDT . This has been demonstrated in choice delay tasks and temporal discounting tasks where children with ADHD are more likely to select small immediate over larger delayed rewards  . In their 2005 review, Luman and colleagues concluded there is some evidence for impaired performance in children with ADHD during intermittent compared with continuous reward delivery ; however, none specifically report slower extinction (as predicted by DDT). While Sagvolden et al.  report hThe Partial Reinforcement Extinction Effect [PREE] is the phenomenon in which behavior acquired under conditions of partial reinforcement  is more persistent under extinction than behavior acquired under continuous reinforcement (hypothesis 5 DTD). Only one study has explicitly tested the PREE in ADHD . Several fMRI studies demonstrate reduced BOLD activity in the ventral striatum during reward anticipation  in those with ADHD compared with TD individuals . Using a signal detection task, Tripp and Alsop  found thRegarding the DDT prediction  that those with ADHD show more variable responding, there is consistent evidence that the responses of children with ADHD show increased variability compared to those of typically developing children across a range of tasks  . We identified only two papers that provide evidence of increased frustration in children with ADHD when anticipated rewards fail to appear; assessed by facial responsivity  have a reduced tendency to persist in the face of non-reward Hyperactivity in ADHD is due to increased responsiveness to stimulation from anticipatory frustration in partial reinforcement conditions.According to Amsel’s frustration theory Amsel , 1992b, As noted earlier only two papers describe evidence for a heightened frustrative response in children with ADHD during intermittent reinforcement  and DDT (no evidence for slower extinction). The delay aversion hypothesis makes fewer predictions than either DTD or DDT and support for all but one of its predictions is strong to very strong. The exception being that children with ADHD show a negative emotional reaction to delay, behavioral evidence for this prediction is to date limited. Douglas and Amsel’s theories both focus on the emotional impact of reward and non-reward. There is very strong evidence for Douglas’s proposal that children with ADHD have an abnormally strong inclination to seek immediate reward. The evidence for her predictions that children with ADHD are more vulnerable to the distracting effects of reward and to increased frustration in face of non-reward is limited. Similarly, there is limited evidence for Amsel’s predictions of increased frustration and reduced behavioral persistence during intermittent reinforcement. To date Amsel’s hypothesized causal link between frustration and hyperactivity has not been tested. In sum, currently the strength of evidence favors the delay aversion hypothesis, in part reflecting the many studies that have tested its predictions as opposed to fewer studies testing the specific predictions of the other theories. However, to varying degrees, the other theories offer explanations for the occurrence of delay aversion in children with ADHD. More research is clearly needed to evaluate the predictions of these other theories. Recognition of their importance to the ongoing development of BPT may encourage this research.The research reviewed indicates there is Compared to reward, the behavioral sensitivity of children with ADHD to punishment has received limited theoretical and empirical attention. Only Amsel  makes a enhance the performance of children with ADHD across a range cognitive tasksExperimentally, mild punishment, operationalized in these studies as negative punishment (response cost), has been shown to n = 8 “hyperactive” boys) showed that negative punishment (in this case ignoring) was ineffective in reducing off-task behavior, leading the authors to conclude that behaviors not driven by attention should not be managed by ignoring  may increase on-task behavior and reduce undesirable behaviors effectively in the short-term. However, its long-term use and/or the use of positive punishment may have unanticipated and unwanted side-effects in children with ADHD when used to manage or shape their behavior. They may focus more on avoiding punishment, it may lead to reduced accuracy, or decrease their engagement in desirable behavior that would lead to better outcomes. Amsel’s hypothesis that punishment led to reduced persistence in children with ADHD was supported by two studies showing a lack of behavioral persistence on the response alternative associated with the higher rate of punishment  . These treatment recommendations are theoretically and logically derived and informed by clinical practice. Some of these recommendations may already be in use by experienced clinicians in their work with parents and teachers managing ADHD. Other recommendations may be new to clinicians, parents and teachers . Additionally, in Table There is accumulating evidence that children with ADHD differ from typically developing children in their processing of motivationally significant events. Parents, teachers and clinicians need to understand these differences to effectively adapt their use and teaching of behavior management principals. This is important to both the successful implementation of behavior management techniques and to the parent/teacher–child relationship. Understanding why the reactions/behavior of children with ADHD to consequences and situational cues differs from that of other children will reduce adult frustration and enhance their motivation to persist with BPT. In addition to advising involved parents and teachers that children with ADHD differ in their responsiveness to consequences, the following information should be shared: (1) Children with ADHD may act to avoid/reduce delays ; (2) be more upset/frustrated when expected rewards are not forthcoming; (3) be more vulnerable to incidental/accidental rewards in the environment ; (4) give up more easily when tasks are perceived as too difficult or punishing; (5) struggle to understand what is expected of them if rules/expectations are not made explicit.Rewards and punishments are defined by their actions on the behaviors that follow them, i.e., behavior that is rewarded increases in frequency while behavior that is punished is expected to decrease in frequency. The literature reviewed indicates children with ADHD differ from TD children in their response to the timing and density of reinforcement. Based on these data we recommend in BPT for ADHD: (1) to maintain high rates of immediate reinforcement during the learning of new behaviors/skills ; (2) to consider instituting individualized stretching of the ratios, i.e., gradual reduction in the density of reinforcement, once new behaviors are acquired. This requires careful attention to the effects of reducing reward on the child’s behavior to ensure rates of reinforcement are sufficient to maintain interest in a task or activity, i.e., update functional analyses. Stretching the ratios offers an opportunity to gradually expose the child to the frustration of not getting a reward and installs persistent adaptive behavior; (3) to identify creative means to maintain high rates of immediate reinforcement throughout tasks or activities to reduce response variability and efforts to escape from, or modify, the experience of delay ; (4) to consider the use of differential outcomes (response specific reinforcers), which may increase the learning of situation-specific stimulus–response associations .more sensitive to punishment than TD children. For children with ADHD positive punishment leads to more errors, missed learning opportunities, and lack of task persistence. All of which argues strongly for caution in the use of punishment, especially positive punishment, with children with ADHD. Therefore it is recommended that (5) parents and teachers should, as much as possible, be encouraged to reward alternative adaptive behaviors to reduce the need to use punishment with children with ADHD. If the use of punishment is unavoidable, its extended use should be avoided and the emotional response of the child carefully monitored.With regards to the use of punishment procedures in BPT, there is good evidence that mild punishment, e.g., response cost improves on-task behavior in children with ADHD. However, recent research, reviewed above, indicates that mild punishment can lead to more errors on tasks and increased emotionality. There is also evidence suggesting children with ADHD are As highlighted in the introduction, it can be difficult to separate the effects of instrumental learning and classical or Pavlovian conditioning on children’s behavior and learning. Both the DTD and DDT theories propose that children with ADHD show impaired acquisition of conditioned reinforcers. The DTD hypothesis suggesting this leads weaker control of behavior by reward-predicting cues . Recommendations to strengthen stimulus control are detailed below.importantly when these expectations change; (2) highlight the outcome of the child’s behavior to them to reduce behavior-consequence ambiguity. Linking rewards to actions before and when delivering reward will assist in scaffolding/shaping the learning of new behaviors; (3) increase the saliency of cues/discriminative stimuli to reduce the impact of incidental rewards, this is especially important in situations involving delay. Wherever possible reduce the salience of immediate incidental rewards, i.e., remove distractors, this may be achieved by further increasing environmental and temporal structure; (4) remind children of expected adaptive behavior when the frequency of reward is reduced. It is important not to assume children with ADHD will know what to do when a learned behavior is no longer rewarded.Stimulus control techniques are important aspects of BPT programs. Commonly recommended practices including the provision of clear instructions and rules and the provision of structure are clearly important for children with ADHD. In addition we recommend parents and teachers be taught to: (1) explicitly draw the child’s attention to rules/expectations in their current context, i.e., what is expected of them, and In addition to providing parents and teachers with the skills to effectively implement behavior management techniques we suggest the outcomes of BPT can be enhanced with the introduction of specific skills training for children with ADHD, and possibly parents and teachers dealing with ADHD. Specifically we suggest clinicians consider the need to teach emotion regulation techniques/frustration management skills to children with ADHD and their parents. We also suggest consideration be given to teaching older children with ADHD how to manage the experience of delay, possibly through learning strategies of self-reward . Self-reinforcement may also be helpful under conditions of extinction (reinforcement is absent) or when the reinforcement rates are less dense.In sum, clearly there are varying levels of support for the recommendations offered, as indicated in Table Behavioral Parent and Teacher Training is an effective treatment with moderate effects in reducing objectively and subjectively measured behavioral problems and in enhancing parenting practices. However, for symptoms of ADHD the effects are somewhat less pronounced, i.e., effects are not corroborated by objective measures , others, including the use of punishment with children with ADHD, offer new insights, practical suggestions for application, and some cautions. We also propose the use of remediation strategies for proposed deficits in learning not commonly used in BPT programs, e.g., the use of stretching the ratios to help with adaptation to partial reinforcement and enhance persistence of behavior, and the use of differential outcomes to strengthen stimulus response outcome associations and the learning of situationally appropriate behavioral responses.The identification of alterations in the responses/reactions of children with ADHD to reinforcement contingencies is empirically based. The impact of these alterations on their daily and classroom behavior are logically derived from the results of these studies and informed by clinical experience. Practice recommendations are also logically and theoretically derived and, in some cases, e.g., stretching the ratios and differential outcomes, based on recent empirical studies. Additional research is required to evaluate the usefulness of many of the proposed modifications and/or additions to the arsenal of behavioral techniques, beginning for example with a series of microtrials thereby testing the use of specific techniques  with samples of parents of children with ADHD in more ecologically valid ways with real-life problem behavior. Microtrials enable testing of intervention components on immediate outcomes and thus seem relevant here . Without such understanding parents and teachers may assume deliberate misbehavior on the part of the child, behavior which is better understood in terms of differential sensitivity to the contingencies operating in their environment. Such knowledge will help ensure the selection and implementation of the most appropriate management strategies, improved child behavior, and increased caregiver engagement. Furthermore, some parents may have ADHD themselves, and potentially similar altered reinforcement processing as their child . Heightened emotional lability is often present among children with ADHD (Graziano and Garcia The current recommendations to adapt BPT and take account of altered reinforcement sensitivity in children with ADHD are based on our existing knowledge of these alterations. It is clear from reviewing the literature that altered reinforcement sensitivity in ADHD is subtle and complex. There is no doubt that in many ways the responses of children with ADHD to reward and punishment mirror those of TD children. Rewarding behavior increases the likelihood it will be repeated, mild punishment for inappropriate behavior reduces its frequency. As researchers continue to investigate the responsiveness of children with ADHD to reinforcement contingencies further adaptions to our recommended practices will undoubtedly be necessary.


Using an elastic net regression model, we aim to classify PS status using polygenic scores (PGS) based on a range of heritable psychiatric and brain-related traits in a multi-PGS model. We also perform univariate PGS associations and evaluate age-specific effects. The multi-PGS analyses do not improve prediction of PS status over univariate models, but reveal that the attention deficit hyperactivity disorder (ADHD) PGS is robustly and uniquely associated with PS  P = 0.0003). This association is driven by subjects of European ancestry , P = 4.15 × 10−7) but is not observed in African American subjects (P = 0.65). We find a significant interaction of ADHD PGS with age (P = 0.01), with a stronger association in younger children. The association is independent of phenotypic overlap between ADHD and PS, not indirectly driven by substance use or childhood trauma, and appears to be specific to PS rather than reflecting general psychopathology in youth. In an independent sample, we replicate an increased ADHD PGS in 328 youth at clinical high risk for psychosis, compared to 216 unaffected controls , P = 0.02). Our findings suggest that PS in youth may reflect a different genetic etiology than psychotic symptoms in adulthood, one more akin to ADHD, and shed light on how genetic risk can be investigated across early disease trajectories.Psychotic symptoms are not only an important feature of severe neuropsychiatric disorders, but are also common in the general population, especially in youth. The genetic etiology of psychosis symptoms in youth remains poorly understood. To characterize genetic risk for psychosis spectrum symptoms (PS), we leverage a community-based multiethnic sample of children and adolescents aged 8–22 years, the Philadelphia Neurodevelopmental Cohort ( Youth experiencing psychotic symptoms typically exhibit a multitude of other comorbid symptoms, such as increased mood, anxiety, and attention deficit hyperactivity disorder (ADHD) symptoms, as well as increased substance use and impairments in global functioning7. While subclinical psychopathology poses a risk for later development of overt psychiatric illnesses11, only a minority of youth reporting psychotic symptoms will convert to full-blown psychotic disorders.Psychotic symptoms, such as delusions and hallucinations, are an important feature of severe psychiatric disorders such as schizophrenia and bipolar disorder. They are, however, also common in the general population, and occur in ~5–10%14. In particular, the landmark genome-wide association study (GWAS) of schizophrenia provides aggregate risk conferred by variants identified, polygenic scores (PGS), which explain about 7–10% of variance in case-control status15. In individuals with bipolar disorder, both genetic risk for schizophrenia as well as for bipolar disorder have been associated with psychotic symptoms17.With recent progress in psychiatric genetics, psychotic disorders are becoming well-characterized genetically19 with the proportion of genetic variance explained by common variants (SNP-heritability) of 3–17% in adolescents20. Adults with psychotic symptoms harbor increased genetic liability for a broad spectrum of psychiatric disorders, including schizophrenia and other neuropsychiatric disorders21. While in adolescents some evidence suggests increased genetic risk for schizophrenia (and major depressive disorder) for specific features of psychosis18, the reported effect sizes are very small, and these effects not very robust22. In pre-adolescent youth, the relationship between genetic risk for psychiatric traits and psychotic symptoms has not yet been explored. The genetic characterization of psychosis spectrum symptoms across development may increase our understanding of their etiological and pathological significance.In the general population, however, the genetic etiology of psychotic symptoms across development is still largely unknown. The heritability of psychotic experiences has been estimated between 30 and 50% from twin studiesn = 9498 in total). The PNC is a multiethnic cohort, with the largest proportion of individuals of European (66%) and African American (26%) ancestry. In this community-based sample that is not ascertained for neuropsychiatric disorders, about 20% of the youth are classified as having psychotic spectrum symptoms (PS). In the PNC, having PS has been associated with structural and functional brain alterations25, qualitatively similar to those present in overt psychotic disorders, as well as cognitive deficits26. These findings underscore both the increased vulnerability in youth experiencing psychosis spectrum symptoms and the importance of investigating psychosis risk as a dynamic developmental process7.To study genetic risk for psychosis symptoms in a population sample of youth, we leverage a large well-characterized community-based sample of youth aged 8–22 years, the Philadelphia Neurodevelopmental Cohort 30, the Structured Interview for Prodromal Syndromes (SIPS)31, and the PRIME Screen Revised (P-SR).Data were obtained from the publicly available Philadelphia Neurodevelopmental Cohort  via the Database of Genotypes and Phenotypes (dbGap) platform. The PNC is a community-based sample consisting of 9498 genotyped youth (ages 8–22 years) who participated in clinical and neurocognitive assessment, with a subsample undergoing MRI, after providing written informed consent or assent with parental consent (youth under 18 years old). Psychiatric symptomatology was assessed using the GOASSESS interview32. These criteria consider lifetime occurrence of positive psychotic symptoms such as hallucinations and persecutory thinking, negative/disorganized symptoms such as flattened affect, as well as age-appropriateness of these symptoms  and negative/disorganized (SOPS) as well as symptoms of ADHD and additional phenotypes for follow-up analyses are described in the 33 and related subjects  were removed within ancestry groups (n = 4852) and one African American ancestry group .Genotyping QC, imputation and selection of individuals of European and African ancestry are described in detail in the y groups –S3. Afte34, a centralized repository for summary statistics (accessed June 2018). Specifically, we included 23 GWAS summary statistics of psychiatric, brain traits and personality traits, that were either publicly available or obtained via personal correspondence. From these, a total of 12 had a linkage disequilibrium (LD) score heritability z-score >5, indicating good statistical power27(which is a function of variance explained and sample size) and complete GWAS information available. If available, we replaced summary statistics in LD hub with more recent or powerful GWAS: For the Psychiatric Genomics Consortium (PGC), we replaced MDD, BIP, ADHD. Finally, we also included the 23andMe traits for Morningness and self-reported depression. For more details on the included GWAS see Supplementary Table We selected GWAS summary statistics from LD hub35, Autism36, bipolar disorder13, schizophrenia12, cross-disorder, a joint analyses of severe mental illness37, major depression38; other psychiatric GWAS for: self-reported depression from 23andMe39 major depressive disorder from CONVERGE40) brain traits (ENIGMA Caudate volume and Putamen volume41) and behavioural traits ).After filtering, the 13 traits included in our analyses include psychiatric disorders  and L1 regularization (used in LASSO), and has been shown to work particularly well in case of correlated predictors, as is expected in the context of highly correlated genetic traits45.As has been successfully implemented previouslyElastic net regularized regression employs two hyper-parameters, alpha and lambda. To achieve optimized balance between variance explained and minimum bias, we fit models to tune over both alpha and lambda parameter values in repeated 10-fold cross-validation, and used the minimal lambda for the prediction model. As a performance measure, we use area under the ROC curve (AUC). Models were trained on a random subset of 70% of the data and weights of the selected variables subsequently used to test their cumulative discriminatory power in predicting psychosis status in the remaining 30%. We performed model fit both in the entire sample as well as within EA and AA separately. To obtain an estimate of the robustness and range of the selected parameters we performed 1000 repetitions of the procedure. In addition, we also generated models for 1000 permutations of the phenotype . Comparing our models to those derived from permutation, we adopt the conservative approach to compare the mean of the 1000 repetitions in the actual sample to the distribution of the permutations.2 and Sex as covariates. Effect sizes are reported as odds ratio (OR) relative to one standard deviation increase in PGS. To account for multiple testing, we applied a Bonferroni correction, dividing the p-value by the total number of tests . Interactions were tested by including the interaction term in the full model.To estimate the effect of each PGS individually, we fit a series of logistic regression models for each of the corrected polygenic scores including Age, AgeSymptom overlap was tested using Fisher’s exact test (pairs of binary traits), Wilcoxon Rank-sum test (binary vs quantitative) and Spearman rank correlation (pairs of quantitative traits).n = 7225 youth ages 8–22 with both phenotypic and imputed data available with two ancestry groups: European ancestry  and African American ancestry . From the total sample, 1369 youth (19%) are classified as having psychosis spectrum symptoms (PS). Figure 2 = 0.11, se = 0.21, P = 0.3, After quality control see , the PNC AA, n = 802. FromP = 0.009, average AUC EA = 0.55 (sd 0.02) P < 0.001). Within the AA cohort, however, the multivariate prediction was not different from chance (average AUC AA = 0.51 (sd 0.02) P = 0.35). In EA, the highest weight was consistently assigned to the PGS of ADHD, with an average standardized coefficient of 0.09 (sem 0.0007) corresponding to an OR of 1.10  55 sd 0.0 P < 0.0055 sd 0.0 P < 0.00 55 sd 0..10 Fig. .Fig. 2MuP = 0.0003, Fig. P = 4.15 × 10−7), and not observed in the AA cohort  P = 0.65). Genetic liability for all other neuropsychiatric traits, including schizophrenia, was not associated with PS in either ancestry group. Since the AA cohort is of a different ancestry than the majority of GWAS cohorts, with different allele frequencies, LD patterns, and effect sizes47, we also performed PGS computation using LDPRED44, a method that explicitly models LD. No other traits were significantly associated using this method either. To test whether the multivariate predictor outperformed ADHD PGS alone, we performed the same classification procedure including only the ADHD GWAS. That is, we estimated the regression coefficient on a training dataset including 70% of data and tested on the subset that was left out. Our multivariate model did not outperform a univariate predictor. In fact, in the case of EA, the univariate predictor even performed slightly better  , 1.18 P Since the EA cohort drives the observed genetic association between PS and ADHD, we next explored the nature and robustness of the association in the EA cohort only.P = 1.25e-06, Fig. P-value thresholds (ii) not driven by subtle population stratification within the EA cohort, (ii) extends to the European-only version of the ADHD GWAS  1, 3.51 PP = 0.02 for the interaction term in the full model, Fig. We hypothesized that the association between PS and ADHD PGS would be strongest in the younger children and weaker closer to the typical age of onset of schizophrenia and other psychotic disorders. As predicted, we observe a significant interaction of ADHD PGS with age, with a stronger association for younger children (age 12 or younger), weakening in late adolescence (P = 0.85): the association between males and females are near-identical, with the OR in males-only 1.23  and females-only 1.25 .We observed no interaction with sex , ADHD and psychosis symptoms are known to co-occur in youth6. Indeed, across ancestries, we observe a strong phenotypic overlap between PS and ADHD symptoms in the PNC . A large fraction of ADHD cases also endorse psychosis spectrum symptoms, and the majority of subjects in the PS group endorse ADHD symptoms  SCZ and ADHD is minimal . Both higher inattention and hyperactivity scores are associated with an increased probability of being classified as PS, while at the same time higher PRIME and SOPS scores are associated with increased probability of meeting ADHD criteria, across ancestry groups , and significantly increased in the subset of PS subjects that endorse hallucinations , P = 0.02). As expected, the ADHD PGS is associated with ADHD status , P = 0.01). Conversely, and contrary to existing evidence48, the schizophrenia PGS is not associated with ADHD status (P = 0.51).Thus, the association between increased ADHD liability and PS in youth does not appear to be driven by symptom overlap. Moreover, ADHD genetic risk is not only associated with PS as a categorical variable, but also similarly with the psychosis severity scales, measured quantitatively , and not cocaine or over the counter substance use (P > 0.05). Including these as covariates in the model did not alter the estimated effect sizes  P = 0.001), when we exclude subjects endorsing traumatic events the association remains stable  P = 0.02). However, these phenotypes both overlap strongly with PS (Table P > 0.4). The opposite, however, does hold: the association between ADHD PGS and PS remains consistent even after excluding subjects who endorsing either of these three phenotypes  PS Table , and the,1.18 PS Thus, the association between PS and ADHD PGS is not driven by symptom overlap, or indirectly driven by substance use or childhood trauma. Moreover, it appears to be specific to PS, and not a measure of general psychopathology.51. NAPLS2 is an eight-site longitudinal study of predictors and mechanisms of conversion to psychosis, and includes help-seeking adolescents and young adults at clinical high risk (CHR) for psychosis  as well as unaffected control subjects (n = 216)52.We sought to replicate our finding of increased polygenic liability for ADHD in youth with psychotic spectrum symptoms in the North American Prodrome Longitudinal Study, Phase 2 (NAPLS2) cohortP = 0.02; in EA, OR = 1.09  P = 0.03; n = 124 and n = 70, respectively). These effect sizes are similar to the ones observed in the >16 age group in the PNC EA cohort .As in our discovery sample, we observe increased ADHD risk in CHR youth compared to controls  53. To our knowledge, this is the first investigation of ADHD polygenic scores for association with symptoms of psychosis in youth. We therefore replicated our finding in an independent cohort of subjects at clinical high risk for psychosis.Leveraging a large community-based sample, we sought to characterize genetic risk profiles for psychotic spectrum symptoms across childhood and adolescence. We applied multi-PGS prediction models as well univariate statistical tests, based on GWAS of multiple brain and behavioural traits. Notably, we observed a modest but robust association between broadly defined psychosis symptomatology and genetic liability for ADHD, but not for schizophrenia or any other psychiatric traits. This effect was only observed in participants of European ancestry, for whom those within the highest decile of ADHD genetic risk have an almost 2.5-fold increased likelihood of being in the PS group, compared to those with lowest ADHD polygenic scores. This association is strongest in children 12 years or younger, and diminishes closer to typical age of onset of schizophrenia. In addition to being associated with the dichotomous PS phenotype, the ADHD PGS is associated with the quantitative symptom scales as well, generally improving power21, psychosis spectrum symptoms in youth did not yield a general association with multiple psychiatric illnesses, but with ADHD specifically. While an association between schizophrenia genetic risk and psychosis symptoms has been reported in adults21 and older adolescents aged 15–1918, the lack of such an association in our study is consistent with literature in young adolescents . Rather than testing a specific hypothesis, we test and correct for multiple genetic risk scores in a single cohort. This is an unbiased way of establishing the genetic architecture of a trait and reduces the risk of identifying false positive associations through performing single tests.Contrary to recent genetic evidence based on psychotic experiences in adulthood49, the association with PS is not substantially mediated by trauma, or substance use.The association between PS and ADHD PGS, while modest, holds even when excluding all subjects that endorse any ADHD symptoms. Moreover, while we observed some association between ADHD PGS and the experience of trauma, replicating earlier evidence54. Despite observing strong phenotypic overlap between PS and symptoms of depression, mania and anxiety domains, we did not observe a robust association for these phenotypes with ADHD PGS in the PNC cohort.One important question is whether the association between ADHD PGS and PS is specific to psychosis, or reflect more general liability for psychopathology. For example, a weak association between ADHD PGS and early onset depression has been reported prevoiuslyIn our study, the multivariate approach did not improve classification accuracy above a single trait association of ADHD. However, future efforts to improve risk scoring methodology and especially more powerful GWAS of related traits are likely to improve prediction as well.As the discovery GWAS of ADHD included 55,374 children and adults , ADHD genetic risk across all developmental ranges is captured in the downstream polygenic scores. An important avenue for future work will be to investigate if the association with general psychotic symptomatology is driven more by genetic liability present in children versus adults diagnosed with ADHD.55. Our study offers further evidence that polygenic scores, at this point, have limited predictive power in non-European ethnic groups. As PGS scores are approaching clinical utility56, the crucial equity issue that arises as a result from this discrepancy should not be taken lightly. Novel tools to generate risk scores across ancestries, such as by scoring only segments of the genome matching the GWAS population in admixed populations, may improve applicability of the risk scores across ancestries. Most importantly, however, larger samples from different ancestries are needed to begin to close this gap.Despite similar phenotypic correlations across ancestry groups, the absence of any genetic association in youth of African ancestry highlights the need for increasing ethnic diversity in GWA studies. Because allele frequencies, linkage disequilibrium patterns, and effect sizes of common polymorphisms vary with ancestry, current common variant genetic findings do not translate well across populations7. An important follow-up question is whether youth with psychotic symptoms that ultimately develop a psychotic disorder have different genetic characteristics than those who do not. Consistent with our present findings in the PNC, we recently found that subjects meeting psychosis risk syndrome criteria that do not develop psychosis in a 2-year follow-up in the NAPLS cohort do not have increased genetic risk for schizophrenia compared to controls. However, polygenic liability for schizophrenia is a predictor for conversion to overt psychosis6. We now show, in the same NAPLS cohort, that ADHD PGS is also increased in CHR youth, but was not associated with conversion. While there are important clinical differences between PNC PS and NAPLS CHR cohorts , the consistency of our findings and similar effect sizes across cohorts confirms the robustness of the ADHD PGS association with psychosis symptoms.Based on a follow-up study of PNC youth, about half of youth experiencing psychotic symptoms, symptoms persist or get worse over a 2-year follow-up, while even those whose psychotic symptoms remit exhibited comparatively higher symptom levels and lower functioning than typically developing youthsOur findings shed light on the genetic architecture of psychosis symptoms in a population-based youth cohort and suggest that broad psychosis spectrum symptoms in youth may reflect a different genetic etiology than psychotic symptoms in adulthood, or those that convert to psychosis. Rather, the genetic etiology of psychosis symptoms in youth seems more akin to ADHD. Findings indicate that genetic risk can be investigated across early symptom trajectories, and in non-help-seeking populations, to improve our understanding of disease risk factors and psychiatric comorbidities.Supplementary Figure and Table legendsSupplementary FiguresSupplementary noteTable S1Table S2


The aim of this cross-sectional questionnaire-based study was to identify associations between the doses of cannabinoids and terpenes administered, and symptoms of attention deficit hyperactivity disorder (ADHD).n=18) and high  MC monthly dose and low adult ADHD self-report scale  score  or high ASRS score  subgroups.Participants were adult patients licensed for medical cannabis (MC) treatment who also reported a diagnosis of ADHD by a physician. Data on demographics, ADHD, sleep, and anxiety were collected using self-report questionnaires. Data collected on MC treatment included administration route, cultivator, cultivar name, and monthly dose. Comparison statistics were used to evaluate differences in reported parameters between low  of them. The high MC monthly dose group consumed higher levels of most phyto-cannabinoids and terpenes, but that was not the case for all of the cannabis components. The high dose consumers and the ones with lower ASRS score reported a higher occurrence of stopping all ADHD medications. Moreover, there was an association between lower ASRS score subgroup and lower anxiety scores. In addition, we found an association between lower ASRS score and consumption of high doses of cannabinol (CBN), but not with Δ-9-tetrahydrocannabinol (THC).These findings reveal that the higher-dose consumption of MC components (phyto-cannabinoids and terpenes) is associated with ADHD medication reduction. In addition, high dosage of CBN was associated with a lower ASRS score. However, more studies are needed in order to fully understand if cannabis and its constituents can be used for management of ADHD. Attention deficit hyperactivity disorder (ADHD) is a common, heritable, neuropsychiatric disorder affecting 2.5%–5% of adults.12The management of ADHD typically includes psychostimulant medications (methylphenidate and amphetamine derivatives),20Increasingly, there is recognition that medical cannabis (MC) may offer an alternative treatment option for adult ADHD.Currently there is a gap in the literature concerning the clinical effects of the specific cannabis plant cannabinoid and terpenoid components, best termed “chemovars” rather than utilizing “strain names,” otherwise termed “cultivars.”Medical cannabis in Israel is governed by the Israeli Ministry of Health (IMOH) under regulations of cannabis use for medical purposes. There are specific indications for which a physician can request a license for a patient; ADHD is not a qualifying condition for a MC license. However, it is a comorbidity of some patients with an approved indication . Generally, a MC application is received by one of the board members of the Medical Cannabis Unit (MCU) that would reply to the physician if the request is approved or refused, and the reason for the refusal.Physicians in Israel decide in collaboration with the patient on the route of administration that is approved by the MCU, either inflorescence for smoke and vaporization, and/or oil extracts for sublingual use. The monthly dose of MC is decided by the physician . Physicians provide consultation for the selection of specific MC cultivar or combination of cultivars. However, the final decision on the selection of MC cultivar(s) is in the hands of the patient. Hence, the consumption of cannabinoid or terpenoid doses is not controlled. Every patient goes through a personal trial-and-error process to find the cultivar or the combination of cultivars that best meets his/her therapeutic needs. Moreover, instructions for titration  of MC treatment are made either by a nurse in some centers, but mostly by instructions provided by one of the nine licensed suppliers, eight of which are cultivators. Importantly, these guidelines are only recommendations and are not enforced.The purpose of this cross-sectional study was to examine the differences between MC monthly dose and ADHD symptoms frequency scores subgroups of ADHD patients, their specific chemovar consumption, and ADHD medication use. Additionally, sleep and anxiety symptoms were evaluated as well as MC treatment AEs.Participants were eligible to participate if they were Hebrew-speaking, aged ≥18 years, reported a diagnosis of ADHD by a physician, and had a standing MC license for the treatment of any approved condition.All participants received written explanation of the study via email prior to their enrollment. They were asked to sign an electronic informed consent form before the start of data collection. Only patients that signed the informed consent form were allowed to participate in the survey. The study was approved prior to data collection by the institutional ethics committee of the Technion (# 011-2016).n=3,218). Patients that reported having a diagnosis of ADHD , and who had previously agreed electronically to disclose their email address for future studies, received an email with an explanation of the study and a link to the online questionnaires. Participants who signed the electronic consent form, and confirmed their ADHD was diagnosed by a physician, were invited to complete the questionnaires. Data were collected in October 2019 to January 2020. No financial compensation was offered to participating patients. Additionally, most clinically administered cultivars of all eight approved cultivators in Israel were evaluated in the laboratory for their cannabinoid (by liquid chromatography–mass spectrometry [LC-MS]) and terpenoid (by gas chromatography–mass spectrometry [GC-MS]) presence and quantity.The data for this cross-sectional study were collected from an existing database of Israeli patients with a pre-existing MC license for various indications .28Questionnaires collected demographic information that included age, gender, education, body mass index (BMI), and approved MC treatment duration (years). Data on ADHD comorbidities included the past or present diagnosis of: clinical depression, anxiety disorders, antisocial disorders, bipolar disorder, dyslexia, substance abuse, alcohol abuse, and the past or present pharmaceutical treatment of at least one of these comorbidities. Validated questionnaires included the adult ADHD self-report scale (ASRS-v1.1),Phyto-cannabinoid analyses were performed using a Thermo Scientific ultra-high-performance liquid chromatography (UHPLC) system coupled with a Q Exactive™ Focus Hybrid QuadrupoleOrbitrap mass spectrometer (MS) .34Terpenoid analyses were performed on a Trace 1310 gas chromatography (GC) system (Thermo Scientific) coupled to a TSQ 8000 Evo triple-quadrupole MS (Thermo Scientific) equipped with a DB-35MS UI capillary column  as described elsewhere.35d test.n=30) or high ASRS score  subgroups. We analyzed the differences of all measures between MC monthly dose subgroups and ASRS subgroups. Notably, due to missing data (n=6) on MC monthly dose, demographic data are presented only for patients with that information. The Shapiro–Wilk test of normality demonstrated non-normal distribution for all measures, thus, data are presented as median and quartiles 25 and 75 . Differences were considered significant at the P<0.05 level, after Bonferroni corrections. Incidences are presented as number and percentage of patients.R software (V.1.1.463) with tidyversen=3,218), including chronic pain , oncology , post-traumatic stress disorder , irritable bowel diseases , neurological disorders , and acquired immune deficiency syndrome complications care . Data were missing for 75 patients. This population reported on a variety of comorbidities and associated symptoms , aged 43 (33–56) years.We established a patient-reported outcomes database of Israeli patients with a pre-existing MC license for various MCU-approved indications (symptoms . The datn=80), they were directed to complete the questionnaires. A total of 59 patients answered the study questionnaires, from which, 53 patients reported their MC monthly doses. Notably, most  patients consumed inflorescences, either by smoking, vaporizing, or both. Five (9%) patients combined oil extracts and inflorescences, and one (2%) patient consumed only oil extracts. Medical cannabis treatment duration of our sample ranged from 1 to 16 years. The MC chemovar constituents dose consumption (i.e. cannabinoid and terpenoid amounts) could be calculated for 27 (50%) of the patients that consumed only MC inflorescence and reported fully on their MC treatment regimen.In this database population, 367 patients (11%) reported having a diagnosis of ADHD. Of them, 110 patients responded to our invitation to participate in the study (30% response rate). Upon confirmation that a physician diagnosed them with ADHD (n=35) consumed MC more frequently, with a median of 6 (4–12) times per day, while the low MC dose subgroup  consumed MC 3 (2.2–5.8) times per day . Sample demographics were similar for both MC dose subgroups, the subgroups consisting of a majority of females , with median age of 38 years (31–46) (The high MC dose (g) subgroup  . NotablyMedical cannabis treatment is very complex, firstly because of the variety of cultivars in Israel (about 150 different “strain names”) and secondly because patients consume in general more than one cultivar as well as different dosages. Consequently, in the current study we have 27 unique combinations of MC cultivars. P<0.01 for all). Additionally, cannabichromene (CBC), cannabigerol (CBG), and tetrahydrocannabinol-C4 (THC-C4), and the terpene trans β farnesene  were also significantly higher in the high MC dose subgroup. The THC:CBD ratio dose was also higher among the high MC dose subgroup  (P<0.01).For the 27 patients that monthly MC chemovar (phyto-cannabinoids and terpenes) could be calculated for, we found that the high MC dose group consumed significantly higher amounts of the following phyto-cannabinoids compared to the low MC dose subgroup: THC, tetrahydrocannabivarin (THCV), CBD, and cannabinol (CBN)  . RemarkaP>0.05). Specifically, for the low and high MC dose subgroups, patients reported on past and current diagnosis of depression , anxiety , dyslexia , as well as substance abuse  and past alcohol abuse . A current diagnosis of bipolar disorder was reported by three patients (6%) from the high MC dose subgroup only. No antisocial disorder was reported. Current pharmaceutical treatment for the abovementioned diagnoses was reported by two (4%) patients in the low MC dose subgroup and eight (15%) in the high MC dose subgroup.Mental illnesses were reported by most  patients of the sample. No significant differences were found between the low and high MC dose subgroups of these comorbidities  were in the high MC dose subgroup. Specifically, the low and high MC dose subgroup reported use of methylphenidate hydrochloride , methylphenidate hydrochloride slow release , amphetamine and dextroamphetamine combination , amphetamine and dextroamphetamine combination extended release , and lisdexamfetamine dimesylate . Two patients (4%) of the high MC dose subgroup reported use of methylphenidate hydrochloride extended release. In addition, there was an association between the high MC dose treatment and ADHD medication regimen. Specifically, the high MC dose subgroup reported significantly higher rates of changing (i.e. any type of change) their ADHD medication regimen since MC treatment initiated . Furthermore, the high dose subgroup reported more on stopping all ADHD medications since MC treatment began   patients reported current use of ADHD pharmaceutical medication consumption, the majority of them ( P<0.05) .n=59) responses into low ASRS score  or high ASRS score  subgroups by our sample distribution, we found few significant differences between the subgroups . Specifically, ADHD medications were changed more since the initiation of MC by the low ASRS score subgroup than by the high ASRS score subgroup . The low ASRS score subgroup stopped all ADHD medications since MC treatment began more than the high ASRS score subgroup . Notably, anxiety scores were higher in the high ASRS score subgroup (median 10 [IQR 7–13]) than for the low ASRS score subgroup (4.5 [3–7]) . Importantly, the low ASRS score subgroup consumed higher (28 [17–41] mg) monthly CBN doses than the high (15 [12–20] mg) ASRS score subgroup . However, although CBN is a metabolite of THC, we found no significant differences of monthly THC doses between the low (5000 [3400–6700] mg) and high (4600 [3200–5900] mg) ASRS score subgroups   .P<0.001 for all). Importantly, we did not find any difference between ASRS score subgroups and ADHD rating scale regarding the monthly MC dose consumption (40 [30–50] g for both subgroups of both measures)  than for the low ASRS score subgroup   of the sample; AEs were not significantly different between the MC dose subgroups (P>0.05). Reports of AEs included central nervous system , gastrointestinal , psychological , cardiovascular , ophthalmic , musculoskeletal , and auditory  AEs.Medical cannabis-related AEs were reported by a total of 28%  for which they are approved to take MC; however, they may self-titrate available cultivars for an effect they find therapeutic and comforting for both the conditions they are approved for and for other non-indicated comorbidities, such as ADHD. The complexity created with whole-plant products that include over 144 phyto-cannabinoidsMore recently, characterizing cultivars between THC-dominant and CBD-dominant cultivars has been used.Previous studies considered cannabis as a single product in ADHD research,In this study, we demonstrated that patients treated with MC stopped their ADHD medications, especially in the high MC dose and in the low ADHD symptoms frequency subgroups. Comparably, case reports have demonstrated similar ADHD medication-sparing effects.The neurobiology of ADHD is reported as being similar to other psychiatric conditions, such as bipolar disorder, which may explain the report by Katzman et al. of strong familial links between the two conditions.Finally, the literature is rich in studies associating lower educational attainment and lower levels of employment in patients with adult ADHD.The current study has a few limitations. Firstly, the small sample size could have biased our results. Nonetheless, we used non-parametric models as is customary. Secondly, self-report bias could have occurred. However, the questionnaire was anonymous, letting patients answer with no effect on their current treatment by their physician. Thirdly, due to our study design, we did not have access to patients’ data before initiation of MC treatment, making it impossible to draw causal conclusions. Fourthly, this cohort had a diagnosis other than ADHD for which they were approved to use MC, so the data for ADHD were essentially a secondary endpoint. Nonetheless, we evaluated ADHD symptom severity by validated questionnaires.In summary, ADHD is a common psychiatric disorder in the adult population that is frequently unrecognized, under-diagnosed, and under-treated. It is often comorbid with other psychiatric disorders. Although MC is not directly indicated for ADHD, low ADHD symptom frequency and ADHD medication-sparing effects were found to be associated with MC treatment. In addition, high dosage of CBN was associated with lower ASRS, hinting at a possible combination effect in whole-plant MC treatment. Nevertheless, although we found the abovementioned association with CBN, it is minorly expressed in most MC cultivars, thus, we assume that other phyto-cannabinoids might be more essential for the effect on ADHD patients. These results, although not causal, might shed light on the potential beneficial effects of MC on ADHD symptom severity and motivate future prospective studies in order to validate our results and perhaps even consider making ADHD an approved indication for MC license in Israel in future.


Previous studies using molecular markers on approx. twenty landraces from this region suggested that they belonged to a Pyrenees-Galicia Flint genetic group and originated from hybridizations between Caribbean and Northern Flint germplasms introduced to Europe. In this study, we assessed the structure and genetic diversity of 194 SWF maize landraces to better elucidate their origin, using a 50K SNP array and a bulk DNA approach. We identified two weakly differentiated genetic groups, one in the Western part and the other in the Eastern part of the studied region. We highlighted the existence of a longitudinal gradient along the SWF area that was probably maintained through the interplay between genetic drifts and restricted gene flows. The contact zone between the two groups observed near the Garonne valley may be the result of these evolutionnary forces. We found in landraces from the East part of the region significant cases of admixture between landraces from the Northern Flint group and landraces from either the Caribbean, Andean or Italian groups. We then assumed that SWF landraces had a multiple origin with a predonderance of Northern Flint germplasm for the two SWF groups, notably for the East part.From the 17th century until the arrival of hybrids in 1960s, maize landraces were cultivated in the South-West of France (SWF), a traditional region for maize cultivation. A set of landraces were collected in this area between the 1950s and 1980s and were then conserved  Z. mays L. subsp. parviglumis, about 9000 years ago in Southern Mexico [et al. [Maize was domesticated from teosinte, n Mexico . Thereafn Mexico –3. Durinn Mexico –6. In thn Mexico , 7. Genen Mexico , 9, and n Mexico , 7–11. Get al. [et al. [et al. [et al. [i.e. did it arrive directly from America or indirectly through NF landraces from the North of Europe. These two patterns of NF introductions were proposed by Tenaillon and Charcosset [Other molecular studies showed that maize landraces cultivated at intermediate latitudes in Europe originated from hybridizations between maize landraces from Caribbean, South American and North American landraces , 10–13.  [et al.  found th [et al.  analysed [et al.  argued tet al. [FIS and FIT). Nevertheless, bulking is highly efficient to estimate most parameters of interest regarding population genetic structure and to make inference about the evolutionary history of populations. Recently, this bulk approach was investigated on SNP markers in maize [All the above information highlights the need for genetic markers analyses to better understand the evolution of maize landraces located in intermediate regions of Europe. Since maize is an outcrossing species, landraces are expected to display relatively high levels of genetic diversity. To assess this diversity, molecular studies must thus include several individuals. However, for large sets of landraces, molecular characterization based on several individuals per landrace is limited by laborious and costly experimental processes. To overcome this problem, several studies on maize landraces were performed on bulks of several plants per landrace, for RFLP analysis , 14, 15 in maize , leadingin maize .et al. [et al. [et al. [In this report, we focus on the South-West of France (SWF), one of the main traditional maize cultivation areas in Europe. Maize cultivation in SWF was first reported in 1626 in the ‘Béarn’ region, and in 1628 and 1637 respectively in the towns of ‘Bayonne’ and ‘Castelnaudary’ . Based oet al.  and Mir  [et al.  using SS [et al.  using SNhttps://urgi.versailles.inra.fr/siregal/siregal/grc.do) and seed lots regenerated through four successive generations of multiplication using between 100 and 200 full-sib ears for each landrace. Passport data including information about the area of collection  and geographical coordinates (latitude and longitude) are available for each landrace although geographic coordinates are lacking for 36 of these 194 landraces  groups  groups . The PG_  and gene diversity  using ae v3.0.3 .DeltaK parameter following the method proposed by Evanno et al. [To assess the population genetic structure underlying our panel of SWF maize landraces, we used the software ADMIXTURE v1.07 . This meo et al. . Each laFST /(1- FST) values following Rousset [FST values were calculated over SWF landraces using the Gst estimate proposed by Nei [To describe the genetic structure of SWF landraces, we first looked for links between the genetic structure and the geographic localization of the landraces. To this aim, we calculated pairwise genetic distances over the 194 maize landraces using the modified Rogers’s distance , 31. On  Rousset , and the Rousset . Pairwisd by Nei . The stad by Nei , R veganWe also explored relationships between the genetic structure and climatic variables. To this aim, we created a climatic data base containing values of monthly precipitation and monthly mean temperatures of prospection sites for the 194 landraces from the SWF. We first retrieved data for monthly precipitation and monthly minimum and maximum average temperatures from the WORLDCLIM database . Then, wet al. [He) were estimated in each of these groups and, to compare allelic richness (Ar) among groups of different sizes, we used the rarefaction method proposed by Petit et al. [n = 1000 resampling. To estimate the expected heterozygosity (He) for each group, we calculated the averaged values of allelic frequencies at the 23K SNP over the landraces owing to each group. Pairwise comparisons of Ar and He values between groups were carried out using Wilcoxon signed-rank tests across all the 23 K SNPs. Statistical analyses were computed using a R Core Team [To compare allelic richness and gene diversity between well-known maize genetic groups and our set of SWF landraces, we used results obtained using ADMIXTURE on our panel of 194 maize landraces for K = 2 and considered the seven genetic groups identified by Camus-Kulandaivelu et al. . Allelict et al.  with n =ore Team  script  defined as the product of the difference in allele frequencies between populations X and Y, and the difference in allele frequencies between populations X and W. If the focal population X can be considered as resulting from an admixture or hybridization event between populations Y and W, the value of the f3-stat can be negative. A Z-score value <-2 indicates a significant mixture [To determine whether SWF landraces originated from hybridizations between ancestral landrace groups, we used the 3-populations test  implemen mixture .In our analysis, we tested two scenarios for the origin of SWF landraces. In the first one, we made the hypothesis that SWF landraces originated from hybridizations between maize landraces from Caribbean (CAR) and Northern Flint (NF) genetic groups as proposed in previous articles. To this aim, we applied 3 population s tests on triplets composed of a focal SWF group previously identified using ADMIXTURE analyses and the two genetic groups representing CAR and NF. In order to test the distinct involvement of NF materials from North America and NF from Northern Europe in the origin of SWF landraces, we subdivided NF landraces into American Northern Flint (NFA) and European Northern Flint (NFE) groups. Then, we analysed two hypotheses: SWF landraces originate from (1) an hybridization between Caribbean landraces and Northern Flint landraces previously introduced in Europe (NFE), or (2) an hybridization between Caribbean landraces and American Northern Flint landraces (NFA) potentially independently introduced in the South-West of France.a priori about the parental groups. For example, to determine whether SWF landraces originated from hybridization between landraces belonging from NF and MEX groups, we performed TreeMix 3-population tests using each of the genetic groups identified in the SWF as the focus group and NF and MEX groups as the parental groups. All these groups were defined on the basis of structure analysis using the arbitrary cut off of upper than 0.7.In the second scenario, we assumed that SWF landraces originated from hybridizations but without any i.e. MEX, AND, CAR and NF groups). The European maize landraces (including SWF landraces) were added as supplementary data. Due to their recent origins, the landraces of CBD group [To vizualize genetic relationships between SWF landraces and worldwide reference genetic groups, we also performed a Neighbor joining tree with ape R package and a principal component analysis (PCA) with ade4 R package. For both analyses, we used the modified Rogers’ genetic distance matrice  estimateBD group  were alsn = 342). At landrace level, the proportion of polymorphic loci varied from 13.5% for IPK60, a German Northern Flint landrace, to 92.8% for EPZMV23, a landrace from Spain. On average, the proportion of polymorphic loci within landrace was 68.7%.Among the 23412 SNPs analysed, 378 exhibited missing data for at least one landrace and discarded, leaving 23034 SNPs. Among them, 15 were monomorphic in all the landraces considered in this study (Ar) per landrace was 1.70, and varied from 1.33 to 1.86. Mean gene diversity (He) was 0.22 per landrace . The second group, referred to hereafter as ‘West South-West France’ (W-SWF), included 126 landraces mostly originating from the Hautes-Pyrénées, Pyrénées-Atlantiques and Landes districts. Twenty-three landraces from this group were nevertheless collected in the Eastern part of the area. Interestingly, most of the landraces collected in the Haute-Garonne and Ariège districts exhibited patterns of admixture between W-SWF and E-SWF groups  separated landraces located in the Western part . The fact that Ar is lower and He is higher in E-SWF group compared to W-SWF group indicates that allelic frequencies are more balanced in E-SWF group than in W-SWF group. The W-SWF/E-SWF differentiation explained a low but significant proportion of the overall genetic diversity: FST = 0.026 . The mean FST between pairs of landraces was 0.104 and 0.168 for the W-SWF and E-SWF groups, respectively. This shows that the E-SWF landraces are, on average, more differentiated from each other than W-SWF landraces.We analysed the genetic diversity of both groups. The allelic richness of W-SWF was significantly higher than that of E-SWF: r = 0.72; p-value < 10−15) and latitudinal coordinates , highlighting the existence of both longitudinal and latitudinal genetic gradients. We also identified a significant correlation between the pairwise FST / (1- FST) ratio and pairwise geographic distances  landrace coordinates on the first axis of the PCoA  performep-value = 0.01 for geographical values VS, p-value = 0.67 for climatic values). This suggests that the demographic history (instead of selection) of these populations is the main factor driving population differentiation.Examining climate characteristics from May to October in the collection sites of our SWF landraces, we observed that landraces belonging to the E-SWF group originated from sites associated with higher temperatures and weaker precipitations than for W-SWF landraces . DiffereAr) and gene diversity (He) than the Northern Flint group, but lower allelic richness and gene diversity than the Corn Belt Dent (CBD), Andean (AND) and Caribbean (CAR) groups.As shown in f3-stat values, suggestive of a hybridization event between two reference groups as ancestors, were detected for scenarios 1 and 2 for the E-SWF group  SWF landraces originated from hybridizations between landraces from Caribbean (CAR) and Northern Flint (NF) groups, or (2) SWF landraces originated from hybridizations between any of the historical genetic groups other than CAR x NF. Negative WF group  but not WF group . Z-scoreWF group . No negaWe did not observe signals for hybridization events involving CBD or MEX groups as origins of E-SWF and W-SWF groups, suggesting that these were not influenced by introductions from MEX landraces, nor by hybrids originating from CBD landraces after their introduction to Europe.Results of the PCA analysis performed on SNPs for the whole set of 342 maize landraces are presented in To further analyse the relationship between landraces from the SWF groups and reference groups, we performed a neighbor-joining tree based on Roger’s distance matrice on SNPs data of 342 landraces . We obseTo identify genetic distances between landraces from SWF and those from America, we used a heatmap representation with R gg2plot function to visualize the result of genetic distance estimation between SWF landraces and the 82 American landraces . The heaFIS fixation indices [The usefulness of the bulk DNA approach in genetic diversity investigations has been proven in numerous studies , 21, 42. indices , 34 cann indices , GENEPOP indices , HZAR [4 indices  and STRU indices  software indices .et al. [Despite these constraints, the genetic proximities we revealed between American and European landraces using the 50K SNPs on DNA bulks were in accordance with what is known about maize diffusion in America and the main paths of maize introductions to Europe. Indeed, our PCA and Neighbor-joining analyses allowed distinguishing between the main historical maize genetic groups previously identified by Camus-Kulandaivelu et al.  using SSet al. –6. We alet al. , 7.FST = 0.03). These 2 groups displayed a large genetic variability as compared with other groups.Using a genetic database of 23412 SNP markers to analyse the genetic diversity of maize landraces that were collected in the South-West of France circa 50 years ago, we were able to identify two main groups of landraces, located respectively in the Eastern and in the Western side of the South-West of France. This differenciation was consistently found in the different analyses  even if the genetic differentiation between them was relatively low . We also highlighted a longitudinal gradient along SWF using a multivariate technique (PCoA) based on a genetic distance matrix with SNP data from 158 landraces, which led to a significant correlation coefficient between the first PCoA axis and the longitudinal coordinates of their prospection sites.et al. [The geographical trend observed in the diversity of SWF landraces could have been the result of diversifying selection. The occurrence of a genetical longitudinal gradient along the Pyrenees area as observed in this study has been reported for several species –49. GradWe found differences for temperature and precipitation between the Eastern and Western parts of SWF, but regression analysis showed that, when considering geographical covariates, climatic variations did not explain genetic variability observed between SWF landraces. Since climate variation are geographically linked with longitude and latitude, we still cannot completely exclude the involvement of climatic variation in the differentiation of SWF landraces into two genetic groups; our results rather suggest that an equilibrium between restricted gene flow and genetic drift is the main driver of population differentiation between landraces in this region. This is supported by the longitudinal and latitudinal gradients that we observed on the first axis of PCA, which is determined by a large number of SNPs. However, the genetic differences observed for SWF landraces could be also explained by farmers’ practices: the management of seed exchanges in different valleys limited by hilly mountains probably contributed to differentiate SWF landraces in different districts. However, the ethnobotanical survey realized in 2012–2013 among farmers in the Pyrenean area did not reveal any major differences in farmers’ practices between the East and West parts of the Pyrenees . As the To elucidate the origin and evolution of maize landraces in the South-West of France, we conducted an investigation of the relationship between SWF and putative ancestors.FST = 0.03 between the Pyrenees_Galicia_2 group and each of the groups from the South-West of France) [We did not observe any clear differentiation between SWF landraces and those of the Pyrenees-Galicia group, suggesting that SWF landraces originated from a single genetic group close to the ancestors of the Pyrenees-Galicia group ( France) , 8, 10.Several studies on genetic diversity of European and American maize landraces , 5, 7 hii.e. first-cycle inbred lines directly derived from landraces after few generations of selfing, were issued from an admixture between inbred lines belonging to European Northern Flint landraces and those derived from Southern Spain lines. In our TreeMix 3-population test, we found a predominant involvement of the NFA group in the origin of the E-SWF group. However, our PCA analysis showed a closer genetic proximity between maize landraces from the Eastern part of SWF and Northern Flint landraces located in the North of Europe (NFE), supporting the scenario involving some gene flow from European Northern Flint landraces. These observations are probably due to the genetic similarity between NFA and NFE (FST = 0.04), which makes it difficult to distinguish between the two sources.NF landraces played an important role in the evolution of SWF landraces and more generally in the adaptation of maize in Europe , 6 and iOur PCA analysis showed genetic proximity between 10 SWF landraces and landraces belonging to the Corn Belt Dent genetic group (CBD). CBD is a group of landraces identified in previous studies as resulting from hybridizations between Northern Flint and U.S Southern Dent materials , 54. Theet al. [et al. [In our TreeMix 3-population test, we found that the E-SWF group originated from crosses between NF and Andean landraces. Mir et al.  showed t [et al.  because https://en.wikipedia.org/wiki/Immigration_to_Chile, march 2020).Our collection of SWF landraces presented the lowest genetic differentiation with landraces from Chile (except for CHZMO8050) compared to the remaining American landraces. All these Chilean landraces have been shown to originate from different genetic groups , with a th and 20th centuries in SWF [More generally, we thought that the South-West of France had been submitted to several introductions of maize with various genetic origins, as already reported for maize landraces in Spain  and in Ps in SWF .All the results above allowed us to describe at least two scenarios of origin that take into account the influence of Northern Flint landraces from the North of Europe predominently in the Eastern part and the genetic proximity of W-SWF landraces with Tropical ones. For the first scenario, we postulated that, after the introduction of hybridized maize landraces from Spain , the NFE landraces spread from the North to the Eastern part of SWF where they hybridized together.et al. [et al. [et al. [et al. [In the second scenario, we hypothesized that the first maize landraces introduced to the South-West of France displayed predominantly Northern Flint ancestries as do Galician landraces . Thus, tet al. , Patto e [et al. , Branden [et al.  and Mir  [et al.  found thThe contribution of maize landraces from various genetic groups found in this study makes it difficult to determine which one of the two plausible scenarios mentioned above best explains the origin of SWF landraces. Additional historical data on maize introduction to Northern Spain and SWF would certainly help to shed more like light on this aspect.et al. [et al. [Assessing the population genetic structure and diversity of a collection of crop accessions is the best way to develop an efficient management strategy and to improve breeding programs. Here we used DNA bulk analyses with a 50K SNP array to investigate the diversity and population structure for a panel of 194 maize landraces collected 30 to 60 years ago in the South-West of France. In this study, we assumed that the maize landraces from this area mostly originated from hybridizations between landraces from the Caribbean and Northern Flint groups. Introduced around 1626 through Atlantic harbours such as Bayonne, these SWF landraces have probably been posteriously submitted to gene flows from landraces belonging to various countries of America and Europe, as expected by Revilla Temiño  [et al.  for SpanThe new results obtained for SWF in our study are encouraging to expand the approach to other regions of the world, to get a better understanding of diversity and history of local varieties.S1 FigGroup numbers varied from K = 1 to K = 13.(TIF)Click here for additional data file.S2 FigAt K = 2, we differentiated W-SWF (in cyan) and E-SWF (in blue) genetic groups. At K = 3, 15 landraces (in dark-grey) previously assigned to E-SWF group at K = 2 constituted a group distinguished from E-SWF and W-SWF groups. At K = 4, we observed a fourth group consisting of about 10 landraces located principally in the “Lot” and in “Lot et Garonne” districts. At K = 5, landraces from Gironde (in turquoise) differ from W-SWF groups; Landraces from the “Lot” and “Lot et Garonne” districts were integrated again in E-SWF group and we observed differentiation between landraces from the third group at K = 3.(TIF)Click here for additional data file.S3 FigAmerican landraces were sorted according to the latitude of their collection sites and colored as per their genetic groups previously identified by Camus-Kulandaivelu et al. . We also(TIF)Click here for additional data file.S1 TableW-SWF = "West South-West France»; E-SWF = " East South-West France".(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Tablep-value<5%).This table contained means of temperature and precipitation for W-SWF and E-SWF groups from May to October. We shaded in bold months for which differences for mean temperatures and precipitations between the two groups were significant ((XLSX)Click here for additional data file.S4 TableThis table represents a summary of TreeMix 3-population test results performed using all combinations of three groups shaped by each of the two groups from SWF (E-SWF and W-SWF) considered as focal group, and two other groups (Reference groups 1 and 2) considered as the two potential ancestors of the focal group. MEX = Mexican, AND = Andean, CAR = Caribbean, NFA = Northern Flint material from America, NFE = Northern Flint material from Europe, CBD = Corn belt dent, ITA = Italian, E-SWF = East South-West France, W-SWF = West South-West France.(XLSX)Click here for additional data file.


Lipoptena cervi and L. mazamae) have been identified as vectors of Bartonella bacteria in cervids in Europe and the USA. In an earlier study we showed that Japanese sika deer (Cervus nippon) harbor three Bartonella species, namely B. capreoli (lineage A) and two novel Bartonella species (lineages B and C); however, there is currently no information on the vector of Bartonella bacteria in sika deer. The aim of this study was to clarify potential vectors of Bartonella in Japanese sika deer.Two species of deer ked (L. fortisetosa) and 36 ticks  were collected from sika deer. The prevalence of Bartonella in the arthropods was evaluated by real-time PCR targeting the 16S−23S internal transcribed spacer (ITS) and by culture of the organisms. The total number of Bartonella bacteria were quantified using real-time PCR. The distribution of Bartonella bacteria in deer ked organs was examined by immunofluorescence analysis. The relationship of Bartonella strains isolated from sika deer and arthropods were examined by a phylogenetic analysis based on concatenated sequences of the gltA, rpoB, ftsZ, and ribC genes, followed by a BLAST search for gltA and rpoB.Thirty-eight wingless deer keds , while B. capreoli (lineage A) was not detected in the keds. Two novel Bartonella species (lineages D and E) were isolated from one ked.Lipoptena fortisetosa likely serves as a vector of at least two Bartonella species (lineages B and C), whereas ticks do not seem to play a significant role in the transmission of Bartonella between sika deer based on the lower detection rates of Bartonella in ticks compared to keds. Bartonella species in lineages D and E appear to be L. fortisetosa-specific strains. Bartonella species are Gram-negative, facultative intracellular bacteria. To date, more than 30 species and three subspecies have been described in the genus [Bartonella bacteria to mammalian hosts, including sand fly (Lutzomyia verrucarum) for B. bacilliformis [Pediculus humanus humanus) for B. quintana [Ctenocephalides felis) for B. henselae [Lipoptena, Hippobosca and Melophagus keds in the family Hippoboscidae are involved in the transmission of Bartonella bacteria to ruminants [he genus . Severalliformis , human bquintana  and cat henselae . Within uminants .Lipoptena spp.) are recognized as obligate ectoparasites of ruminants but they can accidentally infest humans and other mammals [L. mazamae) from a mother deer to its offspring due to close contact [Deer keds , roe deer (Capreolus capreolus) and moose  [Bartonella-derived DNA was first detected in wingless L. cervi collected from roe deer in France [L. cervi may be epidemiologically associated with the transmission of Bartonella in this deer species. Bartonella schoenbuchensis was subsequently isolated from 73.3% of wingless L. cervi collected from roe deer and red deer in Germany [B. schoenbuchensis in the midguts of deer keds [B. schoenbuchensis DNA was detected in wingless L. cervi (83.3%) collected from white-tailed deer in Massachusetts, USA [Bartonella DNA was detected not only in developing larvae (71%) but also in winged L. cervi (6.4%) in Hungary [B. schoenbuchensis-like DNA was also detected from 13 pupae and one winged L. cervi collected in the field [B. schoenbuchensis may be transstadially transmitted from the pupal to the winged stages of L. cervi.In Europe, s alces) . Bartonen France , with th Germany . Immunoheer keds . In additts, USA , and Bar Hungary . In Finlhe field . This epCervus nippon) is native to Japan and genetically divided into six subspecies, among which Honshu deer  is widely distributed throughout the country, with the exception of Hokkaido, Shikoku and Kyushu islands. Yezo deer is also a subspecies (Cervus nippon yesoensis) of sika deer and inhabits only Hokkaido island [Bartonella bacteria from 67.6% of Honshu deer and 50% of Yezo deer examined. A genetic analysis showed that Honshu and Yezo deer harbor at least three Bartonella species, including B. capreoli and two novel Bartonella species. Hematophagous arthropods, such as deer keds and ticks, were frequently detected on sika deer that tested positive for Bartonella bacteria. These observations suggest that these ectoparasites are involved in the transmission of Bartonella bacteria between sika deer. To date, there have been no studies investigating the role of hematophagous arthropods in the transmission of Bartonella bacteria between sika deer. The aim of the study reported here was to determine whether deer keds and/or ticks serve as vectors of Bartonella bacteria in sika deer. To achieve this aim, we used a variety of bacteriological, molecular biological and immunohistochemical techniques.The Japanese sika deer  and Shizuoka (N = 9) Prefectures, Japan. Blood samples were collected from the deer and immediately transferred into EDTA-containing collection tubes. The blood samples collected from Nara Prefecture were utilized for the isolation of Bartonella bacteria in our previous study [Between 2009 and 2012, 17 Honshu deer were captured in Nara  and Shizuoka Prefectures (N = 28). All of the keds were morphologically identified as Lipoptena fortisetosa. Five deer keds from Shizuoka Prefecture were used for immunofluorescence analysis to determine the distribution of Bartonella bacteria within the bodies of the insects. A total of 36 ticks were collected from the deer in Nara (N = 33) and Shizuoka Prefectures (N = 3). Based on morphological analysis under stereomicroscopic observations these ticks were identified as Haemaphysalis flava (N = 16), H. megaspinosa (N = 15), H. longicornis (N = 4) and Ixodes monospinosus (N = 1). The live arthropod samples were immediately sent to the same laboratory under room temperature or refrigeration conditions (approx. 4 °C).A total of 38 wingless deer keds were collected from the deer captured in Nara  with 0.01 M phosphate buffered saline (PBS) containing 0.5% fetal bovine serum . Each arthropod was then homogenized in 400 μl of sodium sucrose glutamic acid buffer  for 1 min using a Micro Smash MS-100R homogenizing system  set at 3000 rpm, 4 °C. An aliquot (200 μl) of the homogenate was mixed with 200 μl of medium 199 supplemented with 1 mM sodium pyruvate solution and 20% volume of FBS, and 200 μl of this mixture was inoculated onto a heart infusion agar (HIA) plate  containing 5% rabbit blood.Isolation of o et al. . To isol2 for up to 4 weeks. Bacterial colonies on HIA were tentatively identified as Bartonella based on colony morphology , and five colonies per sample were subcultured on a fresh HIA plate using the same conditions as for the primary culture.The inoculated plates were incubated at 35 °C in a moist atmosphere under 5% COBartonella [Bartonella DNA. To avoid false-negative reactions, TaqMan Exogenous Internal Positive Control (Exo IPC) Reagents  were also added to each well according to the manufacturer’s instructions. The reaction mixture (25 μl) consisted of 2.5 μl of the DNA extracts, 1.25 μl of each primer (10 μM), 12.5 μl of 2× TaqMan Fast PCR Master Mixture, 1.25 μl of FAM-labeled probe (5 μM), 2.5 μl of 10 × Exo IPC Mix including the specific primers and VIC-labeled probe, 0.5 μl of Exo IPC DNA (Applied Biosystems) and 3.25 μl of nuclease-free water. Three non-template controls (nuclease-free water) were prepared as a negative control for each PCR. Real-time PCR was performed under the following conditions: 50 °C for 2 min to activate uracil-N glycosylase; 95 °C for 10 min to activate the DNA polymerase; then 95 °C/15 s and 60 °C/1 min for 45 cycles. The targeted DNA was amplified using the 7500 Fast/Real-Time PCR system (Applied Biosystems), and fluorescence was detected through the FAM channel for ITS amplification and the VIC channel for IPC amplification.A 200-µl aliquot of the homogenate from each arthropod was used for the extraction of DNA using InstaGene Matrix . Real-time PCR targeting the 16S−23S internal transcribed spacer (ITS) region of rtonella , 18 was Bartonella species to estimate the total number of Bartonella bacteria in each culture-positive ked. A standard curve for estimating ITS copy number in each sample was constructed using serial dilutions of plasmid DNAs; the ITS amplicons from ked strains amplified by the 16SF and 23S1 primers [1 to 1 × 107 copies/μl with nuclease-free water. As the Bartonella genome carries two ITS copies [Bartonella per ked was calculated by dividing the detected number of ITS copies by two copies.We used quantitative real-time PCR (qRT-PCR) targeting the ITS of  primers  were insS copies , the totBartonella bacteria in deer keds. After fixation in 4% paraformaldehyde/PBS, the keds were sectioned toward the sagittal direction using a cryofracture technique and adhesive film [Bartonella bacteria inside the ked body were visualized by indirect immunofluorescence staining. First, mouse anti-sera was made by immunizing mice with the four deer Bartonella strains  [Bartonella bacteria and actin fibers were visualized using a fluorescence microscope (model IX71) with the appropriate fluorescence filters . Digital images of each section were captured for processing and analysis using the imaging software ‘cellSens’ (Olympus).Immunofluorescent analysis was performed to investigate the distribution of ive film . Bartonezo-25.1)  in our lgltA) [rpoB) [gltA and rpoB sequences were compared with those of the representative deer Bartonella strains from 11 genogroups [gltA and/or rpoB.Genomic DNA was extracted from whole bacterial cells using InstaGene Matrix (Bio-Rad) and subjected to genus-specific PCR targeting the citrate synthase gene (gltA)  and RNA ) [rpoB) . The PCRnogroups  and genoftsZ) [ribC) [gltA, rpoB, ftsZ, and ribC using the maximum-likelihood method with the General Time Reversible model in MEGA 6 [The lineages of the genogroups were classified as described previously . Thus, aftsZ)  and the ) [ribC) . A phylon MEGA 6 .Bartonella bacteria were isolated from eight of the nine deer (88.9%) captured in Shizuoka Prefecture and subsequently isolated from 17 of 33 (51.5%) deer keds, whereas only one (H. megaspinosa) of 36 ticks (2.8%) was positive for Bartonella bacteria. Bartonella DNA was detected in 29 of 33 keds (87.9%), but only in three of 36 ticks (8.3%). The Bartonella-positive ticks were identified as H. megaspinosa (N = 1) and H. longicornis (N = 2). IPC amplification was confirmed in all of the reactions.Bartonella bacteria were isolated (see above), a qRT-PCR analysis indicated that the total number of Bartonella bacteria per ked ranged from 1.4 × 104 to 7.0 × 106 cells, with a mean of 9.2 × 105 per ked  were recovered from 15 keds, one tick, and eight deer. More three isolates were obtained from two keds (ID# D91-Ked1 and D91-Ked5) because a few colonies of Bartonella bacteria were grown on the agar plates. As a result, a total of 123 isolates were obtained in the present study and were classified into 15 genogroups (I to XV); the genogroups XII (10 strains), XIII (three strains), XIV (two strains), and XV (10 strains) were newly found in the present study. The new sequence variants of the gltA, rpoB, ftsZ, and ribC in the representative strains from novel genogroups have been registered at INSD and accession numbers assigned to each of the variant sequences  were identical to those of deer strains Honshu-9.1 and Honshu-18.5. The rpoB sequence of ked strain D13-Ked2.1 (XII) showed 98.8% similarity with that of deer strain Honshu-12.1. The gltA sequence of ked strain D8-Ked2.1 (XIII) showed 97.6% similarity with strain MUD detected from Lipoptena sp. in the USA. The rpoB sequence of ked strain D8-Ked2.1 (XIII) showed 99.6% similarity with five uncultured Bartonella strains from L. cervi in Poland. The gltA sequence of ked strain D8-Ked2.2 (XIV) showed 96.7% similarity with deer strains Honshu-9.1 and Honshu-18.5 from sika deer, whereas the rpoB sequence showed 97.2% similarity with an uncultured Bartonella strain detected from a white-tailed deer (Odocoileus virginianus) in the USA. The gltA and rpoB sequences of ked strain D93-Ked3.1 (XV) showed sequence similarity of 100% and 99.4% for gltA and rpoB, respectively, to deer strain Honshu-16.1.The ch Table . The gltBartonella strains of lineage B, whereas two keds (ID# D93-Ked3 and D96-Ked2) harbored lineage C strains  as the hematophagous arthropods D11-Tick12, D12-Ked1, D89-Ked2, D93-Ked1, D93-Ked2 and D93-Ked4. In contrast, deer 8, 13, 91 and 96 harbored Bartonella strains of lineage A or B, but no strains of the same lineages were detected from the keds that infested the deer.Deer 11, 12, 89 and 93 harbored Lipoptena fortisetosa and found to harbor Bartonella bacteria at a high rate (87.9%). Halos et al. [Bartonella bacteria were present at a high rate (93.8%) in wingless L. cervi collected from French roe deer. Since then, it has been reported that Bartonella bacteria are prevalent also in the keds collected from red deer and roe deer in Hungary [Bartonella DNAs were detected from both wingless L. cervi (83.3%) [L. mazamae (28.9%) collected from white-tailed deer in the USA [L. mazamae collected from gray brocket deer in Brazil [Lipoptena keds harbor high levels of Bartonella bacteria and are likely to play an important role in transmitting the bacteria between various deer species.In the present study, wingless keds collected from Japanese sika deer were morphologically identified as s et al.  first de Hungary  and Pola Hungary  and from Hungary . Likewis (83.3%)  and wing the USA , and fron Brazil . These eBartonella bacteria from 51.5% of the wingless L. fortisetosa collected. More than 1000 Bartonella colonies were recovered from a ked (ID# D93-Ked4) using the culture method, and a very high number of Bartonella cell counts (7.0 × 106) were estimated by Bartonella-specific qRT-PCR. These data suggest that L. fortisetosa offer an optimum environment for Bartonella bacteria. Results from a survey of deer in Germany demonstrated that a large number of Bartonella colonies (> 1000 per L. cervi) could be recovered from L. cervi by the culture method, with the immunohistochemical and transmission electron microscopic analyses also showing that bacterial aggregates were only present in the ked midguts, suggesting that Bartonella bacteria proliferated in the midgut of L. cervi [Bartonella aggregates were only detected in the midgut of L. fortisetosa. This result is consistent with those of the previous study [Bartonella bacteria may also propagate in the midgut of L. fortisetosa.We isolated L. cervi . In the us study  and suggBartonella DNAs were detected from Ixodes ricinus ticks in France [Bartonella DNAs were host-borne or not. Moreover, it is suggested that the mere presence of Bartonella DNA in ticks is not enough to prove vector competence of Bartonella bacteria [Bartonella DNA was not found in 1719 questing I. ricinus nymph and adult ticks collected in the field in the Netherlands. In the present study, the isolation rate from ticks was considerably lower than that from keds, as Bartonella bacteria were isolated only from one engorged Haemaphysalis tick collected on a bacteremic sika deer. The lineage of the Bartonella isolated from tick D11-Tick12 was the same (lineage B) as that of the deer from which the tick was collected. This suggests that the Bartonella bacteria might have been present in the deer blood ingested by the tick. Therefore, it is possible that Ixodes and Haemaphysalis ticks do not play a significant role in the transmission of Bartonella in deer.Although n France  and Polan France , it is ubacteria . Tijsse-bacteria  reportedBartonella strains in lineage A were identified as B. capreoli; however, the strains in lineages B and C did not cluster with known Bartonella species, suggesting that these strains are novel Bartonella species. From these results, genogroup XII in lineage B and genogroup XV in lineage C are also suggested to be novel Bartonella species. The ked strains D8-Ked2.1 (genogroup XIII) and D8-Ked2.2 (genogroup XIV) formed the new independent lineages D and E, respectively. Furthermore, the gltA and rpoB sequences of ked strain D8-Ked2.1 (genogroup XIII) were closest to those of uncultured Bartonella species detected from Lipoptena keds in the USA and Poland. Although the gltA sequence of ked strain D8-Ked2.2 (genogroup XIV) was similar to deer strains Honshu-9.1 and Honshu-18.5, the rpoB sequence of the same genogroup was similar to uncultured Bartonella species detected from white-tailed deer in the USA [Bartonella species.The phylogenetic analysis shows that novel genogroups XII and XV were included in lineages B and C, respectively. A BLAST search also indicated that ked strain D13-Ked2.1 (genogroup XII) was closest to deer strains Honshu-9.1, Honshu-18.5 and Honshu-12.1 in lineage B, whereas ked strain D93-Ked3.1 (genogroup XV) was closest to deer strain Honshu-16.1 in lineage C. In our previous study [ the USA . These fBartonella strains from Hokkaido, Wakayama and Nara Prefectures were classified in lineages A to C [Bartonella strains from the deer in Shizuoka Prefecture were classified in lineages A and B, while most of the strains from L. fortisetosa were classified in lineages B and C. These data indicate that L. fortisetosa harbors two novel Bartonella species, namely lineages B and C, and may transmit the bacteria to Japanese sika deer. The other novel Bartonella species, namely lineages D and E, were found in only one ked (D8-Ked2), but not in sika deer or other deer species in other countries. Further analyses are required to determine whether these new lineages are deer ked-specific Bartonella species.In our previous study, the deer s A to C . In the L. mazamae on white-tailed deer can mechanically transfer between individuals during direct contact between deer. In the present study, the Bartonella lineages of deer keds differed from those of four sampled deer , raising the possibility that wingless L. fortisetosa may also be able to transfer between individuals within the deer population. Given that Bartonella bacteria propagate in the ked midgut, Lipoptena keds may serve as a biological vector for transmitting Bartonella bacteria to deer.Deer keds are generally thought to stay on the same deer body after dropping their wings. However, Samuel and Trainer  found evB. schoenbuchensis can be transmitted not only vertically from adult L. cervi to offspring [L. cervi [Bartonella bacteria in L. fortisetosa.It has been suggested that ffspring , but alsL. cervi . UnfortuB. capreoli (lineage A) was not found in any deer keds examined in our study, although this Bartonella species was isolated from three sika deer. To date, B. capreoli has not been detected from L. cervi and/or L. mazamae in Europe and the USA although this species has frequently been isolated from several deer species. The absence of this Bartonella species in Lipoptena species suggests that other hematophagous arthropods may be involved in the transmission of B. capreoli between deer populations.Interestingly, L. fortisetosa likely serves as a vector of at least two Bartonella species in Japanese sika deer, similar to L. cervi and L .mazamae transmitting Bartonella bacteria to deer in Europe and the USA. In contrast, Ixodes and Haemaphysalis ticks may not play a significant role in the transmission of Bartonella in the sika deer.Our data indicate that