Past research has demonstrated that attention-deficit/hyperactivity disorder (ADHD), specific learning disorders (SLD), and socioeconomic status (SES) affect a host of educational outcomes. However, there are no studies examining whether SES moderates the association between these neurodevelopmental disorders (ND) and the academic achievement of children and adolescents. The present investigation examined the impact of ADHD and SLD on academic performance in 1,287 Spanish students aged 5–17 from a low-middle (LM)- and a high-income population, when adjusted for comorbidity and demographic factors that may influence educational functioning.Parents completed a questionnaire regarding demographic data along with the Strengths and Difficulties Questionnaire. Additionally, teachers provided information on learning difficulties trough the Protocol for Detection and Management of Dyslexia. Teacher’s Version. Academic performance across multiple domains  was obtained from school records. ND were determined using standardized diagnostic methods based on the Diagnostic and Statistical Manual of Mental Disorders criteria. To examine the effects of ADHD and SLD on academic achievement and the potential moderating role of SES, a series of ordinal logistic regressions were conducted.Emotional/behavioral problems, learning difficulties, and ND were more frequent among individuals from the LM-income population. After controlling for gender, age, parental divorce/separation, grade retention, frequency of screen use, and daily meals, both ADHD and SLD were associated with worse educational outcomes. Lower SES also increased the risk for academic impairment, although the interactions with ADHD or SLD were not significant.These findings indicate that ADHD and SLD exert a pervasive impact on academic performance across different socioeconomic backgrounds. Therefore, early detection and effective intervention strategies aimed at students with these ND are crucial to improve their educational functioning and mitigate the negative consequences related to academic problems. Neurodevelopmental disorders (ND) emerge at an early age and affect normal development, producing delays in the expected social, emotional, language, and cognitive performance. Attention-deficit/hyperactivity disorder (ADHD) and specific learning disorders (SLD) are among the most common ND in school-age children worldwide, with prevalence estimates ranging from 2 to 7% and 5 to 15%, respectively . ADHD isPast research has demonstrated a strong negative relation between ADHD symptoms and academic outcomes in clinical and community samples, with attention problems being the primary predictor of poorer achievement from early childhood into adulthood –6. TheseOn the other hand, demographic characteristics such as gender, SES, stressful events , and lifestyle behaviors  are also important variables that affect academic performance in children –35. In pThus, literature consistently shows that ADHD, SLD, and SES affect a host of educational outcomes in children and adolescents , 22, 36.The current cross-sectional population-based sample is part of a larger research called INSchool, which started in 2011 with the aim of identifying children and adolescents’ mental health problems in a school setting. For the current investigation, we used data from six different schools, which participated in this ongoing research during the academic years 2015–2016 and 2016–2017.The schools were equally distributed between two different territories of the Barcelona Metropolitan Area: Rubí, a LM-income area with 74,536 inhabitants, and Sant Cugat del Vallès, a high-income area with 87,830 inhabitants . Socioecn = 793) were boys and 48.2% were girls, with a mean age of 9.83 years . Demographic characteristics for the total sample and by SES are summarized in The LM- and the high-income sample included 836 and 694 participants, respectively. Overall, 51.8% . Finally, the information on academic performance was obtained from school records at the end of the academic year. The Department of Health and the Department of Education  authorized the project, and ethical approval was granted by the Ethics Committee of the Vall d’Hebron Hospital Universitari (PR(AG)72-2012), in Barcelona. Six schools from the Barcelona Metropolitan Area were contacted in two academic years  and invited to participate after explaining the study to the school staff. All of them accepted, which included four public primary and two secondary schools equally distributed across a LM-income and a high-income area. All students enrolled in the selected schools, with ages comprised between 5 and 17 years, were considered for study inclusion, resulting in 2,135 eligible subjects. A two-stage procedure was applied: in the first phase of the project , families were informed and we obtained informed consent for 1,699 children (participation rate = 79.6%), 693 of whom were at least 11 and also gave permission. Parents of the participating students received a questionnaire regarding demographic data and school-related factors along with the Strengths and Difficulties Questionnaire (SDQ) , which wnever, 2 = occasionally, and 3 = always), and reported how frequently the student played video games, used the cell phone, and social networks. Each of these three categories had four possible responses  and were summed to compute the mean frequency of screen use. Finally, sleep duration was derived from the answer to the following questions: “At what time does your child usually go to bed?” and “At what time does your child usually wake up?”Demographic data included child’s gender, age, country of birth, adoption, parental divorce/separation, and whether he or she had repeated any grade. Parents were asked if their child had ever received a diagnosis of ADHD, SLD, or another developmental disorder from a medical professional. They also provided information about their child’s eating habits by indicating how often they had breakfast, lunch and dinner , thus yielding a score that ranges between 0 and 10. Furthermore, a Total difficulties score may be derived by summing the first four subscales (range = 0–40). The parent and adolescent versions of the SDQ used in the present study have been validated as feasible instruments to identify mental health problems in children aged 5–17 by Español-Martín et al. . In the present study, subjects with five or more high-risk indicators on the PRODISCAT were regarded as potential cases of dyslexia.The PRODISCAT  is a scrThe K-SADS/PL  is a semThe PROLEC-R  is one oThe PROLEC-SE-R  evaluateThe TALE  allows tThe PROESC  aims to unsatisfactory achievement, fail, 0–4.9; C = satisfactory achievement, pass, average, 5–6.9; B = good achievement, above average, 7–8.9; and A = excellent achievement, 9–10). Given the high correlation between Catalan and Spanish grades , we calculated the academic performance on first language as the mean of the two scores.Academic performance on four core subjects  was obtained from school records at the end of the academic year. However, schools varied in the way they scored those subjects and, thus, grades were converted into a 4-point scale from D to A   , 60. TheIn order to determine whether there was evidence of clustering within the data, we first ran an intercept-only model for each educational outcome  with school as a random effect. Results from the unconditional models justified the use of a single-level approach, since the variance components for school were not significant, indicating that grades within schools were not different than grades between schools. A series of backward regressions were then performed to remove non-significant demographic predictors, followed by multiple ordinal logistic regressions that retained the significant demographic predictors identified in the preliminary analysis and added the primary variables of interest as described below. Analyses were conducted separately for each educational outcome, with A as the lowest category and D as the highest.p < 0.05) were retained.Gender, age, nationality, adoption, parental divorce/separation, grade retention, frequency of screen use, sleep duration, and having three meals a day were entered into a series of backward regressions. Significant predictors in each model  and their corresponding 95% confidence interval (CI) were reported. A two-sided p-value of 0.05 was set as significance level in all tests.To examine the impact of ADHD and SLD on academic achievement, and the hypothesized moderating role of SES, a series of ordinal logistic regressions were performed. As noted above, the significant demographic predictors from the preliminary analyses were entered in Step 1. ADHD and SLD (Step 2), and SES (Step 3) were then added to test main effects, while controlling for comorbidity. Last, we included interaction terms  into the final model (Step 4) and conducted stratified analyses in case of significant interactions. The Nagelkerke n = 793) of the participants were boys and 48.2% were girls, with a mean age of 9.83 years . The proportion of boys was higher in the LM- than in the high-SES sample , while foreign origin was more prevalent among children from the high-income group . The proportion of participants reporting parental divorce/separation, adoption, and not having three meals a day was larger in the LM-income population (p < 0.001).The LM- and the high-income sample included 836 and 694 subjects, respectively. Overall, 51.8% .p = 0.249). In particular, students who achieved a grade of A or B were over-represented within the high-income sample for all educational outcomes . By contrast, children from the LM-income population received lower grades, except on foreign language where the number of students with a grade of D was greater in the high-income group.As shown in n = 119) and did not differ by SES . Based on the diagnostic assessment conducted in the second phase, however, a total of 282 (21.9%) subjects met criteria for at least ADHD or SLD and significant differences were found between the LM- and the high-income sample . Specifically, 123 students were identified as having ADHD, which represented an overall prevalence rate of 9.56%. Of these, 63 (4.90%) met criteria for the combined presentation, 4.20% (n = 54) had the predominantly inattentive presentation, and 0.47% (n = 6) were diagnosed with the predominantly hyperactive–impulsive presentation. The prevalence of SLD was 16.4% (n = 211), with reading and writing difficulties being present in 15.4% (n = 198) and 6.29% (n = 81) of the total sample, respectively. Notably, children from the LM-income population appeared to have a significantly higher prevalence of SLD  and reading difficulties , while the rate of writing difficulties  and ADHD  was similar across samples. Last, over 18% (n = 52) of the students who received a diagnosis of ND suffered from both ADHD and SLD. Thus, the overall prevalence was 4.04% and did not differ by SES .According to parent reports, the prevalence of students who already had a diagnosis of ND prior to the start of the study was 9.25% (p < 0.001), parental divorce/separation , grade retention (p < 0.001), frequency of screen use , and not having three meals a day ; age, nationality, and adoption, on the other hand, were not retained (p > 0.05) for the primary analyses described below. Significant predictors of poor academic performance on mathematics included age (p < 0.001), parental divorce/separation (p < 0.001), grade retention (p < 0.001), and not having three meals a day (p = 0.038), while gender, nationality, adoption, frequency of screen use, and sleep duration were not retained (p > 0.05) . Results indicated that grades on first language and foreign language were negatively associated with male gender ( > 0.05) ; Step 1.OR = 3.94, 95% CI = 2.48–6.26, p < 0.001), while those with SLD were over 6 times more likely to perform poorly . SES was also found to predict academic achievement . These findings remained in Step 4 , where we added interaction terms into the final model to examine the potential moderating role of SES. However, there were no significant interactions between ADHD or SLD and SES . Furthermore, the effects of ADHD and SLD were still significant in Step 4  and did not differ by SES, since no significant interactions were observed . These associations remained mainly the same when interaction terms were introduced in Step 4 , although the interaction between ADHD or SLD and SES was not significant  in a sample of 1,287 Spanish children from a LM- and a high-income population, and whether the association was modified by SES, when controlling for comorbidity and demographic factors that may influence educational functioning.In accordance with previous studies –42, 61, Our findings also supported the hypothesis that ADHD would increase the risk for academic impairment and are consistent with previous literature, showing that youth with ADHD experience a variety of academic difficulties, including poor grades, low academic achievement, special education need, grade retention and failure to complete high school, even after adjusting for intelligence, SES, and learning disabilities , 11, 65.Overall, these results confirmed that ADHD, SLD and, to a lesser extent, low SES are significant predictors of poor performance across multiple academic domains, even after adjustment for comorbidity and demographic variables that may influence educational functioning . However, studies that examine the role of SES on academic achievement among children who suffer from these ND are surprisingly sparse. Indeed, the current research was the first to investigate whether high SES might attenuate the association between ADHD, SLD and adverse educational outcomes. Given the lack of significant interactions with SES and the strongest main effect observed for ND in all the academic domains assessed, our findings indicate that SES does not provide the hypothesized buffer against the negative impact of ADHD and SLD on academic performance. Similarly, a recent study, which evaluated whether the association between a clinical diagnosis of depression and lower educational attainment was modified by SES, did not find significant moderating effects .Considering that ADHD and SLD, unlike SES, are more easily modifiable risk factors, these results have large public health implications as the ADHD- and SLD-related academic problems can lead to both short- and long-term consequences, including lower productivity, unemployment, economic hardship, stress, anxiety, depression, and low self-esteem , 68–70. The current research should be interpreted in the light of some strengths and limitations. One of the main strengths is that, for the first time to our knowledge, we investigated the impact of ADHD and SLD on children’s academic performance across specific domains  in Spain, and whether SES moderates the association between ND and educational outcomes after adjusting for comorbidity and demographic variables that may influence educational functioning. Additional advantages include the large size and age range of the sample, composed of 1,287 students aged 5–17 years, and the comprehensive case identification through the administration of standardized screening instruments and DSM-based clinical interviews by trained psychiatrics and neuropsychologists. Moreover, our study involved the use of real-life measures of academic performance in a school-based sample, which allowed the detection of undiagnosed children and provides a more valid reflection of the general population than a clinical sample. Finally, we controlled for multiple demographic risk factors and limited shared method variance by using different informants for clinical diagnoses and academic achievement . NeverthOverall, the present investigation adds to the evidence for mental health disparities across socioeconomic backgrounds, and expands previous research on the relation between ND and academic performance by analyzing children from LM-income and high-income populations in order to determine whether SES moderates the association. Our results confirmed the higher prevalence of psychiatric symptoms, learning difficulties, and ND observed in disadvantaged communities. We also found that ADHD, SLD and, to a lesser extent, low SES are significant predictors of poor performance across multiple academic domains, even after adjustment for comorbidity and demographic variables that may influence educational functioning . However, SES did not modify the association, suggesting that students with a clinical diagnosis of ADHD or SLD are more likely to achieve lower grades on first language, foreign language, and mathematics regardless of their socioeconomic background. Given the extensive consequences associated with academic problems, these findings highlight the need for early detection and intervention strategies aimed at students who suffer from ND in order to improve their functioning at school. In this sense, integrating mental health services within the school setting or in routine pediatric revisions could be helpful, especially for children from low SES communities who might have limited access to health care. Moreover, the identification of factors that may attenuate the risk for academic underachievement conferred by ADHD and SLD is imperative to design and implement targeted interventions for particularly vulnerable individuals. Therefore, future research should explore other potential moderators, such as parental involvement, personal attributes and social networks, educational support, or treatment type and length. Alternatively, studies examining whether the relation between ND and academic performance is modified by SES should include participants from more financially disadvantaged backgrounds, and combine individual measures of SES with data at the community level to simultaneously estimate individual and contextual effects. Further, a broader selection of covariates  is required to fully validate the results of the current investigation.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the Ethics Committee of the Vall d’Hebron Hospital Universitari, the Department of Health, and the Department of Education . Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.GE-M, MP, and RB: study conception and design. GE-M, RP, and CR: data collection. GE-M, MP, and RP: data curation. GE-M and MP: data analysis and interpretation of results. JR-Q, MC, and RB: study supervision. MC: funding acquisition. GE-M and MP: writing–draft manuscript preparation. JR-Q, MC, and RB: writing–review and editing. All authors contributed to the article and approved the submitted version.This work was funded by Fundació “la Caixa,” Diputació de Barcelona, and Departament de Salut . The funders were not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.GE-M has received travel grants from Angelini Pharma, Laboratorios Rubió, Lundbeck, and Takeda for participating in psychiatric meetings. JR-Q has served on the speakers’ bureau and acted as consultant for Bial, Bristol Myers Squibb, Janssen-Cilag, Laboratorios Raffo, Laboratorios Rubió, Medice, Novartis, Shionogi, Shire, Sincrolab, Takeda, Tecnofarma, and Uriach. He has received travel awards from Bial, Janssen-Cilag, Laboratorios Rubió, Medice, Shionogi, Shire, and Takeda for participating in psychiatric meetings. The Department of Psychiatry chaired by JR-Q has received unrestricted educational and research support from Janssen-Cilag, Laboratorios Rubió, Oryzon, Psious, Roche, and Shire in the past 3 years. MC has received travel grants and research support from Eli Lilly and Co., Janssen-Cilag, and Shire. He has been on the advisory board and served as a consultant for Eli Lilly and Co., Janssen-Cilag, and Shire.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Background: Attention-deficit hyperactivity disorder (ADHD) is a condition which has been consistently documented to impact educational outcomes. Children with ADHD are regularly found to have lower educational attainment and increased likelihood of dropping out of school compared to children without ADHD.Objectives: To project the long-term societal economic consequences of reduced educational attainment, as measured by total lifetime earnings, in an untreated cohort of individuals diagnosed with ADHD in childhood, in Germany. In addition, this research aims at illustrating a cost-benefit analysis framework which could be applied to economically appraise the rate of return from investments in hypothetical health interventions targeting ADHD.Methods: Observational ADHD evidence was collated with demographic and human capital economics methods to quantify ADHD’s impact on educational attainment and long-term labour outcome in Germany. The theoretical benefits deriving from effective interventions targeting ADHD were also quantified.Results: It was estimated that the average per capita lifetime earning loss associated with ADHD was €92,000 suggesting a societal loss of €2.93 billion from a single cohort . The benefit-cost analysis suggested that reasonably effective intervention may justify considerable investment in ADHD targeted intervention.Conclusions: Considering the broad economic consequences of the condition might suggest that interventions which change the life course of individuals with ADHD could offer cost-savings and influence future economic outputs.


Development of sexual identity during adolescence is a major process of transition in individual life which in cases of ADHD specifically interacts with other ontogenetic, pathological and psychosocial conditions. According to recent findings growing consumption of internet pornography mainly in male ADHD population is closely related to compulsive sexual behavior and hypersexuality. Recent findings also indicate that consumption of internet pornography in ADHD individuals and other sexual activities may serve as a mood-altering “self-medication” which may help to cope with stressful events and decrease depression and anxiety. Taken together recent findings indicate that internet pornography consumption mainly in ADHD individuals is closely related to stressful experiences, anxiety, depression and identity problems in partnerships which significantly increase their vulnerability to the so-called “problematic pornography use” and other forms of addictive sexual behavior. From this developmental perspective “problematic pornography use” in ADHD individuals represents significant epidemiological problem which requires further research mainly with focus on clinical diagnostics and treatment. Development of sexual identity is a major process of transition in individual life that is mainly established during adolescence, and it is related to various physiological, anatomical and behavioral changes leading to development of sexual activities and fantasies –4. MainlOne of these specific pathological influences that may negatively affect normal development of sexual functioning and behavior is Attention Deficit and Hyperactivity Disorder (ADHD) mainly because executive dysfunctions usually related to ADHD may cause various problems mainly related to impulsivity and hypersexuality, aggressive behavior and other problems which may negatively affect psychological development of sexual identity and sexual functioning , 13, 15.Nevertheless, the diagnosis of ADHD as a developmental disorder according to the DSM-5 requires clear evidence that the symptoms may reduce the quality of life and everyday functioning mainly associated with a variety of risks factors –24. UsuaIn this context, some studies also reported lower relational satisfaction, impaired quality of romantic relationships, higher rate of separations and divorces, increased risk of intimate partner violence and verbal violence , 34 and Although ADHD likely has no direct influence on individual development and on sexual maturation in comparison to individuals without ADHD there is evidence that psychological development of sexual identity and functions is significantly affected by ADHD , 13, 15.Basic mechanism for this “self-medication” might be reward deficiency that is typical of ADHD  which caIn this context, some findings suggest that risky sexual behaviors in ADHD individuals represent a dysfunctional form of emotional regulation , 59, 60,According to recent findings hypersexuality is frequently related to compulsive form of sexual behavior (CSB) usually characterized by unsuccessful effort to control excessive sexual behavior that may lead to various psychopathological symptoms and negatively affect close relationships and partnership, and significantly decrease quality of life , 73–77. In this context, some studies indicate a strong association between ADHD and CSB , 80, 81 As epidemiological findings indicate, PPU in ADHD population but also in the general population became a widespread problem for mental health due to unlimited access of pornographic material on the internet and the availability of the internet , 83–86 aIn the 11th edition of the International Classification of Diseases (ICD-11), PPU is characterized by persistent, excessive, or compulsive use of pornographic content and intensive participation in it, despite distress and adverse consequences , 89–93. Some studies also suggest that ADHD symptoms may represent significant predictive factor for PPU –7, 96–98In addition some findings suggest that hypersexuality and PPU might be related to anxiety due to difficulties in forming a secure attachment during individual psychological development –102. DueThis severity of PPU as a mental health problem is documented by recent research which indicates that more than 80% of people seeking treatment for a compulsive sexual behavior disorder reported an inability to control their use of pornography, despite negative consequences , 122–126This increased interest to experience online pornography likely will increase susceptibility to PPU not just in ADHD individuals but also in general population and as some findings indicate PPU is associated with various sexual dysfunctions –132.Recently mental health problems related to pornography use became epidemiologically significant mainly because of severe increase in online pornography consumption by pre-adolescent children and adolescents , 76, 78,From this perspective further research regarding PPU and its clinical diagnostics and treatment represent significant epidemiological problem. Although the Compulsive Sexual Behavior Disorder (CSBD) is included in the International Statistical Classification of Diseases and Related Health Problems (ICD-11) , there iCurrently the evidence-based treatment methods of PPU, other forms of problematic online sexual behavior and CSBD in ADHD and other psychiatric patients , 137–143In this context of the treatment of ADHD individuals it is important to take into account that their PPU related problems may be related to their “reward deficiency” and “increased sensitivity” , 145. MaThe original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.MP and PB did the research and wrote the manuscript. All authors contributed to the article and approved the submitted version.This research was supported by Charles University project Cooperatio SVV.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Autism spectrum disorders (ASD) are neurodevelopmental conditions accompanied by differences in brain development. Neuroanatomical differences in autism are variable across individuals and likely underpin distinct clinical phenotypes. To parse heterogeneity, it is essential to establish how the neurobiology of ASD is modulated by differences associated with co-occurring conditions, such as attention-deficit/hyperactivity disorder (ADHD). This study aimed to (1) investigate between-group differences in autistic individuals with and without co-occurring ADHD, and to (2) link these variances to putative genomic underpinnings.We examined differences in cortical thickness (CT) and surface area (SA) and their genomic associations in a sample of 533 individuals from the Longitudinal European Autism Project. Using a general linear model including main effects of autism and ADHD, and an ASD-by-ADHD interaction, we examined to which degree ADHD modulates the autism-related neuroanatomy. Further, leveraging the spatial gene expression data of the Allen Human Brain Atlas, we identified genes whose spatial expression patterns resemble our neuroimaging findings.In addition to significant main effects for ASD and ADHD in fronto-temporal, limbic, and occipital regions, we observed a significant ASD-by-ADHD interaction in the left precentral gyrus and the right frontal gyrus for measures of CT and SA, respectively. Moreover, individuals with ASD + ADHD differed in CT to those without. Both main effects and the interaction were enriched for ASD—but not for ADHD-related genes.N = 25 individuals in the ADHD only group is relatively small compared to the other subgroups, which limits the generalizability of the results. Also, we assigned subjects into ADHD positive groupings according to the DSM-5 rating scale. While this is sufficient for obtaining a research diagnosis of ADHD, our approach did not take into account for how long the symptoms have been present, which is typically considered when assessing ADHD in the clinical setting.Although we employed a multicenter design to overcome single-site recruitment limitations, our sample size of Thus, our findings suggest that the neuroanatomy of ASD is significantly modulated by ADHD, and that autistic individuals with co-occurring ADHD may have specific neuroanatomical underpinnings potentially mediated by atypical gene expression.The online version contains supplementary material available at 10.1186/s13229-023-00568-z. Autism spectrum disorders (ASD) are highly heterogeneous neurodevelopmental conditions characterized by differences in social interaction and communication, alongside restricted, repetitive behaviors and interests . These fAutism is a condition with a high prevalence of co-occurring conditions. More specifically, 72% autistic adolescents have at least one co-occurring psychiatric disorder, and often meet diagnostic criteria for two or more co-occurring conditions . Among tSo far, only few studies have explored the neuroanatomy of autism with co-occurring ADHD. A study by Mizuno et al.  reportedTraditional investigations of brain structure have mainly focused on cortical volume, measured on the whole-brain, regional, and/or vertex-level. However, cortical volume is, by definition, the product of two different cortical features, namely CT and SA. Previous research by our group has shown that measures of brain volume, therefore, do not characterize a specific  aspect of the neural architecture, but can be explained by separable variations in CT and SA . These r = 0.22 for autism and schizophrenia (SCZ), r = 0.14 for autism and bipolar disorder; . From the neurodiverse control group without an ASD diagnosis, we collected those individuals who met criteria for ADHD as a third subgroup [further referred to as ADHD only group ] and those who did not meet ADHD criteria as our fourth subgroup [further referred to as typically developing (TD) controls ]. The ADHD DSM-5 rating scale was based on either parent- or self-report scores depending on participants’ age. For this study we used the categorical output of the ADHD rating scale, which measures the presence of symptoms, evaluated on a 0–3 scale . To be evaluated with a clinical concern, a participant must at least score six responses with a 2 or 3  . TherefAll participants underwent MR imaging in 3-T scanners, at six different sites . High-resolution structural T1-weighted volumetric images were acquired with full head coverage, at 1.2 mm thickness with 1.2 × 1.2-mm in-plane resolution  was used to derive models of the cortical surface for each T1-weighted image. These well-validated and fully automated procedures have been previously described elsewhere   Table . There wp < 0.05, two-tailed), the main effect of autism was associated with increased CT in the anterior-cingulate cortex  24/33), in the left superior and middle temporal gyrus (BA 21/22), and the right precuneus cortex (BA 31). By contrast, autism was associated with decreased CT in the parietal cortex (BA 7) and the middle frontal gyrus (BA 6/8/9)  for the main effects of autism and ADHD, and all other model terms are displayed in the Additional file Following RFT-based cluster-correction  was significantly modulated by co-occurring ADHD (or ASD) including the left parietal cortex (BA 7), precentral and superior frontal gyrus (BA 6/8), the right temporal gyrus BA 20/21/22), cingulate cortex (BA 23/24/33), and precuneus cortex (BA 31) for measures of CT   NCT = 272 and NSA = 1005 significant genes associated with the main effect of ADHD, and (3) NCT = 1258 and NSA = 233 significant genes associated with the ASD-by-ADHD interaction term. Within these gene sets, we observed a significant enrichment of genes known to be associated with autism, and particularly for genes that are known to be differentially expressed in autism during childhood and adolescence . This resulted in sets of (1) DHD Fig. A, B.Fig.Different gene sets were found to be enriched in the SA maps Fig. C, D. HerOverall , there was little overlap between genes significantly associated with the main effect of ASD, ADHD, and/or the ASD-by-ADHD interaction terms on the transcriptomic level . For exN > 500 that compare ASD or ADHD individuals with neurotypical controls [The effect sizes associated with the main effect of ASD and ADHD were relatively small, overall, and did not exceed a value of 0.2 on the vertex level. Small-to-medium effects associated with between-group differences in neuroanatomy have previously been observed even in large-scale neuroimaging studies with controls , 14. Thecontrols , thus hiWhile previous studies have focused on the effects of ASD and ADHD in separate case–control designs , 61, we Our additional analysis within the ASD ± ADHD subsample showed significant differences between both groups in the left precentral gyrus for measures of CT. Here, individuals with co-occurring autism and ADHD had a significantly thinner cortex compared to those individuals with autism alone. For measures of SA, no significant clusters for this contrast were observed. Taken together, our findings suggest that (1) the neuroanatomy of autism is significantly modulated by co-occurring ADHD symptomatology, and (2) although ADHD is highly co-occurring in autism, both conditions seem to have separable neuroanatomical underpinnings.In a next analysis step, we examined whether the patterns of CT and SA attributed to the main effects and the interaction term are linked to the genetic etiology of autism or ADHD. Similar to Romero-Garcia et al. , we founThis finding agrees with previous genetic studies demonstrating that ASD and ADHD are genetically correlated, with a SNP-based genetic correlation of 0.37 . Many ofMoreover, while ASD and ADHD are known to be genetically related, little is currently known about the functional involvement of genes that are specific to ASD and/or ADHD. Moreover, distinct imaging phenotypes could be caused by more complex genetic interactions between ASD- and ADHD-related genes, which cannot be identified based on the gene set enrichment analyses performed in the present study. This highlights the need for conducting future large-scale genome wide association studies (GWAS) to link genetic variation associated with neurodevelopmental conditions to differences in neuroanatomical phenotypes.Also, while we observed a significant enrichment of autism-related genes, there was no significant enrichment of ADHD risk genes in the main effect of ASD or ADHD. However, the number of recognized ADHD-susceptibility genes remains as yet small, which limits the statistical power of enrichment tests. Moreover, little is currently known about the functional role of ADHD genes and their impact on cortical gene expression. Future genetic and/or transcriptomic studies are therefore needed to provide further insights into the genomic underpinnings of ADHD, and to expand the set of genes that might be utilized to link ADHD-related differences in brain anatomy to putative underlying mechanisms.N = 25 individuals in the ADHD only group is relatively small compared to the other subgroups, which limits the generalizability of the results. Also, we assigned subjects into ADHD positive groupings according to the DSM-5 rating scale. While this is sufficient for obtaining a research diagnosis of ADHD, our approach did not take into account for how long the symptoms have been present, which is typically considered when assessing ADHD in the clinical setting. It will therefore be important to repeat our analyses in a bigger sample of pure ADHD cohorts that were diagnosed according to clinical gold standards to make our study comparable to previous findings in these cohorts. Furthermore, future studies employing a dimensional approach are also required to provide a more nuanced picture of the heterogeneity associated with autism. Last, our gene expression decoding analysis was based on the Allen Human Brain Atlas [The present study needs to be interpreted in light of several limitations. Although we employed a multicenter design to overcome single-site recruitment limitations, our sample size of in Atlas , which iOur findings indicate that the neuroanatomy of ASD is significantly modulated by ADHD, and that autistic individuals with co-occurring ADHD may have specific neuroanatomical underpinnings potentially mediated by atypical gene expression.Additional file 1. Methods. 1. Sample Description. 2. MRI Data Quality Assessments. 3. Effects of Intellectual Disability. 4. Site effects. 5. General Least Square (GLS)-decoding accounting for autocorrelations in spatially embedded transcriptomic maps. Figure S1A. Effects of Intellectual Disability (ID) for measures of cortical thickness (CT). Figure S1B. Effects of Intellectual Disability (ID) for measures of cortical thickness (CT). Figure S1C. Effects of Intellectual Disability (ID) for measures of surface area (SA). Figure S1D. Effects of Intellectual Disability (ID) for measures of surface area (SA). Figure S2A. Effects of acquisition sites for measures of cortical thickness (CT). Figure S2B. Effects of acquisition sites for measures of cortical thickness (CT). Figure S2C. Effects of acquisition sites for measures of surface area (SA). Figure S2D. Effects of acquisition sites for measures of surface area (SA). Figure S3. Significant differences of cortical thickness (CT) and surface area (SA) for the main effects of ASD, ADHD and the ASD-by-ADHD interaction term. Figure S4. Effect size plots for individual model terms. Figure S5A. Interaction plots for all significant clusters for measures of cortical thickness (CT). Figure S5B. Interaction plots for all significant clusters for measures of surface area (SA). Figure S6. Gene enrichments as resulting from the GLS-decoding approach Figure S7. Overlap between significant decoded genes. Table S1. MRI Acquisition Parameters across sites. Table S2. Vertex-wise differences in CT and SA for the main effect of ASD. Table S3. Vertex-wise differences in CT and SA for the main effect of ADHD. Table S4. Vertex-wise differences in CT and SA for the ASD-by-ADHD interaction term. Table S5. Vertex-wise differences in CT for the main effect of ASD + ADHD.


Attention deficit hyperactivity disorder (ADHD) has been characterized by impairments among distributed functional brain networks, e.g., the frontoparietal network (FPN), default mode network (DMN), and reward and motivation-related circuits (RMN). In the current study, we evaluated the complexity and functional connectivity (FC) of resting state fMRI (rsfMRI) in pre-adolescents with ADHD for pathology-relevant networks.We leveraged data from the Adolescent Brain and Cognitive Development (ABCD) Study. The final study sample included 63 children with ADHD and 92 healthy control children matched on age, sex, and pubertal development status. For selected regions in relevant networks, ANCOVA compared multiscale entropy (MSE) and FC between the groups. Finally, differences in the association between MSE and FC were evaluated.We found significantly reduced MSE along with increased FC within the FPN of pre-adolescents with ADHD compared to matched healthy controls. Significant partial correlations between MSE and FC emerged in fewer regions in the participants with ADHD than in the controls.The observation of reduced entropy is consistent with existing literature using rsfMRI and other neuroimaging modalities. The current findings of complexity and FC in ADHD support hypotheses of altered function of inhibitory control networks in ADHD. ADHD occurs worldwide and is estimated to affect 5% of children and approximately 2.5% of adults . AlthougIn ADHD, altered functional connectivity has been reported in the default mode network (DMN), frontoparietal network (FPN), and reward and motivation-related circuits RMN; . ImportaAlongside functional connectivity analyses that assess the signal coherence between nodes, nonlinear analyses of neural signals from fMRI that characterize the signal complexity within a node have been proposed as measures for information processing capacity of brain areas and networks , or indiIn the current study, we aimed to address this critical gap in the extant literature and evaluated the functional connectivity and complexity of rsfMRI in pre-adolescents with ADHD for the three main networks commonly associated with ADHD: FPN, DMN, and RMN. We combined MSE complexity analysis with functional connectivity analysis to elucidate the functional alterations present in ADHD on network nodes, at node-to-node edges, and on nodal complexity and node-to-node connectivity interaction levels. According to the literature, we hypothesized that compared to the healthy controls, pre-adolescents with ADHD had lower MSE in the FPN and altered functional connectivity in the FPN, DMN, and RMN. Due to the lack of previous studies, we did not postulate a hypothesis in terms of the difference between ADHD and control groups on the association between MSE and functional connectivity.2.2.1We leveraged the baseline demographic, clinical, T1 structural, and rsfMRI data from the Adolescent Brain and Cognitive Development (ABCD) Study . The ABC2.23, 256 × 256 matrix, flip angle = 8°, and 2x parallel imaging. Other scan parameters slightly varied by scanner platform, i.e., Siemens Prisma, Philips, or GE 3T scanner16. Each participant had 3–4 eyes-open (passive crosshair viewing) rsfMRI scans, each of which was approximately 5-minutes in duration. All rsfMRI scans were collected using a gradient-echo EPI sequence of 383 volumes in total . Head motion was monitored during scan acquisition using real-time procedures to adjust scanning procedures as necessary.All T1-weighted scans were acquired with voxel resolution = 1mmFor the current study, we used rsfMRI run1 and run2. Spatial and temporal image preprocessing was performed in the CONN toolbox . Default parameter setup was used including motion-realignment, coregistration and normalization to MNI152 template space and smoothing with a 6mm FWHM Gaussian kernel. In the denoising process, white matter, CSF, and motion realignment parameters were included for temporal preprocessing and denoising of rsfMRI data. While motion-scrubbing was included in the preprocessing for functional connectivity analysis, this step was excluded for complexity analysis.2.32.3.1github.com/kayjann/complexity) for each preprocessed and denoised rsfMRI sequence for each participant. SampEn is defined as the natural logarithm of the conditional probability that a pattern length of Voxel-wise multiscale entropy (MSE) was computed using the in-house developed LOFT Complexity Toolbox  by 2  analysis of covariance (ANCOVA) on the mean MSE in each ROI was conducted with PDS (self-reported) and scan-site as covariates. We were only interested in the main effects of Group here and in this study’s other ANCOVA analyses. To reduce skewness and kurtosis , PDS scores were Rankit-transformed and then z-scored. These values were used as the continuous covariates in all the ANCOVAs in the current study. A Benjamini-Hochberg correction  was perfIn order to evaluate the association between complexity and ADHD behavior symptoms, the partial correlation between MSE and CBCL DSM5 ADHD scores controlling for sex, PDS z-score, and scan-site was computed for the whole sample. We also computed the partial correlation between SampEn at each temporal scale and the CBCL DSM5 ADHD scores controlling for the same covariates for the whole sample. Note that the CBCL DSM5 ADHD scores were Rankit-transformed and then z-scored in this partial correlation analysis.2.3.2After data preprocessing and denoising, the first-level analyses on functional connectivity were conducted for each participant across both runs using the CONN toolbox default setup. Time series were averaged over voxels in each ROI, correlated between each pair of ROIs using Pearson’s correlation analysis, and then Fisher’s Z-transformed. The same ANCOVA including PDS z-score and scan-site as covariates was then performed for functional connectivity (Fisher’s Z-transformed) using a seed-to-seed analysis. A Benjamini-Hochberg correction  was perfIn order to evaluate the association between functional connectivity and ADHD behavior symptoms, the partial correlation between functional connectivity and CBCL DSM5 ADHD scores controlling for sex, PDS z-score, and scan-site was computed for the whole sample. Note again that the CBCL DSM5 ADHD scores were Rankit-transformed and then z-scored in this partial correlation analysis.2.3.3z score) between functional connectivity (between each seed ROI and each other ROI) and MSE in each seed ROI for each group by controlling for sex, PDS z-score, and scan-site. A group comparison (ADHD vs. controls) was conducted on the partial correlations for each  linkage. The same analysis was repeated for the partial correlation between SampEn at each temporal scale and functional connectivity.To investigate the association between complexity and functional connectivity, we computed the partial correlation  by 2  ANCOVA on the mean MSE in each ROI was conducted with PDS z-score and scan-site as covariates. The same ANCOVA was repeated for SampEn at each temporal scale and for functional connectivity at each seed-to-seed edge.3.3.1There were no group differences in age 3.2t-tests indicated that the participants with ADHD had lower MSE values than the controls in all the ROIs in FPN  by 2  ANCOVA on the mean MSE in each ROI was conducted with PDS z-score and scan-site as covariates. Please refer to The same ANCOVA was replicated for functional connectivity at each seed-to-seed edge. It revealed significant main effects of Medication at two edges, i.e., left middle frontal gyrus-to-right frontal orbital cortex  reduced rsfMRI complexity in areas of the FPN in pre-adolescents with ADHD as compared to the matched controls, and (2) increased functional connectivity between anterior portions of the FPN in the ADHD group relative to the control group. We did not observe a significant group difference in terms of the association between complexity and functional connectivity in any interested linkage.The FPN has been hypothesized to play a role in instantiating and flexibly modulating cognitive control . CognitiThe observation of significant reductions in MSE in rsfMRI time series in pre-adolescents with ADHD was consistent with the findings in adults with ADHD using the same modality . Guan etenhanced connectivity within FPN, i.e., the right superior frontal gyrus and left middle frontal gyrus using the anterior cingulate gyrus as the seed in pre-adolescents with ADHD  by 2  ANCOVA on the mean MSE, SampEn at each temporal scale, and functional connectivity in each ROI was conducted with PDS z-score and scan-site as covariates. The result after correction indicated no significant main effects of Medication for MSE, SampEn at each temporal scale, and functional connectivity in any ROI. Second, it is worth mentioning that the patients included in the current work had no previous or current psychiatric diagnoses other than ADHD. Many previous complexity studies in ADHD indeed examined ADHD with potential various comorbidities such as oppositional defiant disorder/conduct disorder that might confound the results. The current results removed this concern and further confirmed the finding of reduced complexity. Moreover, the lack of a unified understanding of functional connectivity in ADHD across literature may be due in part to different rates of comorbid conditions in those studies. The current finding of enhanced functional connectivity in ADHD relative to the controls in the FPN might potentially contribute to clarifying the mystery and provide a greater understanding of this field. Third, due to the limitation of networkwise Benjamini-Hochberg correction, the group difference in terms of cross-network functional connectivity and cross-network partial correlation between MSE and functional connectivity was absent. However, we showed significant cross-network group differences in In conclusion, our analyses support the feasibility and utility of temporal signal entropy in investigating the changes in complexity of rsfMRI signals in pre-adolescents with ADHD when compared to healthy controls. We found reduced complexity in the anterior cingulate gyrus, bilateral middle frontal gyrus, and bilateral superior frontal gyrus in the FPN and greater functional connectivity in the right superior frontal gyrus and left middle frontal gyrus using the anterior cingulate gyrus as the seed in pre-adolescents with ADHD. We suggest that combining analyses of complexity and functional connectivity is a useful and easily obtainable measure to reveal changes in ADHD brain dynamics.Supplement 1


Spirodela, Landoltia, Lemna, and Wolffia genera, including interspecific hybrids, auto- and allopolyploids. Genome size measurements revealed no quantitative genomic changes potentially caused by cryopreservation. The expression of CBF/DREB1 genes, considered as key factors in the development of freezing tolerance, was studied prior to cooling but was not linked with duckweed regrowth after rewarming. Despite preserving chlorophyll fluorescence after rewarming, the rewarmed fronds demonstrated nearly zero photosynthetic activity, which did not recover. The novel protocol provides the basis for future routine application of cryostorage to duckweed germplasm collections, saving labor for in vitro cultivation and maintaining characterized reference and mutant samples.Vegetatively propagating aquatic angiosperms, the Lemnaceae family (duckweeds) represents valuable genetic resources for circular bioeconomics and other sustainable applications. Due to extremely fast growth and laborious cultivation of in vitro collections, duckweeds are an urgent subject for cryopreservation. We developed a robust and fast DMSO-free protocol for duckweed cryopreservation by vitrification. A single-use device was designed for sampling of duckweed fronds from donor culture, further spin-drying, and subsequent transferring to cryo-tubes with plant vitrification solution 3 (PVS3). Following cultivation in darkness and applying elevated temperatures during early regrowth stage, a specific pulsed illumination instead of a diurnal regime enabled successful regrowth after the cryopreservation of 21 accessions of  The Lemnaceae (duckweeds) are the smallest and fastest growing aquatic monocotyledonous flowering plants. Due to their high adaptability to environmental conditions , high growth rate, and capability to be dispersed by migratory waterfowl, duckweeds are widely distributed on all continents except Antarctica . Due to The fast growth of duckweed populations is ensured by vegetative propagation, while formation of flowers and seeds occurs rarely, possibly due to the fact that some species of duckweed are interspecific hybrids ,6. There2O molecules [Cryopreservation is currently considered to be the most efficient method for the long-term preservation of vegetatively propagating plant germplasm and an alternative to permanent in vitro maintenance . Among colecules . Dimethyolecules  and incrolecules . While tolecules , PVS3 doolecules  and is tSo far, Lemnaceae proved recalcitrant to conventional cryopreservation techniques because living in fresh water habitats makes them sensitive to desiccation stress. In addition, the duckweed fronds contain a thick layer of aerenchyma with considerable air chambers, which provide reliable buoyancy of duckweed. The surface of the air-faced side is similar to the adaxial surface of terrestrial plant leaves with stomata, cuticle, and wax layers, while the water-faced side additionally is covered with lignin/suberin layers , which aLandoltia and Lemna genera was reported by Sauter (1993) [Spirodela, Wolffia, and Wolffiella genera, no reproducible regrowth after cooling in liquid nitrogen was achieved. The US patent WO2011005502A3 [The first successful application of cryopreservation by vitrification to duckweed accessions of r (1993) , applyin005502A3  uncovers005502A3 . It is b005502A3 , thus giCBFs enhance freezing tolerance [CBF expression might be predictive for cell viability after cryopreservation and searched for a potential correlation between CBF gene expression during cryopreservation and the subsequent ability of duckweeds to regrow.The aim of this study was to develop a simple cryopreservation method for a wide range of Lemnaceae accessions. In addition, the effects of cryopreservation on the photosynthetic performance of duckweed fronds was examined. Moreover, to elucidate the importance of the integrative regulatory hub in plant responses to low temperature, the C-repeat binding factors/dehydration-responsive element binding protein (CBF/DREB1) transcription factors was investigated. CBF/DREB1s were described as the main link regulating cold- and drought-responsive genes ,27,28. Tolerance ,32, whilolerance ,34. TherLe. gibba 7742 were blotted on filter paper and exposed in 1 mL of PVS3. To ensure complete and reproducible penetration of PVS3 [Excised shoot apical meristems are the most frequently used explants for cryopreservation by vitrification. During duckweed frond development, no cytohistological zonation and/or delimitation of a tunica and corpus occur at the frond tip, indicating that no conventional shoot apical meristem is formed . Potenti of PVS3  and to a of PVS3 . To impr of PVS3 ,39, foll−2·s−1) in a phytochamber for 1 day. We hypothesized that rewarmed duckweed fronds may develop daughter fronds when bleaching is delayed. Therefore, early efforts were focused on finding conditions that delay bleaching.After the first cryopreservation experiments following the protocol given in w/v) is reported to be toxic for many plant species [A high concentration of glycerol in PVS3  is often used to rescue interspecific hybrid embryos . Therefor fronds . The newLe. gibba 7742: (1) standard (12/12 h light/dark cycle at 25 °C/22 °C); (2) cold acclimation , and (3) imitation of night frost , with or without increased osmotic pressure (0.015 to 0.4 M sucrose) during 6 days. Overall, pre-cultivation in a medium with 0.4 M sucrose under standard growth conditions provided the best regrowth  on day 11 , and subsequently, three days under the “30/30” regime and transfer of rewarmed plants to standard cultivation condition  duckweed sampling and transfer of the fronds to the tube, (2) spin-drying of plant material, and (3) maintaining the duckweed fronds under the PVS3 surface in cryo-tubes during cryoprotection and cryo-cooling stages. After PVS3 vitrification using a perforated aluminum foil, the regrowth results for Le. gibba 7742 using 0.4 M sucrose for pre-culture was less optimal for other duckweed accessions, presumably due to a lack of adaptation to all components of PVS3. Therefore, the pre-culture medium was supplemented with either glycerol or sucrose or both for comparison and tested for Le. gibba , La. punctata 7260, and S. polyrhiza 9509  and small molecule size. Therefore, glycerol can interact more efficiently with the lipid bilayers and membrane proteins and can stabilize them during cryopreservation .After obtaining promising regrowth results for six accession from three Lemnaceae genera , we cryoAlmost all tested accessions demonstrated regrowth substantially higher than 15%, the minimum viability value, established in our laboratory, and only for two of them, the regrowth was close to this cut-off value.Le. gibba 9206 and Le. minor 9533, as well as of interspecific hybrids Le. gibba × minor 7641, Le. japonica (minor × turionifera) 8434 and allopolyploid interspecific hybrid Le. japonica (minor × turionifera) 8627,  8627, .Overall, no quantitative genomic changes were found between the duckweed fronds prior to cryopreservation and the newly developed fronds after cryopreservation. Regrown duckweeds were true to type according to the data from flow cytometry; therefore, the developed method for duckweed cryopreservation could be used for long-term conservation without concern for alteration in the genome size during regrowth.The observed bleaching of duckweed fronds under illumination after rewarming raised the question about a possible correlation between functional activity of the photosynthetic apparatus in chloroplasts and the regrowth of daughter fronds. To address this question, we monitored the functional activity of the photosynthetic apparatus of rewarmed fronds during two weeks after rewarming by measuring a set of chlorophyll fluorescence parameters and subsequent calculation of photosynthetic performance in samples differing in regrowth due to different pre-cultures see .0) of the dark-adapted plants, the maximal fluorescence level (Fm) transiently induced by a saturating light pulse, the maximum fluorescence yield in the light-adapted state (Fm′), and the fluorescence under actinic illumination (Fs) for the Le. gibba 7742, Le. gibba 7796, Le. gibba 7922, and Le. gibba 9602 rewarmed fronds that were pre-cultured in three different solutions before cryopreservation. The photosynthetic performance was estimated by calculating the variable fluorescence (Fv), maximum quantum yield of photosystem II (Fv/Fm), and operating efficiency of photosystem II (ΦPSII)  is closely connected to the photochemical reactions. Changes in Fv reflect mainly the redox state of the first stable electron acceptor in PSII plastoquinone A.We measured the minimal fluorescence level (FSII) see . F0 deri0 and Fm as well as between accessions and pre-culture conditions  in all cases demonstrated values on average not more than 10% of values for intact control plants , the new daughter fronds started to grow. At this stage, the surfaces of these new tiny fronds started to overlap with the surfaces of rewarmed mother fronds; thus, a precise separation between the areas of the rewarmed fronds from areas of the new fronds was impossible during fluorescence data processing. Up to day 7, the new fronds reached larger dimensions and developed their photosynthetic apparatus. Thus, subsequent decreasing of the F0  and Fm , distinguishing them from related ERF transcription factors [Le. gibba, 28 genes of La. punctata, and 20 S. polyrhiza-encoding proteins with a DREB-specific domain  together with the Arabidopsis CBFs AtCBF1-4. The identified CBFs are highly similar and form an individual subtree. The identified proteins from Le. gibba, La. punctata, and S. polyrhiza, we designated as LgCBF1, LgCBF2, LgCBF3, LpCBF1, LpCBF2, SpCBF1, and SpCBF2. Besides the AP2/ERF domain, which is involved in DNA binding, the CBFs possess the LWSY-motif in the activation domain at the C-terminus and a nuclear localization signal (NLS) near the AP2/ERF domain  and even on different chromosomes.DREB protein subfamily members contain a highly conserved APETALA2/ethylene-responsive element-binding factor (AP2/ERF) domain with a characteristic valine residue at position 14 that determines the binding affinity to  factors ,61. Usinc domain . These pps I–IV, . Since GF domain . Unlike CBF/DREB1 genes, we analyzed their promoter regions for the presence of regulatory cis-elements. The survey revealed both E- and G-boxes in the duckweed CBF promoters that indicates the possibility of regulation of their expression by low temperature and light (CBF genes contained multiple elements responsive to water stress and dehydration (MYC) as well as to methyl jasmonate, abscisic acid (ABRE), and ethylene (ERE). Compared to Arabidopsis, the promoters of duckweed CBF genes have reduced numbers of cis-elements for the circadian rhythm of expression.To gain insight into the transcriptional regulation of nd light . All proCBFs is regulated by a circadian clock in Arabidopsis [LgCBF1-3 in Le. gibba 7742 every 4 h during a day and revealed no oscillation of mRNA abundance for LgCBF1, whereas LgCBF2 and LgCBF3 showed circadian regulation with a peak at 4:00 corresponding to the Zeitgeber unit . After the addition of 0.4 M sucrose, all tested genes were induced and showed elevated transcript levels, especially for LgCBF1, with an expression 80-fold higher than that under the control condition . The highest mRNA abundance was recorded for LgCBF1 after treatment with 0.4 M sucrose at 4 °C. The mRNA abundance of reatment , usuallyCBF genes during cryopreservation and the ability to re-grow, the mRNA abundance of CBF1 and CBF2 turned out to be highly variable. The level of LgCBF1 mRNA abundance of Le. gibba 7742 was the highest after pre-culture with 5% glycerol and 0.4 M sucrose , was applied. Before the cryopreservation, the duration of the last subculture of donor duckweed plants was 1–2 weeks.Duckweed accessions used in this study are from a stock collection at the Matthias Schleiden Institute—Plant Physiology, University of Jena, and were kindly provided by Klaus Appenroth . Duckwee−2·s−1 with the spectrum shown in For cold acclimation see  of the dLe. gibba were pre-cultured in solutions of different composition according to For chlorophyll fluorescence measurement see , duckweeCBF gene expression .For diurnal rhythm analysis of sion see , 21 flasFor the gene expression analysis during preparation of the duckweed for the cryopreservation procedure see , duckweeLycopersicon esculentum Mill. convar. infiniens Lehm. var. flammatum Lehm. ‘Stupicke Rane’  as an internal reference standard using the DNA staining kit ‘CyStainR PI Absolute P’ . Approximately 10,000 nuclei per sample were analyzed, and at least four independent measurements per clone were performed on two independent days. The absolute DNA contents (pg/2C) were calculated based on the mean values of the G1 peak and the corresponding genome sizes (Mbp/1C) according to [Genome size measurements were performed according to  using a rding to .Chlorophyll fluorescence parameters were measured using the pulse-amplitude-modulated (PAM) technique ,69,70 an0) was determined by applying a weak, pulsed measuring light (PAR ≤ 0.2 µmol photons m−2 s−1) that does not drive photosynthesis, and a saturating light pulse  was applied to induce the transiently maximal fluorescence level (Fm).In the dark-adapted state, the minimal fluorescence level (Fv) was calculated as follows: Variable fluorescence  was measured during exposure to a saturating light flash, and the operating efficiency of PSII (ΦPSII) was determined from the steady state chlorophyll fluorescence under actinic illumination (Fs) and Fm′ according to the following equation: Subsequently, induction of chlorophyll fluorescence was followed for 3 min at a light intensity of 100 µmol photons mThe fluorescence data were processed using FluorCam7 software  and subsequently were exported to MS Excel for further calculation and charts drawing. During fluorescent data processing for each separated frond or unseparated colony, the individual areas were selected manually with subsequent background exclusion using a cut-off value of 20. The areas corresponding to new daughter fronds which appeared after rewarming were manually (as precise as possible) excluded from the areas of rewarmed mother fronds.The measured values of the fluorescence parameters of each individual frond or colony were averaged for each sample by all rewarmed 24 fronds or colonies in each Petri dish (that represented 8 fronds randomly taken at the second day after rewarming from 3 cryo-tubes).Arabidopsis thaliana and from the monocotyledonous model plant Ozyza sativa OsDREB1A , and OsDREB1B , OsDREB1C , downloaded from the NCBI database [DREB gene subfamily members in genomes of Le. gibba 7742a , La. punctata 5635 DWC138 , and S. polyrhiza 9509  available on the CoGe Comparative Genome Browser [CBFs, the sequences 2000 bp upstream from the start codon of the CBF genes were extracted from the genome database and analyzed using the PlantCARE tool [To access the duckweed orthologues of genes encoding transcription factors of the CBF/DREB1 family, we searched the duckweed genome sequences using as queries the reference protein sequences of AtCBF1 , AtCBF2 , and AtCBF3  from the dicotyledonous model plant  Browser . To veri Browser . Multipl Browser , as impl18 , in a total volume of 20 µL and diluted to 1:5 with nuclease-free water. qRT–PCR was performed in a 384-well thermocycler QuantStudio™ 6 Flex Real-Time PCR System  using the PowerUp™ SYBR™ Green Master Mix  and gene-specific primers  from 100 μg of duckweed fronds, which were collected, thoroughly blotted, frozen in liquid nitrogen, and then ground using a RNeasy Plant Mini Kit . The quantity of isolated RNA was estimated using a NanoDrop One C spectrophotometer . In total, 500 ng of total RNA was used as a template for synthesis of the first cDNA strand, using RevertAid H Minus First Strand cDNA Synthesis Kit, primed by oligo(dT)t method  and visuThe relative spectral power distribution of light from the light sources in the phytochamber, used in experiments, was measured using the HPCS300P Spectral Illuminance Sensing Module . The data processing was performed using OHSP Spectral Illuminance Analyzer V 1.42 software .All experimental conditions were reproduced independently a minimum of 3 times as biological replicates. Each biological replicate included 3 technical repeats as 3 cryo-tubes, the duckweeds of which were independently processed after rewarming. Using whole duckweed fronds submersed in PVS3 as the material for cryo-cooling and due to the relatively small dimensions of duckweed fronds, we did not calculate the exact number of fronds that we transferred to the cryo-tube.Le. gibba 7742 fronds transferred to the cryo-tubes during optimization experiments (25–50 fronds per cryo-tube) was calculated by visual analysis of 40 representative photo-images of the rewarmed fronds, transferred from one cryo-tube to a glass tube with liquid nutrition medium after rewarming. To accelerate and simplify the collection and processing of the results of the optimization experiments, the regrowth events per cryo-tube, observed for all 3 biological replicates and the technical repeats for each experimental condition, were visually calculated and provided as a range from absolute minimal to maximal values.The number of CBF1-2 expression and chlorophyll fluorescence measurements. The regrowth was calculated for 24 separated duckweed fronds (or colonies) per experimental condition, three in each well of a 24 well plate filled with SH medium and supplemented with 0.5% sucrose and 0.5% glucose (pH 7.1–7.2). The three times 8 wells represented 3 technical repeats (corresponding to 3 cryo-tubes). Each well of the plates was photo-documented for subsequent regrowth calculation. The resulting regrowth of each well can take one of four values: 0—no regrowth event detected in the well; 1—one rewarmed mother frond or unseparated colony generated (a) new frond(s); 2—two rewarmed mother fronds or unseparated colonies generated new frond(s); and 3—three rewarmed mother fronds or unseparated colonies generated new frond(s). The values for the regrowth for each of the 8 wells with the fronds from one technical repeat were summarized  and were divided by 24 (the whole number of monitored rewarmed fronds from a given cryo-tube). To obtain the average regrowth, the mean values and standard deviation were calculated for all biological replicates for each used duckweed accession and/or experimental condition. All calculations were performed using MS Excel software from Microsoft Office Standard 2019. The standard deviation values were calculated using the “STDEV.S” function.The average regrowth was calculated for the experiment aimed at optimizing the solution composition for pre-cultivation for all tested duckweed accessions cryopreserved using the optimized cryopreservation protocol and for experiments of Spirodela, Landoltia, Lemna, and Wolffia. Cryopreservation of duckweed did not cause obvious changes in the genome size of polyploids or interspecific hybrid accessions. Using whole duckweed fronds instead of excised meristems for cryopreservation saves time and labor and allows for rapidly changing conditions for optimization. To our best knowledge, the representatives of the Lemnaceae family are the first freshwater angiosperms being successfully cryopreserved and, therefore, could be considered as the basic model for the cryopreservation of vascular freshwater aquatics.A simple, fast, and DMSO-free protocol for cryopreservation by vitrification of duckweed was developed. The protocol was successfully tested on a wide range of Lemnaceae accessions of the genera A combination of pulsed illumination with elevated cultivation temperature for the early regrowth stage yielded for most tested duckweed accessions a substantial increase in regrowth that was in all cases higher than the minimal viability criteria of 15%. Using a newly designed single-use perforated foil insert allowed for fast and less laborious sampling of duckweed fronds from the donor culture, providing increasing protection against contamination, especially when simultaneously working with a large number of accessions, and decreasing the variability in regrowth results by spin-drying of duckweed fronds from the rests of liquid nutrition medium before submersion in PVS3.Despite a substantial amount of chlorophyll in the rewarmed fronds, their photosynthetic machinery in the chloroplasts was not functional and did not recover. A green color of the rewarmed fronds and chlorophyll fluorescence by itself cannot be considered for viability. However, monitoring of photosynthetic performance via measurement of the chlorophyll fluorescence parameters of rewarmed fronds can serve as sensitive and non-destructive real-time tool for the detection and estimation of early regrowth of new fronds emerging from rewarmed fronds after cryopreservation. Moreover, this method can point out potentially non-optimized elements in the protocol for early regrowth.CBF during the preparation of duckweed for cryopreservation cannot be used as a genetic marker for viability and regrowth competence after cryopreservation. Probably, the CBFs are necessary for adaptation to various abiotic stress appearing during cryopreservation but are insufficient to predict successful regrowth of duckweed after cryopreservation.The mRNA abundance of Overall, our novel cryopreservation protocol  provides


Previous observational researches have discovered a connection between circulating concentrations of micronutrients and attention deficit hyperactivity disorder (ADHD). However, the results may be influenced by confounding factors and reverse causation. This study aims to explore the causal relationship between circulating concentrations of micronutrients and ADHD using Mendelian randomization (MR). In a two-sample MR context, we used summary data from the major European genome-wide association studies (GWAS) for these illnesses to assess the genetically anticipated effects of circulating concentrations of micronutrients on ADHD risk. In order to achieve this, we took single nucleotide polymorphisms (SNPs) from the GWAS that were highly related with concentrations of nine micronutrients. The corresponding data for ADHD were extracted from the Psychiatric Genomics Consortium. Inverse-variance weighted (IVW) method was used as the main MR analysis, and the reliability of the study’s conclusions was assessed using sensitivity analyses. Our MR analyses showed that the copper level may be associated with a reduced risk of ADHD. However, the significance of the research results is weak. There were no clear relationships between other micronutrients and ADHD. Our sensitivity studies confirmed the findings of the primary IVW MR analyses. According to this study, there may be some association between copper level and ADHD, but the significance of the research results is weak, and it is recommended that copper level should be used as a long-term monitoring indicator for further research. The results provide a new idea for the further study of ADHD, and provide guidance for the prevention and treatment of ADHD. According to the study, one of the most prevalent childhood problems is ADHD, which affects 7.2% of children3. As a complex disease caused by genetic, social and environmental factors, ADHD symptoms can last for several years, and have extensive and lasting negative effects on children's study, work, life and other aspects5. At the same time, the potential link between micronutrients and ADHD has attracted extensive attention from researchers, which can offer fresh suggestions for ADHD treatment.In children and adolescents, attention deficit hyperactivity disorder (ADHD) is a prevalent mental disorders. The main clinical manifestations are age-inappropriate obliviousness, impulsivity, hyperactivity and other behaviors10. Kids with ADHD reported significantly lower levels of iron, magnesium, zinc, and vitamin D compared with normal healthy children, suggesting a link between micronutrients and mental disorders11, it is unknown if these relationships are causative. Mendelian randomization (MR), which uses genetic variation as an instrumental variable, can be used to determine whether there is a probable causal association between exposures and disease14.Micronutrients include vitamins and minerals needed by the human body, which have a key part in the growth and development of the human body and the prevention and treatment of diseases. Previous research has found the correlation between several serum micronutrients  and psychiatric disorders such as ADHD15. As the genotype is assigned at random during conception, genetic variants are unaffected by potential confounding factors, so it can overcome the limitation of traditional observational research17.MR is an important tool in epidemiological studies, can effectively use the Genome—wide Association Study (GWAS) data as a result, genetic variation as the instrumental variables (IVs), to investigate the relationship between an interesting exposure and an outcomeWe investigated the probable causal connection between nine micronutrients  and ADHD in the present study, using a two-sample Mendelian randomization study. Our results will provide new directions for the mechanisms and treatment of ADHD.18: (1) IVs and the concentration of circulating micronutrients are strongly associated, (2) There are no confounders influencing both exposure and outcome that are related to IVs, (3) IVs only affect ADHD through circulating micronutrient concentration. This study followed the recommendations of the STROBE-MR19. Figure The two-sample MR approach was used to examine the potential causal relationship between the concentration of circulating micronutrients and ADHD. The reliability of the results is tested by sensitivity analysis. To ensure the reliability of the results, MR is based on three critical assumptions20. The PGC aimed to facilitate quick progress in revealing the genetic basis of psychiatric diseases by unifying most of the field’s genetics research21. There were 20,183 individuals diagnosed with ADHD and 35,191 controls from 12 cohorts. Only individuals of white European descent were included in our research to reduce any confounding caused by ancestry .Genotype data on ADHD were extracted from the Psychiatric Genomics Consortium (PGC)22, IEU OpenGWAS (https://gwas.mrcieu.ac.uk/), and Pubmed. The initial inventory contains 15 nutrients: iodine, lead, zinc, magnesium, copper, arsenic, manganese, folate, selenium, iron, and vitamins A, vitamins B1, vitamins B2, vitamins B12, and vitamins D24. Due to the lack of GWAS, Vitamins B1, B2, iodine, arsenic, manganese and lead were eliminated. In total, nine micronutrients with appropriate genetic instruments were examined in this study: magnesium, iron, copper, zinc, selenium, vitamin A, B12, D and folate30.The comprehensive details for the GWAS datasets used in this research was presented in Table Published GWAS on micronutrients, were searched by using GWAS Catalog−8), all SNPs connected to a relevant exposure were retrieved. Since some phenotypes have fewer SNPS (less than 3), we expand the P-value to 5 × 10−6, or even 5 × 10−4, as in copper. Independent SNPs were chosen using conventional clumping factors 31. These SNPs are not in LD. Phenoscanner database (http://www.phenoscanner.medschl.cam.ac.uk/) searches were done to make sure the contained SNPs weren’t connected to any known confounding factors. The strength of association between IVs and exposure factors was evaluated by calculating F statistics. The following formula was used to determine the F statistic: F = R2 × (N − 2)/(1 − R2)32. Only SNPs with an F statistics > 10 were used in future analyses to reduce weak instrument bias. Meanwhile, ambiguous and palindromic SNPs were removed in the harmonizing process. Finally, this research identified 279 SNPs associated with 9 circulating micronutrient concentrations as IVs, including 6 SNPs for magnesium, 129 SNPs for copper, 13 SNPs for iron, 7 SNPs for zinc, 11 SNPs for selenium, 8 SNPs for folate, 7 SNPs for vitamin A, 7 SNPs for vitamin B12, and 94 SNPs for vitamin D. The comprehensive details for genetic IVs used in this research was presented in Supplementary Table At the genome-wide significance level  were used for sensitivity analysis. To assess the degree of heterogeneity, we used Cochrane’s Q heterogeneity test, with p < 0.05 indicating a high rate of heterogeneity. When there is high heterogeneity (P < 0.05), the multiplicative random effect IVW method is used37. By examining whether the intercept of the connection between exposure and outcome differs from zero, the MR-Egger method can identify potential pleiotropy36. After adjusting for pleiotropy, the method then provides a more conservative estimate of causal effects38. To reduce the bias caused by horizontal pleiotropy, this study used MR-PRESSO39 to detect broad horizontal pleiotropy in all results. Furthermore, using leave-one-out sensitivity analysis, it was determined whether the results were influenced by individual influential SNPs. R software (version 4.1.2) was used for this study's total data analysis. The R packages used include the TwoSampleMR and MR-PRESSO packages.In this study, five methods, such as inverse-variance weighted (IVW), MR-Egger, weighted median, modal-based simple estimation, and modal-based weighted estimation, were used to conduct Mendelian randomization analysis of two samples, and the odds ratio (OR) value and 95% confidence interval (CI) were used to evaluate the potential causal relationship between micro-nutrients and ADHDF statistics did not suggest the existence of weak instrumental bias F > 10). Figure 0. FigureThe IVW method, the key MR analysis, was not impacted by heterogeneity in any of the studies, according to Cochrane’s Q test Table . Given tIn this research, we systematically assessed the causal relationships between nine micronutrients  and ADHD using a two-sample MR method. The findings revealed that no genetic evidence was found for a significant causal link between circulating concentrations of the remaining micronutrients and the risk of ADHD, which held up well in various sensitivity analyses. This may imply that reported epidemiological associations may be the result of confounding factors that cannot be controlled for.40. In another randomized controlled trial of micronutrient treatment for ADHD, Rucklidge et al. reported that ADHD patients with micronutrient treatment showed significant improvement in symptoms such as inattention, compared to the control group41. In addition, an observational study of 810 children by Huss et al. showed that magnesium and zinc intake had a positive effect on symptom improvement in children with ADHD, which is similar to those discovered in a research by Rucklidge et al.42. However, in our MR research, no significant association was found between circulating micronutrients and the occurrence of ADHD.Our results are contrary to those of a meta-analysis by Khoshbakht et al. who suggested a strong connection between vitamin D levels and the development of ADHD44, there is a connection between vitamin D and cognitive function. In the central nervous system, VDR is a nuclear receptor. 1,25(OH)2D3 binds to VDR to control the expression of dopaminergic genes. These findings confirm the hypothesis that the risk of ADHD might be mediated by circulating concentrations of micronutrients. However, these findings do not mean that changes in these micronutrient concentrations directly cause ADHD, and cannot resolve the previous controversy over whether micronutrient deficiencies are a cause or a result of ADHD. In summary, these findings support an association between ADHD and micronutrients, but, based on our MR study, there may not be a causal relationship between the two.This inconsistency may be due to the following reasons: First, previous studies were mostly from observational studies and randomized controlled trials, and the results may have been influenced by confounding factors and reverse causation. In addition, previous studies still have the problem of small study size and sample size. Studies have shown that some trace elements, as key regulatory factors of serotonin synthesis, can regulate the synthesis of serotonin in a tissue-specific way, thus having a direct impact on the occurrence of ADHD and other mental diseases. According to Gall and Pertile et al.The advantages of our study are that, first of all, our data comes from largest available GWAS datasets, which has strong statistical power. Comparing MR to observational research, confounding factor bias can be reduced. Secondly, in order to reduce the bias caused by horizontal pleiotropy, this study used MR-PRESSO to detect broad horizontal pleiotropy in all results and eliminate abnormal SNPs. In addition, we used the Cochrane’s Q, MR-Egger test and leave-one-out methods to carry out sensitivity analysis, which guaranteed the reliability of the analysis results. And finally, in our study, the bias for confusion due to ancestry is reduced because our research was limited to participants of white European descent.Our study has the following limitations. Firstly, while using a variety of MR methods to minimize the impact of pleiotropy on the data, we were unable to totally rule out the bias caused by unidentified pleiotropy. Second, due to the enlargement of the genome-wide significance level of certain phenotypes , this may affect how well we understand the results. Third, due to the minimal variance of the exposures explained by the SNP instruments or the short GWAS sample sizes, some of our MR analyses lacked the sensitivity to detect minor effects.In order to investigate the possible correlations between genetically predicted amounts of nine micronutrients and the risk of ADHD, we carried out the first comprehensive two-sample MR study. Our study found no genetic evidence of a significant causal relationship between circulating micronutrient concentrations and the risk of ADHD, and only suggested that there may be some association between copper levels and ADHD, but the significance of the findings was weak, so it is recommended that copper levels be used as a long-term monitoring indicator for further study. No heterogeneity or pleiotropy was found in sensitivity analysis. In order to reduce the incidence of ADHD and improve the quality of life of people with ADHD, more research can be focused on the potential link between micronutrients and ADHD in the future.Supplementary Figure S1.Supplementary Figure S2.Supplementary Table S1.Supplementary Table S2.